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Electronic Theses, Treatises and Dissertations The Graduate School

2015

Effects of Resistance Training and ProteinSupplementation on Body Composition,Muscular Strength, and Physical Function inBreast Cancer SurvivorsTakudzwa A. (Takudzwa Arthur) Madzima

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FLORIDA STATE UNIVERSITY

COLLEGE OF HUMAN SCIENCES

EFFECTS OF RESISTANCE TRAINING AND PROTEIN SUPPLEMENTATION ON

BODY COMPOSITION, MUSCULAR STRENGTH, AND PHYSICAL FUNCTION

IN BREAST CANCER SURVIVORS

By

TAKUDZWA A. MADZIMA

A Dissertation submitted to the Department of Nutrition, Food, and Exercise Sciences

in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Degree Awarded: Spring Semester, 2015

ii

Takudzwa A. Madzima defended this dissertation on February 6, 2015.

The members of the supervisory committee were:

Lynn B. Panton

Professor Directing Dissertation

Thomas Ratliffe

University Representative

Robert Moffatt

Committee Member

Michael J. Ormsbee

Committee Member

The Graduate School has verified and approved the above-named committee members, and

certifies that the dissertation has been approved in accordance with university requirements.

iii

Dedicated to my family: Welbourne, Rufaro, Pamela and Thelma Madzima and Stacey Burr.

Your unconditional love and support have made me the man I am today.

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ACKNOWLEDGMENTS

Dr. Lynn Panton: Thank you for being the best mentor, teacher, friend, workout partner and

“mother” a student could ask for. I will always cherish your guidance and support throughout my

academic journey, as well as all the laughs and stories we have shared during our weekly

stadiums workouts.

Dr. Michael Ormsbee: Thank you for inspiring me to lead a healthy and fit lifestyle. Your Sports

Nutrition class really made an impact on the way I view exercise and nutrition and motivated me

throughout my doctoral training. Thank you for your mentorship and your friendship.

Dr. Robert Moffatt and Dr. Tom Ratliffe: Thank you for your willingness to serve on my

committee and contributing to this study. This dissertation would not be possible without your

guidance and support.

National Strength and Conditioning Association: Thank you for funding my proposal that made

this study possible.

Dr. Robert Wildman and Dymatize Nutrition™: Thank you for providing the protein supplement

for this study. Without your contribution, this study would not be possible.

Research Participants: Thank you for making such a positive impact in my life. It was a pleasure

getting to know all you and thank you for sharing your stories and experiences with me. I feel

blessed to have made 33 new great friends.

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TABLE OF CONTENTS

List of Tables ............................................................................................................................... viii

List of Figures ................................................................................................................................ ix

Abstract ............................................................................................................................................x

CHAPTER 1: INTRODUCTION ....................................................................................................1

1.1 Purpose ...........................................................................................................................3

1.2 Research questions .........................................................................................................3

1.3 Research hypotheses ......................................................................................................4

1.4 Assumptions ...................................................................................................................4

1.5 Delimitations ..................................................................................................................5

1.6 Limitations .....................................................................................................................5

1.7 Definition of terms .........................................................................................................6

CHAPTER 2: REVIEW OF LITERATURE ...................................................................................9

2.1 Mechanisms of the loss of muscle mass in healthy aging ...........................................14

2.2 Skeletal muscle loss in breast cancer ...........................................................................22

2.3 Adverse effects of breast cancer treatment on muscle .................................................23

2.4 Adverse effects of breast cancer treatment on muscular strength and physical

function. .......................................................................................................................25

2.5 Resistance training in healthy aging adults ..................................................................27

2.6 Resistance training in breast cancer survivors .............................................................28

2.7 Dietary influences on muscle mass in breast cancer ....................................................30

2.8 The role of protein supplementation to augment the anabolic effects of resistance

training .........................................................................................................................31

2.9 The anabolic effect of protein on skeletal muscle ........................................................31

2.10 Protein needs of aging muscle .....................................................................................32

2.11 Protein supplementation in healthy older adults ..........................................................35

2.12 Protein supplementation in breast cancer survivors .....................................................38

2.13 Resistance training and insulin-like growth factor ......................................................40

2.14 Resistance training and adiponectin.............................................................................41

2.15 Resistance training and C-reactive protein ..................................................................42

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2.16 Concluding remarks .....................................................................................................44

CHAPTER 3: RESEARCH DESIGN AND METHODS ..............................................................45

3.1 Study overview ...........................................................................................................45

3.2 Inclusion criteria ..........................................................................................................45

3.3 Exclusion criteria .........................................................................................................46

3.4 Data collection—laboratory visit 1 ..............................................................................46

3.5 Data collection—laboratory visit 2 ..............................................................................48

3.6 Diet and exercise interventions ...................................................................................49

3.7 Participant recruitment, retention, and compliance .....................................................52

3.8 Anticipated risks and solutions ....................................................................................52

3.9 Stopping signal.............................................................................................................55

3.10 Statistical analyses .......................................................................................................56

CHAPTER 4: RESULTS ...............................................................................................................57

4.1 Participants ..................................................................................................................57

4.2 Resistance training volume and intensity ...................................................................62

4.3 Muscular strength, physical activity and function ......................................................66

4.4 Body composition .......................................................................................................69

4.5 Dietary and supplemental nutrient intake and adherence ...........................................72

4.6 Blood biomarkers ........................................................................................................77

4.7 Lymphedema history and monitoring ........................................................................80

CHAPTER 5: DISCUSSION ........................................................................................................85

5.1 Muscular strength, physical activity and function ......................................................86

5.2 Body composition .......................................................................................................89

5.3 Dietary and supplemental nutrient intake and adherence ...........................................93

5.4 Blood biomarkers ........................................................................................................98

5.5 Lymphedema history and monitoring ......................................................................102

5.6 Concluding remarks ..................................................................................................104

APPENDIX A: IRB APPROVAL LETTERS ....................................................................106

APPENDIX B: TELEPHONE INTERVIEW .....................................................................108

APPENDIX C: INFORMED CONSENT DOCUMENT ....................................................110

APPENDIX D: PHYSICIAN CONSENT DOCUMENT ...................................................114

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APPENDIX E: DEMOGRAPHIC/MEDICAL QUESTIONNAIRE ..................................115

APPENDIX F: PEDOMETER LOG ...................................................................................123

APPENDIX G: LICENSES TO PUBLISH FIGURES .......................................................124

REFERENCES ....................................................................................................................129

BIOGRAPHICAL SKETCH ...............................................................................................154

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LIST OF TABLES

1. Baseline Participant Characteristics ...........................................................................................60 2. Resistance Training Volume and Progression ...........................................................................65 3. Muscular Strength, Physical Activity and Physical Function ...................................................68 4. Body Composition .....................................................................................................................71 5. Diet and Supplemental Nutrient Intake......................................................................................76 6. Blood Biomarkers ......................................................................................................................80 7. Lymphedema History at Baseline ..............................................................................................81

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LIST OF FIGURES

1. Mechanisms of accelerated muscle wasting associated with age, behavior and disease ...........15 2. Mechanisms of muscle protein synthesis ...................................................................................19 3. Mechanisms of anabolic resistance of muscle protein synthesis with aging .............................34 4. Flow of participants through the study ......................................................................................58 5. Upper extremity lymphedema measurements: % difference between involved versus uninvolved arms .............................................................................................................................82 6. Upper extremity lymphedema measurements: % difference between involved versus uninvolved arms with only participants that had lymph nodes removed .......................................83 7. Upper extremity lymphedema measurements: % difference between involved versus uninvolved arms with all participants ............................................................................................84

x

ABSTRACT

Breast cancer survivors (BCS) encounter side effects from cancer treatments that negatively

affect muscular strength and body composition, particularly the loss of lean mass. Studies have

shown that resistance training (RT) can maintain lean mass, but few have observed increases in

lean mass. This may be due to the lower intensities of RT used or the inadequate protein intake

of the participants in these studies. PURPOSE: To evaluate the efficacy of higher intensity RT

(n=16) and RT+protein (n=17) interventions to improve muscular strength and body composition

in BCS over 12 weeks. METHODS: Thirty-three (59 ± 8 years) BCS were measured pre and

post RT for the following variables: muscular strength (chest press and leg extension) via one-

repetition maximal (1-RM) and handgrip (HG) strength via HG dynamometer, physical function

via the Continuous Scale of Physical Functional Performance, body composition (lean mass, fat

mass) via dual-energy X-ray absorptiometry (DXA), blood biomarkers of muscle and fat

metabolism [insulin-like growth factor-1 (IGF-1) and adiponectin] and total body inflammation

[human C-reactive protein (CRP)]. RT consisted of two days/wk using ten exercises performed

for three sets of 10-12 repetitions at ~65-85% of 1-RM. RT+protein also consumed 20g of a

protein supplement twice a day. Data were reported as means and standard deviations.

Dependent variables at baseline were analyzed by one-way analysis of variance (ANOVA).

When group differences in baseline variables were observed, an analysis of covariance

(ANCOVA) was performed with the baseline variable as the covariate. Dependent variables

were analyzed by a 2 by 2 factorial ANOVA (group x time) with repeated measures on the last

factor. One-way ANOVA post hoc tests were used to compare group or time differences. An

intent-to-treat analysis was used to evaluate pre and posttest scores to address the effects of the

interventions on all randomized participants regardless of whether they completed the study or

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not by using the principle of last observation carried forward. Significance was accepted at

p<0.05. RESULTS: The total weight training volume (weight lifted x repetitions x sets) over the

12 weeks for the upper body exercises was 227,673 ± 65,732 kg for the RT+protein group and

185,760 ± 62,932 kg for the RT group and was approaching significance (p= 0.071). The total

training volume for lower body exercises was not different between the RT+protein and RT

groups (258,877 ± 75,997 vs. 219,274 ± 73,906 kg). Average RT intensity was not different

between the RT+protein and RT groups during weeks 1-6 for upper body (70 ± 7% vs. 71 ± 4%)

and lower body (69 ± 5% vs. 70 ± 6%) percent of baseline 1-RM and during weeks 7-12 for

upper body (77 ± 7% vs. 75 ± 8%) and lower body (80 ± 9% vs. 83 ± 9%) percent of the 6-week

1-RM. No group x time interactions were detected for variables measured except upper body

lean mass, which was higher in the RT+protein group compared to the RT group at 12 weeks.

Both groups (n=33) significantly increased upper (86 ± 22 to 115 ± 29 kg), lower body (97 ± 25

to 116 ± 31 kg), HG (51 ± 9 to 54 ± 8 kg) strength and total physical function (69 ± 14 to 72 ± 15

units). Lean mass (40.4 ± 6.2 to 41.3 ± 6.5 kg), fat mass (29.4 ± 9.3 to 28.9 ± 9.4 kg), percent

body fat (41.4 ± 5.4 to 40.4 ± 5.6%) significantly improved over the 12 weeks of RT. There were

no group by time interactions for any of the blood biomarkers. Serum levels of IGF-1

significantly increased from baseline to 12 weeks in both the RT+protein group (110 ± 40 to 119

± 37 ng/ml) and the RT group (102 ± 34 to 115 ± 33 ng/ml) but adiponectin and CRP did not

change. At baseline, the RT group had a significantly greater percent difference in upper

extremity volume, a measurement of lymphedema, than the RT+protein group (9.5 ± 11.2 vs 1.8

± 10.2%, respectively. The percent difference in upper extremity volume significantly decreased

from baseline to week 5 to a greater extent in the RT group (9.5 ± 11.2 to 0.18 ±7.7%) than the

RT+protein group (1.8 ± 10.2 to 1.87 ± 7.4%). The average percent difference in upper extremity

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volume of all the BCS significantly decreased from 5.6 ± 11.2% at baseline to 2.0 ± 5.6% in

week 9. CONCLUSIONS: Twelve weeks of RT at 65-81% of 1-RM was well tolerated and

significantly improved muscular strength, physical function, body composition and lymphedema

in BCS. RT significantly increased IGF-1, the blood biomarker of muscle metabolism in both

groups, but the values did not exceed the normal range. Although the protein supplement was

well tolerated and adhered to, supplementing with 40g/day did not provide additional benefits to

RT. The greater increments in upper body lean mass were likely due to the somewhat higher

training volume in the upper body exercises in the RT+protein group and not the daily protein

supplementation. RT at higher intensities can help counteract the cancer related changes and

significantly improve muscular strength and body composition without exacerbating

lymphedema or causing any musculoskeletal injuries.

1

CHAPTER 1

INTRODUCTION

Breast cancer is the most prevalent cancer in American women with approximately

225,000 new cases and 40,000 annual deaths reported in 2012 (245). Despite the improved five-

year survival rate in the past several years, breast cancer survivors (BCS) are left to struggle with

adverse side effects as a result of chemotherapy and hormone suppressant therapy (213). Cancer

therapy negatively affects body composition, particularly the loss of muscle mass, which may

lead to sarcopenia (98), and the concurrent increase in fat mass, termed sarcopenic obesity. This

multifactorial ill condition will ultimately have negative impacts on the quality of life and

physical function of BCS (27, 263). Importantly, the accelerated decrements in muscle mass can

lead to frailty, a geriatric syndrome in which the risks of adverse health and physical outcomes

increases as a result of the declining physiologic capacity of aging adults (87, 99). Recently,

Villasenor et al. (2012) sought to find the association between the prevalence of sarcopenia,

defined as the appendicular skeletal mass (ASM;kg) adjusted for height (m²) of <5.45 kg/m², and

breast cancer specific mortality in 471 women with breast cancer (stages I-III). Sarcopenia as

defined by an ASM index of <5.45 kg/m² was evident in 75 (16%) of the women, and was an

independent predictor of mortality (273). In a few studies by Prado et al. breast, lung and

gastrointestinal cancer patients with sarcopenia were 2.6 times more likely to develop secondary

malignancies (211), as well as being at an increased risk of chemotherapy toxicity (208) and a

having a shorter time to death (209). Therefore, understanding the mechanisms of breast cancer

therapy related decrements in skeletal muscle mass is paramount to implementing appropriate

interventions. Two intervention programs that may be promising for BCS include resistance

training (RT) and protein supplementation.

2

Intervention programs in RT at intensities between 60 and 100% of 1-repetition

maximum (1-RM) have been shown to increase skeletal muscle mass and strength in healthy

adults (43, 101). Although RT interventions in BCS have shown improvements in muscular

strength (59, 284), few have reported significant accretion of muscle mass (235) while other

studies have found no increases in muscle mass (160, 284) following RT. These differences may

be due to the differences in exercise intensity that these studies used with the former prescribing

3 sets of 70-75% of 1-RM and the latter prescribing 1-3 sets of 60-80% of 1-RM. As a result it is

reasonable to deduce that exercise intensity is a determining factor for providing a stimulus

sufficient enough to observe changes in muscle mass in BCS. Be that as it may, a more

significant stimulus for accretion of muscle mass in BCS may be the provision of amino acids.

Healthy older adults have a blunted post-absorptive muscle protein synthetic rate in

response to amino acid feeding (112, 139). Therefore, it has recently been recommended that

older adults need to increase their daily protein intake from the RDA of 0.8 g/kg/day to

consuming 1.4-1.6 g/kg/day (25, 51). This increased protein dose may be most appropriately

achieved by the addition of a protein supplement to the diet of the aging adult. Further,

increasing the daily protein intake of older adults by consuming a 15g protein supplement twice

a day in combination with RT, has been shown to be sufficient enough to increase lean body

mass (+ 1.3 ± 0.4 kg; P=.006) in frail elderly adults (78 ±1 years) (267). Thus, a combined RT

and protein supplementation intervention may provide the necessary stimulus to overcome the

age- and disease related anabolic resistance to accretion of muscle mass in BCS. To date, no

studies have investigated this non-pharmacological intervention to counteract the disease and

treatment induced side effects in BCS.

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1.1 Purpose

The purpose of the present investigation was to examine the efficacy of RT and protein

supplementation in combination or RT alone for improving body composition (lean mass and fat

mass), muscular strength, physical function, and biomarkers of muscle and fat metabolism in

post-menopausal breast cancer survivors (BCS).

1.2 Research questions

The present study was designed to answer the following research questions:

1. To what extent will 12 weeks of RT combined with protein supplementation (RT+protein)

improve body composition (lean body mass and fat body mass) compared to RT alone in 33

post-menopausal BCS?

2. To what extent will 12 weeks of RT combined with protein supplementation

(RT+protein) improve skeletal muscular strength and physical function compared to RT

alone in 33 post-menopausal BCS?

3. To what extent will 12 weeks of RT combined with protein supplementation (RT+protein)

improve metabolic biomarkers of muscle (insulin-like growth factor 1), fat metabolism

(adiponectin) and inflammation (C-reactive protein) compared to RT alone in 33 post-

menopausal BCS.

4

1.3 Research hypotheses

The hypotheses of the present study included the following:

1. Post-menopausal BCS participating in RT combined with protein supplementation will

demonstrate greater increases in lean body mass and greater decrements in fat mass compared

to BCS participating in RT alone.

2. Post-menopausal BCS participating in RT combined with protein supplementation will

demonstrate greater improvements in skeletal muscular strength and physical function

compared to BCS participating in RT alone.

3. Post-menopausal BCS participating in RT combined with protein supplementation will

demonstrate greater improvements in the metabolic biomarkers of muscle and fat metabolism,

insulin-like growth factor 1 and adiponectin, respectively and decreases in the biomarker of

inflammation, C-reactive protein, to a greater extent compared to BCS participating in RT

alone.

1.4 Assumptions

Assumptions for the present study included the following:

1. All participants accurately reported their age, breast cancer medical history (diagnosis and

treatment), menopausal status, current exercise status, and current dietary intake.

2. All participants followed the instructions given to them regarding the maintenance of their

current dietary habits and current daily physical activity outside of the prescribed intervention.

3. All participants followed the instructions given to them regarding protein supplement

consumption and honestly and accurately reported their adherence to the protein

supplementation when prompted to do so.

5

4. All laboratory equipment yielded accurate measurements over the course of repeated testing.

1.5 Delimitations

The delimitations of the present study included the following:

1. Only stage 0-III female BCS were allowed to participate in the present study. Therefore, male

breast cancer patients, female survivors of stage IV breast cancer, or females with active

cancer, were not eligible to participate in the present study.

2. Individuals with uncontrolled hypertension, diabetes, or heart disease were not eligible to

participate in the study.

3. Female BCS must have been 3 months post-surgery and 2 months post-cancer therapy.

4. The present study consisted of 33 BCS, with 16 in the RT group and 17 in the RT+protein

group for an intervention period of 12 weeks.

5. The women in the RT+protein group consumed 20 g of protein in a ready to drink bottle twice

a day. The women consumed the first 20 g serving of protein within 30 minutes of completing

each RT session on training days and in the morning before breakfast on the non-training

days. The women consumed the second 20 g serving of protein as their last meal consumed

within 30 minutes of going to bed on all days of the week.

1.6 Limitations

The limitations of the present study included the following:

1. Only female BCS were included in the present study, and therefore results obtained may not

be generalized to male breast cancer patients or patients suffering from other forms of cancer.

6

2. Participants were recruited on a volunteer basis, and thus may have been more motivated than

the general female breast cancer population. Therefore, the results obtained may not be

generalized to the entire breast cancer population.

3. Participants were recruited from the Tallahassee, Florida and surrounding regions. Therefore,

the results obtained may not be generalized to female breast cancer survivors in other

geographical regions.

1.7 Definition of terms

Adjuvant Chemotherapy – Chemotherapy prior to or after surgery and/or radiation treatment

that is prescribed to eradicate undetectable residual cancer cells after surgery has eradicated

all detectable tumor (medical-dictionary.thefreedictionary.com).

Appendicular Skeletal Muscle Index - appendicular skeletal muscle mass (arm + leg muscle

mass) adjusted by height (ASMI; kg/m²) (183).

Aromatase - An enzyme responsible for the synthesis of estrogens from androgen precursors.

As a result of estrogens role in promoting certain cancers, inhibition of aromatase enzymes is

a form of cancer treatment (medical-dictionary.thefreedictionary.com).

Aromatase inhibitors - Drugs that prevent the formation of the hormone estradiol by

inhibiting the enzyme aromatase. Aromatase inhibitors are used as a method of hormone

therapy in hormone dependent cancers (www.cancer.gov/dictionary).

Body Composition - The relative proportions of protein, fat, water, and mineral components

in the body (medical-dictionary.thefreedictionary.com).

7

Bone mineral density (BMD) - A measure of the mineral content, particularly calcium and

phosphorous in a volume of bone. BMD measurements are used to diagnose osteoporosis

(www.cancer.gov/dictionary).

Cancer - a term for diseases caused by the uncontrolled growth of abnormal cells.

(www.cancer.gov/dictionary).

Breast Cancer - Cancer that forms in tissues of the breast, commonly in the ducts (thin

tubules that deliver milk to the nipple) and the lobules (milk glands) of the breast. In stages

Stages 0 and 1, the cancer is called carcinoma in situ (in the original place) and therefore

contained to place of origin, whereas in Stage 2 the cancer has begun to grow and spread but

is still contained in the breast area. Stage 3 is an advanced stage in which the cancer has

spread and invaded surrounding tissues (lymph nodes). In Stage 4 the cancer has spread

beyond the breast region to other areas of the body (brain, bones, liver)

(http://www.nationalbreastcancer.org).

Cachexia - severe muscle wasting that is defined as the disease induced, rapid and

involuntary loss of body weight (≥ 5% of body weight within 1β months) caused by

increased systemic inflammation that is often accompanied by reduced food intake (anorexia)

(90).

Dual energy x-ray absorptiometry (DXA) - A method of measuring bone density by passing

x-rays at two different energy levels through the bone (www.cancer.gov/dictionary).

Frailty - a geriatric syndrome in which a decline in physiologic reserve increases the risk of

adverse health and physical outcomes, including physical dependence, falls, fractures, and

mortality (87, 99).

8

mTOR - Mammalian target of rapamycin (mTOR), a kinase that integrates signals from

growth factors, energy, oxygen and amino acids to regulate downstream pathways that

stimulate mRNA translation of proteins (157).

Osteopenia - A less severe form of bone loss, classified as having a BMD that lies between 1

and 2.5SD below average value for young healthy individuals (World Health Organization).

Osteoporosis - A more severe form of bone loss typically diagnosed when an individual has a

BMD that is 2.5SD or more below the average value for young healthy individuals (World

Health Organization).

Radiation Therapy - A form of cancer treatment that uses high-energy radiation from x-rays,

gamma rays, protons and neutrons to kill cancer cells (www.cancer.gov/dictionary).

Sarcopenia - The age related loss of skeletal muscle mass and strength, by approximately 0.5

– 1% loss per year after the age of 50. Sarcopenia is defined as having an appendicular

skeletal muscle mass (arm + leg muscle mass) adjusted by height of <7.26 kg/m² in men and

< 5.45 kg/m² in women (17).

Sarcopenic obesity - the simultaneous occurrence of low muscle mass (sarcopenia) and high

adiposity (obesity) (209).

Quality of life - an individual’s sense of well-being, ability to perform various activities and

overall enjoyment of life (www.cancer.gov/dictionary).

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CHAPTER 2

REVIEW OF LITERATURE

Older adults experience voluntary and involuntary weight loss as part of the aging

process. Voluntary weight loss occurs with increased exercise and food restriction. However,

unintentional weight loss in older adults is often a result of chronic disease, starvation and/or the

natural aging process and puts them at risk for poor health outcomes. The most common cancer

in older women is breast cancer and it is often associated with disease and treatment related

accelerations in skeletal muscle loss. The incidence of cancer diagnosis is highest in older adults

(>60 years) (128) and increases with advancing age (26). Although survival rates from breast

cancer are high, survivors are often left to live with alterations in body composition as a result of

the cancer itself and cancer therapy. Breast cancer survivors (BCS) experience accelerated

muscle loss from hormone therapy, chemotherapy and corticosteroids that interfere with the

mechanisms of muscle protein synthesis (MPS) (68, 98, 104, 213).

Older men and women who have a body mass index (BMI) of less than 22 kg/m² (>65 years)

and less than 20.5 kg/m² (>75 years) have been found to have impaired functional capacities and

increased mortality risk (5, 20, 152). Several factors contribute to the weight loss in older adults,

but an important contributor is the loss of muscle mass across the life span. Healthy young adults

have a balance between muscle protein synthesis and degradation and therefore have no

significant net change over time. In contrast, as normal aging progresses muscle mass in

sedentary adults decreases at approximately 1-2% each year after the age of 50 years (123, 124)

largely due to reduction in muscle protein synthesis (183). Furthermore, decrements in motor

unit number (76) and muscle fiber size (29) occur with aging. Muscle wasting due to aging can

10

lead to decrements in muscular strength (6) and physical performance, which ultimately leads to

frailty and disability.

The decline in muscle mass across the lifespan can ultimately lead to significant functional

declines and ultimately disability in older adults. Developed in the early 1960’s, Nagi’s model of

disablement, identified four related conditions that ultimately lead to disability; active pathology

(disease or muscular abnormalities), which leads to physical impairments (anatomical and

physiological), and thus to the development of functional limitations (physical function and

quality of life) and eventually disability (132). Sarcopenic or cachectic adults have the potential

to have impaired ability to perform activities of daily living (ADL) and arrive at disability sooner

than their non-sarcopenic and non-cachectic counterparts.

Skeletal muscle abnormalities, such as sarcopenia and cachexia, are underlying

components of frailty in older adults (87). Frailty is defined as a geriatric syndrome in which a

decline in physiologic reserve increases the risk of adverse health and physical outcomes,

including physical dependence, falls, fractures, and mortality (87, 99). The estimated economic

costs associated with sarcopenia was $18.5 billion dollars in the United States in 2000, with a

10% reduction in the prevalence of sarcopenia projected to save $1.1 billion dollars per year in

healthcare costs (127). In addition, healthcare costs attributable to hip fractures are projected to

increase by $2 to $6 billion dollars by 2030 (150, 155). Fried et al. (2001) characterized the

frailty phenotype as having at least three of the five measurable criteria: (1) unintentional weight

loss (10 lbs within a year), (2) exhaustion (self-reported), (3) weakness (hand grip strength test),

(4) slow walking speed, and (5) low physical activity (99). Further measures of frailty include

poor balance, reduced mobility, inadequate nutritional intake, urinary incontinence and cognitive

impairment (87, 99, 222, 224, 262, 286). Older adults (≥ 65 years) comprise over 50% of all

11

medical surgeries in the United States of which 16% of the gross domestic product is consumed

by health care spending (221), frailty in adults contributes to the economic cost of aging.

Thompson et al. (2011) found a significant positive association between pre-operative frailty and

increased health care costs six months after colorectal surgery in 60 older (≥ 65 years) men and

women using a pre-operative frailty assessment (221). The cost of operations extends beyond in-

patient care and therefore it is important to understand and minimize age and disease related

contributors of frailty, particularly skeletal muscle disorders. Skeletal muscle disorders and

muscle wasting are predominantly realized in the forms of sarcopenia or cachexia, which are

both multifactorial conditions that affect the physical function, and overall quality of life of older

adults (17). These disorders in muscle mass and muscle function can be a result of aging,

physical activity and malnutrition (sarcopenia) or due to chronic diseases such as cancer

(cachexia).

Sarcopenia is defined as the age-related loss of muscle mass, which was first defined in

the late 1980s by Irwin Rosenberg (227). Sarcopenia affects 5 to 13% of adults between 60 and

70 years old, and 11 to 50% of adults over the age of 80 years (181). The World Health

Organization (WHO) estimates more than 50 million people worldwide are sarcopenic, with the

prevalence expected to increase to 1.2 billion people by 2025 (62). Sarcopenia is further defined

as having an appendicular skeletal muscle mass (arm + leg muscle mass) adjusted by height

(ASM; kg/m²) of 2 standard deviations or more below the young adult mean of the reference

population (183). Additional criteria for sarcopenia includes an ASM index (ASMI) of <7.26

kg/m² in men and < 5.45 kg/m² in women as determined by Baugmeneter et al. (17). However,

sarcopenia is no longer considered a condition solely associated with aging, but a multifactorial

geriatric syndrome (225) that often coincides with other syndromes prevalent in the elderly such

12

as anorexia, frailty, osteoporosis, and falls (62, 225). Furthermore, a sedentary lifestyle,

inadequate nutrition, pharmaceutical drugs, and bed rest encompass the multifactorial nature of

sarcopenia.

Cachexia is severe muscle wasting that is defined as the disease induced, rapid and

involuntary loss of body weight (≥5% of body weight within 12 months). Increased systemic

inflammation is a key component of cachexia that is often accompanied by reduced food intake

(anorexia). Additionally an absolute value of muscle mass below the fifth percentile is the

accepted diagnostic criterion of clinically significant muscle wasting (90). In addition to chronic

inflammation, increased muscle protein degradation and insulin resistances are prevalent features

in patients with cachexia (86, 189). Cachexia is commonly observed in patients with advanced

chronic diseases such as cancer (64, 71), human immunodeficiency virus/acquired

immunodeficiency syndrome (HIV/AIDS) (110), and cardiac cachexia as a complication of

congestive heart failure (7). It is estimated that over 1.3 million people in the United States are

affected by cancer cachexia; this number comprises 30% of all cachexia cases (180). Cancer

cachexia is most often observed in patients diagnosed with pancreatic, gastrointestinal, colorectal

and lung cancer (31, 71). In addition to tumor induced inflammation, and anorexia, the lack of

physical conditioning seen in these patients may further confound both forms of muscle wasting

(90).

Interestingly, cachexia can lead to, but is not always associated with sarcopenia.

Sarcopenic individuals are not necessarily cachectic. Adults with diminished muscle mass but

without rapid, involuntary weight loss including loss of fat mass and measurable systemic

inflammation are described as sarcopenic. Therefore, the consensus criteria for sarcopenia is

having both diminished muscle mass and diminished muscle function (physical strength and

13

performance) as agreed upon by the European Working Group on Sarcopenia in Older People

(EWGSOP), the International Academy of Nutrition and Aging (IANA), and the International

Association of Gerontology and Geriatrics-European Region [IAGG-ER] (225). Therefore,

individuals with skeletal muscle loss and function are described as sarcopenic but if their

condition includes rapid weight loss (≥5% of body weight within 1β months; or BMI of less than

20.0 kg/m²) and systemic inflammation associated with underlying illness they are described as

cachetic (225). Therefore, although both conditions are characterized by similar skeletal muscle

mass changes, the underlying mechanisms of each differ, and therefore the appropriate

interventions may differ. Moreover, physical activity, particularly RT is most appropriate for

sarcopenia, but may not have a significant impact on cachexia as a sole intervention (225).

Interventions for cachexia will need to include increasing caloric intake (264), anti-inflammatory

foods and supplements in addition to exercise (85, 134, 264). However, both muscular

abnormalities have some similarities and, therefore, a combination of physical activity and

nutritional interventions may benefit both. Thus if a common mechanism exists between the two,

then a common intervention may exist to target the common pathway involved in the loss of

muscle mass.

Although not to the extent as the aforementioned diseases, breast cancer, the most

common cancer occurring in women is often associated with disease and treatment induced

alterations in body composition, in particular muscle loss and the concurrent increase in fat mass

(8, 98, 166, 213). Muscle wasting in breast cancer (68, 98) occurs as a result of cancer

progression as well as therapy. Cancer drugs, such as anti-androgens, corticosteroids, and

chemotherapy can cause severe toxicity which results in accelerated loss of muscle mass (98,

14

213). These treatment related alterations in body composition may lead to sarcopenia and

sarcopenic obesity in breast cancer patients (211, 212).

Therefore, appropriate and multifactorial interventions to counteract accelerated muscle

mass loss in BCS are warranted to prevent further decrements in muscle mass and possible

progression to sarcopenia and cachexia. Effective interventions should establish baseline muscle

mass using imaging techniques such as Dual-Energy X-Ray Absorptiometry (DXA), measure

muscle function (muscular strength tests), and measure current dietary intake. Further an exercise

and nutrition prescription sufficient to attenuate or reverse muscle wasting is warranted. In

addition it is plausible that accelerated muscle wasting, will result in decrements in muscular

strength thereby impacting physical function and the ability to live independently (27, 53, 227,

263). Therefore, the years following initial diagnosis may be the most optimal window of

opportunity for prevention of additional treatment induced muscle wasting. The purpose of the

present review is to outline the mechanisms of muscle wasting in healthy aging as well as discuss

how this natural process is accelerated in the most common cancer occurring in women, and

examine the ongoing research involving treatment and prevention of further muscle wasting that

may lead to sarcopenia and cachexia in the breast cancer population.

2.1 Mechanisms of the loss of muscle mass in healthy aging

The cause of muscle wasting with healthy aging is multifactorial, with changes in

neuromuscular function, decreases in physical activity, malnutrition, decreases in satellite cell

number and function, decreases in protein synthesis, decreases in mitochondrial content and

function, changes in hormonal levels, increases in inflammation and oxidative stress, and

increases in adiposity. All of these factors together and independently contribute to the loss of

15

muscle mass, muscle function and muscle quality (Figure 1) (33, 277). Recent evidence suggests

that the aging process results in decreases in muscle mitochondrial content and function,

decreases in hormones (androgens, growth hormone and insulin-like growth factor-1), and

increases in inflammation (increased proinflammatory cytokines) that contribute to the decrease

in muscle mass that eventually leads to sarcopenia (77). In addition, disease progression and

recurrence, fatigue and nutritional deficiencies may further exacerbate the skeletal muscle system

wasting.

Figure 1. Mechanisms of accelerated muscle wasting associated with age, behavior and

disease (33).

Advancing age is thought to be associated with a neurological decline that results in the

reduction of the number of neuromuscular junctions (44). In a recent study, Chai et al. found a

significant increase in the number of denervated neuromuscular junctions, particularly in the type

II or fast twitch muscle fibers in older female mice (44). This study may help future studies

16

identify the specific mechanisms for the loss of motor neurons in aging humans. A recent study

identified C-terminal Agrin Fragment, which is the result of the cleavage of a motorneuron-

derived agrin (a nervous system protein) as a marker of neuromuscular degeneration and a

potential diagnostic measurement of sarcopenia in older men. The C-terminal Agrin Fragment

was found to be associated with decrements in appendicular lean mass in men, but not in women.

Further, the concentration of C-terminal Agrin Fragment was reduced by exercise and vitamin D

supplementation (78). It is plausible that the loss of neuromuscular junctions in humans is one of

the major contributing factors to the decrements in muscle fiber number and size observed in

aging adults. Losses in muscle fiber number and size are most notably seen in the fast twitch

muscle fibers (159, 271).

Along with the decline in the neuromuscular junction there are also age-related changes

in satellite cell number and function (271). Satellite cells are muscle stem cells that respond to

mechanical stress such as exercise to repair and regenerate muscle fibers (256). Satellite cell

content, particularly in fast twitch muscle fibers is reduced in aging adults (271) and function by

slower migration speeds to damaged fibers in older compared to younger adults (56). The

compromised satellite cell function during aging is thought to be due to reduced expression of

the glycoprotein integrin that acts as molecules for satellite cell–extracellular matrix adhesion

(56, 259). The combination of impaired satellite cell content and function and reduction in

physical activity as well as inadequate nutrition will inevitably lead to muscle wasting in aging

adults.

The physiological benefits of physical activity in skeletal muscle include improvements

in mitochondrial content and function (169), satellite cell signaling (256), muscle protein

synthesis and reduced long-term inflammation (111). Although the benefits of physical activity

17

are well documented, the levels of physical activity decrease with age. A study by Morse et al.

(β004) reported that even healthy physically active older men (≥ 70 years old) were still γ0% less

physically active than young adults (19–35 years) (184).

In addition to increased physical inactivity, insufficient caloric intake, especially protein

intake is common in the elderly and can increase muscle wasting (179). Starvation in the elderly,

termed anorexia of aging (179, 182) caused by loss of appetite, changes to the gastrointestinal

hormones, and social and economic limitations (15) deprive the skeletal muscles of amino acids

required for protein synthesis, thereby creating protein imbalance in favor of protein degradation

(179, 278). Recently Houston et al. (2008) found a positive association between protein intake

and lean mass in community dwelling older (70-79 years) men and women and found those who

consumed greater (1.1 g/kg/day) than the recommended daily allowance (RDA) of 0.8 g/kg/day

had smaller decrements in lean mass over three years than those that consumed protein at or

below the RDA (122). The type, timing and quantity of protein recommended to prevent muscle

wasting will be discussed later; however inadequate protein intake in aging adults combined with

physical inactivity may further exacerbate the decline in muscle protein synthesis associated with

aging.

Muscle protein synthesis (MPS), particularly of the myosin heavy chain via the Akt-

mTOR-p70S6K pathway (Figure 2) declines with age (183). Impaired MPS is likely caused by

changes in the anabolic hormones, specifically the blunted anabolic response of insulin in the

muscles of older adults in the postprandial period (112). Skeletal MPS in response to nutrient,

contractile, and hormonal stimuli occurs via integration of signals by the kinase mammalian

target of rapamycin (mTOR). mTOR is found in two complexes, mTOR complex 1 (mTORC1)

and mTOR complex 2 (mTORC2). The role of mTOR complex 1 (mTORC1) is the integration

18

of signals from growth factors, energy, oxygen and amino acids to regulate downstream

pathways that stimulate mRNA translation of proteins (157). In response to the binding of insulin

to its receptor on the cell surface, tyrosine kinase activates the insulin receptor substrate 1 (IRS1)

and phosphor-inositide 3-kinase (PI3K) that leads to the activation of Akt. mTORC1 is inhibited

at rest by tuberous sclerosis (TSC2), however, Akt inactivates TSC2 thereby activating mTORC1

which phosphorylates p70 ribosomal S6 kinase 1 (p70S6K) and eukaryotic initiation factor 4E

binding protein1 (4E-BP1) that increases mRNA translation for the synthesis of proteins (157).

Synergistically, mTOR complex 2 (mTORC2) promotes MPS by activating Akt. However, in

response to low levels of adenosine triphosphate (ATP; starvation), AMP-activated protein

kinase (AMPK) activates TSC2 thereby inhibiting mTORC1 mediated protein synthesis (288). In

addition mTORC1 signaling is inhibited by rapamycin. Although MPS occurs in older adults in

response to anabolic stimuli, this mechanism is attenuated with aging (79). Additionally,

mitochondrial dysfunction (244), insulin resistance (112), and chronic inflammation (133)

contribute to the age-related impairments in MPS. The decline in mitochondrial content,

function and regulatory enzymes with aging has been well documented (126, 191, 244) and

identified as another major contributor to the decline in skeletal mass with healthy aging.

Evidence of declining mitochondrial function has been demonstrated in studies reporting a

decline in both maximal oxygen consumption (VO2max) (223, 244) and resting oxygen

consumption (VO2) (214). Additionally, the maximal synthesis rate of ATP as measured by the

recovery rate of phosphocreatine by magnetic resonance spectroscopy after a brief exercise bout

has been shown to be lower in older adults (243).

19

Figure 2. Mechanisms of muscle protein synthesis (147)

Therefore, the decline in the oxidative capacity of the mitochondria will result in the

decline in skeletal MPS, an ATP dependent process, thereby leading to the loss of skeletal

muscle with age. Further, the reduction in physical activity, particularly aerobic exercise which is

a potent stimulus for the increase in the ability for muscles to produce ATP (54, 243) may add to

the decrements in skeletal muscle oxidative capacity. This is a plausible mechanism for muscle

loss with age as Lanza et al. (2008) showed that older adults (59-76 years old) who aerobically

exercised regularly (≥60 minutes, 6 days per week) for over four years were able to maintain

their mitochondrial content (156). Aging has also been shown to have lower expression of three

key skeletal muscle proteins; (1) peroxisome proliferator-activated receptor- coactivator 1α

20

(PGC-1α – stimulates synthesis of new mitochondria), (2) AMP-activated protein kinase

(AMPK- increases mitochondrial synthesis and enzyme content but paradoxically inhibits

skeletal muscle protein synthesis and hypertrophy), and (3) silent mating type information

regulation 2 homolog sirtuin 1 (SIRT1- attenuates metabolic disorders associated with age) (107,

135, 156, 158).

In addition to the aforementioned mechanisms, hormonal alterations in androgens

(testosterone, dehydroepiandrosterone sulfate, estrogen), insulin, growth hormone (GH) and

insulin-like growth factor-1 (IGF-1) contribute to loss of muscle mass with aging (167, 231).

Testosterone increases skeletal MPS (268), however levels decrease by 1% per year from the age

of 30 years in men (93) and even more rapidly in women between the ages of 20 to 45 years

(178). Testosterone supplementation has been shown to increase muscle mass (257) and strength

(250) in older men. However, testosterone treatment is associated with health risks including

sleep apnea and increases prostate cancer risk (188). Dehydroepiandrosterone is a precursor to

testosterone and estrogen, and increased levels of this hormone by supplementation in older men

and women do not directly increase muscle size or strength (65). Although estrogen has beta

receptors on skeletal muscle membranes (30), the direct effect of estrogen on muscle mass is less

understood with some studies showing a correlation with muscle mass (125) and others reporting

no association in women ≥65 years of age (17).

Of more importance may be the role of insulin, GH and IGF-1 in aging muscle. Insulin

inhibits muscle protein breakdown in response to carbohydrate and amino acid feeding (217) and

therefore promotes the balance of protein turnover towards protein synthesis. Insulin resistance,

common in older adults may reduce the potential of insulin to up-regulate protein synthesis

(200). GH acting via IGF-1 is influential in the regulation of skeletal muscle mass. In skeletal

21

muscle IGF-1 is produced in two isoforms both of which decline with age; (1) mechano-growth

factor (MGF) released in response to exercise is important for satellite cell replenishment and (2)

IGF-1 which up-regulates MPS. Ultimately, IGF-1 via the Akt-mTOR-p70S6K pathway is a

paramount mediator of muscle hypertrophy and repair (201). Hameed et al. (2004) found IGF-1

expression increased in 19 healthy, older men (70-82 years) with GH treatment and an increase

in MGF expression with the addition of 12 weeks of RT to the intervention (117). Interestingly,

Vitamin D, important for regulating bone and calcium homeostasis (66), has been shown to

improve severe muscle weakness (175), and increase fast twitch muscle fiber number and size

(232). Vitamin D levels are often deficient in the elderly (109, 280) and the expression of

vitamin D receptors on skeletal muscle declines with age (232).

Age-related muscle loss has also been linked to chronic inflammation and oxidative stress

associated with both aging and diseases associated with advancing age (e.g. atherosclerosis,

metabolic syndrome) (50, 187, 252). Recently, Meng et al. (2010) reported that molecular

inflammation and oxidative stress causes protein imbalance, myonuclear apoptosis, and

mitochondrial dysfunction (170). Similarly, Chung et al. (2011) suggested that the driving force

of skeletal muscle degeneration is the continuous, irregular inflammatory process during aging

(49). Advancing age is often associated with increased adiposity, which in turn increases the

inflammatory environment that inevitably accelerates muscle loss, a condition termed sarcopenic

obesity (94, 238, 266). Therefore, understanding the mechanisms in which both oxidative stress

and chronic inflammation as a result of aging and obesity is imperative.

Reactive oxygen species (ROS) increase with aging thereby elevating pro-inflammatory

mediators including tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and

interferongamma (IFN- ) mediated by the transcription factor nuclear factor-κB (NF-κB) that is

22

stimulated by both ROS and inflammation (49, 170). The continuous activation of NF-κB by

ROS and the inflammatory mediators (TNF-α, IL-6) causes a chronic inflammatory state that

increases protein degradation via the ubiquitin-proteasome (UbP) proteolytic pathways (Figure

2) (52, 251, 285). Furthermore, muscle regeneration, repair and hypertrophy are impaired due to

the disruption of the muscle stem cells known as satellite cells (48, 154). In addition, NF-Κb

interferes with the processing of the myogenic regulatory factors necessary for satellite cell

proliferation (MyoD and myf-5) and differentiation (myogenin and MRF4) (153).

Lastly, muscle atrophy occurring as a result of increased myonuclear apoptosis (death of

a myonucleus) and decreased regenerative capacity may be due to age-related chronic

inflammation. Evidence suggests the inflammatory cytokine TNF-α triggers apoptosis via

mitochondrial dysfunction (164) and death domain receptor-mediated apoptosis when TNF-α

binds to the TNF-α receptor that is also known as the death receptor (74, 133, 205). Although not

to the same extent, the aforementioned pathways in which chronic inflammation during the

normal aging process leads to muscle wasting is similar to that of muscle wasting associated with

chronic diseases (cachexia). Therefore, understanding the mechanisms that acute and chronic

diseases (cancer, COPD, AIDS) accelerate age-related muscle loss and ultimately lead to

cachexia is paramount to identifying appropriate counter-measure interventions.

2.2 Skeletal muscle loss in breast cancer

There appears to be a related pathway to muscle wasting from treatments for breast

cancer with that of normal aging but it occurs at an accelerated rate (37, 233). While surgery is

often the primary treatment for breast cancer (mastectomy), neoadjuvant (before) and adjuvant

(after) therapies such as hormone suppression therapy and chemotherapy are often included to

23

slow tumor growth or alleviate symptoms (230, 241, 242). Although these treatments are often

effective, with increasing 5-year survival rates (129, 130), BCS are left to live with the side

effects of treatment (98, 213, 240).

Interventions to attenuate and possibly reverse this advanced muscle wasting are unlikely

to succeed (89), unless identification of BCS survivors who are at risk and the prescription of

appropriate exercise and nutritional strategies for this population are implemented. Routine

treatments for the hormone-dependent cancer in women (breast) include neo or adjuvant

chemotherapy, estrogen ablation, and radiation are discussed below. These methods of treatment

directly and indirectly disrupt muscle anabolic pathways. In an attempt to attenuate tumor

proliferation, cancer drugs such as corticosteroids, anti-androgens, and chemotherapy agents

target the PI3K, Akt, and mTOR molecular pathways that are responsible for stimulating MPS

(21).

2.3 Adverse effects of breast cancer treatment on muscle

Common chemotherapy agents such as methotrexate, cyclophosphamide, and

doxorubicin are primarily metabolized in the lean body mass; therefore it is plausible that this

compartment of the body is susceptible to wasting due to drug toxicity (177, 210). Hence, as

skeletal muscle mass is a major component of the lean body compartment, BCS are at risk of

accelerated muscle mass loss. However, often the accretion of fat mass during and after

chemotherapy conceals the decline in muscle mass in cancer patients (209). Therefore, it is

important not to restrict the discussion of muscle wasting in BCS to those who appear thin.

Freedman et al. (2004) observed significant increases in body fat percentage during (+2.3 ± 4%;

P=0.02) and 6 months after (+4.0 ± 6%; P = 0.01) treatment with concurrent decrements in fat-

24

free mass (-2.2 ± 4%; P = 0.02 and -3.8 ± 6%; P = 0.01 respectively) in 20 women (stages I-III)

undergoing adjuvant chemotherapy (98). It has been reported that chemotherapy agents such as

5-fluorouracil, epirubicin and cyclophosphamide (213), and fluoropyrimidines (5-fluorouracil

(5FU) and capecitabine) (208, 211), cause severe toxicity in patients with low lean mass relative

to their height (213). The goal of these cytotoxic, antineoplastic agents is to inhibit tumor cell

division and growth; however, these drugs are not specific to cancerous cells and affect cells

throughout the body including muscle cells. The molecular pathways (PI3K, Akt and mTOR) for

muscle protein synthesis are similar to those for tumor cell growth (21, 81), therefore by

targeting these pathways antineoplastic agents suppress Akt and mTOR, thereby inducing muscle

atrophy (9, 213). Additionally, hormone suppressant therapies such as aromatase inhibitors to

suppress estrogen production and selective estrogen receptors modulators such as tamoxifen are

other common adjuvant treatments for breast cancer patients that can negatively affect body

composition in BCS (230). However, the role of estrogen on skeletal muscle mass is less

understood, with some studies showing an association (125) and others not (17), between muscle

mass and estrogen. The most significant impact of hormone therapy on body composition is the

inhibition of the protective effects of estrogen on bone resorption; thereby increasing bone

mineral loss in BCS (215). Thus, the loss of skeletal muscle during breast cancer is primarily

caused by the aforementioned mechanisms of tumor induced increases in systemic inflammation

(75), however side effects of adjuvant chemotherapy also negatively influence behavioral factors

important for maintenance of muscle mass.

As previously mentioned, a significant contributor to skeletal muscle wasting in aging

adults is physical inactivity. However, in the case of breast cancer, women receiving adjuvant

chemotherapy agents often have decreased levels of physical activity largely as a result of

25

increased levels of fatigue. In one study the chemotherapy agent doxorubicin was reported to

increase fatigue in 25 breast cancer patients (aged 40-65 years; stage I-II) during the first

treatment regimen and one-third of the women continued to experience fatigue after treatment

(36). Similarly, in a larger study, Bower et al. (2000) reported one-third of 1,957 BCS

experienced more severe and persistent fatigue than their healthy age-matched counterparts (24).

Therefore, the elevated levels of fatigue during and after chemotherapy may play a significant

part in decreased levels of physical activity in BCS (68). Demark-Wahnefried et al. (1997)

observed a significant decrease in mean physical activity energy expenditure from 514 ± 117

kcal/d to 461 ± 83 kcal/d (P = 0.04) in 18 women receiving chemotherapy (69). Later, the same

group found 36 women had significantly lower energy expenditure from physical activity (P =

0.01) over 1 year of chemotherapy than 17 women receiving localized treatment (68). In

addition, the women receiving chemotherapy in this study experienced a significant loss in total

body lean mass (-0.4 ± 0.3 kg; P = 0.02) and leg lean mass (-0.2 ± 0.1 kg; P = 0.01) whereas

those receiving localized treatment did not (68). However, not all studies report significant

decrements in lean mass after chemotherapy (38). Although Del Rio et al. (2002) reported an

increase in lean mass in 30 breast cancer patients (stage I-II) after 6 months of chemotherapy;

this was also accompanied by an increase in total body weight (67). Therefore, this may have

been an adaptive increase in lean mass in response to the extra weight gained.

2.4 Adverse effects of breast cancer treatment on muscular strength and physical function

As physical activity is a potent stimulator of MPS even in older adults, the decrease in

physical activity caused by treatment-induced fatigue may accelerate skeletal muscle mass loss

in BCS. Further, if these decrements in skeletal muscle mass are not attenuated, it is plausible

26

that BCS may develop sarcopenia or cachexia and arrive at disability sooner. Progression to

physical disability is likely largely due to the fact that skeletal muscle mass is associated with

muscular strength and physical function (196, 260). In fact, Winters-Stone et al. (2009) found an

association between lower leg strength and incidence of falls in BCS (281). Impaired muscular

strength in BCS may also be related to the side of the body the cancer was treated. Merchant et

al. (2008) observed significantly weaker shoulder protractors, retractors and extensors in the side

of the body affected by cancer in 40 BCS who had completed all treatments at least 6 months

prior (171). Reduced muscular strength in older adults without prior cancer diagnosis is

associated with the inability to perform ADL and increased risk of falls (1, 216). As a result of

the aforementioned paths to muscle wasting in BCS, it is probable to conclude that BCS are at

risk of arriving at physical dependence prematurely.

In a long term study, Sweeney et al. (β006) found that 4β% of 1,068 BCS (≥5 years)

reported the inability to perform heavy household work, 26% were unable to walk half a mile,

and 9% could not walk up and down a flight of stairs (263). Furthermore, women who were

survivors for less than 2 years had higher prevalence rates of functional impairments than those

who were survivors for more than 2 years (263). This demonstrates that improvements in

functional ability over time since diagnosis and treatment are possible in BCS and appropriate

interventions to counteract functional impairments may be necessary early during survivorship.

As functional limitations experienced by many BCS after adjuvant chemotherapy will inevitably

lead to reduced quality of life (27) and increased risk of mortality (209), identifying other

contributing factors of skeletal muscle loss in BCS is imperative. In addition, more research

identifying non-pharmacological interventions to preserve and accrue muscle mass in BCS is

warranted.

27

2.5 Resistance training in healthy aging adults

Exercise training, particularly RT is an effective strategy to counteract skeletal muscle

loss. Although numerous benefits from aerobic exercise in aging adults exist (105), this review

will focus on RT and only include combined exercise programs when paucity of data exist. It is

well documented that RT between 60 to 100% of the 1-repetition maximum (1-RM) stimulates

many adaptions in skeletal muscle that promote increases in muscle mass and strength in older

adults (42, 95, 101, 287). Resistance training provides the mechanical stimulus needed to

attenuate and even reverse age-related muscle loss by increasing MPS (239) via the mTOR/Akt

pathway (Figure 2), increasing anabolic hormones (253), and promoting the activation and

proliferation of satellite cells (272). Most importantly, RT decreases the activity of cytokines

(TNF-α; IL-6) (58), which play an important role in both age and disease related skeletal muscle

degradation. Fourteen weeks of supervised heavy RT (3 sets; 10-12 repetitions; 80% of 1-RM; 3

days per week) significantly increased both type I and II muscle fiber cross sectional area

(muscle biopsy of vastus lateralis) in 28 healthy older (>65 years of age) men and women

(P<0.05) (28). More recently, Candow et al. (2006) showed that 12 weeks of RT (3 sets; 10

repetitions; 70% of 1-RM; 3 days per week) significantly increased lean mass (Bod Pod), muscle

thickness of the elbow, knee and ankle flexors extensors (B-Mode Ultrasound) as well as upper

and lower body strength (1-RM) in 29 older men (59-76 years; P<0.05) (42). Of most

importance to aging adults, the same group later reported that the age-related deficits in total

body lean mass (Bod Pod), regional muscle thickness (B-Mode Ultrasound) and muscular

strength (1-RM) were reversed after 22 weeks of heavy supervised RT (3 sets; 10 repetitions;

70% of 1RM; 3 days per week) in 17 healthy older men (60-71 years) (43). After 22 weeks of

RT, the lean mass, muscle thickness and strength were comparable to that of healthy sedentary

28

younger men (18-31 years) (43). Resistance training promotes the maintenance and accretion of

muscle mass in healthy older adults thereby attenuating the age-related decrements in muscle

mass and progression to sarcopenia. It is possible these benefits extend to BCS as well.

2.6 Resistance training in breast cancer survivors

Similarly, RT in BCS decreases fatigue (237), increases muscular strength (148), and

improves quality of life (194). However, conflicting findings have been reported in regards to

increments in lean mass in BCS following a RT program with only one study observing a

significant training effect lean mass (235), some showing gains in lean mass only when

compared to the non-exercising control groups (16, 59, 284), and others not reporting significant

gains (248). The only study to report a significant training effect on lean mass was a six-month

RT program (3 sets; 10-12RM; 2 days per week) that significantly increased lean mass from

baseline by 0.88 kg (P < 0.01) in 39 breast cancer survivors, as measured using DXA (235).

However, in another study breast cancer patients undergoing chemotherapy exercised for 21

weeks in a combined RT (2-3 sets; 40-60% of 1-RM; 2 days per week) and aerobic training

program (n=10; mean age ± SD 57.5 ± 23.0 years). The women significantly increased their

percent lean body mass (+4.0% versus -0.2%; P=0.004), assessed by 3-site skin-fold

measurements, and increased muscular strength (1-RM) only when compared to the non-

exercising controls (n=10; mean age ± SD, 56.6 ± 16.0 years) (16). A RT program for 17 weeks

at 60-70% of 1-RM (2 sets; 8-12 repetitions; 3 days per week) elicited significantly higher

increments in lean body mass (+1.0 kg; 95% CI: 0.5 to 1.5kg; P=0.015) compared to a usual care

group (+0.2kg; 95% CI: -0.3 to 0.6kg) in breast cancer patients beginning chemotherapy (59). In

contrast, 16 weeks of RT (2-4 sets; 10 repetitions; 80% of 1-RM; 2 days per week) and aerobic

29

training program in sedentary, overweight BCS had no effect on body composition (160).

Recently, Winters-Stone et al. (2011) reported that a one year resistance and impact (jump)

exercise program (1-3 sets; 8-12 repetitions; 60-80% of 1-RM; 3 days per week) in

postmenopausal BCS (≥ 50 years of age) did not elicit a significantly greater increments in lean

mass compared to women in the control group participating in stretching exercises (284). A 6-

month resistance training study (60-70% of 1RM; 2 days per week) by Simonavice et al. (248)

did not report any significant increases in lean body mass from baseline in 27 BCS, however, the

women did maintain their lean mass over the 6 months of training as measured by DXA.

Data are conflicting whether resistance training improves lean mass in BCS. Some of the

studies show increases of 2.7 - 4.0% in lean mass only when compared to the non-exercising

controls, or maintenance of lean mass and only one has reported a significant 1.15% body fat (P

= 0.03) decrease in body fat (235). Some of the differences in results could be due to the

intensity of the training programs not being great enough to increase lean mass or the duration

and frequency of exercise not being long enough. Importantly, many of the studies do not report

the nutritional status of their participants which may be a major limitation. In a cross-sectional

study by Page et al. (197) found that the BCS who were consuming higher levels of protein

(>20%) in their diet had higher total BMD than BCS who consumed less. However, there was

not a significant correlation between dietary protein and lean mass (r =0.219). Only calcium was

significantly correlated with lean mass in this study (r=0.444; P < 0.05). Therefore, dietary

intake may play a role in modulating body composition in BCS. Further studies including data on

the nutritional status of BCS may elucidate the differences in lean mass observed in interventions

for BCS.

30

2.7 Dietary influences on muscle mass in breast cancer

Poor dietary habits have been implicated with the risk of developing hormone dependent

cancers (46, 144). Dietary factors influence age at menarche, height, weight and hormones, all of

which play a role in the incidence of breast cancer (55, 143). To date alcohol intake (116), high

fat intake (255) and low fiber and vegetable consumption (143), soy and tea have been

implicated with the risk of breast cancer (116, 120, 143, 206, 254). More importantly dietary

habits influence body composition, with obesity increasing the risk of developing breast cancer

in postmenopausal women by 50%, primarily because of elevated aromatase regulated estrogen

production in fat cells (143).

However, less is known about the influence of dietary protein intake in women diagnosed

with breast cancer. Inadequate caloric intake deprives skeletal muscle of amino acids for MPS

and is commonly observed in patients with cancer cachexia (90). However, energy imbalance by

excess caloric intake can cause obesity related metabolic changes such as insulin resistance

thereby down-regulating the IRS-1-PI3K pathway for Akt-mTOR mediated MPS (Figure 2) (19,

57). Denmark-Wahnefried at al. (2001) reported breast cancer patients maintained caloric intake

during adjuvant chemotherapy (68), whereas, Harvie at al. (2005) observed an increase in caloric

intake (118). Hence, it is plausible that energy imbalance created by excess calories in the

presence of reduced physical activity over the disease course contributes to muscle loss

experienced by BCS. Therefore, a calorie restricted, high protein diet in combination with

exercise may be appropriate for reducing fat mass while preserving or accruing muscle mass in

BCS as observed in aging adults without cancer (258).

31

2.8 The role of protein supplementation to augment the anabolic effects of resistance

training

In addition to RT as an appropriate intervention for cancer survivors, protein

supplementation may provide additional benefits. As cancer patients who have had hormone

therapy often experience side effects such as accelerated muscle loss and fat accretion,

supplementing with protein in combination with RT may preserve lean body mass and promote

fat loss. Several studies have reported preservation of muscle mass and weight loss with an

increase in protein intake in healthy obese adults (138, 141, 142, 174). The same body

composition benefits may extend to BCS. To the best of our knowledge there have been no

studies to investigate the possible benefits of protein supplementation in combination with RT as

an appropriate (non-pharmacological) intervention for BCS to counteract the side effects

associated with cancer therapy. However, animal studies have shown that manipulating the

dietary carbohydrate:protein ratio in favor of increased protein intake (40% energy from

carbohydrate; 35% energy from protein) reduces breast tumor progression in rats (186) and

tumor development and progression in mice (15% energy from carbohydrate; 58% energy from

protein) (119).

2.9 The anabolic effect of protein on skeletal muscle

Protein is a major nutritional determinant of muscle mass via stimulation of the PI3K,

Akt, mTOR molecular pathways for MPS (Figure 2). Amino acids from dietary protein,

particularly the essential amino acid (EAA) leucine, up-regulate the guanosine triphosphate-

(GTP)-binding protein, Ras homologue enriched in brain (Rheb), which binds directly to mTOR

and increases the activity of mTOR kinase which phosphorylates p70S6K to initiate protein

32

synthesis (162). Amino acids and IGF-1 also positively regulate Rheb by binding to IRS-1,

which activates the PI3K-Akt to phosphorylate and down-regulate the activity of TSC 1 and TSC

2, which lowers the capacity for Rheb to stimulate mTOR kinase. In response to low ATP (low

energy), AMPK inhibits Rheb by promoting the formation TSC1 and TSC2 thereby inhibiting

MPS (140, 207). Increased protein intake, as part of a weight loss diet or in combination with

exercise has been shown to have positive effects on body composition (39, 123, 198, 249).

2.10 Protein needs of aging adults

Increasing dietary protein has the potential for muscle mass accretion and optimizing

body composition in healthy aging adults. The current recommended daily allowance (RDA) for

protein is 0.8 g/kg/day for adults over the age of 19 years (40). However, early nitrogen balance

studies have suggested aging adults (56-80 years) need to consume 1.14 g/kg/day of protein (40).

In fact, it has recently been reported that 25% of older adults consume less than the RDA of

protein (0.8 g/kg/day) and up to 50% consume less than the recommended 1.14 g/kg/day of

protein (228). A more recent recommendation for protein intake for older adults has increased

the daily needs of older adults to 1.4-1.6 g/kg/day (25, 51). Currently, the gold standard for

assessing protein consumption with protein needs is the adaption-accommodation principle, in

‘adaption’ refers to a steady state environment in which physiologic functions are either

augmented or not compromised in response to a change in protein intake. Whereas,

‘accommodation’ is defined as a non-steady state in which physiologic functions are hindered in

order to conserve protein in response to a decline in protein intake (41). Physiologic

accommodation was observed in a 14-week study with 29 older men and women (54-78 years)

consuming the recommended daily allowance (RDA) for protein (0.8 g/kg/day), as a 21%

33

reduction in nitrogen excretion was reported and was significantly correlated (r=0.83) with a -1.7

cm2 decrease in thigh muscle cross-sectional area (P < 0.05) (41). A decrease in nitrogen

excretion with a concurrent decrease in fat-free mass may indicate the compromise of MPS in

order to conserve total body protein in response to decreased protein intake. The findings from

this study indicated that the RDA for protein may not be adequate for the maintenance of skeletal

muscle in aging adults.

Recent evidence has suggested older adults have an anabolic resistance to amino acid

feeding thereby having a blunted post-absorptive muscle protein synthetic rate which leads to

muscle loss (112, 139). Several pathways have been implicated, including impaired digestion

and absorption of protein (22), as well as reduced amino acid uptake (72), insulin-regulated

tissue perfusion (218) and signaling protein activity in the muscle (34, 102) (Figure 3). However,

despite this, the anabolic resistance to MPS with aging is reversed if physical activity is

performed prior to ingestion of protein in elderly men (198). The improvements in the utilization

of dietary amino acids for de novo MPS after physical activity may continue for several days

(35) thereby highlighting the importance of regular physical activity in older adults (34). Aged

skeletal muscle has been estimated to have 50% lower concentrations of mTOR and p70S6K

than younger muscle (63). Additionally, insulin resistance common in older adults decreases the

uptake of amino acids into skeletal muscle and down-regulates the anabolic effect of protein

(103). Furthermore, the delivery of amino acids to skeletal muscle following mixed meals may

be impaired, as elevated levels of the potent vasoconstrictor endothelin-1 (ET-1) have been

observed in the elderly (103). Therefore, the decreased blood flow caused by elevated ET-1

diminishes amino-acid mediated stimulation of MPS and contributes to muscle wasting as

illustrated above in Figure 2 (276).

34

The aforementioned mechanisms of the inability of aging adults to maximally utilize

protein for MPS indicate the need for increased dietary protein in this population. Further,

increased protein intake to 1.4 – 1.6 g/kg/day may be most optimal in healthy older adults or

diseased adults with or at risk of severe muscle wasting. However, achieving an increased

amount of protein may be difficult and inconvenient while trying to limit the amount of fat in a

typical American diet. Ideally, achieving the increased protein and caloric needs of these patients

via normal whole foods would be optimal; it may not be the most practical. Individuals with or at

risk of sarcopenia, cachexia or the elderly in general typically already consume less calories than

needed in their normal diets (185, 220), therefore asking them to increase their caloric intake is

not plausible, particularly if they are currently undergoing some form of treatment. Thereby, the

use of oral nutritional supplementation, most importantly protein supplementation appears to be

the most feasible method of increasing protein intake in these populations.

Figure 3. Mechanisms of anabolic resistance of muscle protein synthesis with aging (34).

35

A high quality protein supplement such as whey protein could help adults increase their

protein intake, in a convenient liquid supplement form that may improve compliance and

adherence to dietary interventions. Protein quality is essential to stimulating MPS. Proteins that

provide the greatest proportion of the essential amino acids (EAAs), including the branched

chain amino acids (BCAAs) leucine, isoleucine and valine are the most effective at stimulating

MPS (114). EAAs, most importantly BCAAs, initiate the signaling molecules for protein

synthesis in addition to being substrates themselves. The BCAA leucine plays the most important

role in MPS. Whey protein, a by-product of the cheese making process, constitutes 20% of the

total protein in milk, and is the liquid that remains after the removal of the curds (caseins) (151).

Whey is a milk-based protein that has an anabolic effect in promoting MPS. Whey protein

supplementation has an important role not only in recovery after exercise, but also in promoting

MPS at various times of the day (114). Composed of approximately 26% BCAAs, whey protein

is a high quality protein with high leucine content. Leucine at a dose of 3.5g is likely the most

important essential amino acid for initiating MPS via the mTOR/Akt pathway (Figure 2). Whey

protein is also a potential appetite inhibitor, as it has the potential to prolong satiety by

promoting the secretion of active Glucagon-like Peptide 1 (GLP-1), an appetite inhibiting

hormone, by inhibiting dipeptidyl peptidase IV, the hormone that is responsible for breaking

down active GLP-1 (113). Several studies have shown the benefits of milk-based proteins such

as whey in healthy adults (14, 138, 265, 270).

2.11 Protein supplementation in healthy older adults

Evidence is growing to recommend increasing the protein:carbohydrate ratio in attempt

to improve muscle mass in older adults (149, 267). Consumption of protein before or after

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exercise augments the anabolic effect of exercise and results in accretion of muscle mass (198,

204), and has been recommended to combat sarcopenia and frailty in the elderly (226). An early

study found that older men participating in a 12-week RT program (3 days per week) and given a

nutrition supplement (43.3% carbohydrate,16.6% protein, 40.1% fat) had greater gains in mid-

thigh cross sectional area than the men on an ad lib diet but not consuming the protein dense

supplement. The differences between groups in this study is most likely because the

supplemented group consumed significantly more calories than the non-supplementing group,

(2960 ± 230 vs 1620 ± 80 kcal/d) by the end of the 12 weeks, although both groups were on an

ad lib diet (172). The inclusion of the added calories may be of benefit to both sedentary and

active, older adults as it is reported that the energy intake of older adults is often inadequate

(220). Later, Singh et al. (1999) reported a 10.1 ± 9.0% (P = 0.033) increase in type II muscle

fiber area after 10 weeks of RT (3 days/week) with a nutritional supplement (360 kcal; 60%

carbohydrate, 17% soy-based protein, 23% fat,) in 26 older men and women (N=26; 72-98 years)

(249). These earlier studies observed benefits of nutrient supplements with a more traditional

macronutrient distribution; however evidence showing the manipulation of this distribution in

favor of increased protein in older adults is promising. Campbell et al. (1995) compared protein

consumption of either the RDA of 0.8 g/kg/day or 1.6 g/kg/day older adults (56-80 years)

participating in a 12-week RT program and found the participants who consumed 1.6 g/kg/day of

protein had a greater uptake of amino acids for protein synthesis (P<0.02) but no differences in

lean mass were observed (39). A recent study reported a significant increase in lean body mass

(+ 1.3 ± 0.4kg; P=.006) after consuming a 15g protein supplement twice a day (1 after breakfast

and 1 after lunch) in frail elderly adults (78 ±1 years) who were also participating in a 24-week

RT program (2 days per week) compared to a group of frail elderly adults only participating in

37

the RT intervention. However, although strength and physical performance significantly

increased in both the groups (P=.000) as a result of the RT, only the group consuming the daily

protein supplement experienced significant improvements in lean body mass. These findings

support the hypothesis that dietary protein supplementation augments the gains in muscle mass

in elderly people performing RT (267). Of clinical relevance, the net 1.3kg increase in lean mass

in the protein supplementation group was enough to offset the reported age-related 0.5 – 1.0kg

per year loss in muscle mass (123). In contrast Chalé et al. (2013) did not observe any significant

group differences in gains in lean mass between mobility limited older adults (70-85 years)

consuming a 40g whey protein concentrate supplement (20g twice a day) or an isocaloric (45 g

maltodextrin) placebo who were participating in a 6-month RT program (3 days per week).

However, in response to the RT intervention, both the whey protein and placebo groups

increased lean mass (1.3% and 0.6% respectively), muscle cross-sectional area (4.6% and 2.9%

respectively), all measures of muscular strength (16-50%) and stair-climbing performance. The

lack of gains in muscle mass induced by the protein supplement in this study was attributed to

the distribution of the supplement into two separate 20g servings, which may not have had a

sufficient leucine content needed to maximally stimulate MPS in older adults (45). As previously

mentioned, older adults have a blunted anabolic response to amino acid feedings, and it has been

reported that older adults require a greater amount of leucine to optimally stimulate MPS than

younger adults (140). The inability of 20g of a protein supplement to augment the anabolic effect

of RT was also observed by Moore et al. (2009) in young adults (176). However, Cuthberson et

al. (2005) did not observe increased gains in MPS after protein supplement doses greater than

20g in older adults (63). The inconsistency of these findings highlight the need for more research

involving protein supplementation in older adults and the optimal dose to maximally stimulate

38

MPS. Nevertheless, the potential benefits of protein supplementation to increase or maintain

muscle mass are evident, and are possibly applicable to diseased populations.

2.12 Protein supplementation in breast cancer survivors

Although the aforementioned studies discuss the potential benefits of higher protein

intake to promote favorable body compositional changes in healthy, older adults, few studies

have examined the effect of a high quality protein such as whey and its influence on cancer

patients and survivors who have experienced disease and treatment related muscle wasting. To

date, no studies have included an oral protein supplement to increase lean mass in BCS.

However, a few studies have investigated the use of an oral protein dense supplement to increase

muscle mass in patients with cancer cachexia.

As previously mentioned, cancer cachexia patients have reduced rates of MPS and

increased rates of protein degradation as a result of chronic inflammation and anorexia that leads

to severe muscle wasting (90, 261). Vissers et al. (2005), observed lower plasma amino acid

concentrations in breast, colon and pancreatic cancer patients compared to age and sex matched

controls; thereby leading to the availability of amino acids for MPS (275). Amino acid feeding

was reported to acutely stimulate MPS in advanced ovarian cancer patients with cachexia after

consumption of 40g of amino acid supplement; however, the anabolic response was blunted

compared to the healthy older controls (73). The use of an oral protein supplement has the

potential to counteract muscle wasting in cancer patients (137). An early study found

consumption of an energy dense n-3 fatty acid enriched oral protein supplement (310 kcal; 16 g

protein; 1.1 g eicosapentaenoic acid) twice a day for eight weeks was significantly correlated

with increase in lean body mass (r = 0.33, p = 0.036) in 95 cachectic pancreatic cancer patients

39

and was significantly different from 105 patients consuming the isocaloric, isonitrogenous

control supplement. Both supplements were effective in attenuating weight loss, but the addition

of the n-3 fatty acids, eicosapentaenoic acid appears to augmented gains in lean mass (91).

Eicosapentaenoic acid has been shown to have anticachetic effects by inhibiting proteolysis

inducing factor’s (PIF) regulation of the ubiquitin-proteasome proteolytic pathway thereby

down-regulating protein degradation (279). Therefore, the addition of n-3 fatty acids to protein

supplements may be beneficial in promoting MPS in cancer patients. A promising study by

Deutz et al. (2011) investigated the effect of a high protein, leucine rich (4.16g free leucine)

formulated medical beverage (EXP n=12; 27% kcal from whey protein) on muscle protein

synthesis compared to a control medical beverage (CON n=12; 15% kcal from casein protein) in

a heterogeneous group of cancer patients with cachexia (70). They found that a leucine rich

medical protein beverage significantly stimulated muscle protein fractional synthesis rate (FSR)

in cancer patients compared to a conventional medical food (P = 0.023) (70). Therefore, a

leucine rich nutritional supplement has the potential to improve muscle protein synthesis in

cancer patients. More human studies investigating the appropriate dose and type of protein

required to maximally stimulate MPS in cancer patients is needed. However studies involving

cachectic mice have shown an increase in MPS (82-84) and an attenuation of muscle mass loss

(199) after consumption of high doses of leucine. Further, although limited data exist, it is

plausible that BCS who experience treatment induced muscle wasting can benefit from oral

protein supplementation to preserve and/or gain muscle mass. More research investigating the

use of oral protein supplementation in BCS is warranted. Additionally, the influence of RT and

protein supplementation to alter biomarkers of muscle and fat metabolism such as IGF-1,

40

adiponectin and C-reactive protein in favor of accretion of muscle in BCS needs further

investigation.

2.13 Resistance training and insulin-like growth factor

Although serum levels of the anabolic hormone IGF-1 decrease with age and therefore

contribute to the age-related loss of skeletal muscle, elevated levels of growth factors such as

insulin and IGF-1 increase the risk of developing breast cancer in postmenopausal women (146).

Often associated with obesity, the increased levels of insulin and IGF-1 lead to the increased

secretion of estrogen by adipose tissues that can cause the down-stream development of

estrogen-mediated breast carcinogenesis (146). Hence, a paradox exists in regards to increasing

levels of anabolic hormones such as IGF-1 through various means such as resistance exercise

and potentially increasing the risk of cancer reoccurrence in BCS. Normal serum IGF-1 levels in

healthy adults range from 40-258 ng/mL, with the average for women over the age of 45 years

old ranging from 106-143 ng/ml (100). In healthy overweight and obese adults (53.3 ± 8.7 yrs,

mean age ± SD; 32.2 ± 3.4 kg/m², BMI) progressive RT (6-12RM, 6 sets per muscle group, 3

days/week) and higher protein intake (43.5 ± 1.6% of total energy intake) significantly increased

IGF-1 values (+16.0 ± 7.5%; P < 0.05) but did not exceed normal values (11). A 6-month RT

intervention (2d/wk) did not significantly increase IGF-1 (+8.29 ± 6.26 ng/mL) and significantly

decreased levels of IGF-2 (-26.23 ± 16.73 ng/mL; P = 0.02) and body fat (-1.15 ± 0.45%) in 39

BCS (53.3 ± 8.7 yrs; mean age ± SD) with normal insulin and IGF axis hormone levels at

baseline (235). These results demonstrate that a 6-month RT intervention did not significantly

increase IGF-1 levels above normal in BCS. Therefore, RT is a safe exercise modality in BCS,

and no evidence exists of the contribution of RT to increase IGF-mediated risk of cancer

41

reoccurrence. More importantly, the ability of RT to reduce body fat in BCS may be more

clinically relevant as elevated body fat is implicated in altering other hormonal levels such as

adiponectin.

2.14 Resistance training and adiponectin

Low levels of adiponectin are associated with obesity and risk of developing breast

cancer (80, 173). Adiponectin, an adipokine that is secreted by white adipose tissue binds to the

adipose receptors on the cell membrane and activates AMP-activated protein kinase (AMPK),

which inhibits the PI3/Akt pathway for cell growth (146). Interestingly, although adiponectin is

secreted by adipose tissue, elevated body fat actually decrease the levels of adiponectin secreted.

This is largely due to the obesity related increase in IL-6 and TNF-α which both inhibit

adiponectin expression (32, 193). This is evident, as adiponectin levels have been shown to

increase after weight loss (121, 165). In fact, adiponectin is anti-proliferative, inhibits

angiogenesis and promotes cell apoptosis. Thus, when adiponectin levels are low, adipose and

tumor cells develop and proliferate, thereby increasing the risk of obesity and breast cancer

(192). Conflicting results exist with the direct effect of exercise and diet on adiponectin levels. A

diet and/or slow movement, low intensity resistance exercise intervention (2 sets, 20 RM, 3 days

per week) did not find any significant effect on adiponectin levels (96). Similarly, interventions

utilizing aerobic exercise with or without diet interventions in postmenopausal women did not

report any changes in adiponectin levels (108, 229). It is plausible that the absence of an effect of

these interventions on adiponectin may be due to the absence of weight loss (108). Whereas,

aerobic and diet interventions that reported weight loss also observed 6.6 – 9.5% increases in

adiponectin levels in postmenopausal women (2). Adiponectin levels did increase by 94% in 17

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obese adults after 7 months of an intense exercise (3.3 ± 2.1 hours/day) and diet intervention as

part of the “Biggest Loser” program (3). However, this intense method of weight loss is most

likely not appropriate for BCS and may result in poor adherence to the intervention. A study with

BCS utilized a 16-week combined RT (lower body exercise; 50 minutes, 2 days per week) and

home based aerobic training (90 minutes per week) intervention and did not find any changes in

adiponectin levels (161). It is conceivable weight loss may be the major determinant in observing

improvements in adiponectin levels after exercise and dietary interventions, as there is an inverse

relationship between adiponectin levels and adiposity (13). Although limited data exist on the

impact of exercise to modulate adiponectin levels in BCS, it is plausible that interventions such

as RT combined with protein supplementation that have been shown to decrease adiposity in

healthy overweight and obese adults (12) may be successful in BCS as well. Furthermore, the

reduction in inflammation from RT could result in attenuation of the inhibition of adiponectin by

the inflammatory markers IL-6, TNF-α and CRP.

2.15 Resistance training and C-reactive protein

A marker of inflammation that is secreted by the liver in response to elevated IL-6 and

TNF-α, is CRP which levels have a positive association with risk of breast cancer development

and reoccurrence (246). As previously mentioned, chronic inflammation is one of the major

contributors to the age- related decrements in muscle mass. Many cancers, including breast

cancer are associated with elevated levels of inflammatory markers such as CRP and IL-6, which

may further exacerbate muscle wasting (145). Additionally, CRP levels are positively correlated

with body weight (97) and potentially with the risk of developing breast cancer (192). In elderly

women without prior cancer diagnosis, RT (8-RM, days/wk) reduced the circulating marker of

43

inflammation TNF-α by γ7% and decreased the overall inflammatory environment (IL-6, IL-1 ,

and TNF-α) after 10 weeks of RT (γ sets, 8 RM, γ days per week) (202). In a more recent study

from the same group, RT for 12 weeks (3 sets, 8-12RM, 3 days per week,) decreased circulating

C-reactive protein by 33%, without any changes in body composition, in obese postmenopausal

women (65.6 ± 2.6 yrs; mean age ± SD) (203). Therefore, RT in healthy postmenopausal women

does reduce inflammation, however less is known whether the same effect of RT occurs in BCS.

To the best of our knowledge, only one study measured CRP levels after a RT intervention in

BCS, and found a non-significant 44% (P=0.29) decrease from baseline after 6 months of RT

(248). Only two studies have measured CRP levels after an exercise intervention in BCS, but

these studies used aerobic training as the exercise modality to modulate CRP levels in BCS. Of

these studies, one found aerobic training decreased CRP (88) and the other did not find an effect

of aerobic training on CRP levels (136). For this reason, more studies are needed that investigate

the impact of different modes of exercise on inflammation, which as previously described plays a

role in accelerating muscle loss with aging and cancer.

Therefore, a RT intervention alone or in combination with protein supplementation may

improve the hormonal milieu in favor of accretion of muscle mass in BCS by increasing IGF-1,

within normal levels. Furthermore, the potential to decrease body fat may increase adiponectin

levels and decrease levels of the inflammatory marker, CRP. Thus, as increased body fat has

been associated with increased risk of cancer recurrence and mortality (269), the potential for a

RT and protein supplementation intervention for decreasing body fat will be advantageous to

BCS.

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2.16 Concluding remarks

Breast cancer is the most common cancer in women in the United States. Despite

improved survival rates, the cancer and treatment for cancer accelerates muscle loss in these

patients to a greater extent than that of normal aging. BCS are left to live with diminished muscle

mass and function which can ultimately lead to frailty and disability. Further, without

appropriate interventions muscle wasting in BCS may progress to sarcopenia and cachexia. Non-

pharmacological interventions such as resistance exercise and protein supplementation should be

implemented to attenuate or reverse muscle wasting in BCS. The years following initial

diagnosis may be the most optimal window of opportunity for prevention of additional

treatments and age-related induced muscle wasting.

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CHAPTER 3

RESEARCH DESIGN AND METHODS

3.1 Study overview

This study was a stratified controlled clinical trial (stratified by age, lean mass, stage of

cancer, type of cancer treatment, and calcium and vitamin D supplementation) designed to

examine the effects of two non-pharmacological treatments on body composition, muscular

strength, physical function, and biomarkers of muscle and fat metabolism and inflammation

during a 12-week period. Women BCS who received chemotherapy, radiation and/or hormone

suppressant therapy alone or in conjunction with any other form of traditional cancer treatment

and who had completed all their treatments with the exception of hormone suppressant therapy

were included. The rationale for accepting BCS still taking hormone suppressant therapies was

because after initial treatments are completed, hormone suppressant therapies are prescribed for

5 to 10 years. The exclusion of women currently on hormone suppressant therapies would have

significantly reduced the number of participants that would be eligible for the study.

3.2 Inclusion criteria

Thirty-three post-menopausal (induced or natural) women BCS (stages 0-III), ages 40-75

years, having completed chemotherapy and/or radiation (at least 2 months post treatment), were

recruited from Tallahassee, FL and surrounding areas. Women who were taking or who had

completed hormone suppressant therapies were eligible to participate in this study. There were

no restrictions to race or socioeconomic status. All women had a physician’s consent form

signed before participating in the study to verify cancer remission status and the absence of any

underlying condition that would contraindicate protein consumption and RT. Thirty-three

46

participants were recruited, with 17 in the RT+protein group and 16 in the RT group. Based on

the study by Schmitz et al. who found significant differences between the control and RT group

the effect size of 1.14 was calculated from lean body mass (235). Based on an α-level of 0.05 and

90% power a minimum of 9 participants per group was determined. This study was approved by

the Florida State University Institutional Review Board (Appendix A).

3.3 Exclusion criteria

Male breast cancer survivors were not eligible for this study. Women diagnosed with

stage IV breast cancer or those who were currently diagnosed with active cancer; those receiving

endocrine (e.g., prednisone, other glucocorticoids) or neuroactive (e.g., dilantin, phenobarbital)

drugs or any other prescription drugs known to influence fat or muscle metabolism; those with a

history of hypo or hyperthyroidism or any other disease known to alter metabolism; those with

uncontrolled hypertension (≥160/100 mmHg), uncontrolled diabetes (blood glucose >β50 mg/dl),

heart disease, kidney disease, allergies to milk protein; those participating in a regular exercise

program (RT>1 time per week or aerobic exercise >2 times per week); those treated with

pharmacologic doses of vitamin D or anabolic steroids were not able to participate in the study.

In addition, all participants must have been at least 3 months post-surgery and completed with

treatment (2 months) in order to participate.

3.4 Data collection—laboratory visit 1

Once participants had been screened and given an orientation to the study via the

telephone (Telephone interview-Appendix B) and met the initial requirements of the study, they

were invited to the Clinical Exercise Physiology Laboratory at The Florida State University for a

47

further orientation to the study. During the orientation visit, the study coordinator reviewed the

time commitment and explained the study protocol (Informed Consent-Appendix C). Participants

were given the opportunity to ask questions. If the participant was interested in participating in

the study, she completed an informed consent and was given a physician’s consent form to get

completed by her physician for approval to participate in study (Physician’s Consent-Appendix

D). Questionnaires on demographics and medical history were also completed at this time

(Screening Questionnaires-Appendix E). Once eligibility was confirmed, physician’s consent

received, and the participant had consented to participate, the participant was scheduled for her

first testing visit.

Prior to all laboratory testing, the participants were asked to refrain from alcohol or

exercise for 24 hours. During the first testing visit participants came to the laboratory after an

overnight fast (>8 hours). Blood pressure and heart rate was measured in a quiet room on the

brachial and radial artery respectively, after the participants had been seated for a period of 5

minutes. Fasting blood draws were taken from a forearm vein in the amount of 20 milliliters by a

trained phlebotomist to measure insulin-like growth factor 1 (IGF-1) as an anabolic marker of

muscle metabolism, adiponectin as a marker of fat metabolism, human C-reactive protein (CRP)

as a measure of systemic inflammation. Due to the scope of this study, these particular

biomarkers were chosen in order to understand possible mechanisms for the influence of RT and

protein on muscle and fat in BCS. The whole blood was then centrifuged (4oC for 15 min @

3500 RPM) and serum was separated into individual aliquots and frozen at -80oC. All blood

samples were analyzed at the conclusion of the intervention at 12 weeks using commercially

available ELISA kits (R&D Systems®) that were run in duplicate. Following the blood draw,

height and weight was assessed using a standardized scale. Waist and hip circumference were

48

taken at least 2 times at the narrowest part of the waist and largest protrusion around the

buttocks, respectively. Body composition measurements (iDXATM, Lunar, GE) of total body,

android and gynoid regions, and appendicular measures of fat-free mass and fat mass were

assessed with the participant still fasted and laying supine on the DXA machine. Handgrip

strength was measured using a handgrip dynamometer (Creative Health Products, INC. Ann

Arbor, Michigan). Handgrip measurements were taken three times on each arm, and the highest

measurements from each arm were added together to compute the combined handgrip score.

Both upper and lower body strength were assessed using the chest press and leg extension

exercises (MedXTM, Ocala, FL), respectively. After a warm-up, participants were progressed

towards the maximum weight that they could lift one time (1-RM) through a full range of

motion. All measurements were recorded, with the goal of achieving a 1-RM within 3 to 5

maximal attempts. Three-day food records (2 weekdays and 1 weekend day) were explained and

distributed and were collected during the second visit.

3.5 Data collection—laboratory visit 2

On the second visit, participants returned their 3-day dietary records and had their resting

blood pressure and heart rate measurements repeated. Participants also had their 1-RM strength

measures repeated. The highest value obtained during the 1-RM testing from either the first or

second visit was the criterion measure of strength. Functionality was measured objectively via

the continuous scale-physical functional performance (CS-PFP) test. The CS-PFP test consists of

a series of tasks that mimic normal activities of daily living. This test has been shown to have

convergent, construct, and face validity for 16 everyday household tasks in previously published

research with a high reproducibility (r=0.97) and sensitivity to change, as well as having an

49

effect size of 0.8 (61). Furthermore, the CS-PFP test does not have ceiling or floor effects and

thus is able to measure function in highly functional individuals as well as in functionally

impaired individuals that cannot perform a particular task (60). Variance is minimized by giving

the test under standard conditions thereby enhancing the ability to detect changes from an

intervention. The tasks included in the CS-PFP-10 include carrying a weighted pan, putting on a

jacket, picking up scarves, reaching, floor sweeping, doing laundry, sitting and standing from the

floor, stair climbing, getting on and off a simulated bus, carrying groceries, and walking for 6

minutes. Scores range from 0-100 with 0 indicating “worst” and 100 indicating “best” and is

determined by the time it takes to complete each task, the amount of weight carried, and for

some tasks the distance traveled.

All measurements were repeated the week after completion of the 12-week intervention.

In addition, measurement of 1-RM was repeated at 6 weeks for both the training groups

(RT+protein and RT) in order to progress RT appropriately.

3.6 Diet and exercise interventions

Upon completion of baseline testing, each participant was stratified by the principal

investigator by age, lean mass, stage of cancer, and treatment as well as calcium and Vitamin D

intake to 1 of the 2 intervention groups: 1) resistance training and protein consumption

(RT+protein), or 2) RT alone. Stratification was performed by assigning participants to each

group depending on their baseline age, lean mass, stage of cancer, type of cancer treatment, as

well as calcium and Vitamin D intake in order maintain similarity between the means of the two

groups at baseline. Both groups were given a daily pedometer and physical activity log at

baseline to record physical activity for 1 week (randomly selected) out of the 1st, 2nd, and 3rd

50

month of the study (Appendix F). It was anticipated that several of the participants were calcium

and/or vitamin D supplement users; therefore we asked them to maintain their normal calcium

and/or vitamin D intake and to monitor their daily intake via a calcium and vitamin D log.

Participants that were not consuming supplemental calcium and vitamin D or those that were not

consuming a minimum of 1200mg of calcium and 800IU of vitamin D were asked to consume a

daily calcium and vitamin D supplement (Member’s Mark ™) that we provided to reach the

minimum dosage for the duration of the 12-week intervention.

For the length of the 12 weeks, the RT+protein group was instructed to consume 2

servings of a ready to drink (RTD) protein (serving size is 340 ml: 140 kcals, 1.0 g fat, 12.0 g

carbohydrate, 20 g protein; Supreme Protein®, Dymatize Enterprises, LLC, Dallas, TX), for a

total of 40 g of protein daily from the supplement. The rationale for choosing this dose of protein

was that it is well tolerated by participants on a daily basis, and positively influenced body

composition in non-malignant overweight middle-aged to older adults (10, 12). In addition, this

extra protein was intended to have participants in the protein group consuming >20% protein

which appears to be beneficial for BCS (197). The women in the RT+protein group consumed

the first 20 g serving of protein within 30 minutes of completing each RT session on training

days and in the morning before breakfast on the non-training days. The women consumed the

second 20 g serving of protein as their last meal consumed within 30 minutes of going to bed on

all days of the week. The participants in the RT+protein group were advised to adjust their food

intake to account for the additional energy from the protein supplement but not to make any

changes to their diet. Additionally, the RT+protein and RT groups completed 12 weeks of a

supervised RT program.

51

Protein change, which is the change in habitual protein intake, was determined according

to the calculations of Bosse and Dixon (23) as:

Change in habitual protein intake = [((g / kg / day intake during study – g / kg / day

intake at baseline) / g / kg / day intake at baseline) x 100]

Furthermore, the protein spread, which is the % difference in protein intake between

experimental and control group was also calculated using the formula from Bosse and Dixon

(23) as:

Between group % spread in protein intake = [((higher protein group g / kg / day intake

during study control group g / kg / day intake during study) / control group g / kg / day

intake during study) x 100]

Training was completed under the supervision of qualified graduate and undergraduate exercise

science students on 2 non-consecutive days each week for 12 weeks. Participants performed 2

sets of 10 repetitions and a 3rd set to muscular exhaustion for the upper and lower body as

previously described (195). Intensity began at 65% of each participant's 1-RM and slowly

progressed to an intensity not exceeding 85% of the most recent 1-RM throughout the 12 weeks.

All exercise sessions were carefully monitored and recorded by the exercise instructors. Exercise

machines included the MedXTM chest press, leg press, leg extension, biceps curl, and triceps

press down, overhead military press, seated row, leg curl, abdominal crunch, and lower back

extension. The rationale for using the proposed intensities was that body composition

improvements have been reported using intensities within this range (131, 274). The

prescription for the RT program followed the guidelines recommended by the American College

of Sports Medicine (92).

52

3.7 Participant recruitment, retention, and compliance

BCS (stages 0-III) with diverse racial and ethnic backgrounds, including African

Americans, Asians, and Hispanics who live in Tallahassee metropolitan and rural areas within

reasonable commuting distances were recruited via flyers, feature stories, science articles, as

well as oncologist and health specialists and local breast cancer support groups and events.

To achieve our specific aims, participant retention and compliance was a top priority. We

provided incentives and small gifts via raffles every week (e.g. gift cards to local merchants). We

collected empty protein containers for the RT+protein group and calcium/vitamin D containers

for both groups to verify compliance every 2 weeks. Furthermore, we asked participants in the

RT+protein group to complete a daily protein log to further record compliance to consuming the

protein supplement. Compliance to RT sessions was recorded by the exercise trainer scheduled

to conduct the weekly exercise sessions. Participants who missed an exercise session were called

to remind them of their next appointment and were scheduled for a make-up session.

3.8 Anticipated risks and solutions

All participants needed medical clearance from their oncologist or primary care

physicians verifying that they did not fall within the exclusionary criteria for the study. At any

time during the study, participants who did not meet the inclusion criteria were not able to

continue with the study. Potential physical risks to participants in this study were minimized by

using only skilled technicians in testing and intervention procedures. All personnel involved in

the study were CPR and First Aid Certified. If participants expressed significant fatigue or did

not feel comfortable with testing procedures, the test was not completed at that time. If at any

time a participant experienced chest pain or had any signs or symptoms of dizziness or had any

53

abnormal blood pressure or heart rate response to testing or training, emergency personnel were

contacted. Participants engaging in RT and testing have the risk of experiencing muscle soreness.

Care was taken to minimize soreness by slowly progressing participants through the RT

intervention and thoroughly stretching after RT and testing sessions. Qualified graduate and

undergraduate exercise instructors oversaw all exercise sessions in order to ensure proper

exercise techniques and to monitor exercise intensity. There are little data on the injury rates in

strength training. Our previous experience with strength testing and training in older individuals

indicates that the musculoskeletal injury rate is low during RT. The injury rate may be higher

during strength testing, but the risk in the present study was kept low by careful warm-up and

slow progression. The risk of any cardiovascular complication during strength testing and

training is also low. Participants in the RT groups were taught the proper exercise techniques to

minimize any injury that may occur from the training procedures. In case of emergency,

emergency personnel were available within five minutes on the university campus.

Lymphedema, which is defined as the swelling in one or more of the limbs as a result of

the blockage in the lymphatic system prevents the adequate draining of lymph fluid in the

affected limb. Breast cancer patients and BCS that have had damage or removal of one of more

lymph nodes due to surgery or radiation treatment are at risk for developing lymphedema. The

accumulation of fluid causes swelling in the affected arm and can result in pain, discomfort and

skin discoloration. There is no cure for lymphedema, but it can be controlled through manual

lymph drainage via therapeutic massage, wearing compression garments and exercise. For many

year, clinical practice instructed BCS with or at risk of developing lymphedema to refrain from

lifting more than 15 lbs of weight with the affected limbs including performing upper body

exercise, believing that this would exacerbate the lymphedema. However, recent evidence

54

suggests the contrary as moderate intensity exercise has been shown not to cause or exacerbate

lymphedma (4, 168). In a 6-month BCS study by Simonavice et al. (2014), none of the

participants developed lymphedema, participants’ arm circumferences were measured every β

weeks for the duration of the study (248). Nevertheless, in order to ensure safety participants in

the RT groups were monitored monthly via arm circumference measurements. Circumference

measurements were taken every 3 cm on each arm beginning at the styloid process of the ulna

and continued 45 cm proximally. An increase in arm circumference of >2 cm at one of the

landmarks was an indication of swelling and therefore we reduced of the prescribed RT intensity.

Furthermore, if the participants that experienced any signs of symptoms of lymphedema

including swelling in the upper extremities, shoulders, or chest; a heavy sensation in the arms;

skin tightness or discoloration and reduced flexibility in the hand or wrist were asked to notify

the principal investigator and exercise intensity was decreased accordingly and participants were

referred to their physician or oncologist. Participants that had or were at risk of developing

lymphedema were encouraged to wear their compression garments during the RT exercise

sessions.

The potential for weight gain is possible for participants consuming the extra calories

from protein, however, based on their dietary logs, recommendations were given on how to

balance energy intake and body weight was measured at every session.

Adverse events could include those associated with DXA, which involves a low exposure

to radiation (<5 mrem per DXA scan). Doses received from DXA scans examinations are small

in comparison to other common radiation sources and are believed to represent no significant

health risk. By comparison, natural background radiation is about 300 mrem per year, an x-ray of

55

the spine is 70 mrem, a mammogram is 45 mrem, and a typical cross-country plane flight is

approximately 6 mrem of radiation.

There is some risk associated with the blood draw, particularly local bruising, tenderness,

and infection. This was minimized by using only trained phlebotomists and sterile techniques.

Only one adverse event occurred and forms were used to report the details. This adverse

event was not related to the exercise or the protein, nevertheless it was reported to the PI who

then informed the IRB. There were no unanticipated adverse events. In the absence of moderate

or serious adverse events, as is appropriate with minimal risk studies, reports of study progress

were submitted to the IRB for review on a quarterly basis.

All data and samples collected were coded numerically and results kept confidential

throughout the course of the study. The master sheet of codes and questionnaires obtained were

retained by the PI and kept in a locked cabinet in a locked room in the Department of Nutrition,

Food and Exercise Sciences after completion of the research project. Results of this study will be

published and/or presented at meetings but no names, initials, or other identifying characteristics

will be reported. Medical records will be maintained in strictest confidence according to current

legal requirements and will not be revealed unless required by law.

3.9 Stopping signal

If participants acquired any of the exclusion criteria during the course of the study they

were not be able to continue with the study and were referred to their primary care physicians

and/or oncologists.

56

3.10 Statistical analyses

Descriptive statistics were calculated for all variables and included means and standard

deviations for normally distributed continuous variables and medians, minima and maxima for

non-normally distributed continuous variables. Frequency and percentages were calculated for

categorical variables. Distributions of outcome variables examined graphically for symmetry and

for outliers. Extreme outliers were investigated to determine whether there were any technical or

clerical errors and if such outliers were not attributed to technical or clerical error, it was

included in the analysis The primary aim of this study was to investigate the ability of RT and

protein, individually, and in combination to improve body composition, muscular strength,

physical function and metabolic biomarkers of muscle and fat metabolism in a stratified

randomized controlled clinical trial in post-menopausal BCS. Dependent variables at baseline

were analyzed by one-way analysis of variance, and when group differences in baseline variables

were observed, an analysis of covariance was performed with the baseline variable as the

covariate. Dependent variables were analyzed by a 2 by 2 factorial analysis of variance (group x

time) with repeated measures on the last factor. When interactions were significant, ANOVAs

were used to compare between group values as well as pre and posttest values within groups. All

significance was accepted at p≤0.05. All analyses were performed using the SPSS (v.21)

statistical package (IBM®, Armonk, New York). An intention-to-treat analysis was used to

evaluate pre and posttest scores to address the effects of the interventions on all randomized

participants regardless of whether they completed the study or not. Using the principle of last

observation carried forward, missing posttest scores was filled using the test scores that were

collected closest to the time of dropout. Pearson product moment correlations were completed on

variables of strength, body composition, dietary intake and the blood biomarkers.

57

CHAPTER 4

RESULTS

4.1 Participants

A total of 57 BCS responded to recruitment efforts for the present study. Of these, 10

declined to participate upon receiving a detailed description of the commitments of the study,

and 13 did not meet the eligibility requirements for the study for one of the following reasons:

currently participating in a vigorous exercise program (n=2) or still undergoing primary

treatment (n=11). Of the 34 participants that gave consent, one did not complete baseline testing

as a result of the time commitment of the study. Therefore, 33 were stratified randomly by age,

lean mass, stage of cancer, type of cancer treatment, and calcium and vitamin D supplementation

into one of the two intervention groups: 1) resistance training and protein consumption

(RT+protein), or 2) RT alone. Seventeen women were assigned to the RT+protein group of these

one did not complete the RT intervention during the 6th week due to medical complications not

related to cancer. Additionally, one participant in the RT+protein group did not complete her

second day of post-testing visit due to unforeseen family emergency that arose after the first day

of post-testing visit. The remaining 16 women were assigned to the RT alone group, with 13 of

these participants completing the entire intervention. One of the women could not return for her

second day of post-testing due to travel conflicts, one woman dropped out during the 7th week of

the intervention because of the time commitment, and the other participant was unable to

continue due to medical complications unrelated to the study. However, as an intent-to-treat

analysis was the main statistical goal of the study, all 17 women in the RT+protein group and all

16 women in the RT group were included in the analyses. An outline of the participant flow from

recruitment to analysis is displayed in Figure 4.

58

Figure 4. Flow of participants through the study

At baseline, there were no significant differences in age, height, weight, BMI and

physical activity as well as lean mass, stage of cancer, type of cancer treatment, and calcium and

Assessed for eligibility: N=57

Participated in baseline

testing: N=34

Randomized: N=33

Resistance training+protein

(n=17)

Discontinued due to medical complications not related to

cancer or exercise (n=1)

Did not complete post-testing (n=1)

Intent to treat analysis (n=17)

Resistance training alone

(n=16)

Discontinued due to medical complications not related to cancer or exercise (n=1), due

to time commitment (n=1)

Did not complete post-testing (n=1)

Intent to treat analysis (n=16)

Refused: n=10 Ineligible:

n=13

59

vitamin D supplementation between the women in the two intervention groups. Thirty-two of the

women in this study were Caucasian and one woman was African-American. The overall

average age of the women in the study was 59 ± 8 years, ranging from 40-74 years. The average

BMI of all the women was 27.2 ± 5.6 kg/m2 with 33% (n=11) being classified as overweight and

27% (n=9) being classified as obese with a range from 20.9 to 44.1 kg/m2. Furthermore, based on

their average baseline pedometer steps of 6,286 ± 2,734 steps/day (range from 2,278 to13,421

steps/day) the women in this study would be described as low activity individuals. The

participants in both groups shared similar menopausal ages of 50 ± 4 years in the RT+protein

group and 47 ± 6 years in the RT group, with 50% (n=8) and 59 % (n=10) of the women in the

RT+protein and RT groups respectively entering early menopause induced by cancer treatment.

The history of cancer diagnosis was also similar between both groups with the RT+protein and

RT groups being 76.1 ± 55.3 and 73.9 ± 65.2 months respectively since primary diagnosis for

breast cancer. The distribution of cancer diagnosis within the RT+protein group was fairly

balanced with 24% (n=4), 29% (n=5), 18% (n=3) and 29% (n=5) being diagnosed with stages 0,

I, II, and III breast cancer, respectively. Whereas, in the RT group 50% (n=8) of the women were

diagnosed with Stage I breast cancer and the remaining stages 0, II and III each had 18% (n=3)

of the women in the RT group. However, there were no statistically significant differences in

stage of breast cancer diagnosis between the two intervention groups.

Similarly, both groups did not differ in time since completion of primary cancer treatment

which, included surgery, chemotherapy, radiation or a combination of these, nor did they differ

in time since completion of hormone therapy for those who had hormone therapy. The

RT+protein group was 70.5 ± 55.5 months from completion of primary treatment, with 59%

(n=10) of the women having received chemotherapy and 53% (n=9) having received radiation.

60

Table 1. Baseline Participant Characteristics (N=33)

RT Group (n=16) RT+PRO Group (n=17)

Age (years) 59 ± 9 59 ± 7

Height (cm) 161.2 ± 4.4 163.5 ± 6.9

Weight (kg) 70.7 ± 14.8 74.2 ± 15.0

BMI (kg/m2) 27.2 ± 5.6 27.9 ± 6.0

Lean mass (kg) 39.4 ± 6.1 41.3 ± 6.2

Physical activity (pedometer steps) 6700 ± 2724 5945 ± 2777

Menopausal age (years) 47 ± 6 50 ± 4

Treatment induced menopause (%) 50% 59%

Time since diagnosis (months) 73.9 ± 65.2 76.1 ± 55.3

Stage 0 (%) 19% 24%

Stage I (%) 50.0% 29%

Stage II (%) 19% 18%

Stage III (%) 19% 29%

Received chemotherapy (%) 44% 59%

Received radiation (%) 50.0% 53%

Received hormone therapy (%) 13% 24%

Time since hormone therapy completed (months) 101.0 ± 111.7 31.0 ± 31.9

Time since primary treatment completed (months) a 68.3 ± 66.4 70.5 ± 55.5

Currently receiving hormone therapy (%) 25% 24%

Currently taking Calcium (%) 63% 65%

Calcium dose (mg) 1202.3 ± 439.6 1239.3 ± 362.6

Currently taking Vitamin D (%) 75% 88%

Vitamin D dose (IU) 1671.4 ± 631.8 1828.1 ± 1219.8 Data are presented as mean ± standard deviation or % of sample for categorical data. RT=Resistance training;

RT+PRO=Resistance training + protein supplementation; BMI=body mass index a primary treatment = surgery, chemotherapy and/or radiation.

In addition, 24% (n=4) of the participants in the RT+protein group had completed

hormone therapy 31.0 ± 31.9 months prior to beginning the study and 24% (n=4) were currently

receiving hormone therapy during the study. In the same manner, the RT group was 68.3 ± 66.4

months from completion of primary treatment, with 44% (n=7) of the women having received

61

chemotherapy and 50.0% (n=8) having received radiation. In addition, 13% (n=2) had completed

hormone therapy 101.0 ± 111.7 months prior to beginning of the study and 25% (n=4) were

currently receiving hormone therapy during the study. Furthermore, 65% of the women in the

RT+protein group (n=11) and 63% of women in RT group (n=10) were currently supplementing

with either calcium bicarbonate or citrate. Among the six women in the RT+protein group not

consuming a regular daily calcium supplement, we assigned our 1200 mg calcium supplement to

three of them, one participant was consuming less than 1200 mg and agreed to increase the daily

dose of her own calcium to reach 1200 mg and two participants were advised by their physicians

not to supplement with calcium. Additionally, of the six participants in the RT group not

consuming a daily calcium supplement, three women agreed to consume our 1200 mg

supplement, two women preferred to consume their own calcium and agreed to consume a

minimum of 1200 mg, and one participant was consuming less than 1200 mg refused to increase

the dose of her calcium supplement from 310 mg to 1200 mg. In addition, 88% of the

participants in RT+protein group (n=15) and 75% of the participants in the RT group (n=12)

were consuming a vitamin D supplement at baseline. The two women in the RT+protein group

not consuming a minimum of 800 IU on a regular basis, one met this requirement by consuming

our vitamin D supplement, and the other agreed to consume her own vitamin D supplement.

Similarly, three women in the RT group agreed to consume our 800 IU vitamin D supplement

and one participant in the RT group preferred to consume her own daily vitamin D supplement.

However, at baseline the amount of supplemental calcium was similar between the RT+protein

and RT groups (1239.3 ± 362.6 vs. 1202.3 ± 439.6 mg/day) as was the daily dose of vitamin D

(1828.1 ± 1219.8 vs. 1671.4 ± 631.8 IU/day). The values for the baseline participant

characteristics as well as breast cancer history are displayed in Table 1.

62

4.2 Resistance training volume and intensity

The RT training volume and progression as well as the average exercise adherence over

the 12 weeks of the RT intervention for both groups are presented in Table 2. The women

performed their RT training sessions two days per week and the total adherence for all the

participants in both groups including those that did not complete the intervention was 89.7 ±

19.7%. During each exercise session the participants performed 2 sets of 10 repetitions and a 3rd

set to muscular exhaustion on 10 exercises performed in a superset design in which the women

performed a set on an upper body machine and with no rest performed a consecutive set on a

lower body machine until three sets on each machine was completed before continuing to the

next pairing of upper and lower body exercises. The exercises were performed on MedXTM

machines in the following order: chest press paired with the leg extension, seated row with a

seated leg curl, triceps press down with the leg press, biceps curl with the abdominal crunch and

the overhead military press with 45º lower back extension. Exercise intensity began at 65 ± 2%

and 64 ± 2% of each participant's 1-RM for the chest press and leg extension machines

respectively, and the starting weights for the remaining exercises were estimated based on each

participant’s 1-RM for the chest press and leg extension. Training load on each exercise was

increased at the beginning of each new week based on the number of repetitions performed

during each participant’s γrd set to muscular exhaustion on each exercise on their last training

session the previous week. Thus, for every 2 repetitions performed past 10 repetitions in their 3rd

set to muscular exhaustion the weight was increased by 1.81kg (4lbs) on the MedXTM machines.

In addition, if the participant was able to complete 10 repetitions in their 3rd set to muscular

exhaustion the weight was also increased by 1.81kg (4lbs) the following week in order to ensure

participants progressed each week. The weight was maintained on the exercises that participants

63

were unable to perform 10 repetitions on their 3rd set to muscular exhaustion during their last

training session of the week. The total training volume over the 12 weeks was calculated by

multiplying the weight lifted by the number of repetitions performed for each set for each week

(weight lifted x repetitions x sets) and was statistically similar between the groups. The total

weight lifted over the 12 weeks for the RT+protein and RT groups were 486,550 ± 140,402 kg

and 405,028 ± 135,685 kg respectively. In addition, the total weight lifted over the 12 weeks for

the upper body exercises was 227,673 ± 65,732 kg for the RT+protein group and 185,760 ±

62,932 kg for the RT group and was approaching significance (F(1,31)=3.492, p= 0.071).

However, the total weight lifted for the lower body exercises over the 12 weeks was not

statistically different between the RT+protein and RT groups (258,877 ± 75,997 kg vs. 219,274 ±

73,906 kg). Furthermore, the 1-RM for the chest press and leg extension were repeated after 6

weeks of training therefore training intensity for weeks 1-6 of training was calculated as a

percentage of their baseline 1-RM while training intensity for weeks 7-12 was calculated as a

percentage of their 6-week (mid-study) 1-RM for chest press and leg extension. The exercise

intensity for the chest press and leg extension machines was used to represent upper and lower

body intensity respectively, over the 12-week RT intervention. The overall average intensity for

both groups over the 12 weeks was 78 ± 9% of baseline 1-RM for upper body intensity and 75 ±

9% of baseline 1-RM for lower body intensity. Table 2 displays the exercise intensity and

adherence between the two groups. During weeks 1-6 the average upper body and lower body

exercise intensity for both groups was 70 ± 5% and 69 ± 5% of baseline 1-RM respectively and

progressed to 76 ± 7% and 81 ± 9% of their 6 week 1-RM during weeks 7-12. There were no

significant differences between exercise intensity between the RT+protein and RT groups during

weeks 1-6 for upper body (70 ± 7% vs. 71 ± 4%) and lower body (69 ± 5% vs. 70 ± 6%) percent

64

of baseline 1-RM. Similarly, exercise intensity did not differ between the RT+protein and RT

groups during weeks 7-12 for upper body (77 ± 7% vs. 75 ± 8%) and lower body (80 ± 9% vs.

83 ± 9%) percent of the 6-week 1-RM.

Exercise adherence was calculated by taking a percentage of attendance to the 24 RT

training sessions during the 12-week intervention. The average of adherence to RT sessions of all

the participants (N=33) including those that dropped out (n=3) did not statistically differ between

the two groups, with the RT+protein group being 92.4 ± 18.8% (n=17) adherent and the RT

group attending 86.8 ± 20.9% (n=16) of their RT sessions. Among only the participants that

completed the exercise intervention (N=30), the average exercise adherence for both groups was

95 ± 9%, and was similar between the groups with the RT+protein group (n=16) attending 97 ±

7% of the RT sessions and the RT group (n=14) attending 94 ± 10% RT sessions. Furthermore,

adherence to intake of the daily protein supplement averaged 91 ± 9% for the RT+protein group.

The participants in both groups were asked to maintain their normal intake of calcium and

vitamin D supplements and adherence was calculated from their daily supplement logs. Of the 17

women in RT+protein group, two participants were advised by their physicians not to consume

any supplemental calcium but were already consuming vitamin D at baseline therefore we did

not provide them with any calcium supplements and asked them to maintain their vitamin D

intake. Therefore, in the RT+protein group we provided our daily calcium (1200 mg) and

vitamin D (800 IU) supplement to four women and three women increased their own calcium

and vitamin D supplements to meet the minimum for the duration of the study. The remaining 11

women in the RT+protein group were already consuming a minimum of 1200 mg of calcium and

800 IU at the beginning of the study and were asked to maintain their current dose.

65

Table 2. Resistance Training Volume and Progression (N=30)

RT Group (n=14) RT+PRO Group (n=16)

Total training volume (weight lifted x

repetitions x sets) (kg) 405,028 ± 135,685 486,550 ± 140,402

Total upper body training volume (weight

lifted x repetitions x sets) (kg) 185,760 ± 62,932 227,673 ± 65,732$

Total lower body training volume (weight

lifted x repetitions x sets) (kg) 219,274 ± 73,906 258,877 ± 75,997

Week 1-6 Upper Body Intensity (%1-RM) 71 ± 4 70 ± 7

Week 1-6 Lower Body Intensity (%1-RM) 70 ± 6 69 ± 5

Week 7-12 Upper Body Intensity (%1-RM) 75 ± 8 77 ± 7

Week 7-12 Lower Body Intensity (%1-RM) 83 ± 9 80 ± 9

Exercise Adherence (%)

94 ± 10% 97 ± 7%

Protein Supplement Adherence (%) Not applicable 91 ± 9%

Calcium and Vitamin D Supplement Adherence

(%) 84 ± 19% 94 ± 6%¥ Data are presented as mean ± standard deviation.

RT+PRO=Resistance training + protein supplementation; RT=Resistance training; 1RM = one

repetition maximum.

¥ p ≤ 0.05, significantly different between groups at 1β weeks

$ p =0.07, significantly different between groups at 12 weeks

Among the 16 women in the RT group, three women consumed our daily calcium (1200

mg) and vitamin D (800 IU) supplement, and two women consumed their own calcium and

vitamin D supplements. One participant in the RT group was consuming 310 mg and preferred

not to increase her calcium intake. The remaining 10 participants in the RT group maintained

their daily calcium and vitamin D intake that they were consuming at baseline. Twenty-six

women returned their calcium and vitamin D logs and there was a significant difference between

66

the groups in adherence of consuming their daily supplements. The average adherence of the

women in the RT+protein group (n=16) was 94 ± 6% while the women in the RT group (n=10)

had an average adherence of 84 ± 19% (F(1,24) =4.259, p≤0.05).

4.3 Muscular strength, physical activity and function

The intensity of the 12-week RT intervention was sufficient to elicit significant

improvements in handgrip strength, 1-RM chest press and 1-RM leg extension and physical

function. All participants were able to complete all strength testing with the exception of one

participant in the RT+protein group who was not able to successfully perform the baseline 1-RM

leg extension due to pain in the anterior portion of her lower leg from peripheral neuropathy.

Therefore, she did not have baseline and 12-week measurements for 1-RM leg extension. She did

however perform the leg extension as part of the RT intervention, but at a low amount of weight.

At baseline the women in the RT+protein and RT groups had similar handgrip and 1-RM chest

press strength values, however the 1-RM leg extension strength was significantly greater in the

RT+Protein group compared to the RT group at baseline (105.2 ± 24.4 kg vs. 88.1 ± 23.4 kg;

F(1,30)=4.103, p= 0.052). Therefore, an analysis of covariance was completed for the analysis of

leg extension strength. The analysis of covariance revealed that when the baseline 1-RM leg

extension was normalized at 96.8kg, there was no significant difference in the adjusted means at

12 weeks (means ± standard errors; RT+protein: 118.6 ± 3.11 vs. RT: 111.9 ± 3.11 kg; p=0.480).

There was no group by time interactions for 1-RM chest press, however a group by time effect

for handgrip strength was approaching significance (F(1,31) =3.538, p= 0.069, ES=0.102).

Significant time effects were observed for handgrip strength (F(1,31) =20.772, p≤0.05, ES=0.401),

1-RM chest press (F(1,31) =93.496, p≤0.05, ES=0.751) and 1-RM leg extension (F(1,30) =87.205,

67

p≤0.05, ES=0.744). The improvements in all measures of muscular strength from baseline to 12

weeks are displayed in Table 3. The RT+Protein group significantly improved handgrip strength,

1-RM chest press, and 1-RM leg extension by 4%, 32% and 23% respectively from baseline to

12 weeks. Likewise, the RT group increased their handgrip strength, 1-RM chest press, and 1-

RM leg extension by 9%, 39% and 17% respectively from baseline to 12 weeks. In order, to

ensure the aforementioned improvements were due to the RT intervention, the participants were

asked to maintain their regular physical activity levels for the duration of the 12-week

intervention.

Their physical activity levels were determined by the average daily steps measured

during one week at baseline, and again for one random week during the second and third months

of the study via a pedometer. Physical activity levels were not significantly different between the

RT+protein and RT groups at baseline (5,945 ± 2,777 vs. 6,700 ± 2,724 steps/day), at 4 weeks

(5,433 ± 1,896 vs. 6,790 ± 2,533 steps/day) and at 12 weeks (5,395 ± 2,027 vs. 5,912 ± 3,300

steps/day). There were no significant group by time or time effects observed in physical activity

levels.

Physical function as measured objectively by Continuous Scale-Physical Functional

Performance and a total function score of 57 or higher indicates a physical reserve that is

associated with a greater ability to live independently. The average total physical function did

not differ between the two groups at baseline. However, at baseline 3 women in the RT+protein

group and 2 women in the RT group had a total function score below 57 units. Of these 5

women, only one from each group completed the intervention and post-testing. The participant in

the RT+protein group increased her total function score from 51 to 58 during the 12-week

68

intervention whereas the participant in the RT group improved her total function score from 45

to 52 and thus was still below the functional threshold.

Table 3. Muscular Strength, Physical Activity and Physical Function (N=33)

RT Group (n=16) RT+PRO Group (n=17)

Baseline 12 weeks Baseline 12 weeks

Handgrip dynamometer

(kg) 47.9 ± 7.3 52.4 ± 7.5# 53.2 ± 9.2 55.1 ± 9.0#§

1-RM Chest press (kg) 78.5 ± 21.9 109.2 ± 28.8# 92.3 ± 21.5 121.5 ± 29.8#

1-RM Leg extension (kg) 88.1 ± 23.4 103.4 ± 25.8# 105.2 ± 24.4€ 128.9 ± 31.3#

Physical activity

(steps/day) 6,700 ± 2,724 59,12 ± 3,300 5,945 ± 2,777 5,395 ± 2,027

Continuous Scale-Physical Functional Performance (Units)a

Upper body strength 67.7 ± 16.4 71.5 ± 17.0

# 70.1 ± 15.5 76.0 ± 15.4

#

Upper body flexibility 80.5 ± 11.5 84.5 ± 7.8 83.0 ± 8.9 83.6 ± 8.3

Lower body strength 63.3 ± 18.6 69.4 ± 18.5

# 59.5 ± 15.6 65.3 ± 18.8

#

Balance & coordination 71.0 ± 15.5 74.9 ± 15.8

# 67.4 ± 13.1 69.5 ± 15.0

#

Endurance 72.1 ± 15.5 75.6 ± 16.2

# 68.2 ± 13.2 70.3 ± 15.2

#

Total function 69.8 ± 14.8 74.1 ± 15.5

# 67.2 ± 13.1 70.5 ± 15.2

#

Data are presented as mean ± standard deviation; RT+PRO=Resistance training + protein supplementation;

RT=Resistance training; 1-RM=One repetition maximum aScores range from 0-100; 0=worst function; 100=best function;

* p≤0.05, significantly different between groups at same time point # p≤0.05, significantly different from baseline within group

€ p≤0.05, significantly different between groups at baseline

§ p=0.069, significant difference between groups at 12 weeks

There were no significant group by time interactions observed for any of the measures of

physical function. However, there were significant time effects observed for all aspects of

physical function with the exception of upper body flexibility. Over the 12-week RT

69

intervention, the BCS significantly improved upper body strength by 7% (F(1,31) =7.967, p≤0.05,

ES=0.204), lower body strength by 10% (F(1,31) =22.612, p≤0.05, ES=0.422), balance and

coordination by 4% (F(1,31) =8.982, p≤0.05, ES=0.225), endurance by 4% (F(1,31) =9.656, p≤0.05,

ES=0.238) and total function by 5% (F(1,31) =18.512, p≤0.05, ES=0.374). Table 3 displays the

comparison between the RT+protein and RT groups in the measures of physical function at

baseline and 12 weeks.

4.4 Body composition

The comparison of anthropometric and body composition measurements are detailed in

Table 4. The anthropometric measures of body weight and BMI were not different between the

groups and did not change over the 12-week intervention. The BMI of the women in the study

ranged from 20.9 to 44.1 kg/m² at baseline and remained similar at 12 weeks (21.2 to 45.3

kg/m²). Similarly, waist and hip girth measures as well as the waist to hip ratios did not differ at

baseline. At baseline, the waist circumference for all the women averaged of 85.6 ± 13.6 cm and

ranged from 65.4 to 118.9 cm with eight women in the RT+protein group and four women in the

RT group having a waist circumference greater than 88 cm. Although there were no group by

time interactions in the girth measurements, there were significant time effects observed for

waist (F(1,31) =17.436, p≤0.05, ES=0.360) and hip (F(1,31) =7.019, p≤0.05, ES=0.185) girth, and

thus waist to hip ratio (F(1,31) =9.523, p≤0.05, ES=0.235). However, only one participant in the

RT+protein had a decrease in waist circumference from 89.3 to 81.2 cm. The remaining seven

participants in the RT+protein group and the four participants in the RT group with waist

circumferences greater than 88 cm did not reduce their waist circumferences below 88 cm. There

were no significant differences at baseline in measures of total body lean and fat mass, lean to fat

70

mass ratio, arms and legs lean mass, the ASMI, total and regional body fat percent and BMD as

measured by DXA. Total body lean mass and total body fat percent at baseline ranged from 25.4

to 52.4 kg and 30.0 to 52.8% respectively. In addition, the ASMI ranged from 4.68 to 10.66

kg/m² at baseline and one participant from the RT+protein group and one from the RT group had

an ASMI that fell below the sarcopenic threshold (<5.45 kg/m²). Neither participant increased

her ASMI above the sarcopenic threshold at the end of the 12-week RT intervention. There were

no group by time interactions in all measures of body composition with the exception of the lean

mass of the arms (F(1,31) =4.493, p≤0.05, ES=0.127). The lean mass of the arms increased to a

greater extent in the RT+protein group (8%) compared to the RT group (2%) from baseline to 12

weeks. Similar to the anthropometric measurements, there were significant time effects observed

for total body lean (F(1,31) =27.416, p≤0.05, ES=0.469) and fat mass (F(1,31) =6.012, p≤0.05,

ES=0.162), lean to fat mass ratio (F(1,31) =17.856, p≤0.05, ES=0.γ65), arms’ (F(1,31) =15.396,

p≤0.05, ES=0.γγβ) and legs’ (F(1,31) =21.269, p≤0.05, ES=0.407) lean mass, the ASMI (F(1,31)

=39.588, p≤0.05, ES=0.561), total body fat percentage (F(1,31) =23.366, p≤0.05, ES=0.430) as

well as android (F(1,31) =6.788, p≤0.05, ES=0.180) and gynoid (F(1,31) =24.746, p≤0.05,

ES=0.444) body fat percent. Therefore, both the RT+protein and RT groups observed similar

significant changes in total body lean (3% vs. 2%) and fat mass (-2% vs. -2%), lean to fat mass

ratio (5% vs. 4%), legs lean mass (2% vs. 3%), the ASMI (4% vs. 3%), total body fat percentage

(-1% vs. -1%) as well as android (-1% vs. -1%) and gynoid (-1% vs. -1%) body fat percent from

baseline to 12 weeks. There were no time effects for total body BMD observed during the 12-

week RT intervention.

71

Table 4. Body Composition (N=33)

Anthropometric

RT Group (n=16) RT+PRO Group (n=17)

Baseline 12 weeks Baseline 12 weeks

Weight (kg) 70.7 ± 14.8 70.9 ± 15.8 74.2 ± 15.0 74.6 ± 14.8

BMI (kg/m2) 27.2 ± 5.6 27.3 ± 6.0 27.9 ± 6.0 28.1 ± 6.1

Waist girth (cm) 82.7 ± 14.1 80.9 ± 13.8# 88.3 ± 13.0 86.2 ± 12.0#

Hip girth (cm) 106.6 ± 10.0 105.9 ± 9.9# 109.0 ± 11.5 108.2 ± 11.6#

Waist to Hip Ratio 0.77 ± 0.08 0.76 ± 0.09# 0.81 ± 0.06 0.80 ± 0.05#

Dual Energy X-ray Absorptiometry (DXA)

RT Group (n=16) RT+PRO Group (n=17)

Baseline 12 weeks Baseline 12 weeks

Lean mass (kg) 39.4 ± 6.1 40.1 ± 6.6# 41.3 ± 6.2 42.4 ± 6.4#

Fat mass (kg) 28.6 ± 9.5 28.1 ± 9.5# 30.1 ± 9.3 29.5 ± 9.6#

Lean/fat mass ratio 1.46 ± 0.37 1.52 ± 0.41# 1.46 ± 0.32 1.53 ± 0.35#

Arm lean mass (kg) 3.93 ± 0.84 4.03 ± 0.74# 4.16 ± 0.77 4.50 ± 0.80#¥

Leg lean mass (kg) 13.5 ± 2.7 13.9 ± 2.9# 14.2 ± 2.7 14.5 ± 2.8#

ASMI (kg/m2) 6.70 ± 1.3 6.87 ± 1.3# 6.87 ± 1.3 7.12 ± 1.3#

Total body fat (%) 41.4 ± 5.6 40.6 ± 5.7# 41.4 ± 5.4 40.3 ± 5.7#

Android fat (%) 42.3 ± 8.5 41.8 ± 8.6# 44.0 ± 7.4 42.7 ± 8.2#

Gynoid fat (%) 46.2 ± 5.7 45.0 ± 5.9# 45.4 ± 5.3 44.3 ± 5.6#

Android to gynoid ratio 0.92 ± 0.17 0.93 ± 0.17 0.97 ± 0.10 0.96 ± 0.11

Total BMD (g/ m2) 1.11 ± 0.17 1.11 ± 0.17 1.11 ± 0.11 1.11 ± 0.12

Total BMD T-score 0.33 ± 1.66 0.28 ± 1.64 0.29 ± 1.09 0.27 ± 1.16 Data are presented as mean ± standard deviation; RT+PRO=Resistance training + protein

supplementation; RT=Resistance training; BMI = Body mass index; BMD = Bone mineral density; # p≤0.05, significantly different from baseline within group

¥ p≤0.05, significantly different between groups at 1β weeks

72

4.5 Dietary and supplemental nutrient intake and adherence

Three-day dietary logs were analyzed at baseline, 6 and 12 weeks in order to compare the

caloric intake of the participants and to ensure the participant maintained their normal dietary

habits throughout the 12-week intervention period. The only exception would be an expected

increase in the protein, calcium and vitamin D intake of the BCS in the RT+protein as a result of

consuming their assigned protein supplement. At baseline, the BCS consumed an average of

1,758 ± 517 kcal/day, ranging from 214 kcal/day to 2,707 kcal/day, with an average of 16.4 ±

4.3% from protein (1.00 ± 0.32 g/kg/day), 46.0 ± 7.0% from carbohydrates, and 38.1 ± 5.0%

from fat. Furthermore, protein intake was significantly correlated with percent body fat (r=-

0.502) and lean to fat mass ratio (r=0.487) at baseline. The protein intake based on the three-day

dietary food recall at baseline of all the women ranged from 0.10 g/kg/day to 1.82 g/kg/day (7%

to 27 % of total calories from protein), with three women from the RT+protein group and five

women from the RT group consuming less than the RDA for protein (0.8 g/kg/day). Five women

from each group were consuming more than the recommended intake for aging adults (1.14

g/kg/day) and only one participant from the RT group was consuming more than the recently

recommended intake of 1.4-1.6 g/kg/day).

The range of protein intake for all the BCS remained similar (0.10 g/kg/day to 1.89

g/kg/day) at 12 weeks, however no women in the RT+protein group consumed less than the

RDA for protein whereas, five women in the RT group consumed less than the RDA, four of

whom did not at baseline and thus reduced their protein intake during the 12-week intervention.

At 12 weeks, 10 participants from the RT+protein group were consuming more than 1.14

g/kg/day, with six of those consuming more than 1.4 g/kg/day. Whereas, three women from the

73

RT group were consuming greater than 1.14 g/kg/day of protein at 12 weeks, two who consumed

less than 0.8 g/kg/day at baseline and therefore increased their protein intake.

The comparison of dietary intake between the RT+protein and RT groups is displayed in

Table 5. At baseline there were no significant differences in total caloric intake (kcal/d) between

the RT+protein (1,843.6 ± 473.1 kcal/d) and the RT (1,660.2 ± 563.0 kcal/d) groups, in addition

there were no differences between the groups in the intake of dietary protein (g/d), carbohydrate

(g/d) and fat (g/d), as well as dietary and supplemental calcium (mg/d), dietary vitamin D (IU).

There were significant time effects observed for changes from baseline to 6 weeks in total

calories consumed (F(1,30) = 4.593, p≤0.05, ES=0.133), protein intake in grams per day (F(1,30) =

6.594, p≤0.05, ES=0.180) and percent of total calories (F(1,30) = 23.485, p≤0.05, ES=0.439),

carbohydrate intake (g/d) (F(1,30) = 7.584, p≤0.05, ES=0.202), fat intake (% of total caloric

intake) (F(1,30) = 7.449, p≤0.05, ES=0.199). However, there were no significant group by time

interactions for changes in total caloric intake, as well as protein, carbohydrate, and fat intake

(g/d and % of total caloric intake) at 6 weeks. The protein intake in grams per day did increase to

a greater extent from baseline to 6 weeks in the RT+protein group (72.1 ± 12.5 g/d to 91.5 ± 27.8

g/d) compared to the RT group (70.8 ± 29.4g/d to 77.6 ± 37.0 g/d) but was not statistically

different. In addition, percent of total calories from protein at 6 weeks was similar between the

RT+protein and RT groups (21.4 ± 3.8 vs. 20.1 ± 6.4%). These results suggest that from baseline

to 6 weeks the changes in protein intake occurred in contrast to our expectations. In addition

there were no significant time or group by time interactions in any of the dietary variables from 6

weeks to 12 weeks. However, the changes from baseline to 12 weeks did increase as we

anticipated. As a result of the daily supplemental protein provided to the RT+protein group there

was a significant group by time interaction (F(1,30) =4.529, p≤0.05, ES=0.131) for the percent of

74

total caloric intake coming from protein with the women in the RT+protein group increasing

their protein intake (% of total caloric intake) from 16.2 ± 3.9 to 21.2 ± 4.2% compared to the

women in the RT group who maintained their protein intake (% of total caloric intake) from

baseline to 12 weeks (16.6 ± 4.9 to 17.3 ± 6.5%). There was also a significant time effect for

changes in protein intake (% of total caloric intake) (F(1,30) =8.178, p≤0.05, ES=0.214). There

was no significant time effect for changes in protein intake in grams per day (g/d) but it was

approaching significance (p=0.083) for a group by time interaction for protein intake with the

RT+protein increasing their intake of protein from baseline to 12 weeks (72.1 ± 12.5 to 89.7 ±

14.7 g/d) compared to the RT group (70.8 ± 29.4 to 69.3 ± 36.2 g/d). At 12 weeks the protein

intake for the RT+protein group was significantly greater than the RT only group (89.7 ± 14.7

g/d vs. 69.3 ± 36.2 g/d, respectively; F(1,30) =4.576, p≤0.05). The protein spread (% difference in

protein intake between experimental and control group) at 12 weeks was 29.4%. Bosse & Dixon

(23) reported that a protein spread of at least 66.1% has been observed in those studies that

reported group differences between the groups consuming and not consuming protein during an

RT intervention. However, since we did not observe any group by time interactions in protein

intake from baseline to 6 weeks and considering both groups actually increased protein intake

during the first 6 weeks of the intervention, we decided to take the average of the 6-week and 12-

week three-day logs to determine whether the RT+protein group actually consumed significantly

more protein compared to the RT only group during the 12-week intervention. Further analyses

revealed that there were significant time effects for changes in protein intake in grams per day

(F(1,30) =5.013, p≤0.05, ES=0.143) and percent of total calories (F(1,30) =17.613, p≤0.05,

ES=0.370) from baseline to the average of the 6-week and 12-week food logs. However, there

was no significant group by time effect for protein intake (g/d and % of total calories from

75

protein) from baseline to the average of the 6-week and 12-week food logs. These findings

indicate that there was variance in the protein intake of both groups and that the supplement

provided to the RT+protein group did not actually significantly increase the amount of protein

consumed during the 12-week intervention period. This suggests that the participants in both

groups made changes to their habitual dietary intake during their participation in the 12-week

intervention contrary to our instructions or they may not have accurately completed their three-

day dietary food logs.

This is a possible explanation because the protein change (change in habitual protein

intake) of the RT+protein group was an average of 27.3 ± 34.5% and ranged from -2.8% to

143.1%. Whereas, the protein change of the RT only group averaged 5.19 ± 45.3% and ranged

from -69.6% to 96.2%. Further analysis for group differences in changes in lean mass were

performed to only include the participants in the RT+protein group that had a protein change

greater than 20% (n=8) and a group by time effect that was approaching significance was

observed (F(1,22) =3.389, p=0.079, ES=0.133). Therefore, the RT+protein group increased lean

mass to a greater extent when compared to the RT (+1.47kg vs. +0.68kg; p=0.079), although not

significantly. However, when additional analysis for group differences in changes in lean mass

were performed that only included the participants in the RT+group that had a protein change

greater than 40% (n=4) the group by time interaction was no longer significant (p=0.617). There

were also no group differences when comparing those in the RT+group that had a protein change

greater than 40% and those in the RT group that did not have a positive protein change. Only one

participant in the RT+group and two participants in the RT group achieved a protein change

above the recommended 59% (23).

76

Table 5. Diet and Supplemental Nutrient Intake (N=32)

RT Group (n=15)

Baseline 6 weeks 12 weeks

Total calories (kcal/d) 1,660.2 ± 563.0 1,466.2 ± 479.5# 1,509.3 ± 514.6

Protein (g/d) 70.8 ± 29.4 77.6 ± 37.0# 69.3 ± 36.2*§

Protein (%) 16.6 ± 4.9 20.1 ± 6.4# 17.3 ± 6.5*#¥

Carbohydrate (g/d) 196.3 ± 71.5 172.8 ± 58.2 185.3 ± 79.3

Carbohydrate (%) 48.0 ± 7.6 47.9 ± 7.0*# 49.1 ± 10.3*

Fat (g/d) 68.2 ± 3.3 56.0 ± 3.5 59.9 ± 4.4

Fat (%) 37.0 ± 5.3 34.4 ± 6.6# 35.7 ± 7.7

Dietary Calcium (mg/d) 900 ± 426

798 ± 381*£ 719 ± 331*#¥

Dietary Vitamin D (IU/d) 221 ± 222

200 ± 179*#£ 152 ± 252*#

Supplemental Calcium (mg/d) 1,202 ± 440

1,202 ± 440 1,202 ± 440

Supplemental Vitamin D (IU/d) 1,671 ± 632

1,671 ± 632 1,671 ± 632

RT+PRO Group (n=17) Baseline 6 weeks 12 weeks

Total calories (kcal/d) 1,843.6 ± 473.1 1,710.3 ± 441.6# 1,725.8 ± 315.3

Protein (g/d) 72.1 ± 12.5 91.5 ± 27.8# 89.7 ± 14.7*§

Protein (%) 16.2 ± 3.9 21.4 ± 3.8# 21.2 ± 4.3*#¥

Carbohydrate (g/d) 204.4 ± 62.3# 180.8 ± 50.8 174.4 ± 52.6

Carbohydrate (%) 44.2 ± 6.2 42.8 ± 7.1*# 40.3 ± 8.3*

Fat (g/d) 80.3 ± 2.3 65.6 ± 3.3 68.8 ± 2.3

Fat (%) 39.2 ± 4.4 34.5 ± 6.7# 35.9 ± 6.5

Dietary Calcium (mg/d) 763 ± 179

1,189 ± 559*£ 1,324 ± 413*#¥

Dietary Vitamin D (IU/d) 179 ± 176

374 ± 272*#£ 468 ± 244*#¥

Supplemental Calcium (mg/d) 1,239 ± 363

1,239 ± 363 1,239 ± 363

Supplemental Vitamin D (IU/d) 1,828 ± 1,220

1,828 ± 1,220 1,828 ± 1,220

Data are presented as mean ± standard deviation RT+PRO=Resistance training + protein supplementation; RT=Resistance training; * p≤0.05, significantly different between groups at same time point; # p≤0.05 significantly different from baseline within group p≤0.05 ¥ p≤0.05, significantly different between groups at 1β weeks

£ p≤0.05, significantly different between groups at 6 weeks

§ p=0.083, approaching a significant difference between groups at 12 weeks

77

However, there was a group by time interaction (F(1,30) =8.075, p≤0.05, ES=0.212) for

changes in dietary calcium intake (mg/d) from baseline to 6 weeks but there were no significant

time or group by time interaction for changes in calcium intake from 6 weeks to 12 weeks. In

addition, there were significant group by time (F(1,30) =30.366, p≤0.05, ES=0.503) and significant

time (F(1,30) =7.982, p≤0.05, ES=0.210) interactions for changes in dietary calcium intake from

baseline to 12 weeks with the women in the RT+protein group increasing their dietary calcium

intake from 763 ± 179 to 1,324 ± 413 mg/d whereas, the women in the RT group decreased their

dietary calcium intake from 900 ± 426 to 719 ± 331 mg/d. Furthermore, group by time (F(1,30) =

8.598, p≤0.05, ES=0.223) and significant time (F(1,30) = 5.545, p≤0.05, ES=0.156) effects were

observed for changes in dietary vitamin D intake (IU/d) from baseline to 6 weeks. There were no

significant time or group by time interaction for changes in vitamin D intake from 6 weeks to 12

weeks. From baseline to 12 weeks, there were also significant group by time (F(1,30) =13.317,

p≤0.05, ES=0.307) and significant time (F(1,30) =5.012, p≤0.05, ES=0.143) effects for changes in

dietary vitamin D intake following the same trend as the changes in calcium intake. The

RT+protein group increased their dietary vitamin D intake from 179 ± 176 to 468 ± 244 IU/d

while the RT group experienced a decrease in their intake of vitamin D from 221 ± 222 to 152 ±

252 IU/d.

4.6 Blood biomarkers

The comparisons between RT+protein and RT groups in baseline and 12-week

measurements of the blood biomarkers of muscle (IGF-1) and fat (adiponectin) metabolism as

well as inflammation (CRP) are displayed in Table 6. Of the 33 women that enrolled in the

study, two did not complete the 12-week intervention due to medical complications not related to

78

cancer, one participant dropped out during the 7th week because of the time commitment, and

two had unsuccessful post intervention blood draws. Therefore, a total of five women did not

have 12-week blood samples for analysis, thus 28 samples underwent analysis via ELISA. The

averages of the duplicate samples were used for analysis. Furthermore, only samples with

coefficient of variation less than 20% were analyzed. Only one sample from the IGF-1 ELISA kit

had a coefficient of variation of 28% and was therefore dropped from analysis. The intra-assay

coefficients of variation for IGF-1, adiponectin, and CRP were 10.8%, 4.6%, and 2.8%

respectively. In addition, the inter-assay coefficients of variation for IGF-1, adiponectin, and

CRP were 15.7%, 6.7% and 3.3% respectively.

At baseline, the average values for IGF-1, adiponectin and CRP for the 28 participants

who had serum samples analyzed were 109.6 ± 40.3 ng/mL, 12.71 ± 7.06 mg/L and 1.72 ± 1.07

mg/L respectively. The values for IGF-1 ranged from 41.1 ng/mL to 200.6 ng/mL at baseline,

and all participants were within the normal ranges for IGF-1 of 40-258 ng/mL. Furthermore, the

12-week measures of IGF-1 ranged from 46.9 ng/mL to 202.5 ng/mL and therefore remained

within the normal values for IGF-1. Serum levels for adiponectin ranged from 1.35 mg/L to 32.7

mg/L at baseline, with two participants in the RT group above the normal range for adiponectin

of 0.865-21.4 mg/L. The adiponectin levels ranged from 1.51 mg/L to 26.3 mg/L at 12 weeks,

with the same two participants remaining above the normal range of adiponectin, one of which

maintained her levels at 24.7 mg/L whereas, the other reduced from 32.7 mg/L to 26.2 mg/L. At

baseline, IGF-1 and adiponectin values were similar between the groups. However the women in

the RT+protein group had significantly greater CRP values than the women in the RT group

(2.14 ± 1.17 mg/L vs. 1.24 ± 0.71 mg/L; p≤0.05) and these differences between the two groups

remained at 12 weeks (1.91 ± 0.95 mg/L vs. 1.26 ± 0.70 mg/L; p≤0.05). The CRP values for all

79

the participants ranged from 0.246 mg/L to 4.70 mg/L, with four women in the RT+protein

group that were above 3.0 mg/L which is considered a high CRP threshold although the normal

values for healthy adults range from 0.109-4.29 mg/L. Of the four women above 3.0 mg/L of

CRP, only one had a CRP value greater than 4.29 mg/L and was the only one of the four women

that remained above 3.0 mg/L after the 12 weeks of RT. However, one participant in the

RT+protein group had an increase in CRP from 2.29 mg/L at baseline to 3.20 mg/L at 12 weeks.

There were neither time nor group by time interactions in any of the blood biomarkers with the

exception of a significant time effect observed in IGF-1 (F(1,25) =5.631, p≤0.05, ES=0.184). The

mean values of serum measurements of IGF-1 for both groups significantly increased from 106.2

± 36.8 ng/mL to 115.7 ± 34.6 ng/mL. Furthermore, at baseline CRP was negatively correlated

with adiponectin (r= -0.412; p≤0.05) and was positively correlated with total body weight

(r=0.634; p≤0.01), BMI (r=0.588; p≤0.01) android body fat (r=0.509; p≤0.01), lean mass

(r=0.565; p≤0.01), fat mass (r=0.610; p≤0.01) and total body fat % (r= 0.4ββ; p≤0.05). In

addition, baseline values of adiponectin were negatively correlated with total body weight (r=-

0.403; p≤0.05), BMI (r=-0.453; p≤0.05), android body fat (r=-0.538; p≤0.01), lean mass (r=-

0.388; p≤0.05), fat mass (r=-0.376; p≤0.05). At 1β weeks, CRP no longer had a significant

positive correlation with total body weight, lean mass and total body fat %. However, a

significantly negative correlation remained between CRP and adiponectin (r=-0.503; p≤0.05),

and CRP was still positively correlated with BMI (r=0.376; p≤0.05), android body fat (r=0.γ79;

p≤0.01), and fat mass (r=0.401; p≤0.05). Similarly, significantly negative correlations between

adiponectin and total body weight (r=-0.467; p≤0.05), BMI (r=-0.498; p≤0.05), android body fat

(r=-0.516; p≤0.01), lean mass (r=-0.482; p≤0.01), fat mass (r=-0.400; p≤0.05) remained at 1β

80

weeks Interestingly, in contrast to baseline correlations, IGF-1 was negatively correlated with

total body fat % at 12 weeks (r=-0.404; p≤0.05).

Table 6. Blood Biomarkers (N=32)

Biomarker of muscle metabolism

RT Group (n=12) RT+PRO Group (n=15)

Baseline 12 weeks Baseline 12 weeks

IGF-1 (ng/mL) 101.2 ± 33.0 α 112.0 ± 32.8α# 110.2 ± 40.2 118.7 ± 36.9#

Biomarker of fat metabolism

RT Group (n=13) RT+PRO Group (n=15)

Baseline 12 weeks Baseline 12 weeks

Adiponectin (mg/L) 14.97 ± 8.43 14.66 ± 7.78 10.75 ± 5.14 9.57 ± 4.68

Biomarker of inflammation

RT Group (n=13) RT+PRO Group (n=15)

Baseline 12 weeks Baseline 12 weeks

CRP (mg/L) 1.24 ± 0.71€ 1.26 ± 0.70¥ 2.14 ± 1.17€ 1.91 ± 0.95¥ Data are presented as mean ± standard deviation. RT+PRO=Resistance training + protein supplementation; RT=Resistance training alone;

IGF-1= Insulin-like growth factor; CRP = C-reactive protein; α

sample contains one participant less due to

a coefficient of variation greater than 20%.

# p≤0.05 significantly different from baseline within group p≤0.05 € p≤0.05, significantly different between groups at baseline; ¥ p≤0.05, significantly different between groups at 12 weeks

4.7 Lymphedema history and monitoring

The comparison in lymphedema history at baseline between the RT+protein and RT

groups is detailed in Table 7. At baseline, the RT+protein and RT groups shared similar

characteristics in having history of complications with lymphedema (18% vs. 19%, respectively),

lymph nodes removed from the right arm (41% vs. 31% respectively), lymph nodes removed

from the left arm (35% vs 19% respectively) and lymph nodes removed from both arms (6% vs.

6%, respectively). However, more women in the RT group (44%) did not have any lymph nodes

removed from either side compared to the number of women in the RT+protein group (18%).

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Exacerbation of lymphedema as a result of the RT in all the women participating in the

study regardless of having lymph nodes removed was monitored on the first RT training session,

and repeated during the first training sessions of week 5 and week 9 of the study.

Table 7. Lymphedema History at Baseline (N=33)

RT Group (n=16) RT+PRO Group (n=17)

History of complications with lymphedema 19% 18%

Lymph nodes removed from right arm (%) 31% 41%

Lymph nodes removed from left arm (%) 19% 35%

Lymph nodes removed from both arms (%) 6% 6.0%

No lymph nodes removed from either arm (%) 44% 18%

Data are presented as % of sample for categorical data; RT=Resistance training; RT+PRO=Resistance training + protein supplementation

Lymphedema was monitored by taking circumference measurements every 3cm along the

involved arm (the arm with lymph nodes removed) and uninvolved arm (the arm without any

lymph nodes removed), and then calculating the percent difference between the arms. A positive

percent difference indicates the involved arm had greater volume than the uninvolved and

indicates the possibility of edema. However, a greater than 10% difference is the diagnostic

criteria for the presence of lymphedema. Among the participants that did not have any lymph

nodes removed from either side of their upper body, the percent difference between the arm with

the larger volume and the arm with the lesser volume was analyzed. Interestingly, although less

women in the RT group had any lymph nodes removed during surgery, the baseline comparison

of the upper extremity percent difference between the involved arm and uninvolved arm was

significantly (F(1,31) =4.266, p≤0.05) greater in the RT group (9.5 ± 11.2%) compared to the

RT+protein group (1.8 ± 10.2%) as displayed in Figure 5. There was a significant group by time

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interaction observed in percent difference between the involved arm and uninvolved arm with

the RT group decreasing from 9.52 ± 11.2% in week 1 to 0.18 ±7.7% in week 5 (F(2,31) =3.904

p≤0.05, ES=0.112) whereas the RT+protein group changed from 1.82 ± 10.2% to 1.87 ± 7.4%

from week 1 to week 5 of the RT intervention respectively. In addition a significant time effect

was also observed in percent difference between the involved arm and uninvolved arm with the

average difference in arm circumference of all the participants decreasing from 5.6 ± 11.2% in

week 1 to 1.1 ± 7.5% in week 5 and increasing to 2.0 ± 5.6% in week 9 (F(2,31) =4.177 p≤0.05,

ES=0.119)(Figure 5). Therefore, the RT intervention reduced the percent difference in volume

between the involved arm and uninvolved arm in the women participating in this study and thus

did not exacerbate lymphedema.

Figure 5. Upper extremity lymphedema measurements: % difference between involved

versus uninvolved arms (N=33). RT=Resistance training; RT+PRO=Resistance training +

protein supplementation; * significantly different from RT+PRO at baseline p≤0.05.

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Further analysis was conducted on only the women in both groups that had lymph nodes

removed as a result of breast cancer. Similar trends in difference between groups at baseline and

changes in measurements between weeks 1 and 5 as well as weeks 5 and 9 (Figure 6). In the

women who had lymph nodes removed, those in the RT group (n=9) no longer had significantly

greater differences in percent arm circumference than those in the RT+protein group (n=13) (6.4

± 12.4% vs 2.8 ± 9.1%). There were no significant time nor group by time interactions in the

differences in percent arm circumference between the involved arm and uninvolved arm.

Figure 6. Upper extremity lymphedema measurements: % difference between involved

versus uninvolved arms with only participants that had lymph nodes removed (N=22).

RT=Resistance training; RT+PRO=Resistance training + protein supplementation.

Lastly, Figure 7 displays the changes in percent difference in arm circumference with all

the women grouped together. The percent difference in arm circumference decreased

significantly from week 1 to week 5 (F(2,31) =3.904 p≤0.05, ES=0.112) but not from weeks 5 to 9.

One participant experienced self-reported upper extremity swelling in the involved arm after

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week 1 of the study, therefore upper body exercise intensity was reduced from the initially

prescribed 65% to 50% of 1-RM and was slowly progressed throughout the study until week 9

when she returned to 65% of upper body 1-RM.

Figure 7. Upper extremity lymphedema measurements: % difference between involved

versus uninvolved arms with all participants (N=33).

RT=Resistance training; RT+PRO=Resistance training + protein supplementation.

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CHAPTER 5

DISCUSSION

The main findings of the present study demonstrate that 12 weeks of RT at moderately

high intensity (65-81% 1-RM) was sufficient to significantly increase muscular strength,

physical function, lean body mass and decrease fat mass in female BCS with no adverse effects

on lymphedema nor increases in IGF-1 beyond normal ranges. In fact the RT significantly

decreased lymphedema for those women who had higher values at baseline. The RT intervention

significantly increased serum levels of IGF-1, a biomarker of muscle accretion but did not have

an effect of serum levels of adiponectin and human CRP. Although, the protein supplement

appeared to provide additional benefits to the RT intervention for gains in lean mass in the upper

body, confounding factors may have influenced these results. The training volume of the upper

body exercises performed was approaching significance (p=0.07) to be greater in the RT+protein

group and considering the RT+protein group did not significantly increase protein intake over

the entire 12-week intervention we cannot conclude that the protein supplement consumed in the

present study provided additional benefits to the RT intervention. Perhaps the somewhat higher

intake of protein allowed the women in this group to recover quicker and perform more

repetitions of the exercises, which may have influenced upper body lean mass in the present

study. Further research needs to be completed on evaluating the effects of compliance to

increased levels of protein and the amount of protein that should be consumed by this population

to elicit changes in body composition. Therefore, we must reject our hypothesis that greater

changes in body composition, muscular strength, physical function and blood biomarkers would

be seen in BCS who consumed a protein supplement combined with resistance training

compared to a BCS who only resistance trained.

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5.1 Muscular strength, physical activity and function

The improvements in muscular strength and physical function in the present study are

congruent with other studies that have utilized RT at varying intensities in female BCS (59, 248,

282). Similar to our findings, studies have reported significant improvements in muscular

strength in both breast cancer patients undergoing treatment (59) and BCS (236, 248, 282). In

breast cancer patients, Courneya et al. (59) reported significant improvements in upper body

strength (8-RM on bench press) and lower body strength (8-RM on leg extension) when

compared to patients undergoing normal care after 16 weeks of RT (2-4 sets; 10 repetitions; 80%

of 1-RM; 2 days per week). The advantage of performing RT while undergoing treatment to

maintain muscular strength is of relevance to BCS as Simonavice et al. (247) reported that once

completed treatment, BCS were 17% and 29% weaker in upper and lower body strength

respectively, than healthy age-matched postmenopausal women. In a later study Simonavice et

al. (248) observed that after a 6-month RT intervention performed twice a week for 2 sets of 8-12

repetitions at an intensity of 52-69% of 1-RM, both the upper and lower body strength gained by

BCS at the end of the intervention was similar to untrained healthy age-matched postmenopausal

women. Interestingly, although measured on the same resistance machines (248), the upper body

(averages ranging from 80 ± 17 to 91 ± 20kg) and lower body (averages ranging from 87 ± 28 to

100 ± 21kg) strength of 27 BCS after the 6-month intervention (163) was lower than that

observed in the overall values of upper (116 ± 29kg) and lower body (116 ± 31kg) strength after

the present 12-week intervention. The differences in the muscular strength improvements

between the present study and that of Simonavice et al. (248) are largely explained by the

differences in the average exercise intensities throughout the study (65-81% vs. 52-69% of 1-RM

respectively) and training volume (3 sets vs. 2 sets respectively) utilized. In any case, regardless

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of exercise intensity and volume, the aforementioned studies and others (236, 282) demonstrate

the ability of RT to help BCS gain the strength lost as a result of cancer treatments and physical

inactivity, and plausibly exceed that of their healthy age-matched physically inactive

counterparts.

Ultimately, the improvements in muscular strength lead to improvements in physical

function as measured objectively using the CS-PFP assessment. The BCS survivors in the

present study significantly improved their total physical function score as well as all the

subscales of physical function (upper body strength, lower body strength, balance and

coordination, and endurance) with the exception of upper body flexibility. In agreement, a

previous study from our laboratory reported similar significant improvements at 12 weeks in all

the subscales of the CS-PFP except upper body flexibility (163). This may be due to the fact that

the intervention did not include any prescribed flexibility training other than the full body

stretches performed after each RT session. As the RT sessions were only twice a week, the

amount of stretching performed during the intervention fell short of the recommended American

College of Medicine guidelines to see improvements in flexibility (≥ β-3 day per week) (106). To

date, our previous study (163) and the present study are the only ones to utilize the CS-PFP to

objectively measure physical function in BCS after a RT intervention. In contrast to our findings,

Cheema and Gaul (47) reported a significant improvement in upper body shoulder range of

motion of flexion, extension and abduction using a Leighton flexometer in both the ipsilateral

(surgical) and contralateral shoulders of the side of the body affected with cancer following an 8-

week RT intervention. However, the BCS in the study by Cheema and Gaul were part of a BCS

dragon boat team and thus were likely more physically flexible than the participants in the

present study. The two tasks of the CS-PFP that contribute to the assessment of upper body

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flexibility include a jacket task and a reach task. During the jacket task, participants are asked to

pick up a jacket, put it on, pull the fronts of the jacket together and remove the jacket as quickly

as possible without zipping or buttoning the jacket. The score is based on the time it takes to

complete the task, but it is not likely that the arm located on the side of the body affected by

breast cancer (involved arm) would affect the outcomes of this task. However, the reach task

requires the participants to place a sponge on a shelf, let go and then remove the sponge off the

shelf in a controlled manner. It is not a timed test, and the participants’ scores are based upon

how high they can reach and place the sponge on the shelf with complete control. It is plausible

that this task may have been confounded by whether or not the BCS used their involved arm for

the testing assessments, and thus may explain the lack of significance observed for this one

subscale of physical function. Therefore, future studies may need to control for whether the

participants use their involved arm or uninvolved arm of surgery for all assessments of the reach

task in the CS-PFP. Furthermore, although the BCS improved muscular strength, Winters-Stone

et al. (282) did not observe any significant improvements in both subjective (SF-36 Physical

Function scale and Late-Life Function and Disability Instrument) and objective (Physical

Performance Battery - five repeated chair stands, standing balance, 4 m usual gait walk test)

physical function after a 52-week RT and impact (jump) exercise intervention (1-3 sets; 8-12

repetitions; 60-80% of 1-RM; 3 days per week).

Most importantly, the results of the present study and of a previous study (47)

demonstrate the ability of RT to increase physical function in BCS. As the CS-PFP is a series of

tasks that mimic routine activities of daily living, our findings suggest that moderately vigorous

RT performed twice a week can counteract the effects of cancer treatments and physical

inactivity and thus enable BCS to live independently and possible delay the arrival of disability

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associated with aging. As the women in both groups experienced similar improvements in

muscular strength and physical function, it appears that increasing protein intake in BCS may not

augment the effects of RT on strength and physical function.

5.2 Body composition

This is one of only two studies that we are aware of to observe a significant training

effect on total and regional lean body mass. Previous studies (16, 59, 235, 248) have utilized

various intensities and have observed significant differences between the RT experimental group

and the non-RT control groups but to the best of our knowledge only one other study (235) has

found a significant time effect on changes in lean body mass in the groups participating in RT

and few have observed changes in fat mass. Nevertheless, in those studies that found significant

differences between the RT groups, and non–exercising controls in body composition variables,

Battaglini et al. (16) found a 4% increase in lean body mass and an 11% decrease in body fat

percentage compared to a 1% reduction in lean body mass and 4% increase in percent body fat in

the control group after a 21-week combined RT (2-3 sets; 40-60% of 1-RM; 2 days per week)

and aerobic training program. This study utilized the 3-site skinfold method to measure body

composition, which may be a less accurate technique to assess body composition. Similarly, a

one-year resistance and impact (jump) exercise program (1-3 sets; 8-12 repetitions; 60-80% of 1-

RM; 3 days per week) (284) and a 16-week of combined RT (2-4 sets; 10 repetitions; 80% of 1-

RM; 2 days per week) and aerobic training intervention did not elicit significant training effects

on body composition in BCS. It appears, the varying intensities (% of 1-RM), training volume

(sets, repetitions, days per week) and progression utilized in these studies may explain why the

BCS did not experience significant changes in body composition over time. In contrast, the

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present study observed significant changes over time, with the BCS experiencing average

changes of +2% (+0.88 kg) in lean body mass, -2% (-0.51 kg) in body fat, -1% in body fat

percentage, +5% in the lean to fat mass ratio, and +3% in the ASMI. Similar to our findings, a 6-

month RT intervention (3 sets; 10-12 RM, ~ 67-70% of 1-RM; 2 days per week) by Schmitz et

al. (235) that used the DXA to assess body composition found lean mass to significantly increase

from baseline in RT by 0.88 ± 0.23 kg as well as a significant reduction in body fat percentage (-

1.15 ± 0.45 %). It is important to note that these changes occurred after 6 months of RT, whereas

the significant improvements in body composition in the present study, although modest, were

observed after only 12 weeks of RT performed twice a week. Be that as it may, the training

volume and intensity utilized that used a superset design, and most importantly had the women

perform their 3rd set of each exercise to muscular fatigue, and thereby exceeding the 12

repetitions, often utilized in studies, created a greater volume and intensity than that used in

previous studies. Furthermore, this approach allowed us to appropriately increase the amount of

weight lifted by each participant at the beginning of each week depending on the amount of

repetitions above 10 repetitions she was able to perform during her 3rd and final set of each

exercise. Thus, the protocol utilized in this present study ensured that the moderately vigorous

exercise intensity was maintained and progressed according to each participant’s weekly strength

increases. The RT protocol utilized in the present study performed over a longer duration than 12

weeks has the potential to result in even greater changes in body composition over time.

This is plausible because a previous 6-month RT intervention from our laboratory (248)

performed similar exercises, twice a week as those in the present study, and prescribed a regimen

of 10 exercises, for 2 sets of 8-12 repetitions at an intensity of 52-69% of the 1-RM therefore the

participants never exceeded 69% of their previous 1-RM (measured every 4 weeks) for both

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upper body and lower body strength. The BCS in the present study began their RT at 65% of

each participant's 1-RM in week one of the intervention and performed 2 sets of 10 repetitions

and a 3rd set (>10 repetitions) to muscular exhaustion on 10 exercises performed in a superset

design. The present study design provided a training volume sufficient to increase lean body

mass, but more importantly the women in both groups trained at a similar intensity throughout

the study and progressed according to the target exercise intensity. The BCS in the present study

progressed to an average of 70 ± 5% of the baseline upper body 1-RM during the first 6 weeks

and to 76 ± 7% of their 6-week (mid-study) upper body 1-RM by week 12. Their lower body

exercise intensity progressed from an average 69 ± 5% of baseline 1-RM during the first 6 weeks

to a more vigorous intensity of 81 ± 9% of their 6-week 1-RM during the last 6 weeks. The RT

sessions were well tolerated with an adherence rate of 90%.

Although the adherence to the protein supplement was on average 90.7 ± 8.6 %, with the

exception of changes in the lean mass of the arms, there was no added benefit on changes in

body composition from consumption of the daily protein supplement. However, as previously

stated, the greater improvements in the lean mass of the arms observed in the RT+protein group

is largely explained by the somewhat greater training volume in upper body exercises performed

by the women in the RT+protein group. The absence of any group differences in the remaining

measures of body composition is most likely due to the prescribed 40g of added protein not

creating an adequate protein change to elicit a group by time effect. It was also found that the

women even though compliant to the supplement changed the amount of protein being consumed

in their diet at different time points throughout the study. Therefore we cannot be certain that the

women had the increased protein stimulus throughout the entire 12-week intervention. In

addition, Bosse & Dixon (23) described protein change as the change in habitual protein intake

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from baseline, and have reported that an average protein change of at least +59.5% is needed to

observe group differences in interventions using protein and RT. The protein change for the

RT+protein group in the present study was only +27.3 ± 34.5% and therefore adding 40 g of

protein, consumed in two separate 20 g ready to drink bottles, to the habitual diet of the BCS in

this study was not sufficient to demonstrate an additional benefit of protein. Although the

participants in the present were asked to maintain their regular dietary intake throughout the

study duration, the protein change of the participants in the RT+protein group ranged from -2.8%

to 143.1%. This presents a major limitation of our study because the protein we provided in our

study did not actually supplement the dietary protein consumed by each participant, as those that

had a negative or a moderately positive (+1 to 10%) protein change most likely reduced their

dietary protein intake to compensate for the protein beverage provided during the study. When

an analysis for group differences was performed in changes in lean mass with only those

participants in the RT+protein group that had a protein change greater than 20% (n=8) a group

by time effect that was approaching significance was observed (p=0.079) for total lean body

mass. A greater than 20% protein change in the RT+protein group resulted in greater increase in

total body lean mass that was approaching significance when compared to the RT (+1.47kg vs.

+0.68kg; p=0.079 ). As only one participant in the RT+protein group had a protein change

greater than the recommended +59.5%, future studies should either standardize the diet of their

participants or collect more frequent dietary logs to continuously ensure dietary habits are

actually being maintained and thus the protein beverage is indeed supplementing the diet of the

experimental group. Furthermore, Bosse & Dixon (23) also reported that a protein spread,

defined as the difference in protein consumed (g/kg/day) between the experimental and control

groups, of at least 66.1% has been observed in those studies that reported group differences

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between the groups consuming and not consuming protein during an RT intervention. The

protein spread observed in the present study was 29.4% and therefore not adequate to produce an

effect. This is evident as the protein change in the RT group ranged from -69.6% to 96.2%, thus

some participants increased their dietary protein therefore this did not create an adequate

difference between average intake of the RT+protein (experimental) and RT group (control) even

though the difference in protein intake (% of total caloric intake) at 12 weeks was significantly

different (21.2 ± 4.2 % vs. 17.3 ± 6.5%). It is important to note that the studies reviewed by

Bosse & Dixon to determine the recommendations for protein change and spread were in non-

cancer related populations and thus the requirements may be different for BCS. Nevertheless,

future RT and protein interventions for BCS do need to create a sufficient protein change and

spread to further elucidate the potential benefits of increased protein intake to augment the

positive changes in body composition as a result of RT. Therefore the exercise intensity utilized

in the present study appears to be the determining factor for the significant increases in lean body

mass and decreases in fat mass that are not often observed in female BCS.

5.3 Dietary and supplemental nutrient intake and adherence

With the exception of the lean mass in the arms, the absence of any group differences in

changes in the measures of body composition between the RT+protein and RT, were likely

because of the inadequate protein change and spread. Therefore our findings do not support our

hypothesis that the RT+protein group would demonstrate greater increases in lean body mass and

greater decrements in fat mass compared to the BCS participating in RT alone. Participants

completed three-day dietary food logs at baseline, 6 weeks and at 12 weeks. The women in both

groups consumed a similar amount of protein from their diet at baseline (RT+protein: 1.00 ±

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0.24 g/kg/day vs. RT: 0.99 ± 0.39 g/kg/day) and all the women averaged 1.00 g/kg/day of protein

or 16% of total calories coming from protein in their diet. Early studies recommend that aging

adults (56-80 years) need to consume 1.14 g/kg/day of protein (40) and more recently the

recommendation has increased to 1.4-1.6 g/kg/day (25, 51). At baseline, of the 32 women that

completed the three-day food logs, 24 of them consumed more than the RDA for protein (0.8

g/kg/day) and 8 BCS consumed less than the RDA. In addition, 10 BCS consumed more than the

recommended 1.14 g/kg/day of protein for aging adults at baseline. Protein intake at baseline was

significantly correlated with percent body fat (r=-0.502) and lean to fat mass ratio (r=0.487) in

the present study. In contrast, a previous study (197) from our laboratory found significant

correlations between protein intake and total body (r=0.502) and total femur (r=0.511) BMD in

27 BCS but did not find any relationships between protein intake and any other measures of body

composition. The participants in the present study were younger (59±8 yrs) than the BCS in the

study by Page et al. (197) (age: 64±7yrs) even though they consumed an average protein intake

(1.06±0.54 g/kg/day) similar to that of the BCS in the present study. Nevertheless, both studies

suggest that a higher amount of habitual protein in the diet of BCS may modulate body

composition. The present study aimed to determine whether increasing the amount of protein

through supplementation during an RT intervention would be more advantageous than RT alone.

Initial analyses of baseline to 12-week three-day foods revealed that by the end of the 12 weeks

the BCS in the RT+group consumed a significantly greater amount of protein in their diet than

the RT group as they increased from 1.00 ± 0.24 g/kg/day (16% of total calories coming from

protein) to 1.24 ± 0.30 g/kg/day (21% of total calories coming from protein). The participants in

the RT group maintained their protein intake from 0.99 ± 0.39 g/kg/day (16% of total calories

coming from protein) at baseline to 0.96 ± 0.41 g/kg/day (17% of total calories coming from

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protein). However, changes in protein intake from baseline to 6 weeks were not significantly

different between the two groups, neither were changes from baseline to the average of the

combined 6-week and 12-week food logs. Therefore, because of the variation in the three-day

foods at 6 weeks and 12 weeks we cannot definitively conclude that the RT+protein actually

consumed significantly more protein than the RT only group during the entire 12-week

intervention.

On average the 40 g daily protein supplement provided to the BCS in the present study

was sufficient to increase the average intake of protein to above that of the earlier

recommendations for aging adults of 1.14 g/kg/day of protein (40) if we assume the BCS

accurately reported their dietary food logs. However as a result of the variation in the amount of

protein consumed in the present study we cannot conclude whether adding 40 g of protein to the

habitual diet of BCS is beneficial. Thus, the findings of the present study may provide guidance

to future studies to assign more frequent dietary logs to the participants, as well as analyze the

food logs immediately in order to provide instructions to the participants on making dietary

adjustments in order to remain within the study parameters. Further, in order to achieve a protein

change of 59.5% as recommended by Bosse and Dixon (23), the present study would have had to

provide a 60 g protein supplement to the RT+protein group instead of the 40 g that was

prescribed. Be that as it may, this is to the best of our knowledge the first study to include a

protein supplement as part of an exercise intervention in BCS and thus provides direction for

future studies.

In frail older adults (78 ±1 years) without a previous cancer diagnosis, a 30 g protein

supplement (milk protein concentrate) combined with 24 weeks of RT (2 days per week) elicited

a significant 1.3 kg increase in lean mass (267), whereas, 40 g of whey protein in mobility

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limited older adults (70-85 years) performing RT (3 days per week) for 6 months did not find

significant differences compared to the placebo group consuming an isocaloric maltodextrin

supplement (45). The discrepancies in these results warrant more studies to investigate the ideal

dose and type of protein needed to augment the benefits of RT in both healthy older adults and

cancer survivors. Furthermore, the recommendations are most likely different in the cancer

population as a blunted response in MPS to a 40 g amino acid feeding has been reported in

ovarian cancer patients (73) and lower amounts of plasma amino acid were available for MPS in

a heterogeneous group of breast, colon and pancreatic cancer patients (275) compared to healthy

age and sex matched controls.

Interestingly, although the BCS in both groups were asked to maintain their regular

calcium and vitamin D intake throughout the study, there were significant group by time changes

in dietary calcium and vitamin D intake. Analysis of three-day food logs found no differences

between the groups in dietary calcium and vitamin D at baseline. However, over the 12 weeks,

the women in the RT+protein group increased their average dietary calcium intake by 74% (763

± 179 to 1324 ± 413 mg/d) and the vitamin D intake by 161% (179 ± 176 to 468 ± 244 IU/d),

compared to a 20% (900 ± 426 to 719 ± 331 mg/d) and a 31% (221 ± 222 to 152 ± 252 IU/d)

decrease in dietary calcium and vitamin D intake respectively, observed in the RT group. The

group differences in dietary calcium and vitamin D intake is largely explained by the extra

calcium (600 mg) and vitamin D (320 IU) provided by the daily protein supplement that was

consumed by the RT+protein group. At baseline, the supplementary calcium and vitamin D was

similar between the groups and the participants were asked to maintain their daily

supplementation throughout the 12-week study. However only 26 participants returned

completed calcium and vitamin D logs, and analysis of these logs revealed the 16 women in the

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RT+protein group had a significantly greater adherence to consumption of their supplementary

calcium and vitamin D than the 10 women in the RT group (94% vs. 84%; p≤0.05). As there

were no significant differences between the groups in any of the primary outcome variables, it is

not likely that the differences in calcium and vitamin D intake were confounding factors.

Furthermore, it is not clear what the role of calcium and vitamin D intake plays in muscle and fat

metabolism during a RT intervention in BCS. A previous RT intervention (248) controlled for

calcium and vitamin D intake by asking the participants in both intervention groups to replace

their daily calcium and vitamin D supplements with those provided by the study (900 mg

calcium and 1600 IU vitamin D) and did not find any significant effects of calcium and vitamin

D intake on body composition. However, at baseline a significant correlation was observed

between dietary calcium intake and lean mass (r=0.444) in the 27 women about to begin the 6-

month RT intervention (197). The average calcium intake from food and supplements from that

study was 1,846±746 mg/day and was slightly lower than that of the present study (2,042±710

mg/day) therefore the importance of calcium intake to modulate body composition in BCS is yet

to be elucidated. Winter-stone et al. (283) observed that on average, a sample of 258 BCS were

consuming 40% less calcium than the recommended RDI of 1,200 mg/day and although calcium

intake decreased slightly in both the intervention and control groups, calcium intake was not a

confounding factor during a12-month RT intervention. In the present study, there were no

significant correlations between lean body mass and calcium and vitamin D at baseline and at 12

weeks.

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5.4 Blood biomarkers

Contrary to our hypothesis, the women in the RT+protein group did not increase serum

levels of the anabolic hormone IGF-1, adiponectin, an adipokine nor did they decrease levels of

CRP to a greater extent than the RT group. However, in agreement with the observed significant

increases in lean mass in the BCS in the present study, IGF-1, a marker of muscle metabolism

increased significantly from baseline thereby elucidating a potential mechanism for the

increment in lean mass in BCS from RT. As a growth factor, IGF-1 plays an important role in the

regulation of skeletal muscle mass as the two isoforms of IGF-1 produced by skeletal muscle,

mechano-growth factor (MGF) and IGF-1 up-regulate satellite cell replenishment in response to

exercise, and up-regulates MPS respectively thus are mediators of muscle repair and hypertrophy

(201). Normal levels of IGF-1 range from 40-258 ng/mL(18, 115) and decrease with aging and

therefore contribute to loss of lean mass in aging adults (167, 231). However, as IGF-1 is a

growth factor, a paradox exists as IGF-1 at levels above normal (40-258 ng/mL) can increase the

development of estrogen-mediated breast carcinogenesis (146) via IGF-1’s role in stimulating

estrogen from adipose tissue. Thus the concern for BCS is the risk of cancer reoccurrence by

increasing IGF-1 levels to above normal levels of women over the age of 45 years (100). The

serum levels of IGF-1 of the BCS in the present study increased from 106.2 ± 36.8 ng/mL at

baseline to115.7 ± 34.6 ng/mL by the end of the 12-week RT intervention. Therefore, the BCS

did not exceed the normal range (40-258 ng/mL) for serum levels of IGF-1 as the measured

values at 12 weeks ranged from 46.9 ng/mL to 202.5 ng/mL. Similar to our findings, progressive

RT (6-12 RM, 6 sets per muscle group, 3 days/week) significantly increased IGF-1 levels by

16.0 ± 7.5% in healthy older overweight and obese adults (53.3 ± 8.7 yrs) but did not exceed

normal values (11) and a 6-month RT intervention (2 d/wk) did not significantly increase IGF-1

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above normal values in 39 BCS (53.3 ± 8.7 yrs; mean age ± SD) with normal levels at baseline

(235). These findings are encouraging; as it demonstrates RT in BCS is safe and does not

contribute to the increase in IGF-1 mediated risk of cancer reoccurrence. More importantly,

increasing serum levels of IGF-1 in BCS within the normal range for healthy women potentially

mediates skeletal MPS and thus increases the lean body mass in BCS regardless of protein

intake. In addition, at 12 weeks IGF-1 was negatively correlated with total body fat percentage

(r=-0.404; p≤0.05) thus further elucidating the role of IGF-1 to modulate body composition in

response to RT in BCS. Furthermore, adding 40 g of protein in the present study did not increase

IGF levels out of the normal range and therefore, supplementing the diet with protein for 12

weeks appears to not increase the IGF-1 mediated cancer risk in female BCS.

However, in contrast to our hypothesis and to the decrements in body fat observed in the

present study, serum levels of adiponectin did not increase significantly nor were they

significantly different between the groups. Although adiponectin is secreted by adipose tissue,

secretion of adiponectin is actually inhibited by elevated body fat levels largely due to obesity

related inflammation (32, 193). Normal values of adiponectin range from 0.865-21.4 mg/L and

have been shown to increase after weight loss (121, 165), however, the lack of any significant

changes in adiponectin in the present study are likely because with the exception of two

participants who had adiponectin levels above normal at baseline and at 12 weeks, the BCS were

well within the normal the range. Thus, we were most likely not able to significantly alter values

of adiponectin that were already normal at baseline. Additionally, inflammation, as measured by

CRP, did not decrease during our 12-week RT intervention and therefore may have attenuated

any significant increases in adiponectin. This is evident, as CRP was negatively correlated with

adiponectin at baseline (r= -0.412; p≤0.05) and at 12 weeks (r=-0.503; p≤0.05). Furthermore,

100

human CRP levels were significantly greater in the RT+protein group than the RT group at

baseline and serum levels of CRP remained significantly higher at 12 weeks. Therefore, the

increased protein intake in the present study had no effect on inflammation. Thus, future diet and

exercise interventions in BCS should aim to include anti-inflammatory foods as a component of

the dietary intervention in order to significantly decrease inflammation and accordingly increase

adiponectin levels. This is important, as adiponectin plays a role in cancer prevention and

control. Adiponectin inhibits tumor cell development and proliferation via its anti-proliferative

effects that inhibit angiogenesis and therefore decreases the risk of development and

reoccurrence (192). Previous RT (96) and aerobic exercise (108, 229) interventions have not

reported any changes in adiponectin levels in postmenopausal women with no prior cancer

diagnosis, largely as a result of an absence of weight loss. However, Abbenhardt et al. (2)

reported that an 8.5 – 10.8% weight loss after a reduced calorie and moderately vigorous aerobic

exercise intervention resulted in 6.6 - 9.5% increase in adiponectin levels in healthy, overweight

and obese postmenopausal women. As the body weight of the BCS in the present study did not

change it may be that significant changes in overall body weight are necessary to detect changes

in adiponectin levels. Similar to our findings, Ligibel et al. (161) did not observe significant

weight loss and thus did not find any changes in adiponectin levels after a 16-week combined RT

(lower body exercise; 50 minutes, 2 days per week) and home based aerobic training (90 minutes

per week) intervention in BCS. Therefore, significantly reducing total body weight and perhaps

greater decrements in body fat as well as decreasing the levels of circulating inflammatory

markers such as CRP may be the determining factor in increasing adiponectin secretion in BCS.

Our 12 weeks of RT intervention did not decrease human CRP levels in BCS possibly

due to the absence of significant weight loss. Although total body fat mass decreased by 2% in

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both groups, this was not adequate to produce significant changes in CRP as positive correlations

exist between CRP levels and body weight (97). However, it is likely that our RT intervention

did not significantly decrease CRP because values at baseline were already near optimal.

Average values of CRP of apparently healthy adults range from 0.109-4.29 mg/L, however CRP

levels greater than 3.0 mg/L are considered on the high end of CRP values (219). With the

exception of four participants in the RT+protein group, the remaining participants had CRP

values below 3.0 mg/L at baseline, with an average CRP value of 1.72 ± 1.07 mg/L for the 28

BCS that had serum analyzed. Among the four women that had serum levels above 3.0 mg/L,

three of them reduced their CRP levels below 3.0 mg/L. Therefore, similar to our findings for

adiponectin, we likely did see and significant changes because values were already optimal at

baseline. Similar to our findings, Simonavice et al. (248) did not find significant reductions in

human CRP after a 6-month RT intervention in BCS. To the best of our knowledge, our study

and that of Simonavice et al. (248) are the only two to measure human CRP after an RT

intervention. Simonavice et al. (248) did observe a non-statistically significant decrease of 44%

in CRP (p=0.29), this was likely due to the BCS in that study having high baseline values

ranging from 3.20 ± 4.4 mg/L to 4.13 ± 6.77 mg/L). Although the decrease in human CRP in the

Simonavice et al. (248) study was not significant it does have important health implications for

BCS who may have higher CRP values and the importance of RT. Of the studies utilizing

aerobic training as the exercise mode, one observed a decrease in CRP (88) and the other did not

(136). The study by Fairley el al. (88) that did find CRP to decrease by 1.39 mg/L did not

observe an association between changes in CRP and changes in any measures of body

composition in BCS. For this reason, more studies are warranted to determine the most

appropriate mode of exercise and dietary intervention to reduce CRP levels in BCS. Modulating

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inflammation in BCS is necessary as CRP is positively associated with breast cancer

development and reoccurrence (246). Nevertheless, the present study did demonstrate that RT

did increase the anabolic biomarker IGF-1 but did not exceed normal levels and was therefore

safe and is a potential mechanism for the accretion of lean body mass in BCS. Furthermore, the

RT intervention maintained the values of the biomarkers adiponectin and CRP within the normal

ranges with no detrimental effects from consuming a protein supplement. The safety of our RT

intervention in relation to concerns associated with breast cancer is further demonstrated by the

improvements in lymphedema observed in the present study.

5.5 Lymphedema history and monitoring

The finding of the present study and those of previous studies (234, 236, 248, 283)

demonstrate that RT is safe and does not exacerbate lymphedema in a heterogenous group of

BCS (248) and in BCS with or at risk of breast cancer related lymphedema (283). Only one

participant in the present study, complained of swelling in her involved arm at the beginning of

week 3 of the RT intervention, however she also reported that she had performed a greater

amount of work around the house than normal over the weekend. Regardless, we determined it

best to reduce the intensity of all her upper body exercises from 65% to 50% of her baseline 1-

RM and proceeded to progress her upper body weights slowly over the following weeks. Apart

from this incidence, she did not report any significant arm swelling or pain for the remainder of

the study nor did any other participant throughout the 12-week intervention. Interestingly, even

though at baseline the RT group had more participants who did not have their lymph nodes

removed compared to the RT+protein group (RT: 44% vs RT+protein: 18%), the women in the

RT group had significantly greater differences in upper-extremity volume between the involved

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arms compared to uninvolved arms (RT: 9.52 ± 11.2% vs RT+protein: 1.82 ± 10.2%). However,

these differences at baseline did not remain when further analysis was performed with only the

BCS who had lymph nodes removed. Most importantly, the percent difference in arm

circumference decreased in both groups by week 5 of the intervention and remained on average

below 2% difference for the remainder of the study. Therefore, the results of the present study

add to the current evidence that RT in BCS does not exacerbate and actually improves

lymphedema. Furthermore, RT at a moderately vigorous intensity (65-81% of 1-RM) was well

tolerated and improved muscular strength, body composition and physical function in BCS.

The present study did have some limitations. First, our study did not have a true control

group in the form of a protein only group or a non-exercising control group. Therefore, we

cannot rule out that our findings would not have occurred in BCS who were only on a high

protein group or were not performing structured RT. However, of the studies reviewed that did

include a control group, the majority of studies have reported significant differences between the

exercising intervention groups and the non-exercising control groups in similar variables

measured in the present study. Therefore, we believe the findings of the current study make a

valuable contribution to the literature investigating the efficacy of RT to improve strength, body

composition, and physical function in BCS.

Second, we did not determine at baseline the required amount of protein to prescribe to

elicit an appropriate protein change and spread as previously described to identify an effect of

the protein supplement. Furthermore, we assigned three-day food logs at baseline, 6 weeks and

12 weeks, which revealed variation in the self-reporting of the dietary intake of the participants

in the present study. Future studies should assign dietary food logs more frequently and analyze

them immediately to give participants feedback on whether or not they are adhering to the study

104

parameters. Additionally more objective methods such as asking participants to take photographs

of their meals and mobile phone applications that allow participants to scan the bar codes on the

foods they consume may provide a more accurate representation of dietary habits. As this is to

the best of our knowledge the first study to investigate the use of a protein supplement in

combination with RT in BCS, we believe this study can provide a rationale for prescribing a

significantly greater amount of protein in future studies that aim to improve body composition in

both aging adults and the cancer population. Furthermore, the 40 g per day of protein given in

the present study did not increase the levels of IGF-1 to a greater extent than the RT only, and

neither group had IGF-1 levels increase above normal levels. This finding can provide further

guidance to future studies aiming to investigate efficacy of a similar or higher dose of protein to

potential augment the benefits of exercise in interventions for BCS.

Lastly, the analysis of the blood biomarkers may have produced more significant findings

in regards to the mechanisms associated with the changes in body composition after a RT

intervention if we had baseline and 12-week blood samples to analyze for all the 33 BCS who

enrolled. Unfortunately, three participants were unable to complete the intervention and two had

unsuccessful 12-week blood draws. Furthermore, one sample from the IGF-1 assay was not

analyzed because of a coefficient of variance greater than 20%. Therefore, a larger sample size

may have had greater power and revealed the mechanisms associated with the observed

improvements in body composition in BCS.

5.6 Concluding remarks

In conclusion, this is one of only two studies to demonstrate a significant training effect

from RT on lean body mass in female BCS. The observed improvements in lean body mass

105

translated to significant improvements in muscular strength and objectively measured physical

function in post-menopausal BCS. Although protein supplementation did not have an added

benefit, consumption of 40 g per day in the form of a whey and casein blend protein beverage

was well tolerated and adhered to and did not cause significant weight gain nor did it increase

IGF-1 levels above normal. Future studies will need to include a sufficient dose to create an

adequate protein change and spread in order to detect any significant group differences.

Additionally, future investigations will also need to determine the optimal dose to detect an

effect of protein supplementation but not result in harmful increases in IGF-1. Most importantly,

future studies should monitor dietary intake more frequently and objectively in order to ensure

participants are remaining within study parameters. This may be achieved by assigning weekly

food logs and by asking participants to take photographs of their meals.

A moderately vigorous training intensity and volume of RT was safe and improved

lymphedema in BCS. Most importantly RT at 65-81% was a sufficient training stimulus to elicit

significant improvements in muscular strength, body composition and physical function.

Furthermore, the anabolic blood biomarker IGF-1 appears to play a role in modulating accretion

of lean body mass in BCS, however the efficacy of RT to increase levels of adiponectin and

decrease CRP in BCS is yet to be determined.

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APPENDIX A

IRB APPROVAL LETTERS

107

108

APPENDIX B

TELEPHONE INTERVIEW

Hello, my name is (state your name) calling from The Florida State University regarding the

breast cancer research project that you inquired about. We are currently looking for breast

cancer survivors, ages 40-75 years, having completed chemotherapy treatment. We expect the

study to last approximately 4 months. The 4 months will consist of 2 weeks of initial testing and

2 weeks of post testing. The intervention period will last 12 weeks. The pre and post testing

periods will consist of the following assessments: blood markers for hormone levels and C-

reactive protein, muscular strength by one-repetition maximal tests, physical function by the

Continuous Scale Physical Functional Performance test, and quality of life measured by a

questionnaire.

The women in the study will be randomly assigned to one of two treatment groups for a period of

12 weeks: 1) resistance exercise training and 2) resistance exercise + protein consumption. All

three groups will be given a pedometer to wear for one randomly assigned week each month and

be instructed to record the number of steps obtained daily. The resistance exercise will consist of

meeting twice a week with an exercise instructor for a guided exercise session lasting

approximately 45 minutes at The Florida State University. The resistance training and protein

group will be provided with protein and will be instructed to consume the drink in the morning

and evening or on the days that you exercise after the exercise session instead of the evening

drink. Additionally, all participants will be asked to replace their current supplementations with

a multivitamin that we provide containing 600 mg of calcium and 400 IU of vitamin D (twice per

day).

Do you have any questions? If not, and you are interested, I would like to ask you some

questions regarding your present state to determine your eligibility. If you have any of the

following conditions or are taking any of the medicines listed below, you may not be eligible to

participate in the study.

1. Were you diagnosed with stage IV breast cancer or are currently diagnosed with active cancer?

2. Do you have uncontrolled hypertension (>160/100 mmHg), uncontrolled diabetes (fasting blood glucose >126), uncontrolled heart disease, kidney disease, allergies to milk protein?

3. Are you on endocrine (e.g., prednisone, other glucocorticoids) or neuroactive (e.g., dilantin, phenobarbital) drugs or any other prescription drugs known to influence fat or muscle metabolism?

4. Are you currently participating in a regular exercise program (RET>1 times per week or aerobic exercise > 2 times per week)?

5. Do you have milk allergies? If so, what is the severity?

109

6. Are you allergic to soy, wheat, or grain products? If so, what is the severity?

Since you do not have any of the exclusion criteria, would you like to schedule with me a time

for you come in for a more in depth orientation to the study?

Thank you very much for your time and we are looking forward to working with you shortly.

110

APPENDIX C

INFORMED CONSENT DOCUMENT

111

112

113

114

APPENDIX D

PHYSICIAN CONSENT DOCUMENT

115

APPENDIX E

DEMOGRAPHIC/MEDICAL QUESTIONNAIRE

MEDICAL HISTORY

ID# __________

DATE __________

Answer the following questions, indicating the month and year of the event or diagnosis where

appropriate.

Yes No Month/Year

1. Has a doctor ever told you that you have

heart disease? ___ ___ ____/____

2. Have you ever had a heart attack? ___ ___ ____/____

3. Have you ever had chest pain? ___ ___ ____/____

4. Have you ever had cardiac

catheterization? ___ ___ ____/____

5. Have you ever had balloon angioplasty? ___ ___ ____/____

6. Have you had coronary artery bypass graft

surgery? ___ ___

If yes, list date and number of grafts:

____/____ # grafts: ___ 1 ___ 2 ___ 3 ___ 4+

Mo. Yr.

7. Have you ever had a stroke? ___ ___ ____/____

8. Do you have hypertension (high blood pressure)? ___ ___ ____/____

If yes, how long have you had hypertension?

116

_____ less than 1 year

_____ 1-5 years

_____ 6-10 years

_____ more than 10 years

Yes No Month/Year

9. Do you have diabetes mellitus? ___ ___ ____/____

10. Do you take insulin for diabetes? ___ ___

If yes, how long have you taken insulin?

_____ less than 1 year

_____ 1-5 years

_____ 6-10 years

_____ more than 10 years

11. Do you take oral hypoglycemics for

diabetes? ___ ___

12. Do you have a cardiac pacemaker? ___ ___

If yes, how long have you had a cardiac pacemaker?

_____ less than 1 year

_____ 1-5 years

_____ 6-10 years

_____ more than 10 years

13. Have you had a carotid endarterectomy? ___ ___ ____/____

14. Has your doctor ever told you that you

have a heart valve problem? ___ ___ ____/____

15. Have you had heart valve replacement

surgery? ___ ___ ____/____

If yes, what heart valves were replaced? ___ mitral ___ aortic

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16. Have you had cardiomyopathy? ___ ___ ____/____

17 Have you had a heart aneurysm? ___ ___ ____/____

18. Have you had heart failure? ___ ___ ____/____

19. Have you ever suffered cardiac arrest? ___ ___ ____/____

20. OTHER MEDICAL PROBLEMS: Indicate if you have had any of the following medical

problems:

Past Now

____ ____ Alcoholism

____ ____ Allergies

____ ____ Anemia

____ ____ Arthritis

____ ____ Asthma

____ ____ Back injury or problem

____ ____ Blood clots

____ ____ Bronchitis

____ ____ Cirrhosis

____ ____ Claudication

____ ____ Elbow or shoulder problems

____ ____ Emotional disorder

____ ____ Eye problems

____ ____ Gall bladder disease

____ ____ Glaucoma

____ ____ Gout

____ ____ Headaches

____ ____ Hemorrhoids

____ ____ Hernia

____ ____ Hip, knee, or ankle problems

____ ____ Intestinal disorders

____ ____ Kidney disease

____ ____ Liver disease

____ ____ Lung disease

____ ____ Mental illness

____ ____ Neck injury or problem

____ ____ Neuralgic disorder

____ ____ OB/GYN problems

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____ ____ Obesity/overweight

____ ____ Osteoporosis

____ ____ Parkinson's disease

____ ____ Phlebitis

____ ____ Prostate trouble

____ ____ Rheumatic fever

____ ____ Seizure disorder

____ ____ Stomach disease

____ ____ Thyroid disease

____ ____ Tumors or cancer - List type: _______________

____ ____ Ulcers

____ ____ Other - specify: ________________

List medications you are taking below:

Name of Drug Dosage Times/day Duration of drug use

Please list all vitamins, minerals and herbs and other nutritional supplements you are currently

taking.

How long have you been taking them and how frequently?

Are you allergic, sensitive or intolerant of any foods or medications (e.g. lactose, soy, wheat)?

Yes____ No____

119

If yes, please describe:

Food____________________________________________________________

Medication _______________________________________________________

Other ___________________________________________________________

Do you exercise regularly? Yes____ No_____

What kinds of exercise? How often? How intense?

Do you: Smoke?______ Packs per day_______ # years smoked _____

Drink alcohol? _____ Drinks per day _______

Cancer History

Diagnosis (stage of cancer):

Date of diagnosis:

Types of treatment (surgery, radiation, chemotherapy, hormone therapy):

Beginning and ending dates of each treatment:

120

Are you currently on hormonal therapy (which type)?

Menopausal age (Natural or Treatment induced):

Additional information:

121

DEMOGRAPHIC INFORMATION

ID#

Home address

Street

City State ZIP County

Home phone _____________

Cell phone

Do you text message? Yes ____ No ____

Office phone

Email address ________________________

Family Physician

Office phone

Oncologist

Office phone

Emergency Information

Name: ______________________________________

Relationship to you:

Home phone ________________ Office phone __________________

Cell phone

122

Personal Information

Age ________ Date of birth _____/_____/_____

Month Day Year

Height ______ in. ______ cm

Weight ______ lb. ______ kg

Ethnic Category

____ Hispanic or Latino

____ Not Hispanic or Latino

Racial Categories

____ American Indian/Alaskan Native

____ Asian

____ Native Hawaiian or Other Pacific Islander

____ Black or African American

____ White

____ Other: ________________________

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APPENDIX F

PEDOMETER LOG

Week ____ Subject ID Day One Date: Time pedometer was put on: Time pedometer was taken off: Was the pedometer worn today if yes how many steps? Was pedometer removed during the day (e.g. while swimming, showering)?How long What general activities did you do today? Day Two Date Time pedometer was put on: Time pedometer was taken off: Was the pedometer worn today if yes how many steps? Was pedometer removed during the day (e.g. while swimming, showering)?How long What general activities did you do today? Day Three Date Time pedometer was put on: Time pedometer was taken off: Was the pedometer worn today if yes how many steps? Was pedometer removed during the day (e.g. while swimming, showering)?How long What general activities did you do today? Day Four Date Time pedometer was put on: Time pedometer was taken off: Was the pedometer worn today if yes how many steps? Was pedometer removed during the day (e.g. while swimming, showering)?How long What general activities did you do today? Day Five Date Time pedometer was put on: Time pedometer was taken off: Was the pedometer worn today if yes how many steps? Was pedometer removed during the day (e.g. while swimming, showering)?How long What general activities did you do today? Day Six Date Time pedometer was put on: Time pedometer was taken off: Was the pedometer worn today if yes how many steps? Was pedometer removed during the day (e.g. while swimming, showering)?How long What general activities did you do today? Day Seven Date Time pedometer was put on: Time pedometer was taken off: Was the pedometer worn today if yes how many steps? Was pedometer removed during the day (e.g. while swimming, showering)?How long What general activities did you do today?

124

APPENDIX G

LICENSES TO PUBLISH FIGURES

125

126

127

128

129

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BIOGRAPHICAL SKETCH

Takudzwa Arthur Madzima was born and raised in Harare, Zimbabwe and completed his

Bachelor of Science degree in Exercise Science from Florida State University in 2009.

Takudzwa returned to his home country after graduation only to return to Florida State

University to pursue a Master’s of Science degree in Exercise Physiology in 2010. After

successfully completing his first year of study, his graduate committee felt he had the potential to

succeed as a Ph.D. student, and approved him to do a by-pass of his Master’s degree. During his

doctoral training, Takudzwa also served as a Graduate Teaching Assistant and was awarded

several scholarships, awards and honors. Takudzwa will receive his Doctor of Philosophy degree

in May 2015.