the absolute blood eosinophil count a...

THE ABSOLUTE BLOOD EOSINOPHIL COUNT:

A POTENTIAL BIOMARKER OF RESPONSE TO INHALED

CORTICOSTEROIDS IN RESPIRATORY PATIENTS

A COHORT STUDY INVESTIGATING THE EFFECT OF INHALED CORTICOSTEROIDS

RELATIVE TO DIFFERENT BLOOD EOSINOPHIL COUNTS IN PRIMARY CARE PATIENTS

WITH ASTHMA, COPD AND ACO

A.E.M. van Dijk | s2230577

Supervisor: dr. J.W.H. Kocks | dr. B.M.J. Flokstra-de Blok

Daily supervisor: drs. H.J. Baretta

Department of General Practice | University Medical Center Groningen

July 2017 | Groningen | The Netherlands

Effectiveness of inhaled corticosteroids relative to different blood eosinophil counts in primary care respiratory patients - 2


Abstract

Introduction: The burden of asthma and chronic obstructive pulmonary disease (COPD) on

society is high and therefore research about optimal treatment in these patient groups has

become a wide field of interest. Inhaled corticosteroids (ICS) are used in both asthma and

COPD patients. The peripheral blood eosinophil count (EO-count) has been suggested to be a

promising biomarker for the effectiveness of ICS. However, little is known about the

predicting role of the EO-count in a combined approach of patients with asthma, COPD and

asthma-COPD overlap (ACO) in primary care.

Aim: This study aims to investigate the ICS treatment response in relation to different EO-

counts in real life primary care respiratory patients data.

Methods: This retrospective observational study used anonymized medical data from 2007

till 2016, derived from the Asthma/COPD(AC)-service. Absolute EO-counts were categorized

as follows: ≤150 cells/μL, 151-300 cells/μL, 301-400 cells/μL and > 400 cells/μL. The

primary outcome was the ICS treatment response in terms of improved disease control,

measured by the Asthma Control Questionnaire(ACQ) and Clinical COPD

Questionnaire(CCQ), for the four categories of EO-counts. As secondary outcome, ICS

treatment response in terms of lung function improvement and exacerbation rate was

analyzed. Analyses were performed for all three diseases combined, as well as all three

separately.

Results: 215 asthma patients, 74 COPD patients and 48 ACO patients met study eligibility

criteria. Analyses of the entire study population showed that, after ICS treatment, patients

with an EO-count > 400 cells/μL at baseline were more likely to improve their disease control

compared to patients with an EO-count between 151-300 cells/μL (p=0.005). When

performing specific analyses into patients classified by their diagnosis, similar results were

solely observed in COPD patients. Furthermore, no significant differences in terms of lung

function improvement and exacerbation rate were identified related to the EO-count.

Conclusion: In patients with a high EO-count at baseline, ICS treatment is associated with

larger improvements of disease control compared to patients with a low EO-count. The

absolute EO-count is potentially an important biomarker that could contribute to treatment

decision making in primary care respiratory patients. These results suggest the need for

prospective randomized control trials on larger sample sizes.

Key words: Primary care, Blood eosinophil count, Inhaled corticosteroids, Disease Control


Samenvatting

Introductie: Astma en chronic obstructive pulmonary disease (COPD) zijn veel

voorkomende chronische aandoeningen in de maatschappij met een hoge ziektelast. Inhalatie

corticosteroïden(ICS) spelen een belangrijke rol in de behandeling van deze respiratoire

ziektes. Het eosinofielen gehalte in het bloed (EO-gehalte) wordt gezien als een mogelijke

voorspeller voor de effectiviteit van de behandeling met ICS, echter is er nog weinig bekend

over de rol van het EO-gehalte als biomarker in de behandeling voor eerstelijns patiënten met

astma, COPD en astma-COPD Overlap (ACO).

Doel: Het doel van deze studie is om de relatie tussen het EO-gehalte en de effectiviteit van

ICS in real-life data van patiënten met astma, COPD en ACO uit de eerste lijn te

onderzoeken.

Methode: Dit betrof een retrospectief observationele studie welke gebruik maakte van

geanonimiseerde data tussen 2007 en 2016 afkomstig van de astma/COPD dienst. Er werd

gebruik gemaakt van het absolute EO-gehalte in vier categorieën: ≤150 cellen/μL, 151-300

cellen/μL, 301-400 cellen/μL, >400 cellen/μL. Als primaire uitkomstmaat werd het verschil

van ICS op de ziekte controle ten opzichte van de vier eosinofiel categorieën geanalyseerd, dit

werd gedaan met behulp van de Asthma Control Questionnaire (ACQ) en Clinical COPD

Questionnaire (CCQ). Secundaire uitkomstmaten betroffen de verschillen in effectiviteit van

ICS met betrekking tot de longfunctie en het aantal exacerbaties. De analyses werden zowel

uitgevoerd op de gehele studie populatie als voor de drie verschillende ziektebeelden

afzonderlijk.

Resultaten: 215 astmapatiënten, 74 COPD-patiënten en 48 ACO-patiënten voldeden aan de

inclusie criteria. Over het gehele cohort toonden patiënten met een EO-gehalte van >400

cellen/μL op baseline een grotere verbetering in hun ziekte controle na behandeling met ICS

dan patiënten met een EO-gehalte tussen 151-300 cellen/μL (p=0.005). De specifieke

analyses in astma-, COPD- en ACO-patiënten toonden alleen een vergelijkbaar resultaat

onder COPD-patiënten. Er werden geen significante verschillen gevonden in effectiviteit van

ICS met betrekking tot de longfunctie en het aantal exacerbaties in relatie tot het EO-gehalte.

Conclusie: Behandeling met ICS is geassocieerd met een grotere verbetering in ziekte

controle bij patiënten met een hoog EO-gehalte op baseline in vergelijking tot patiënten met

een laag EO-gehalte. Het absolute EO-gehalte lijkt een potentiele biomarker die kan bijdragen

aan de besluitvorming voor het starten van een behandeling met ICS bij respiratoire patiënten

in de eerste lijn. De resultaten van deze studie geven het belang weer voor prospectieve en

gerandomiseerde control trials in een grotere patiëntenpopulatie.

Trefwoorden: Eerstelijns zorg, Eosinofiel gehalte, Inhalatie corticosteroïden, Ziekte Controle


Table of abbreviations

ACO Asthma-COPD overlap

ACQ Asthma control questionnaire

AC-service Asthma/COPD service

ANOVA Analysis of variance

BDT Bronchodilator test

CCQ Clinical COPD questionnaire

COPD Chronic obstructive pulmonary disease

CRQ Chronic respiratory questionnaire

EO-count Peripheral blood eosinophil count

FEV1 Forced expiratory volume in 1 second

FVC Forced vital capacity

GINA Global initiative for asthma

GOLD Global initiative for chronic obstructive lung disease

GP General practitioner

ICS Inhaled corticosteroids

IQR Interquartile range

LABA Long-acting beta2-agonist

LAMA Long-acting muscarinic antagonist

MCID Minimal clinical important difference

NA Not applicable

NS Not significant

SABA Short-acting beta2-agonist

SAMA Short-acting muscarinic antagonist

SD Standard deviation

SGRQ St. George’s respiratory questionnaire

WMO Medical research involving human subjects act


Table of contents

1. Introduction ................................................................................................................................... 7

1.1. Asthma, COPD and ACO ........................................................................................................ 7

1.2. Blood eosinophil count ............................................................................................................ 8

1.3. Treatment with inhaled corticosteroids ................................................................................... 9

1.4. Role of blood eosinophil count as biomarker ........................................................................ 10

1.5. Real life data .......................................................................................................................... 10

1.6. Aims ...................................................................................................................................... 11

2. Research questions ...................................................................................................................... 12

3. Material and methods ................................................................................................................. 13

3.1. Study design .......................................................................................................................... 13

3.2. Data source ............................................................................................................................ 13

3.3. Participants ............................................................................................................................ 13

3.4. Procedure ............................................................................................................................... 13

3.5. Primary outcome ................................................................................................................... 14

3.6. Secondary outcomes .............................................................................................................. 15

3.7. Data analysis .......................................................................................................................... 15

3.8. Ethics ..................................................................................................................................... 16

4. Results........................................................................................................................................... 17

4.1. Patient characteristics ............................................................................................................ 17

4.2. Follow-up time ...................................................................................................................... 20

4.3. Effect of ICS treatment on disease control ............................................................................ 20

4.4. Effect of ICS treatment on lung function .............................................................................. 22

4.5. Effect of ICS treatment on exacerbation rate ........................................................................ 23

4.6. Sensitivity analyses: differences in follow-up time ............................................................... 23

5. Discussion ..................................................................................................................................... 24

5.1. Main findings ........................................................................................................................ 24

5.2. Comparison with current literature ........................................................................................ 24

5.3. Strength and limitations ......................................................................................................... 26

5.4. Implications and recommendations ....................................................................................... 28

6. Conclusion .................................................................................................................................... 29

7. Acknowledgements ...................................................................................................................... 30

8. References .................................................................................................................................... 31

Appendices ........................................................................................................................................... 35


1. Introduction The prevalence of respiratory obstructive diseases is increasing worldwide(1,2). Asthma and

chronic obstructive pulmonary disease (COPD) are the two most prevalent of them and have

become an earnest and under-treated health problem with a high mortality rate(1,3,4). In the

Netherlands, currently more than 610,000 patients suffer from asthma and 600,000 patients

are diagnosed with COPD(5,6). Besides, these chronic diseases are responsible for increasing

health care costs and indirect costs by absenteeism and disability(4,7). The burden of asthma

and COPD on society is high and, therefore, over the past decades research about optimal

treatment of these diseases has become a wide field of interest.

1.1. Asthma, COPD and ACO

Asthma

Asthma is described in the Global Initiative for Asthma (GINA) as a chronic inflammatory

disorder of the airways that is usually reversible, either spontaneously or with treatment(8).

Classically, asthma consists of three components: airflow limitation, airway hyper

responsiveness and bronchial inflammation. Many cells and cellular elements play a role in

the bronchial inflammation like T-lymphocytes, mast cells and eosinophils. Therefore, asthma

is seen as a Th2-mediated eosinophilic disease(9,10). The T-lymphocytes, mast cells and

eosinophils provide edema, smooth muscle hypertrophy, matrix deposition, mucus plugging

and epithelial damage(3). Wheezing, dyspnea, and predominantly nightly or early morning

coughing are the characteristic symptoms of asthma(8). Usually, allergic agents play a role in

the development of asthma. Therefore, bronchus obstruction is often a result of increased

sensitivity of the respiratory tract to allergic stimuli which consequentially causes the

inflammation(1,3,7).Besides, more than half of asthma patients are atopic and have an

increased immunoglobulin E (IgE) level against specific antigens in their blood, explaining

the allergic reaction of their immune system(5,11). Therefore, atopic diseases like allergic

rhinitis and eczema are frequent comorbidities in patients with asthma(7,12). Most of the

time, asthma typically develops in childhood but, occasionally, the disease becomes active for

the first time at later age(7).

COPD

COPD is a chronical disorder characterized by airflow limitation that is progressive and not

entirely reversible(2–4,13). The airflow limitation is associated with an abnormal

inflammatory response of the lungs to toxic particles and gases and is caused by a mixture of

small airways disease (obstructive bronchiolitis) and parenchymal destruction

(emphysema)(13). Cigarette smoking is the main risk exposure for COPD(13). The risk of

developing COPD is proportional to the number of cigarettes smoked per day(3,14). Less

frequent causes are climate change, biomass fuel exposure and air pollution(3). The

symptoms of COPD are comparable to asthma and comprises productive cough with clear

sputum, dyspnea and wheeze(3,13). Exacerbations contribute to the overall severity in

patients with COPD(13). Exacerbations are provoked by viral or bacterial airway infections

(50% to 70%) or environmental factors like air pollution(4). Different inflammatory cells are

consistently present in the airways and responsible for airflow obstruction in COPD(9).

Neutrophils and CD8+ T lymphocytes are the most important ones and have shown to

demonstrate themselves at all levels of the lung in exacerbations(9,10,12,15). In contrast to

asthma, allergic agents do not contribute to exacerbations in individual patients with

COPD(4). The differences and diagnostic features of both asthma and COPD are listed in

Table 1.


Table 1: Differences between asthma and COPD(7,12,13,16)

Asthma

COPD

Most important risk factor Atopy Tobacco smoking

Airway obstruction Reversible Not completely reversible

Pathophysiology Chronic inflammation in all

airways with good response to

corticosteroids

Chronic inflammation of the small airways,

relatively unresponsive to corticosteroids

Onset Usually childhood Mid-life (>40 years)

Symptoms Dyspnea, cough, wheeze

Varies from day to day

Dyspnea, cough, mucus production

Slowly progressive

Co-morbidities Allergy, rhinitis and/or eczema

are often present

Chronic diseases like heart disease,

osteoporosis, diabetes mellitus and

depression

Lung function Predominantly normal with

good treatment

Persistent reduced, even with optimal

treatment

Life expectancy Normal life expectancy Reduced life expectancy

Inhaled corticosteroids Indicated Not indicated, unless suffering from

exacerbations frequently (≥ 2 exacerbations

per year) Abbreviations: COPD, chronic obstructive pulmonary disease

ACO

In addition to asthma and COPD there is a group of patients who have airway inflammation

with features of both asthma and COPD. The Global Initiative for Chronic Obstructive Lung

Disease (GOLD) and GINA describe a so called Asthma-COPD Overlap Syndrome

(ACOS)(17), which is currently renamed to Asthma-COPD Overlap (ACO) as it does not

describe a single disease entity(8). ACO is characterized by persistent airflow limitation with

several features usually associated with asthma and several features associated with

COPD(10,18,19). However, there is still no generally accepted definition of ACO. Miravitlles

et al. recently proposed an algorithm to identify ACO among patients with COPD or

asthma(20). This algorithm is illustrated in Figure 1. Literature shows that one in four patients

with COPD have ACO(21,22). Unfortunately, less is known about the prevalence of ACO in

those with pre-existing asthma(22). It is important to distinguish ACO from both asthma and

COPD because previous research indicates that patients with ACO have exacerbations more

frequently, are hospitalized more, have worse health-related quality of life and higher

healthcare costs than those with pure asthma or pure COPD(21,22). Contrary, patients with

ACO appear to have a better mortality rate after 1 year compared to patients with pure

COPD(19).

1.2. Blood eosinophil count

As described previously, the airway inflammation of asthma and COPD is different. COPD is

characterized by neutrophilic inflammation, whereas asthma is characterized by inflammation

involving T lymphocytes and eosinophils(10). Often, the presence of eosinophilic

inflammation is viewed as a distinguishing feature between asthma and COPD(9).

However, it is important to note that eosinophilic airway inflammation has been

demonstrated in tissue samples and in 20%-40% of induced sputum samples of patients with

stable COPD(9,12,15). In exacerbations, this airway eosinophilia is increased(9,23).

Comparison of bronchial biopsies taken during acute exacerbations to those of patients with

stable COPD, shows a 30-fold increase in the number of eosinophils(9).


Figure 1: Diagnostic algorithm of

asthma-COPD overlap(20)

Persistent airflow limitation (FEV1/FVC <0.7)

must be confirmed after treatment with

bronchodilators and inhaled corticosteroids or

after a course of oral corticosteroids, when

required. Abbreviations: ACO, asthma-COPD overlap;

COPD, chronic obstructive pulmonary disease;

BDT, bronchodilator test; FEV1, forced

expiratory volume in 1 second; FVC, forced

vital capacity.

Several studies concluded that there is a significant positive relationship between the sputum

eosinophil count and blood eosinophil parameters, in terms of percentage or absolute count,

during exacerbations in patients with asthma, COPD and ACO(23–25).

Previous research showed that peripheral blood eosinophilia is associated with an

increase in all-cause mortality in patients with respiratory diseases(26,27). Therefore, the

peripheral blood eosinophil count(EO-count) is considered a predictor for the severity of the

disease(28).

In a cohort study, Price et al.(29) demonstrated that asthma patients with an EO-count

>400 cells/µL experience more severe exacerbations. This study also investigated the degree

of disease control and health status relative to different EO-counts. It was demonstrated that a

high EO-count >400 cells/µL was associated with a poorer asthma control. However, health

status deterioration was also observed for COPD patients with low EO-counts(30).

Furthermore, there is possibly a relation between EO-count and lung function in

patients with respiratory diseases. A high EO-count might contribute to a greater decline in

lung function, as measured by the forced expiratory volume in one second (FEV1), in patients

with asthma(31). In contrast, in COPD patients with an EO-count persistently >2%, the

predicted FEV1 was higher than that of the control group with an EO-count persistently

<2%(30,32). It is important to note that the differences between these groups were very small

and, therefore, the outcome of doubtful clinical relevance(30,32).

1.3. Treatment with inhaled corticosteroids

Inhaled corticosteroids (ICS) are preferred anti-inflammatory treatment for symptom

reduction, lung function improvement, exacerbation reduction and quality of life

improvement in patients with (allergic) asthma(7). Therefore, over the past decades, ICS have

taken an important role in asthma treatment. Moreover, there is an abundance of evidence

underlining the effectiveness of ICS for patients with asthma(8,33,34).

Several studies described that COPD patients are often unresponsive to corticosteroid

treatment because of their airway inflammation characteristics(12,35,36). Besides, it is known

that cigarette smoking impairs the efficiency of ICS treatment, which clarifies the nonexistent


response to ICS in COPD patients(37,38). However, literature also shows that when the

airway inflammation is dominated by high levels of eosinophils, it is more responsive to

corticosteroids(12,39). As described previously, in patients with severe COPD and frequent

exacerbations, the airway inflammation often consists of eosinophils too, which explains

responsiveness to corticosteroids in severe COPD patients(12). Research proved that ICS,

either solely or combined with long-acting beta2-agonists (LABA), decrease the risk of

exacerbations in COPD patients(40–42).

However, ICS therapy in patients with COPD is associated with more serious side

effects like pneumonia, bone fracture, diabetes and skin thinning(12,43–47). This increased

risk is possibly due to the typically older age and frequent comorbidities, like cardiovascular

diseases(4,12). Possibly, that is why general practitioners (GPs) are generally reserved in

prescribing ICS. Besides, lack of evidence of the effectiveness of ICS in COPD has led to

recommendations in which the use of ICS is restricted to severe COPD and frequent

exacerbations(12).

For patients suffering from ACO, there is a lack of randomized controlled studies

about the effectiveness of ICS(10). However, research does show that COPD patients with

asthma-like-features could benefit from treatment with ICS and might respond better to ICS

treatment than those with pure COPD(22,48,49).

1.4. Role of blood eosinophil count as biomarker

Due to the described side effects and lack of evidence of its effectiveness, the choice to start

with ICS treatment in primary care respiratory patients is a complicated decision, affording a

growing need for a biomarker that can predict the ICS treatment response.

The EO-count might be a possible predictor of the effectiveness of ICS in patients

with asthma, COPD and ACO(15,29). Previous studies suggest that patients with a higher

EO-count will have a better response to treatment with corticosteroids(23,28,39,50–52).

Patients with an EO-count >2% are significant less likely to experience exacerbations when

treated with ICS(51,52). Moreover, it was concluded that withdrawing ICS from patients with

an EO-count >4% or >300 cells/µL induced deleterious effects, like severe exacerbations,

which was not seen in patients with an EO-count below these thresholds(15).

However, the exact role of the EO-count and the effectiveness of ICS still remains

unclear in primary care respiratory patients, given the contradictory results in this field of

research to date. Therefore, research is required to investigate the ICS responsiveness more

extensively in a combined approach of asthma, COPD and ACO patients. To make

personalized care possible, well-defined real-life data on patient characteristics are required to

allow for comparison between patients with a good or poor response to ICS treatment.

1.5. Real life data

Most of previous described knowledge is derived from post-hoc analysis of clinical trials and

retrospective studies while solely a few studies used real life data. Real-life data are health

care data collected under real life practice circumstances. This provides a better representation

of the current care population due to a lack of precise inclusion and exclusion criteria(53).

The asthma/COPD service (AC-service) in Groningen, the Netherlands, is a supporting

service to improve the primary care treatment of asthma, COPD and ACO and consists of

real-life data of primary care respiratory patients(54). This service provides a unique

opportunity for the use of real life data to investigate the effectiveness of ICS relative to

different EO-counts in primary care respiratory patients.


1.6. Aims

This study aims to gain insight into the effect of ICS treatment for different EO-counts in real

life patient data.

The disease control gives a personalized approach to the real health status of the

patient, rather than lung function or exacerbation rate data that only addresses the condition of

the airways(55,56). Therefore, the primary objective is to investigate ICS treatment

effectiveness in terms of improved disease control (by means of the Asthma Control

Questionnaire (ACQ) and the Clinical COPD Questionnaire (CCQ) scores) for different EO-

counts. As secondary objectives the effectiveness of ICS treatment in terms of exacerbation

rate and lung function for different EO-counts will be analyzed.

According to previous work in the field, it is hypothesized that, in primary care

respiratory patients with asthma, COPD and ACO, higher EO-counts will lead to better

treatment response of ICS in terms of disease control, exacerbation rate and lung function.


2. Research questions

The primary research question is:

What is the effectiveness of ICS treatment in terms of improved disease control for

different EO-counts in patients with asthma, COPD and ACO?

Secondary research questions are:

What is the effectiveness of ICS treatment in terms of exacerbation rate for different

EO-counts in patients with asthma, COPD and ACO?

What is the effectiveness of ICS treatment in terms of lung function for different EO-

counts in patients with asthma, COPD and ACO?


3. Material and methods

3.1. Study design

This was a retrospective observational database study in primary care.

3.2. Data source

For this study, data were derived from the AC-service and Certe. The AC-service is part of

Certe, an organization for medical diagnostics and advice in primary and secondary care.

Asthma/COPD service

The AC-service, established in 2007 in Groningen, the Netherlands, is a service in which

general practitioners (GPs) are supported by pulmonologists to diagnose and manage their

asthma and COPD patients. GPs, from the Northern part of the Netherlands, can refer all

patients (≥ 8 years) with complaints indicative of asthma, COPD or ACO. Referred patients

complete a medical history questionnaire, the ACQ, the CCQ and different lung function tests

by spirometry. These data are assessed by an pulmonologist and recommendations concerning

diagnosis, medical and non-medical interventions are made. The GP receives the

pulmonologist’s recommendations within five working days after sending the patient to the

AC-service. Implementation of these recommendations is decided by the GP who is

ultimately responsible for the disease management. However, when a change in medication is

advised by the pulmonologist, patients are normally scheduled for an additional follow-up

visit after 3 months (range 2-4 months) by the AC-service. When no medication change is

advised but the GP does request a follow-up visit, patients will be assessed after 12 months

(range 10-14 months) by the AC-service(54,57). A cross sectional study on the feasibility and

effectiveness of this service showed that 60% of all adult patients with asthma, COPD and

ACO in the target area were assessed by the AC-service at least once(54). Asthma, COPD and

ACO patients visiting the service all showed improved health status and disease control

within three months. The service’ aim is to improve the management of primary care asthma,

COPD and ACO, however, data of included patients are also available for research, providing

a unique opportunity in exploring a large population. The aforementioned study included data

of 11,401 asthma, COPD and ACO patients assessed by the AC-service in 2014(54). Since

2014 the AC-service has continued assessing primary care respiratory patients and their data

were added to the database.

3.3. Participants

Patients who were referred to the AC-service from 2007 till 2016 were eligible for this study.

The first consultation of the AC-service was defined as the indexation date. In Table 2 an

overview of inclusion and exclusion criteria is depicted.

3.4. Procedure

A dataset was created with data from 2007 till 2016 selected from the AC-service database.

This data was combined on patient level with eosinophil data from the Certe-database. For

each patient, the most recent EO-count at the indexation date was used in analyses. Data from

the first follow-up visit after the indexation date were analyzed and compared to the baseline

data at the indexation date. All data concerning demographics (age, weight, height, medical


history, family history etc.), disease control (ACQ and CCQ), lung function, exacerbations

and medical advices given by the pulmonologist were analyzed.

Because the time between the indexation date and first follow-up visit differed per

patient, two different time periods for the follow-up visits were made. Based on previous

work of Metting et al.(54) and the distribution of the follow-up time among the included

patients in this study, these time periods were determined as < 6 months and ≥ 6 months. Sub

analyzes into the comparison between these time periods were performed.

Since this was a database study, a formal power calculation was not applicable.

Table 2: Inclusion and exclusion criteria of population

Inclusion criteria

Exclusion criterion

Age > 7 years

A diagnosis of asthma, COPD or ACO

confirmed by a pulmonologist on or previous

to the indexation date

At least one follow-up visit

Use of ICS treatment on the follow-up visit

A documented blood eosinophil count within

two years prior to the indexation date

Use of either inhaled or systemic

corticosteroids on or prior to the

indexation date

Abbreviations: AC-service, Asthma/COPD service; COPD, chronic obstructive pulmonary disease; ACO, asthma-COPD

overlap; ICS, inhaled corticosteroids.

3.5. Primary outcome

The primary outcome of this study was the difference in disease control after the start of ICS

in patients with asthma, COPD and ACO for different EO-counts. The outcomes were

analyzed for all three diseases combined as well as all three separately.

Patients were divided into subgroups based on their documented EO-count on the

indexation date. A valid EO-count was defined as a numerical value in blood eosinophil

concentrations of cells x 109

per L. Values were transformed to blood eosinophils per µL. The

four different groups were categorized according to the previous work of Watz et al.(15):

Group 1: Blood eosinophil count ≤150 cells/µL

Group 2: Blood eosinophil count 151-300 cells/µL

Group 3: Blood eosinophil count 301-400 cells/µL

Group 4: Blood eosinophil count > 400 cells/µL

To measure disease control, the validated self-administered ACQ and the CCQ were

used(55,58); see Appendices I and II. After referral to the AC-service, every patient needed

to complete both questionnaires.

These questionnaires are helpful for clinicians to not only recognize the clinical status

of the airways, but also emotional dysfunction and activity limitation in patients with asthma

and COPD. The responsiveness, reliability and validity of both questionnaires were proven by

qualitative research and observational studies(55,58). The ACQ includes five questions about

symptoms and one question about short-acting beta2-agonist (SABA) use. The COPD

questionnaire on the other hand includes ten questions divided into three subdomains with two

questions about mental status, four questions about functional status and four questions about

symptoms(55). Both questionnaires use a range of 0 to 6 to score the questions. Stable or

‘controlled’ asthma and COPD were respectively defined as an ACQ-score < 0,75 and CCQ-


score <1 respectively. Unstable asthma and COPD were defined as an ACQ-score ≥ 1.5 and

CCQ-score ≥ 1.7 respectively(59,60).

To measure the disease control, both questionnaires were used for all three diseases

combined. For specific analyzes into asthma patients, the ACQ-score was used to measure the

disease control. For specific analyzes into COPD patients, the CCQ-score was used. Both

questionnaires and equal scoring were used for patients with ACO. The means of disease

control scores at baseline and the first follow-up visit were compared.

It is questioned whether the ACQ- and CCQ-score results might be used for analyses

on the entire cohort and in ACO patients, because the ACQ is only validated for asthma

patients and the CCQ only for COPD patients(55,58). However, use of the ACQ-score for

COPD patients and vice versa is previously described in literature(61–63). Moreover, a

Pearson Correlation of 0.82 (p < 0,001) between the two questionnaires suggests that both

scores are representative for the non-validated patient population as well; see Appendix III.

3.6. Secondary outcomes

Secondary outcomes of this study were the difference in 1) lung function and 2) exacerbation

rate in ICS users with asthma, COPD and ACO for different EO-counts. The secondary

outcomes were analyzed in the same EO-count subgroups as the primary outcomes.

Differences in lung function and exacerbation rate between the baseline and the first follow-

up visit were analyzed. The secondary outcomes were analyzed for all three diseases

combined as well as all three separately.

The lung function was measured by post bronchodilator spirometry in terms of the

FEV1 in percentage of predicted, the FEV1 in liters and the forced vital capacity (FVC) in

liters. The FEV1/FVC ratio and the reversibility were determined both at the indexation date

and the first follow-up visit. The reversibility was defined as the increase in pre-

bronchodilator FEV1 compared to post-bronchodilator FEV1(54).

The exacerbation rate at the indexation date was defined as the number of patient-

reported exacerbations in the year prior to the indexation date. At the first follow-up visit, the

exacerbation rate was defined as the number of patient-reported exacerbations per year in the

period between the indexation date and the follow-up visit. Only the available reported

exacerbation rates of follow-up visits before June 2012 were analyzed, because the AC-

service steering group changed the way in which exacerbation rate data was obtained at the

follow-up visits performed after June 2012.

3.7. Data analysis

Statistical analyses were performed using the program IBM SPSS Statistics version 22.0. All

patients who met the inclusion criteria were included in the statistical analysis.

The baseline population was described by age, gender, body mass index, smoking

history, disease control (ACQ and CCQ), lung function performance and exacerbation history

for the different EO-count subgroups. Normally distributed variables were presented as mean

and standard deviation (SD). Nonnormally distributed scale variables were presented as

median and interquartile range (IQR). Categorized variables were presented as frequency of

appearance (n) and percentage (%). Normality of distributions was assessed by the calculated

Kurtosis and Skewness of histograms. Variables with values between -1 and 1 were

considered to be normally distributed. Furthermore, histograms of variables were interpreted

visually to assess the normality of distributions.


Analysis of the primary and secondary outcomes of this study were performed with

dependent sample t-test for normally distributed data and with the Wilcoxon Rank test for

nonnormally distributed data. The Mc Nemar test was used for dichotomous variables.

To prove differences between the four groups, the Analysis of Variance (oneway-

ANOVA) was used for normally distributed data and the Kruskall Wallis test was used for

nonnormally distributed data. The Chi-square test was used to compare groups for

dichotomous variables. Two tailed P values of less than 0,05 were taken as the threshold of

statistical significance(64).

3.8. Ethics

Patients who were referred to the AC-service agreed to anonymous usage of their data for

scientific research. The anonymous data were stored in a secure area.

Given this is a retrospective observational study and not an intervention study, this

study did not fall under the Medical Research Involving Human Subjects Act (WMO).


4. Results

4.1. Patient characteristics

Between January 2007 and December 2016 17,497 patients were referred to the AC-service.

Of these patients 11,567 were identified with asthma, COPD or ACO. Nine hundred sixty

patients met study eligibility criteria, of whom 337 (35%) had a documented EO-count. The

main reasons for exclusion were ICS treatment prior to or at indexation, or absence of ICS

treatment at the follow-up visit. In Figure 2 an overview of the selection criteria for eligible

patients is depicted.

Figure 2: Flow diagram of the

identification of eligible patients

Abbreviations: AC-service, Asthma/COPD

service; COPD, chronic obstructive pulmonary

disease; ACO, asthma-COPD overlap; ICS,

inhaled corticosteroids. *A valid blood eosinophil count was defined as a

numerical value for blood eosinophils recorded

within 2 years before the indexation date. 81% (n

= 274) was recorded within 1 year before the

indexation date.

Of all 337 patients included in the study, 126(37%) patients had a documented EO-count ≤

150 cells/µL, 151(45%) patients between 151-300 cells/µL, 31(9%) patients between 301-400

cells/µL and 29(9%) patients had an EO-count > 400 cells/µL. The median of EO-count

across all patients was 200 cells/µL (IQR 100-300). Of the entire study population, 215(64%)

patients were diagnosed with asthma, 74(22%) with COPD and 48(14%) with ACO.

38% (n = 129) of all included patients were male. However, higher male proportions

were observed in the patient groups with an EO-count between 301-400 cells/µL and > 400

cells/µL (p = 0,013). The median age across all patients was 55 years (IQR 41-65). Across the

different EO-count groups, the median age was the lowest among the patient group with an

EO-count > 400 cells/µL (median 44, IQR 24-59, p = 0,028).

When considering the smoking status of the entire study population, 33% (112

patients) were current smokers. Similar proportions of current smokers were obtained within

17,497 patients

referred to AC-

service

11,567 patients

with asthma,

COPD or ACO

960 patients

used ICS on

follow-up

337 patients

matched

inclusion criteria

Excluded:

diagnosis uncertain

n = 5,930

Excluded: current

or previous use of

ICS at baseline

n = 5,473

Excluded: no

documented blood

eosinophil count*

n = 623

6,094 patients

were ICS naive

at baseline

Exluded: no use of

ICS at follow up

n = 5,134


the different EO-count groups. SABA was the most received treatment at baseline (n = 107,

32%). Short-acting muscarinic antagonist (SAMA) treatment was used the least (n = 9, 3%).

This holds for all patients combined, as well as for the different patient groups stratified by

EO-count.

Baseline patient characteristics are presented in Table 3 and Table 4, respectively for

all patients together and for four groups of patients based on their EO-count. Supplemental

Table 1, appendix IV shows additionally baseline patient characteristics by asthma, COPD

and ACO diagnosis.

Table 3: Baseline characteristics for all included patients

Variable

Total

Demographics

Gender, male, n(%)

Age, years, median (IQR)

Body–mass index, kg/m2, median(IQR)

n=337

129 (38)

55 (41–65)

27 (23–31)

Smoking status

Current smoker, n(%)

Ex–smoker, n(%)

Smoke exposure, years, median (IQR)

n=337

112 (33)

132 (39)

22 (0–30)

Diagnosis, n(%)

Asthma

COPD

ACO

n=337

215 (64)

74 (22)

48 (14)

Age of disease onset or onset of symptoms, median (IQR)

Mean disease duration, years, median (IQR)

n=320 40 (13–58)

9 (2–24)

Current treatment at first consultation, n(%)

SABA

SAMA

LABA

LAMA

n=337

107 (32)

9 (3)

19 (6)

27 (8)

Disease control, median (IQR)

ACQ

CCQ

n=337

n=326

1.5 (0.8–2.0)

1.6 (1.0–2.4)

Lung function: post bronchodilator spirometry, mean (±SD)

FEV1% predicted

FEV1/FVC

Reversibility*, median (IQR)

n=337

n=320

86 (±19)

71 (±14)

6.7 (2.5-12.4)

≥ 1 exacerbation last year$, n(%) n=168 65 (39)

Abbreviations: COPD, chronic obstructive pulmonary disease; ACO, asthma–COPD overlap;

IQR, interquartile range; SABA, short–acting beta2-agonist; SAMA, short–acting muscarinic

antagonist; LABA, long–acting beta2-agonist; LAMA, long–acting muscarinic antagonist;

ACQ, asthma control questionnaire; CCQ, clinical COPD questionnaire; FEV1, forced expiratory

volume in 1 second; FVC, forced vital capacity.

*Increase in FEV1 pre bronchodilator compared with FEV1 post bronchodilator. $ Exacerbations are defined as having used oral corticosteroids or antibiotics for lung problems last year

Table 4: Baseline characteristics of patients for different EO-count groups

Abbreviations: EO-count, peripheral blood eosinophil count; IQR, interquartile range; COPD, chronic obstructive pulmonary disease; ACO, asthma–COPD overlap; SABA, short–acting beta2-

agonist; SAMA, short–acting muscarinic antagonist; LABA, long–acting beta2-agonist; LAMA, long–acting muscarinic antagonist; ACQ, asthma control questionnaire; CCQ, clinical COPD

questionnaire; SD, standard deviation; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; NS, not significant.

*Increase in FEV1 pre bronchodilator compared with FEV1 post bronchodilator. $Exacerbations are defined as having used oral corticosteroids or antibiotics for lung problems last year.

†Chi-square, **Kruskall-Wallis, ‡ 0ne-way ANOVA, p-values are two-sided and considered significant ≤ 0.05.

Variable

Eosinophils ≤150

cells/µL

Eosinophils 151–300

cells/µL

Eosinophils 301–400

cells/µL

Eosinophils >400

cells/µL

p - value

Demographics

Gender, male, n(%)


Body–mass index, kg/m2, median(IQR)

n=126

41 (33)

54 (37-64)

26 (23-31)

n=151

54 (36)

57 (47-66)

28 (25-32)

n=31

18 (58)

52 (39-72)

27 (23-29)

n=29

16 (55)

44 (24-59)

27 (23-31)

0.013† 0.028** 0.033**

Smoking status


Ex–smoker, n(%)


n=126

41 (33)

47 (37)

21 (0-29)

n=151

56 (37)

61 (40)

24 (6-31)

n=31

10 (32)

10 (32)

25 (0-33)

n=29

5 (16)

14 (48)

16 (0-27)

NS†

NS†

NS**

Diagnosis, n(%)

Asthma

COPD

ACO

n=126

81 (64)

25 (20)

20 (16)

n=151

92 (61)

35 (23)

24 (16)

n=31

19 (61)

9 (29)

3 (10)

n=29

23 (80)

5 (17)

1 (3)

NS† NS†

NS†

Age of disease onset, median (IQR)

Mean disease duration, years, median (IQR)

n=117 35 (14-56)

9 (2-27)

n=144 42 (15-59)

8 (2-25)

n=30 40 (11-60)

12 (3-19)

n=29 32 (8-49)

8( 3-23) NS**

NS**


SABA

SAMA

LABA

LAMA

n=126

38 (30)

4 (3)

7 (6)

10 (8)

n=151

46 (31)

5 (3)

8 (5)

13 (9)

n=31

10 (32)

0 (0)

3 (10)

2 (7)

n=29

13 (45)

0 (0)

1 (3)

2 (7)

NS†

NS†

NS†

NS†


ACQ

CCQ

n=126

n=122

1.4 (0.8-2.0)

1.6 (1.1-2.3)

n=151

n=147

1.3 (0.7-2.0)

1.6 (1.0-2.3)

n=31

n=30

1.8 (1.2-2.3)

1.7 (1.2-2.6)

n=29

n=27

1.7 (1.0-2.1)

1.6 (0.8-2.5)

NS**

NS**

Lung function post bronchodilator, mean (±SD)

FEV1% predicted

FEV1/FVC


n=126

n=118

86 (±19)

72 (±15)

6.1(2.9-12.1)

n=151

n=144

86(±18)

70(±13)

7.4(2.3-13.0)

n=31

n=30

83(±17)

70(±15)

6.9(4.2-13.3)

n=29

n=28

88(±21)

76(±14)

4.6(0.4-9.2)

NS‡

NS‡

NS**

≥ 1 exacerbation last year$, n(%) n=66 26 (39) n=68 24 (35) n=19 8 (42) n=15 7 (47) NS†


4.2. Follow-up time

The median follow-up time after starting ICS treatment was 5 months (IQR 3-13). For the

patient group with a follow-up time ≤ 6 months and > 6 months the medians of the follow-up

time were 3 months (IQR 3-4) and 14 months (IQR 11-36) respectively. Figure 3 shows an

overview of the distribution of follow-up time.

Figure 3: Follow-up time in

months

*Follow-up time is the period

between the first and second visit

to the AC-service.

4.3. Effect of ICS treatment on disease control

The disease control, measured by the ACQ- and CCQ-score, improved in most of the patients

after starting with ICS treatment (mean decrease of the ACQ-score and the CCQ-score was

0.39 (SD 0.33) and 0.37 (SD 0.30) respectively). In all four patients groups classified by EO-

count, there was a significant decline in the ACQ- and CCQ-score between baseline and

follow-up; see Table 5.

Table 5: Effect of ICS treatment on disease control (all included patients)

Abbreviations: ICS, inhaled corticosteroids; ACQ, asthma control questionnaire; CCQ, clinical COPD questionnaire;

COPD, chronic obstructive pulmonary disease; IQR, interquartile range; NS, not significant. $ Wilcoxon matched-pair signed rank test, p-values are two-sided and considered significant ≤ 0.05.

ACQ Baseline Follow-up p-value$

n median (IQR) median (IQR)

Eosinophils ≤ 150 cells/µL 124 1.4 (0.8–2.0) 1.0 (0.5–1.7) <0.001

Eosinophils 151-300 cells/µL 150 1.3 (0.7–2.0) 1.0 (0.5–1.7) <0.001


Eosinophils > 400 cells/µL 28 1.7 (1.0–2.1) 0.6 (0.2–1.3) <0.001

CCQ Baseline

Follow–up p-value$




Eosinophils 301-400 cells/µL 25 1.7 (1.2–2.6) 1.5 (1.0–1.9) 0.016

Eosinophils > 400 cells/µL 23 1.6 (0.8–2.5) 0.6 (0.4–1.7) 0.018

n = 337


The Kruskal-Wallis H test showed that there was a significant difference in decrease of ACQ-

scores between the different EO-count groups; X2(3) = 12.991, p = 0.005, with a mean rank

ACQ-score of 161 for eosinophils ≤ 150 cells/µL, 155 for eosinophils 151-300 cells/µL, 202

for eosinophils 301-400 cells/µL and 211 for eosinophils > 400 cells/µL. Therefore, post-hoc

tests were performed to specify in which groups significant differences in decrease of ACQ-

scores arose. The Mann-Whitney U test only showed a significant difference between the

groups with an EO-count between 151-300 cells/µL and an EO-count > 400 cells/µL (p =

0,005); see Figure 4. The Kruskal-Wallis H test did not show significant differences in the

decrease of CCQ-scores between the different EO-count groups, in analyses of all included

patients.

Figure 4: Boxplot of decrease

in ACQ score between

baseline and follow up for the

four groups categorized on

blood eosinophil count (all

included patients)

Abbreviations: ACQ, Asthma

Control Questionnaire; MCID,

minimal clinical important difference *Decrease of ACQ-score

In stratified analyses for diagnosis, asthma patients showed a significant decline of the ACQ

score for all EO-count groups after starting ICS treatment; see Supplemental Table 2,

appendix IV. COPD patients also demonstrated a significant decrease in CCQ-score after

starting ICS treatment for all EO-count groups, apart from those with an EO-count between

151-300 cells/µL; see Supplemental Table3, appendix IV. No significant decreases in ACQ

and CCQ scores between baseline and follow-up were observed in patients with ACO; see

Supplemental Table 4, appendix IV.

Between the different EO-count groups, specific analyses into asthma patients did not

show any statistically significant difference in decrease of ACQ-scores. However, specific

analyses for COPD patients did show a significant difference in decrease of the CCQ-scores

between the different EO-count groups (Kruskal-Wallis H test; X2(3) = 10.571, p = 0.048,

with a mean rank CCQ-score of 44 for eosinophils ≤ 150 cells/µL, 31 for eosinophils 151-300

cells/µL, 38 for eosinophils 301-400 cells/µL and 53 for eosinophils > 400 cells/µL). Post-hoc

tests, using the Mann-Whitney U test, showed significant differences in decrease of CCQ-

scores between the groups with an EO-count 151-300 cells/µL and an EO-count > 400

cells/µL (p = 0.052) and between the groups with an EO-count ≤ 150 cells/µL and an EO-

count 151-300 cells/µL (p = 0.021). The latter showed a significant greater decrease of CCQ-


score in patients with an EO-count ≤ 150 cells/µL compared to patients with an EO-count

between 151-300 cells/µL; see Figure 5.

The Kruskal-Wallis H test was not performed for the sub analyses into ACO patients,

due to the too small sample sizes within the different EO-count groups.

Figure 5: Boxplot of decrease

in CCQ score between

baseline and follow up for the

four groups categorized on

blood eosinophil count

(COPD patients)

Abbreviations: CCQ, Clinical

COPD questionnaire; COPD, chronic

obstructive pulmonary disease;

MCID, minimal clinical important

difference *Decrease of CCQ-score

4.4. Effect of ICS treatment on lung function

After starting ICS treatment, no significant improvement was found for both the FEV1%

predicted and FEV1/FVC-ratio between baseline and follow-up for all patients classified by

EO-count. Patients with an EO-count between 151-300 cells/µL even showed a significant

reduction in the FEV1/FVC-ratio after starting with ICS treatment (p = 0.022); see Table 6.

Analyses between the different EO-count groups did not show significant differences

in the degree of lung function improvement in both the FEV1% predicted and FEV1/FVC-

ratio, using the Kruskal-Wallis H test.

Stratified analyses for diagnosis did not show any significant differences in FEV1%

predicted after starting ICS treatment in asthma patients. However, significant declines in

FEV1/FVC-ratio were observed in patients with an EO-count ≤ 150 cells/µL (p = 0,001) and

in patients with an EO-count between 151-300 cells/µL (p = 0.011) after ICS treatment; see


Analyses within COPD patients demonstrated an improvement of the FEV1%

predicted after starting ICS treatment only in the group with an EO-count > 400 cells/µL (p =

0,042). None of the four EO-count groups showed an improvement in FEV1/FVC-ratio after

starting ICS treatment; see Supplemental Table 6, appendix IV.

Analyses of patients with ACO did not provide any significant differences in both the

FEV1% predicted and FEV1/FEV-ratio after starting with ICS treatment; see Supplemental

Table 7, appendix IV.


Table 6: Effect of ICS treatment on lung function (all included patients)

Abbreviations: ICS, inhaled corticosteroids; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; IQR,

interquartile range; NS, not significant. $ Wilcoxon matched-pair signed rank test, p-values are two-sided and considered significant ≤ 0.05.

4.5. Effect of ICS treatment on exacerbation rate

There was a decline in the number of patients experiencing ≥ 1 exacerbation per year after

starting with ICS treatment in all four EO-count groups. However, these declines were only

significant in patients with an EO-count ≤ 150 cells/µL (p = 0.003) and between 301-400

cells/µL (p = 0.031); see Table 7.

Analyses between different EO-count groups, using the Chi square test, did not

demonstrate any significant difference in the decline of the number of exacerbations.

Analyses on asthma patients showed only a significant decline in the number of

exacerbations per year in the patient groups with an EO-count ≤ 150 cells/µL; see


Specific analyses of COPD patients only and ACO patients only showed no significant

decrease in the number of patients experiencing ≥1 exacerbation per year after starting ICS

treatment. Also no decrease were observed in all four EO-count groups; see Supplemental

Table 9 and Table 10, appendix IV.

Table 7: Effect of ICS treatment on number of exacerbations (all included patients)

Abbreviations: ICS, inhaled corticosteroids; NS, not significant. *Exacerbation: number of patients experiencing ≥1 exacerbation per year, defined as having used oral corticosteroids or

antibiotics for lung problems $McNemar test, p-values are two-sided and considered significant ≤ 0.05.

4.6. Sensitivity analyses: differences in follow-up time

Sensitivity analyses were performed to account for patients with a follow-up time ≤ 6 months

and > 6 months after starting with ICS treatment. However, stratified analyses based on

follow-up time did not demonstrate any significant differences in the effect of ICS treatment

on disease control, number of exacerbations or lung function (data not shown).

FEV1% predicted Baseline Follow-up p-value$


Eosinophils ≤ 150 cells/µL 126 86 (73–99) 86 (72–98) NS

Eosinophils 151-300 cells/µL 151 88 (73–99) 86 (75–98) NS


Eosinophils > 400 cells/µL 29 94 (77–104) 95 (76–105) NS

FEV1/FVC Baseline

Follow-up p-value$



Eosinophils 151-300 cells/µL 151 72 (64–80) 72 (61–79) 0.022



≥ 1 exacerbation per year* Baseline Follow-up p-value$

n n(%) n(%)

Eosinophils ≤ 150 cells/µL 57 25 (43.9%) 11 (19.3%) 0.003

Eosinophils 151-300 cells/µL 64 22 (34.4%) 16 (25.0%) NS

Eosinophils 301-400 cells/µL 19 8 (42.1%) 2 (10.5%) 0.031

Eosinophils > 400 cells/µL 15 7 (46.7%) 2 (13.3%) NS


5. Discussion

5.1. Main findings

The aim of this study was to gain insight into the effect of ICS treatment for different EO-

counts in real life patient data. Analyses on the entire cohort of 337 real-life primary care

respiratory patients showed that, after ICS treatment, patients with a high EO-count at

baseline were more likely to improve their disease control based on their ACQ-score. This

suggests that a high EO-count is associated with a better response to ICS treatment,

confirming our hypothesis. Although improvement of the CCQ-score after ICS treatment was

observed, this was not related to the EO-count.

Specific analyses of patient subgroups classified by their diagnosis did show

improvement of both the ACQ- and CCQ-score after ICS treatment respectively for asthma

and COPD patients. However, this improvement was only related to the EO-count in COPD

patients. In ACO patients, no improvement on disease control was observed after ICS

treatment.

Furthermore, the hypothesized beneficial effect of ICS on lung function and

exacerbation rate was not related to the EO-count, though the latter did show improvement

after ICS treatment in some of the EO-count groups.

The main findings will be discussed in more detail below.

5.2. Comparison with current literature

Improvement of disease control related to the EO-count

The observed improvement of disease control could not be substantiated with current

literature, regarding asthma, COPD and ACO patients as a whole. As far as known from

previous research, knowledge on this subject is derived from studies on COPD patients only.

In asthma and ACO patients, there is a lack of substantial evidence on this subject.

When considering COPD patients independently, several studies show similar

results(65–67). These studies demonstrated an improvement of disease control related to the

EO-count after ICS treatment. However, contradictory results are observed in current

literature as well(28,35). To specify, one study showed improvement of disease control after

ICS treatment, but this was not related to the EO-count(28). Another study did not even

observe an improvement at all in any of the EO-count groups(35).

Comparison of our results with this existing literature is difficult since the studies

show a great difference in study design. This may also explain in part the observed

heterogeneity in results. First, oral corticosteroids were used in some studies instead of

ICS(28,65). Second, compared to our study all five studies used the EO-count percentages or

levels of sputum eosinophils(28,35,65,66) instead of the absolute EO-count, in which the

latter provides a more accurate representation of the actual number of blood eosinophils.

Moreover, the Chronic Respiratory Questionnaire (CRQ) and St. George’s Respiratory

Questionnaire (SGRQ) were used in the aforementioned studies. While it has been

demonstrated that change in CCQ scores correlates significantly with change in these latter

questionnaires(63), the three questionnaires do differ. For example, the CCQ scores are more

responsive to the effects of pulmonary rehabilitation(68).

In asthma and ACO patients it remains unclear whether the effect of ICS on disease

control is related to different EO-counts, based on our study results. No significant relation

was found between disease control improvement and the EO-count after ICS treatment, when

considering the ACQ-score for asthma patients and both the ACQ- and CCQ-score for ACO

patients. However, the absence of a relation between EO-count and disease control after ICS


treatment in these two diseases separately might be due to the small sample sizes of these

subgroups. Therefore, future research into asthma and ACO patients should include a larger

study sample to be more certain about the effect of ICS on disease control by EO-count.

It is important to note that statistically significant improvement is not the same as

clinically relevant improvement. In this study statistically significant differences were

observed in both the ACQ and CCQ questionnaire when comparing baseline scores with

follow-up scores for different levels of EO-count. However, for patient groups with a low EO-

count (≤ 150 cells/µL) these differences were not of clinical importance in both the ACQ- and

CCQ-score (ΔACQ-score = 0.4, ΔCCQ-score = 0.3), given the minimal clinical importance

difference (MCID) is 0.5 and 0.4 for the ACQ- and CCQ-score respectively(69–71).

Regarding patient groups with a high EO-count (> 400 cells/µL), the observed improvement

on disease control was both statistically significant and clinically relevant (ΔACQ-score =

1.1, ΔCCQ-score = 1.0). There is only one earlier study(65) on this subject which provided a

MCID. In this study by Brightling et al., the Chronic Respiratory Questionnaire (CRQ) scores

were used to assess the effect of ICS on disease control in relation to sputum eosinophils.

Similar to our study, although we used the EO-count instead of sputum eosinophils, results

were only of clinical importance in the group with high eosinophils (<4.5%). Among the other

groups (i.e. <1.3% and 1.3-4.5%), improvements on disease control were proven to be

trivial(65).

No improvement of lung function related to the EO-count

For the entire cohort of respiratory patients, improvement of lung function after ICS treatment

was not observed in any of the EO-count groups. Most likely the chronic progressive

character of the respiratory diseases in this study has contributed to this lack of lung function

improvement. According to previous literature(31,65,66,72–74), on the other hand, it was

expected to observe differences between patients with a low EO-count compared to patients

with a high EO-count, in which a larger improvement was expected in the latter patient group.

In our study, within COPD patients, an improvement of lung function was solely

demonstrated in the group with an EO-count > 400 cells/µL (p = 0,042). However, a relation

between EO-count and lung function improvement after ICS treatment was not identified. In

contrast, according to previous work in the field of COPD patients, a relation between EO-

count and lung function improvement does exist. High sputum eosinophils were associated

with an improvement of the FEV1 when receiving systemic corticosteroids(65) or ICS(67).

This was substantiated by Park et al., showing that a high EO-count was associated with an

improved lung function after 3-months of ICS/LABA treatment in COPD patients(72).

Furthermore, Barnes and colleagues concluded that patients with an EO-count <2% had a

similar rate of post-bronchodilator FEV1 decline with fluticasone propionate as placebo, while

in patients with an EO-count ≥2% the rate of decline decreased with the use of fluticasone

propionate versus placebo(66).

In asthma and ACO patients, the effect of ICS on lung function in relation to different

EO-counts is investigated before as well(31,73,74). The response of lung function to ICS

treatment, measured by the FEV1, was poorer in both asthma and ACO patients with low

sputum and EO-counts compared to patients with high levels of sputum or EO-

counts(31,73,74). In our study, neither improvement of lung function nor a relation between

EO-count and lung function improvement was observed within asthma and ACO patients.

The fact that such a relation between EO-count and lung function improvement was

not observed in this study may be related to the use of four EO-count categories within an

already small sample size of patient groups. To compare, the aforementioned studies used a

maximum of two subgroups classified by EO-count(66,72–74). In present study four EO-


count groups were defined, because using four cutoff values provides a better representation

of the role of EO-count relative to ICS treatment response.

Another explanation for not finding an improvement of lung function after ICS

treatment might be the relatively long follow-up time, given the progressive character over

time (75,76) and the loss of lung function in early stages of the respiratory diseases(77). In

present study the median follow-up time was 5 months (IQR 3-13 months), which is long

compared to the follow-up time used in current literature, ranging from two weeks to three

months(67,72,74).

No improvement of exacerbation rate related to the EO-count

When analyzing the entire study population, a significant decline in the number of self-

reported exacerbations was observed in some of the EO-count groups (i.e. EO-count ≤ 150

cells/µL and EO-count 301-400 cells/µL). The observed declines of the exacerbation

frequency in the other groups (i.e. EO-count 151-300 cells/µL and EO-count > 400 cells/µL)

were not significant, however, these declines can be considered of clinical relevance given the

extent to which the frequencies decreased (9% and 33% respectively for EO-count 151-300

cells/µL and EO-count > 400 cells/µL). The identified declines in exacerbation rate after ICS

treatment were not related to EO-count, which was not in line with our expectation

considering previous work in the field(52,66,78).

Within COPD patients, many previous studies showed that the EO-count at baseline

was related to the exacerbation rate after ICS treatment(52,66,78). Compared to those with a

low EO-count, patients with a high EO-count gained more benefit from treatment with ICS in

terms of a reduced exacerbation frequency(52,66,78). In the present study, the absence of an

association between ICS treatment and reduced exacerbation frequency related to the EO-

count, may be again related to insufficient statistical power, since analyses were performed on

a total of 155 patients and specific analyses on solely 28 COPD patients. Compared to

previous work of Barnes et al.(66) and Pascoe et al.(52), more COPD patients were included

in their studies, respectively 738 and 3.177 patients. They also classified the COPD patients

into two different EO-count based sub groups (< 2% vs. ≥ 2%) instead of the four subgroups

used in the present study. Furthermore, comparison is also difficult because the present study

differs methodologically from the aforementioned studies, in which post-hoc analyses were

performed comparing an ICS treatment group with a control group receiving

placebo(52,66,78).

When considering asthma patients, previous studies did demonstrate a relation

between a higher EO-count and an increased risk of exacerbations, however, whether the

effect of ICS on the exacerbation rate is related to the EO-count is not investigated(29,79).

Belda et al. concluded that asthma patients with stable and well-controlled asthma are at risk

of exacerbation despite regular ICS treatment, especially in patients with an EO-count ≥ 400

cells/µL(79). This result is in contrast to our work, in which we do see a small clinically

relevant improvement of the exacerbation rate after starting with ICS treatment, although not

statistically significant.

Since ACO is a relatively new diagnosis, this is the first study to examine the effect of

ICS on health outcomes within EO-count groups. Unfortunately, the very small sample size of

ACO patients with available data on exacerbation rate withholds us to draw any conclusions.

5.3. Strength and limitations

To the best of our knowledge, this is the first study in primary care that examined the effect of

ICS on disease control, in relation to different EO-counts. Disease control measured by the

ACQ and CCQ reflects patients’ real functional status and health condition, rather than their


clinical observations. Moreover, as far as known, this is the first study investigating ICS

effectiveness in a combined approach of primary care respiratory patients with asthma, COPD

and ACO.

The strength of this study is the use of real life primary care data, which provides a

better representation of the actual situation of such a population with respiratory diseases(53).

In randomized control trials, on the other hand, it is mandatory to use strict inclusion and

exclusion criteria. Therefore, those study populations do not reflect the real patient

population.

Furthermore, in this study the absolute EO-count was used while many previous

studies(28,30,50–52,66,78) defined subgroups based on EO-count percentages. The latter can

be affected by total white blood cells and therefore, the absolute EO-count gives a more

accurate representation of the actual number of blood eosinophils. Besides, our study used

four cut off values instead of two cut off values used in previous studies(28,30,50,51,66,78).

Using more cut off values provides more insight into the exact role of the EO-count in

relation to the ICS treatment response.

A limitation of our study is that no control group was available because data were not

collected prospectively. A control group could have been created retrospectively, but this

would have biased the results because such a control group would consist of patients that did

not receive the advice to start ICS treatment. Hence, these patients were probably already

healthier. Without control group, it is not possible to conclude that the observed

improvements of the outcome measurement are due to ICS treatment alone. The observed

findings could partially be due to spontaneous changes(80). Therefore, our conclusions are

limited to implying a relation between EO-count and the effect size of ICS treatment, rather

than establishing a firm relation. However, both prospective(28,35,65,67,72) and retrospective

studies(15,52,66,78) using patient control groups, also showed an effect of ICS treatment on

related to EO-count. This does substantiate our implied relation.

A further shortcoming is that the AC-service is not established for scientific reasons.

Data derived from the AC-service could potentially be less accurate. For example, we could

not assess whether patients had used their ICS and determine their treatment adherence.

However, poor adherence to ICS would lead to poor disease control(81,82), while in our study

an improvement of disease control was demonstrated. Therefore, it is considered unlikely that

the aforementioned limitation would have affected the quality and outcome of this research

substantially.

Additionally, some patients in the study population used other inhalator medication

simultaneously with their ICS treatment, for which it is unknown whether the patients started

with these treatments concurrently. Therefore, it remains unclear whether the observed

treatment response is solely due to ICS or that other medication plays a role as well. However,

of the included patients only LABA or long-acting muscarinic antagonist (LAMA) treatment

was advised concurrently with ICS and for those treatments it is known that their effect is

greater when combined with ICS treatment(41,83–85).

Finally, as mentioned before, the small number of subjects limited us to draw firm

conclusions. While in very small patients groups it is difficult to find significant results, the

significant differences should also be treated with caution. Accordingly, further adjustments

for potential confounders like sex and age in multivariable linear regression analyses, could

not be performed due to the restricted study size. On the other hand, our study population size

was still larger than those employed in numerous previous studies(28,35,72,79,86).


5.4. Implications and recommendations

This study gives insight into the effect of ICS in relation to different EO-counts in primary

care respiratory patients. In practice, health care providers can expect that primary care

respiratory patients with a high EO-count will experience a better response to ICS treatment

than patients with a low EO-count. Therefore, the EO-count could be an attractive biomarker

to use in clinical practice. Moreover, EO-count measurement is convenient, widely available

and reliable in comparison to sputum eosinophil measurement which requires more skilled

technical support(28).

Further research is needed to further substantiate the observed improvement of disease

control, exacerbation rate and lung function with ICS treatment for patients with a high EO-

count. Especially in patients with asthma or ACO more research is required because of the

lack of evidence in this study population. Therefore, prospective studies with larger sample

sizes are required, also allowing for regression analyses. Moreover, to determine the effect

size of ICS treatment, study results have to be compared with a patient control group without

ICS treatment.

Towards more substantiation in future retrospective studies using real life data, use of

a pharmacy database linked at patient level would be advised to provide dispense data and

accurate data of medication collection. This affords additional information on the duration of

ICS treatment and allows for more extensive investigation into the combined use of ICS with

LABA or LAMA. Besides, the self-reported exacerbation rate could then also be checked by

correlation with the administration of oral corticosteroids or antibiotics.

Additionally, the predictive value of the EO-count in relation to ICS response remains

unclear. Generally, the EO-count tends to stay reasonably stable in individual patients over

time(87,88), however the exact time period over which EO-count can be assumed stable is

currently unknown. Therefore more information is still needed on the positive and negative

predictive value of this stability to define reliable stability ranges. With a firm conclusion on

the stability of eosinophils, it will be evident whether the EO-count is a promising biomarker

to guide disease management.

Finally this study shows that disease control is a promising measure to investigate the

effectiveness of ICS treatment relative to different EO-counts. However, to measure disease

control in primary care respiratory patients, a uniform questionnaire for asthma, COPD and

ACO patients is required, due to the overlap of current questionnaires and lack of a specific

questionnaire for ACO patients(62,63). Moreover, accuracy of the specific questionnaires per

diagnosis is also questionable given the different syndromes are comprised of various

phenotypes. Therefore, development of a general tool assessing the burden of chronic

respiratory conditions in primary care is required and should be used in further research on

this subject.


6. Conclusion

In primary care respiratory patients with a high EO-count at baseline, ICS treatment is

associated with larger improvements of disease control compared to subgroups of patients

with lower EO-counts. The beneficial effect of ICS on lung function and exacerbation rate

showed no correlation with the EO-count. The EO-count is potentially an important

biomarker that could contribute to treatment decision making in primary care respiratory

patients. These findings suggest the need for further studies, including prospective control

trials on larger sample sizes.


7. Acknowledgements

I would like to thank all members of the department of general practice (University Medical

Center Groningen) for their support and for providing me the opportunity to perform a

research project in the interesting field of primary care. Thanks to dr. J.W.H. Kocks (assistant

professor and program leader GRIAC-Primary Care) and dr. B.M.J. Flokstra- de Blok

(assistant professor) for their guidance and feedback. Special thanks to drs. H.J. Baretta and

dr. S.N. Slagter for their enthusiasm, commitment, encouragement and critical view in

completing the research project. A final thanks to drs. E.I. Metting for her assistance and

advice in the statistical analyses.


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Di Franco A, Vagaggini B, et al. Low

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response to beclomethasone in symptomatic

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72.

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Count in Patients with COPD in the UK

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JHM, et al. Stability of blood eosinophils in

COPD and controls and the impact of

gender, age, smoking and baseline counts.

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2017;195(10):1402–4.


Appendices Appendix I Asthma Control Questionnaire

Appendix II Clinical COPD Questionnaire

Appendix III Pearson Correlation

Appendix IV Supplementary tables


Appendix I Asthma Control Questionnaire


Appendix II Clinical COPD Questionnaire

COPD VRAGENLIJST

Omcirkel het nummer dat

het beste beschrijft hoe u zich de afgelopen week heeft gevoeld.

(Slechts één antwoord per vraag)

Hoe vaak voelde u zich in de

nooit

zelden

af en toe

regelmatig

heel vaak

meestal

altijd afgelopen week …

1. Kortademig in rust?

0

1

2

3

4

5

6

2. Kortademig gedurende

lichamelijke inspanning?

0

1

2

3

4

5

6

3. Angstig/bezorgd voor de

volgende benauwdheidsaanval?

0

1

2

3

4

5

6

4. Neerslachtig vanwege uw

ademhalingsproblemen?

0

1

2

3

4

5

6

In de afgelopen week, hoe vaak heeft

u …

5. Gehoest? 0 1 2 3 4 5 6

6. Slijm opgehoest?

0

1

2

3

4

5

6

In welke mate voelde u zich in de

helemaal

héél

een

tamelijk

erg

héél

volledig

afgelopen week beperkt door uw

ademhalingsproblemen bij het

uitvoeren van …

niet

beperkt

weinig

beperkt

beetje

beperkt

beperkt beperkt erg

beperkt

beperkt/

of niet

mogelijk

7. Zware lichamelijke activiteiten

(trap lopen, haasten, sporten)?

0

1

2

3

4

5

6

8. Matige lichamelijke activiteiten

(wandelen, huishoudelijk werk,

0

1

2

3

4

5

6

boodschappen doen)?

9. Dagelijkse activiteiten 0 1 2 3 4 5 6

(u zelf aankleden, wassen)?

10. Sociale activiteiten

(praten, omgaan met kinderen,

0

1

2

3

4

5

6

vrienden/familie bezoeken)?

© University Medical Center Groningen , T. van der Molen

© Op de CCQ berust copyright. De vragenlijst mag niet worden veranderd, verkocht (op papier of elektronisch), vertaald of aange-

past voor een ander medium zonder de toestemming van T. van der Molen, Huisartsgeneeskunde, University Medical Center

Groningen, Postbus 196, 9700 AD Groningen, Nederland.


Appendix III Pearson Correlation

Table 1: Baseline characteristics of patients population per diagnosis

Variable

Asthma

COPD

ACO

Demographics

Gender, male, n(%)


Mean body-mass index, kg/m2, median (IQR)

n=215

66 (31)

47 (30–59)

27 (23–32)

n=74

41 (55)

64 (57–71)

26 (24–30)

n=48

22 (46)

63 (56–70)

27 (25–30)

Smoking status


Ex-smoker, n(%)


n=215

44 (20)

80 (37)

10 (0–24)

n=74

40 (54)

32 (43)

31 (27–36)

n=48

28 (58)

20 (42)

29 (24–35)

Age of disease onset or onset of symptoms, years

Mean disease duration, years

n=209 25 (10–49)

10 (2–24)

n=65 60 (50–64)

4 (1–12)

n=46 41 (19–57)

20 (5–38)


SABA

SAMA

LABA

LAMA

n=215

85 (40)

6 (3)

9 (4)

5 (2)

n=74

10 (14)

1 (1)

7 (9)

17 (23)

n=48

12 (25)

2 (4)

3 (6)

5 (10)


ACQ

CCQ

n=215

n=204

1.5 (0.8–2.2)

1.6 (1.0–2.4)

n=74

1.3 (0.8–2.0)

1.8 (1.1–2.4)

n=48

1.2 (0.7–2.0)

1.5 (0.9–2.3)

Lung function post bronchodilator, mean(±SD)

FEV1% predicted

FEV1/FVC


n=215

n=209

94 (±15)

79 (±9)

5.4 (2.2–10.3)

n=74

n=65

70 (±16)

56 (±10)

7.2 (1.3–11.9)

n=48

n=46

74 (±16)

61 (±9)

12 (8.0–15.9)

≥ 1 exacerbation last year$, n(%) n=121 46 (39) n=29 13 (45) n=18 6 (33)

Blood eosinophil count

Baseline EO-count, median (IQR)

Eosinophils ≤150 cells/µL, n(%)

Eosinophils 151-300 cells/µL, n(%)

Eosinophils 301-400 cells/µL, n(%)

Eosinophils ˃400 cells/µL, n(%)

n=215

200 (100–300)

81 (38)

92 (43)

19 (9)

23 (11)

n=74

200 (100–300)

25 (34)

35 (47)

9 (12)

6 (8)

n=48

100 (100–200)

20 (42)

24 (50)

3 (6)

1 (2) Abbreviations: COPD, chronic obstructive pulmonary disease; ACO, asthma-COPD overlap; IQR, interquartile range, SABA, short-acting beta2-agonist; SAMA, short-acting muscarinic

antagonist; LABA, long-acting beta2-agonist; LAMA, long-acting muscarinic antagonist; ACQ, asthma control questionnaire; CCQ, clinical COPD questionnaire; FEV1, forced expiratory

volume in 1 second; FVC, forced vital capacity; EO-count, peripheral blood eosinophil count.

*Increase in FEV1 pre bronchodilator compared with FEV1 post bronchodilator. $Exacerbations are defined as having used oral corticosteroids or antibiotics for lung problems last year.



Table 2: Effect of ICS treatment on disease control in asthma patients

Abbreviations: ICS, inhaled corticosteroids; ACQ, asthma control questionnaire; IQR, interquartile range. $ Wilcoxon matched-pair signed rank test, p-values are two-sided and considered significant ≤ 0.05.

Table 3: Effect of ICS treatment on disease control in COPD patients

Abbreviations: ICS, inhaled corticosteroids; COPD, chronic obstructive pulmonary disease; CCQ, clinical COPD

questionnaire; IQR, interquartile range; NS, not significant. $ Wilcoxon matched-pair signed rank test, p-values are two-sided and considered significant ≤ 0.05.

Table 4: Effect of ICS treatment on disease control in ACO patients

Abbreviations: ICS, inhaled corticosteroids; ACO, asthma-COPD overlap; COPD, chronic obstructive pulmonary disease;

ACQ, asthma control questionnaire; CCQ, clinical COPD questionnaire, IQR, interquartile range; NS, not significant; NA,

not applicable. $ Wilcoxon matched-pair signed rank test, p-values are two-sided and considered significant ≤ 0.05.








CCQ Baseline

Follow-up p-value$



Eosinophils 151-300 cells/µL 35 1.6 (1.0–2.2) 1.5 (0.9–2.0) NS





Eosinophils ≤ 150 cells/µL 20 1.1 (0.3–1.5) 1.0 (0.2–1.6) NS


Eosinophils 301-400 cells/µL 3 0.7 (0.3–3,8) 0.5 (0.3–1,0) NS

Eosinophils > 400 cells/µL 1 1.3 0.0 NA

CCQ Baseline



Eosinophils ≤ 150 cells/µL 18 1.3 (0.6–1.9) 1.2 (0.7–1.9) NS


Eosinophils 301-400 cells/µL 3 1.1 (0.4–2,9) 1.5 (1.3–1,7) NS

Eosinophils > 400 cells/µL 1 1.6 0.6 NA


Table 5: Effect of ICS treatment on lung function in asthma patients

Abbreviations: ICS, inhaled corticosteroids; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; IQR,

interquartile range; NS, not significant. $ Wilcoxon matched-pair signed rank test, p-values are two-sided and considered significant ≤ 0.05.

Table 6: Effect of ICS treatment on lung function in COPD patients

Abbreviations: ICS, inhaled corticosteroids; COPD, chronic obstructive pulmonary disease; FEV1, forced expiratory volume

in 1 second; FVC, forced vital capacity; IQR, interquartile range; NS, not significant. $ Wilcoxon matched pair signed rank test, p-values are two-sided and considered significant ≤ 0.05.

Table 7: Effect of ICS treatment on lung function (ACO patients)


FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; IQR, interquartile range; NS, not significant; NA,

not applicable. $ Wilcoxon matched-pair signed rank test, p-values are two-sided and considered significant ≤ 0.05.








FEV1/FVC Baseline



Eosinophils ≤ 150 cells/µL 81 79 (74–87) 78 (72–85) 0.001

Eosinophils 151-300 cells/µL 92 78 (73–83) 77 (73–81) 0.011








Eosinophils > 400 cells/µL 5 51 (43–62) 65 (48–73) 0.042

FEV1/FVC n Baseline












Eosinophils > 400 cells/µL 1 74 76 NA

FEV1/FVC Baseline






Eosinophils > 400 cells/µL 1 76 71 NA


Table 8: Effect of ICS treatment on number of exacerbations in asthma patients

Abbreviations: ICS; inhaled corticosteroids; NS, not significant. *Exacerbation: number of patients experiencing ≥1 exacerbation per year, defined as having used oral corticosteroids or

antibiotics for lung problems. $McNemar test, p-values are two-sided and considered significant ≤ 0.05.

Table 9: Effect of ICS treatment on number of exacerbations in COPD patients

Abbreviations: ICS, inhaled corticosteroids; COPD, chronic obstructive pulmonary disease; NS, not significant. *Exacerbation: number of patients experiencing ≥1 exacerbation per year, defined as having used oral corticosteroids or


Table 10: Effect of ICS treatment on number of exacerbations in ACO patients


NS, not significant; NA, not applicable. *Exacerbation: number of patients experiencing ≥1 exacerbation per year, defined as having used oral corticosteroids or



≥ 1 exacerbation per year*

n Baseline Follow-up p-value$

n n (%) n (%)

Eosinophils ≤ 150 cells/µL 44 17 (38.6%) 7 (15.9%) 0.021



Eosinophils > 400 cells/µL 12 5 (41.7%) 2 (16.7%) NS


Baseline Follow-up p-value$

n n (%) n (%)

Eosinophils ≤ 150 cells/µL 9 6 (66.7%) 4 (44.4%) NS


Eosinophils 301-400 cells/µL 5 2 (40.0%) 0 NS

Eosinophils > 400 cells/µL 3 2 (66.7%) 0 NS


Baseline Follow-up p-value$

n n (%) n (%)

Eosinophils ≤ 150 cells/µL 4 2 (0.50%) 0 NS


Eosinophils 301-400 cells/µL 2 0 0 NA

Eosinophils > 400 cells/µL - – – NA

the absolute blood eosinophil count a...

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