School of Public Health & Health Sciences, Department of Biostatistics and Epidemiology

Katherine W. Reeves, PhD, MPH Associate Professor

Department of Biostatistics and Epidemiology

University of Massachusetts Amherst

WHI Cancer SIG

June 20, 2016

Predictors of Vasomotor Symptoms among Breast Cancer Survivors

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Background on Vasomotor Symptoms (VMS)

Include hot flashes and night sweats

Common side effect of breast cancer treatments

Negative effects on treatment adherence, quality of life

Related to elevated BMI and metabolic syndrome (MetS) among women transitioning through menopause

Unclear what, if any, personal and/or behavioral characteristics predict VMS following breast cancer treatment

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Objective and Methods

Objective: To identify pre-diagnostic predictors of VMS following breast cancer diagnosis, with an emphasis on BMI and MetS

Life and Longevity after Cancer Study (LILAC)

• WHI ancillary study of cancer survivors

• N=3,134 breast cancer survivors answering baseline LILAC questionnaire (mean 8.9 years post-diagnosis)

• Self-reported VMS following diagnosis and treatment data from LILAC baseline

• Demographic and medical history data from WHI main study baseline

• Measured BMI and waist circumference from WHI clinic visit prior to diagnosis (mean 4.5 years pre-diagnosis)

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Metabolic Syndrome (MetS)

Defined as at least three of the following:

• Abdominal obesity: waist circumference >88cm

• Hypertension: measured SBP >130 mmHg and/or DBP >85 mmHg, or self-report of taking hypertension medications

• Diabetes: self-reported diabetes

• Hypercholesterolemia: self-report of taking medications to treat high cholesterol

Analyzed each component individually, as a syndrome, and as number of components present

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Table 1. Summary of breast cancer features and treatments, stratified by self-reported VMS post-diagnosis

Breast Cancer Characteristic VMS N=681

No VMS N=2453

P Value

Age at diagnosis, years; Mean (SD) 66.7 (7.2) 69.3 (7.4) <0.001

Regional/distant stage; N (%) 167 (24.8) 512 (20.9) 0.01

Estrogen receptor positive; N(%) 2595 (90.2) 2008 (86.2) 0.006

Chemotherapy; N(%) 245 (36.2) 687 (28.2) <0.001

Radiation; N(%) 491 (72.6) 1751 (71.9) 0.69

Adjuvant hormone therapy; N(%) 551 (81.3) 1565 (64.2) <0.001

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Table 2. Summary of metabolic characteristics at baseline, by self-reported VMS post-diagnosis

Characteristic VMS N=681

No VMS N=2453

P Value

BMI, kg/m2; Mean (SD)* 27.7 (5.7) 28.3 (5.9) 0.03

Hypertension; N(%) 300 (44.8) 1132 (47.7) 0.19

Diabetes; N(%) 8 (1.2) 83 (3.4) 0.001

Hypercholesterolemia; N(%) 53 (8.1) 276 (12.0) 0.004

Metabolic syndrome; N(%) 20 (3.0) 130 (5.4) 0.01

*Measurement taken at WHI clinical visit preceding breast cancer diagnosis

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0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Od

ds

Rat

io

Multivariable model adjusted for (OR, 95% CI): chemotherapy (2.2, 1.5-3.0 vs no chemotherapy or aHT), aHT (3.0, 2.3-4.0, vs no chemo or aHT), age at diagnosis (0.97, 0.96-0.99), age at menopause (0.97, 0.96-0.99), baseline VMS (2.3, 1.8-3.0), mHT (2.1, 1.7-2.8), oophorectomy (1.4, 1.1-1.8), AD use (1.5, 1.1-2.2), current smoking (1.1, 0.8-1.7), number of live births (0.5, 0.4-0.8: 5+ vs 0; 0.9, 0.7-1.1: 2-4 vs 0; 0.8, 0.5-1.1: 1 vs 0

Figure 1. Estimated multivariable odds ratios for post-diagnosis VMS among long-term breast cancer survivors

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Potential Limitations: Misclassification of BMI

Measurements taken mean 4.5 yrs (SD 3.9 yrs) before diagnosis

Similar results when restricted to BMI measurements ≤ 2 yrs pre-diagnosis (N=1144)

Similar results using annual self-reported BMI

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Potential Limitations: Selection Bias

Comparison of WHI Breast Cancer Cases (Invasive only)

Characteristic In LILAC N=3134

Not in LILAC N=6375

P Value

Age at diagnosis, years; Mean (SD) 68.8 (7.4) 70.9 (7.8) <0.001

BMI Category 0.004

<25 kg/m2 34.8 % 30.0 %

25-29 kg/m2 33.7 % 34.6 %

≥30 kg/m2 31.5 % 35.4 %

Diabetes 2.9 % 6.1 % <0.001

Metabolic syndrome 4.9 % 8.8 % <0.001

VMS at WHI baseline 74.2 % 70.5 % 0.002

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Potential Limitations: Selection Bias

VMS No VMS

MetS a b

No MetS c d

VMS No VMS

MetS a b

No MetS C d

Unbiased Selection

Biased Selection

Enrollment of women with MetS related to VMS at baseline

𝑇𝑟𝑢𝑒 𝑂𝑅 = 𝑎 ∙ 𝑑

𝑏 ∙ 𝑐 𝐸𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑂𝑅 =

𝑎 ∙ 𝑑

𝑏 ∙ 𝑪

Calculated OR is lower than

true OR

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Conclusions

Pre-diagnositic BMI and MetS may not be associated with VMS post-diagnosis

Chemotherapy and adjuvant therapy strongest predictors of VMS post-diagnosis

Plan to further evaluate effects of possible selection bias

Important to identify factors that predispose women to VMS post-diagnosis; may help clinicians counsel patients and treat VMS to avoid negative QOL effects and treatment discontinuation