A new measure to assess asthma's effect on quality of life from the patient's perspective

A new measure to assess asthma's effect on quality of life from the patient's perspective

Accepted Manuscript A New Measure to Assess Asthma’s Impact on Quality of Life from the Patient’s Perspective Sandra R. Wilson, PhD, Michael J. Mullig...

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Accepted Manuscript A New Measure to Assess Asthma’s Impact on Quality of Life from the Patient’s Perspective Sandra R. Wilson, PhD, Michael J. Mulligan, MD, Estela Ayala, MD, Alan Chausow, MD, Qiwen Huang, MS, Sarah B. Knowles, PhD, MPH, Santosh Gummidipundi, MS, Mario Castro, MD, MPH, Robert A. Wise, MD. PII:

S0091-6749(17)30887-4

DOI:

10.1016/j.jaci.2017.02.047

Reference:

YMAI 12838

To appear in:

Journal of Allergy and Clinical Immunology

Received Date: 15 June 2016 Revised Date:

10 February 2017

Accepted Date: 23 February 2017

Please cite this article as: Wilson SR, Mulligan MJ, Ayala E, Chausow A, Huang Q, Knowles SB, Gummidipundi S, Castro M, Wise RA, A New Measure to Assess Asthma’s Impact on Quality of Life from the Patient’s Perspective, Journal of Allergy and Clinical Immunology (2017), doi: 10.1016/ j.jaci.2017.02.047. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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TITLE PAGE

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Original Article

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A New Measure to Assess Asthma’s Impact on Quality of Life from the Patient’s Perspective

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Sandra R. Wilson, PhD,1,2 Michael J. Mulligan, MD,3 Estela Ayala, MD,3 Alan Chausow, MD,3

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Qiwen Huang, MS,1 Sarah B. Knowles, PhD, MPH,1 Santosh Gummidipundi, MS,1 Mario Castro,

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MD, MPH,4 Robert A. Wise, MD.5

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Palo Alto Medical Foundation Research Institute, Palo Alto, CA.

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Department of Medicine, Stanford University School of Medicine, Stanford, CA.

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Palo Alto Medical Foundation, Mountain View, CA.

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Departments of Medicine and Pediatrics, Washington University School of Medicine, St. Louis,

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Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.

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Corresponding Author

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Sandra Wilson, PhD

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Palo Alto Medical Foundation Research Institute

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795 El Camino Real

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Palo Alto, CA

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Telephone: 650-853-2898

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E-mail: [email protected]

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Funding: Supported by Grant No. HL119845 (PI: S. Wilson) from the National Heart, Lung and

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Blood Institute/NIH.

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Word count: 6,138

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Abstract:

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Background: The Asthma Impact on Quality of Life Scale (A-IQOLS) assesses the negative

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effect of asthma on quality of life (QoL) from the patient’s perspective, using dimensions of

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Flanagan’s Quality of Life Scale (QOLS), a measure of current QoL.

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Objectives: To determine and compare the psychometric properties of the A-IQOLS and QOLS,

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including their sensitivities to differences and changes in asthma status.

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Methods: In a test-retest design (3-5 week interval), adults with persistent asthma underwent

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spirometry and were administered the A-IQOLS, other asthma outcome measures (ACT, ASUI,

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Marks and Juniper AQLQs), and QOLS.

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Results: Participants’ (n = 147) mean age was 49 yrs.; 76% were White; 12% Hispanic; 65%

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female. A-IQOLS and QOLS scores were significantly correlated with other asthma outcomes

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scores except FEV1, but shared relatively low common variance with these measures. A-IQOLS,

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but not QOLS, score changes were significantly correlated with changes in asthma outcomes.

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The A-IQOLS SEM = 0.27 implies that a within-person score change of ≥ ±0.73 constitutes a

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true change. The QOLS SEM = 0.43.

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Conclusions: A-IQOLS provides a reliable, valid, and unique assessment of the patient-

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perceived negative effect of asthma on their QoL, suitable for use in asthma clinical research and

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potentially in clinical care. Further studies are needed in diverse patient populations. QOLS, a

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measure of current QoL, is less sensitive to disease status changes but may be useful in charac-

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terizing study populations, in treatment adherence research, and as a clinical and research tool in

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patients with multiple, severe, and/or life-limiting chronic conditions.

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(250 words)

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Clinical Implications

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The Asthma Impact on Quality of Life Scale assesses the negative impact of asthma on quality of

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life from the patient’s perspective, providing unique information for evaluating asthma outcomes

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in research and clinical settings.

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Capsule Summary

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This is the first report of the reliability, validity, and sensitivity of the Asthma Impact on Quality

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of Life Scale (A-IQOLS), which assesses the negative impact of asthma on quality of life from

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the patient’s perspective.

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Key words

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Asthma

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Quality of life

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Measurement/Standardized measures

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Clinical outcomes

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Patient-centered outcomes

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Abbreviations used

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ACT: Asthma Control Test; A-IQOLS: Asthma Impact on Quality of Life Scale; AOW: Asthma

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Outcomes Workshop; ASUI: Asthma Symptom Utility Index; BTR: Bronchial Thermoplasty

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Responder study; COPD: Chronic Obstructive Pulmonary Disease; CR: Repeatability Coeffi-

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cient; FEV1: Forced Expiratory Volume in 1 second; IAQLS: Impact of Asthma on Quality of

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Life Scale; ICC: Intraclass Correlation Coefficient; LASST: Long-acting Beta Agonist Step

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Down Study; LOA: Limit of Agreement; Marks AQLQ: Marks Asthma Quality of Life Ques-

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tionnaire; Mini-AQLQ: Juniper Mini Asthma Quality of Life Questionnaire; NIOSH: National

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Institute of Occupational Safety and Health; OCS: Oral Corticosteroid; OSA: Obstructive Sleep

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Apnea; PHQ-9: Patient Health Questionnaire; PROMIS: Patient Reported Outcomes Measure-

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ment Information System; QoL: Quality of Life; QOLS: Flanagan Quality of Life Scale; SDS:

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Disproportionate Stratified Sampling; SEM: Standard Error of Measurement; STROBE:

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STrengthening the Reporting of OBservational studies in Epidemiology; U.S.: United States.

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INTRODUCTION

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The 2010 NIH Asthma Outcomes Workshop (AOW) reviewed existing instruments and proce-

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dures for measurement of all types of asthma outcomes measures. With respect to asthma-

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related quality of life (QoL),1 the AOW concluded that assessing disease impact on patients’

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QoL remains an essential component of the asthma outcome measurement toolbox.2 However, it

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also concluded that no available “asthma-specific QoL” measures, even those in widespread use,

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actually assess the patient’s perception of the effect of asthma on their QoL.2 Instead, existing

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instruments measure the patient’s status in physical, mental, and social health domains as these

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relate to asthma. The conceptual frameworks of such measures consist of health domains --

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symptom frequency and severity, how much asthma limits the individual’s activities (i.e., their

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functional status), and in some cases, negative emotions related to asthma such as concerns,

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fears, or embarrassment.

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The AOW recognized that the content validity of a measure is fundamental, which means

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that, except in rare instances, the content of a measure should have a very direct, obvious rela-

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tionship to its intended purpose and the construct it purports to measure.3 The fact that a health

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status measure is reliable, is logically correlated with other measures of asthma status, and con-

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tains items about the frequency and intensity of functional limitations, does not mean it is a valid

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measures of the patient’s perception of how or how much asthma affects their QoL -- a judgment

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that can only be made by the patient. The effects of asthma on QoL are very likely to be deter-

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mined by factors in addition to symptoms and functional limitations, such as how important it is

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to the patient to engage in particular activities, how difficult for them to avoid things that trigger

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their asthma without having to forego valued activities, etc. Existing instruments may provide an

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assessment of an individual’s asthma and functional status. However, the fact that they do not

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assess the patient’s perception of how the disease affects their QoL is what led the AOW not to

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recommend any existing instrument as a core QoL measure for use in asthma clinical research.

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In the 1970s, by gathering and analyzing narrative reports from a large, diverse sample of

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individuals across the U.S. regarding events/experiences that significantly affected their quality

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of life (positively or negatively), eminent psychologist John C. Flanagan identified 15 dimen-

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sions that affect individuals’ quality of life (Figure 1).4 He developed a Quality of Life Scale

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(QOLS) on which individuals can rate the extent to which their needs and wants are being met

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on each dimension.5 In essence, he considered the quality of life of an individual as defined by

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how well that person felt that their needs and wants were being satisfied across all the dimen-

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sions of life. The QOLS, a generic measure that can be used with any individual, regardless of

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health status, does not ask the respondent to assess the contribution of any particular factor to

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their QoL.

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We propose an approach to measuring an individual’s perception of the impact of a disease

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on their QoL that uses Flanagan’s quality of life dimensions. As an initial example of this ap-

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proach, we created the Asthma Impact on Quality of Life Scale (A-IQOLS). Rather than asking

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how well the individual’s needs and wants are being satisfied, the A-IQOLS asks the individual

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to rate the negative effect of a disease and its treatment on each QoL dimension. Here we report

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the A-IQOLS’ development process and the methods and results of a test-retest study to deter-

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mine its psychometric properties in patients with persistent asthma.

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An alternative to the IQOLS approach would be to simply measure patients’ perception of

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their quality of life (e.g., using the QOLS), and then infer the impact of their disease based on

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temporal changes or between-group differences in QOLS scores. To compare these alternatives

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in asthma patients, and because both types of instruments could have potential uses in research

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and clinical practice, both were administered in this study. To assess the current relevance of the

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quality of life dimensions, we also obtained individuals’ ratings of the personal importance of

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each dimension.

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METHODS

The research reported here was supported by Grant No. HL119845 (PI: Wilson) from the

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National Heart, Lung, and Blood Institute/NIH. The study is approved by the Sutter Health IRB

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(SHIRB No. 14-06-327).

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Instrument Development and Pilot Testing

The development of the A-QOLS and the pilot testing of the A-QOLS, Flanagan’s Im-

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portance questionnaire, and his QOLS in asthma patients, are described in the Supplement. These

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measurement instruments, as used in the present study, are presented in Figure S1, followed by

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their Administration Instructions. The history of the development and use of the QOLS by

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Flanagan also is described in the Supplement, as are subsequent modifications made by other

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investigators. Key distinctions between these versions are described in order to clarify the ra-

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tionale for using Flanagan’s own QOLS’s stem question and rating scale in the present study.

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Test-Retest Study Sample

Eligibility. Inclusion criteria:

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Physician diagnosis of asthma

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Ages 18-70 years (the upper limit was to reduce the likelihood that significant fixed airway

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obstruction would be observed upon assessment of patients’ lung function)

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Current prescription for an asthma controller medication

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Care received from a primary care provider in the large multi-specialty health care system within the preceding 24 mo.

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daytime symptoms < 2times/week and nocturnal symptoms < 2 times/mo.) •

or another lung disease other than asthma)

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Significant healthcare event such as chest or abdominal surgery in past 3 months, cataract or other major surgery in preceding month, or scheduled procedure prior to study follow-up.

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Significant medical co-morbidities that could affect interpretation of the results, (e.g., COPD

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Intermittent asthma (i.e., no routine use of asthma controller medications; seasonal asthma or

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Exclusion criteria:

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Inability to complete basic requirements of the study protocol, including spirometry testing and questionnaires

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Any circumstance preventing the patient from attending two clinic visits, one month apart.

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Primary care physician’s determination that including the patient was inappropriate for any of the above reasons.

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Recruitment

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Patients potentially meeting the inclusion criteria were identified by querying electronic

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clinical and administrative records and randomly selected for recruitment using a disproportion-

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ate stratified sampling (SDS) methodology with stratification by race, ethnicity, sex, and treat-

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ment step of the patient’s current asthma controller regimen.12 Sampling probabilities were de-

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signed to achieve a distribution that: 1) corresponded to the sex and race distribution in the U.S.

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asthma population, and 2) ensured a more uniform distribution across asthma treatment steps

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(and, by inference, levels of asthma severity) than would have resulted from randomly sampling

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patients with persistent asthma, most of whom would have had mild or moderate disease. Poten-

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tial participants were contacted by phone, screened, and (if eligible and interested) scheduled for

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an initial clinic visit.

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Patient Assessment

At baseline, Informed consent and anthropometric measurements were obtained, pre-and

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post-bronchodilator spirometry performed and a questionnaire self-administered. Pre-

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bronchodilator spirometry and the questionnaire were repeated four weeks later (3-5 weeks de-

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pending on patients’ availability).

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Importance of QoL dimensions. This measure asks respondents to rate how important each of the dimensions is to them on a scale from 1 = Not at all important to 5 = Very important. Flanagan QOLS. The QOLS scale (Fig. S2) asks patients to rate how well their needs

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and wants are being satisfied on each quality of life dimension using a bidirectional scale from 1

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= Not at all well satisfied to 5 = Very well satisfied.5 A-IQOLS. The A-IQOLS (Fig. S1) asks respondents to rate the negative effect of their

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asthma and its treatment, over the preceding 4 weeks, on each of 16 quality of life dimensions

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using a standard unidirectional scale ranging from 1 = No negative effect at all to 5 = Extremely

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negative effect.

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Other standardized asthma outcome measures. Asthma control, symptoms and function-

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al impairment were assessed using the Asthma Control Test (ACT),13 Asthma Symptom Utility

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index (ASUI),14 Marks Asthma Quality of Life Questionnaire (Marks AQLQ),15 and Juniper

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Mini Asthma Quality of Life Questionnaire (Mini-AQLQ)16 -- all widely used in asthma re-

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search. The Patient Health Questionnaire (PHQ-9)17 was used to assess depression.

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Spirometry. Research coordinators, certified for occupational spirometry by NIOSH, used standardized research methods and equipment that met or exceeded American Thoracic So-

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ciety standards.18 The percent predicted pre-bronchodilator FEV1 based on age-, sex- and race-

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specific norms,19 is considered a core physiological measure in asthma research.20

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Statistical Analysis

Descriptive statistics were computed for patient demographic and clinical characteristics.

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The A-IQOLS and QOLS summary scores were the averages of their respective dimension rat-

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ings. Other standardized asthma outcome measures were scored and scaled using their published

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algorithms.13, 16, 21–25 Differences between the test and retest administrations on all measures

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were evaluated using t-tests (continuous variables) and chi-square tests (categorical variables).

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Associations between pairs of measures were assessed using Spearman or Pearson Rank-Order

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correlation coefficients, as appropriate to their distributional properties. The Importance ques-

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tionnaire has no summary score; dimension importance ratings are considered individually.

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Measurement reliability. Asthma being an inherently variable disease, it is not reasonable to assume that all changes that might be observed over a 3-5 weeks period are entirely due to

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errors of measurement and not to real changes in the underlying construct a given measure is de-

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signed to assess. However, the baseline and associated follow-up assessments were fairly uni-

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formly distributed over all seasons of the year, and the 3-5 week test-retest interval, while argua-

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bly long enough to reduce recall influences, was short enough to minimize systematic seasonal

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changes in asthma status. It is expected that the observed variability in disease status would be

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typical of the variability that would occur in a clinical trial at a similar interval in the absence of

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any specific intervention. Using the repeated assessments of each patient, a two-way, repeated-measures analysis of

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variance was used to calculate 1) the intraclass correlation coefficient (ICC), a relative reliability

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index, and 2) the within subject variance, whose square root is the estimated standard error of

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measurement (SEM), a less population-dependent reliability index that, unlike the ICC, can be

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interpreted on the original response scale. The repeatability coefficient is based on the SEM (CR

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= 2.77xSEM)26, and is the smallest within-person change that can be considered, with 95% con-

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fidence, to be a real change. The upper and lower bounds of the 95% limit of agreement (LOA)

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around the CR value, and their confidence intervals (CI), were also calculated.26, 27

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Internal consistency reliability. Standardized coefficient alpha was used to estimate the internal consistency of the items of the A-IQOLS, QOLS, and other outcome measures. Construct validity. The content validities of the QOLS and A-IQOLS were established

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by 1) the direct relevance of their root questions to the construct each is intended to measure, and

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2) the original research that defined the quality of life dimensions to which the ratings are ap-

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plied. The continued relevance of the dimension was evaluated by considering the present Im-

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portance ratings. Convergent validity was evaluated by examining the patterns and significance

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of the associations between the A-IQOLS and QOLS and other concurrently administered asth-

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ma outcome measures and their associations with each other. The squared correlations (R2) esti-

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mate the proportion of common variance between any two measures. Divergent validity, the

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amount of unique information provided by a measure, is estimated by 1-R2, the amount of inde-

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pendent variance between a pair of measures as well as variance due to measurement error.

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A significance level of 0.05 was used throughout. To interpret the strength of correlation coefficients, we followed Evans (1996)28: 0.00-0.19 = very weak, 0.20-0.39 = weak, 0.40-0.59 =

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moderate, 0.60-0.79 = strong, 0.80-1.0 = very strong correlation. All statistical analyses were per-

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formed using SAS v 9.2 (SAS Institute, Inc., Cary, NC).

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RESULTS

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Study Population

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Recruitment and Enrollment. Contact was attempted with 950 of the identified, potentially eligible patients, 153 of whom were screened, confirmed eligible, agreed to participate, and

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completed in-person consent and baseline assessment. Of these, 148 (97%) completed both the

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baseline (test) and follow-up (retest) assessments (STROBE diagram, Fig. S3). One was subse-

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quently determined to have COPD, and hence was ineligible, resulting in an analysis sample with

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n = 147 patients.

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Baseline characteristics. Participants’ mean (± SD) age was 49.1 (± 12.3) years; 64.6%

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were female, 75.5% White, 15.0% Black, and the remainder Asian or another race; 11.6% were

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Hispanic (Table 1). The sample was largely well educated and employed/retired, with moderate to

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high income. Just over half reported adult onset asthma, and 95.2% reported aeroallergens among

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their asthma triggers. Approximately three-fourths (76.2%) were never smokers and only 3.4% cur-

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rent smokers. In the year pre-enrollment, they averaged 0.4 (±0.8) exacerbations requiring an oral

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corticosteroid (OCS) and 1.58 (±1.95) asthma medical visits. A high proportion (82.3%) were ei-

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ther overweight (35.4%) or obese (46.9%), and nearly half (49.7% were at high risk for sleep apnea

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based on their Berlin scores. In 2010 the obesity rate was 38.8% in individuals with current asthma

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compared with 26.8% in those without.29 Obesity has been associated with adult asthma onset30

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and obstructive sleep apnea.31 Since this sample has persistent, not just current, asthma, and obesity

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rates have continued to increase since 2010, the obesity and sleep apnea risk rates in this sample are

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not unreasonable. Intentional oversampling of patients with more intense asthma regimens yielded a sample

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with 25.8% of patients at treatment step 2 or 3, 41.5% at step 4, and 32.7% at step 5 or 6 at baseline

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(Table 1). In the population of eligible patients with persistent asthma from which the sample was

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drawn, an estimated 55% were at step 2 or 3, 30% at step 4, and only 15% at step 5 or 6. Over-

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sampling patients with more intense regimens also tended to increase heterogeneity on other, asso-

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ciated disease parameters.

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Clinical characteristics of the sample at baseline and follow-up (Table 2) show that lung function averaged in the normal range with no significant between-assessment difference. Based on

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ACT score, at baseline 54.4% of the enrolled patients had well controlled, 22.4% poorly controlled,

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and 23.1% very poorly controlled asthma, which can be compared with estimated proportions of

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63%, 17%, and 20%, respectively, among all eligible patients. At follow-up, the proportion of pa-

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tients with well-controlled asthma was significantly higher (by 8.2 percentage points), with a corre-

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sponding decrease in the proportions with poorly/very poorly controlled asthma. The mean ASUI

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score at baseline was 0.8, indicating a relatively low level of symptoms, which is consistent with

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mean scores on the Marks AQLQ (Mean = 13.9, between 0 = “Not at all” and 20 = “Mildly” affect-

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ed on the Marks 0-80 scale)32 and Juniper Mini-AQLQ (Mean = 5.4; between 5 = “A Little of the

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Time”/”Some Limitation” and 6 = “Hardly Any of the Time”/”A Little Limitation”).16 All of these

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asthma status measures, as well as mean A-IQOLS scores, differed significantly, but by quite small

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amounts, between baseline and follow-up.

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To compare baseline and follow-up exacerbation and visit rates (Table 2), the 4 week period

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preceding each assessment was examined. In the relatively short period of 4 weeks, visits and exac-

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erbations were relatively infrequent and the proportions of patients who had exacerbations and the

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proportion who had asthma visits did not differ significantly between baseline and follow-up

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(McNemar exact test, p = 1.0 and p = 0.82, respectively).

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Importance of the Quality of Life dimensions

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From 63% to 94% of patients rated 15 of the 16 dimensions, including Independence, as

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either Important/Very Important to them (Table S1). Only Participation in activities relating to

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local and national government and public affairs, was considered Important/Very Important by a

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significantly smaller proportion of individuals (26%). All individuals had dimensions they rated

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as Important/Very Important, but there was considerable individual variation in priorities. The

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pattern of what was typically more or less important (Table S1) was generally consistent with

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Flanagan’s earlier findings for 30-, 50-, and 70-year olds and for men and women in the general

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U.S. population.5 This indicates that these dimensions have lasting importance to individuals

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despite changes in American life in the intervening 40 years. Even Participation in government

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and civic affairs was considered Important/Very Important by more than one-third (35%) of old-

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er women.

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Asthma Impact on Quality of Life Scale (A-IQOLS) The mean baseline (test) and follow-up (retest) A-IQOLS summary scores were 1.35 ± 0.45

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and 1.25 ± 0.34, respectively (Table 2), indicating, on average, a relatively low perceived negative

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impact of asthma on patients’ QoL. Individuals’ summary scores ranged from 1 – 3.9. The entire

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rating scale range (1-5) was used in patients’ ratings of impairment on the individual QoL dimen-

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sions. Ratings of 5 (Extremely Negative Effect) were given on seven of the 16 dimensions and rat-

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ings of either 4 or 5 on 13 of the 16 dimensions. Eleven patients (7.5%) reported a negative impact

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on one or more of nine different dimensions (material well-being, work, independence, relations

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with their spouse/partner, relations with other family members, having and raising children, helping

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others, governmental/civic activities, and personal/spiritual development and practices) that was

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equal to or greater than the impact they reported on health and safety, social activities, and active

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recreation, which are the dominant focus of other measures commonly referred to as asthma-related

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quality of life measures.

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A-IQOLS scores differed by income level (p = 0.008) but not by age, sex, race, ethnicity,

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level of education, or employment status (Table S2). Lower income patients (< $75,000) felt that

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their asthma had a more negative effect on their quality of life than did those at higher income levels

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(A-IQOLS: Mn ± SD = 1.53 ± 0.50 versus Mn ± SD = 1.30 ± 0.42). However, the association with

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income was not significant after controlling for ACT score (p = 0.53), since poorer asthma control

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was more prevalent in the lower income patients. Patients at high risk for obstructive sleep apnea

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(OSA) had significantly higher A-IQOLS scores (i.e., greater negative effect of asthma) than did

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those at low OSA risk (p = 0.01). Smoking status and BMI were not associated with A-IQOLS

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scores.

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Baseline mean A-IQOLS scores differed significantly by level of asthma control -- well-

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controlled (1.15), poorly controlled (1.45) and very poorly controlled asthma (1.73) (p < 0.0001).

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Asthma treatment “step” -- was marginally but not significantly associated with A-IQOLS score (p

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= 0.07). However, the mean score for those at step 6, which is characterized by a need for routine

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use of multiple asthma medications (high-dose ICS + LABA + oral corticosteroid ± Omalizumab),

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was considerably higher (1.78) than that of those at treatment steps 4 or 5 (1.34 and1.39), which al-

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so was higher than for those at steps 2 and 3 (1.25 and 1.24). Mean A-IQOLS scores differed sig-

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nificantly among these three groups (p = 0.02). Reliability. The A-IQOLS intraclass correlation coefficient, ICC = 0.56 (Table 3). This

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value is similar to the ICCs of the other self-reported asthma outcome measures (Table S3). A

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higher ICC was observed for the PPFEV1 (ICC = 0.90), which would be expected for an objective,

339

albeit effort-dependent and labile, clinical measure.

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The standard error of measurement (SEM = square root of the within-subject variance) is a

341

fundamental statistic by which to evaluate the reliability of a measure (Table 3). Unlike a dimen-

342

sionless index such as ICC, the SEM is interpretable in the units of the score scale.33 The A-

343

IQOLS’ SEM = ±0.27 scale score points. The estimated lower and upper bounds of the SEM limits

344

of agreement (LOA) – the range that contains 95% of the differences between repeated measure-

345

ments on the same individual – were -0.83 and 0.63, respectively. The A-IQOLS’ coefficient of

346

repeatability (CR) = 2.77x SEM = ±0.73 units on the impact rating scale, indicating that, with 95%

347

probability, a within-person change in A-IQOLS score of 0.73 units or more, in either direction, can

348

be considered a true/real change in the perceived negative effect of asthma. SEM values of the oth-

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er asthma outcome measures and PHQ-9 are provided in Table S4.

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A-IQOLS internal consistency reliability. The standardized coefficient α for the A-IQOLS

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was high (α = 0.91 at baseline; α = 0.93 at follow-up), and comparable to those of the other self-

352

reported measures on which these patients were assessed (Table S3). Coefficient alpha, an indica-

353

tor of the cross-sectional inter-correlation among the items, is commonly reported for measurement

354

tools. However, it is not informative regarding measurement reliability -- the ability of a measure to

355

discriminate between individuals -- which information is provided by the SEM (and derivative CR).

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Alpha is most useful in item selection to achieve a reduction in the number of items, which was not

357

the relevant for the A-IQOLS or QOLS.

358

A-IQOLS convergent and divergent validity. With the exception of PPFEV1, A-IQOLS scores were significantly correlated with all of the asthma status measures, and depression (PHQ-9

360

(all p-values < 0.0001), at both baseline and follow-up (Table 4). However, in nearly all cases, the

361

shared or common variance (R2) between the A-IQOLS and the other measures was less than 40%.

362

At baseline and follow-up, ACT and A-IQOLS scores were moderately correlated (r = -0.50 and r =

363

.53). A-IQOLS scores also were moderately correlated with ASUI (symptom) scores (r = -0.51 and

364

r = -0.52) and more highly correlated with Marks AQLQ scores (r = 0.74 and r = 0.72) than with the

365

ACT (asthma control), ASUI (symptom), and Juniper AQLQ scores. Even so, the common vari-

366

ance between Marks AQLQ and A-IQOLS was only about 50% and for other measures even lower.

367

At baseline neither the number of exacerbations requiring OCS use nor the number of medi-

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cal visits in the preceding 4 weeks was significantly associated with A-IQOLS scores, but the fol-

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low-up correlation with exacerbations was significant (p = 0.01) (Table 4). Neither the number of

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exacerbations nor of visits in these brief time periods accounted for a meaningful proportion of the

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variance in A-IQOLS scores.

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Depression (PHQ-9) was significantly correlated with patients’ evaluation of the negative impact of asthma on their quality of life (A-IQOLS scores). However, the correlation was not

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strong and the PHQ-9 and A-IQOLS shared only about one-fifth of their variance in common.

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A-IQOLS’ sensitivity to changes in asthma status. Although small, baseline-to-follow-up

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changes in asthma status measures -- asthma control (ACT scores), asthma symptoms (ASUI

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scores), Marks and Juniper AQLQ scores, and number of asthma medical visits -- were significantly

378

correlated with changes in A-IQOLS scores in the expected directions (Table 5). And while the A-

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IQOLS was significantly correlated with the number of exacerbations in the preceding 12 months

380

(Table S2), the extremely small baseline to follow-up differences in the numbers of exacerbations

381

and asthma-related medical visits in the relatively brief (one month) time periods preceding each

382

assessment were not significantly associated with changes in A-IQOLS scores.

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Changes in depression were significantly associated with changes in A-IQOLS scores (r = 0.20; p = 0.01).

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Current Quality of Life (QOLS)

Participants’ mean QOLS summary scores were 3.7 ± 0.8 at baseline and 3.6 ± 0.7 at fol-

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low-up -- on average, they felt that their needs and wants were Well Satisfied or Very Well Satisfied

389

(Table 2). The baseline to follow-up change in mean QOLS scores was borderline significant (p =

390

0.06). QOLS scores did not differ significantly by age, sex, race, level of education, or employment

391

status (Table S1), but were significantly associated with ethnicity (lower in Hispanics than non-

392

Hispanics; p = 0.03) and family income (lower in those with annual family income < $75,000; p =

393

0.01). Smoking status and BMI were not associated with QOLS scores. Patients at high risk for

394

obstructive sleep apnea (OSA) had significantly lower QOLS scores than did those at low OSA risk

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(p = 0.002). Some high risk patients may have had OSA, especially given the high obesity rate, but

396

some may have been reporting sleep problems largely or partially associated with asthma.

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QOLS reliability. The QOLS’ within-subject ICC = 0.67 (Table 3), its standard error of

398

measurement (SEM) = ±0.43, and its repeatability coefficient (CR) = ±1.19 (Table 3). One can be

399

95% confident that within-person QOLS score change of 1.2 units or more in either direction is a

400

true/real change in how well the individual feels his/her needs and wants are being satisfied.

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401 402 403

QOLS internal consistency reliability. The QOLS standardized coefficient α = 0.93 (Table S4). Again, alpha is not an indicator of measurement reliability. QOLS convergent and divergent validity: correlations with health status measures. QOLs scores were not significantly correlated with the percent predicted FEV1 at either baseline or follow-

405

up (Table 4) but were significantly correlated with the other asthma/health status measures and (at

406

follow-up only) with the number of exacerbations requiring OCS use. As expected, the correlations

407

between the asthma status measures and QOLS scores, and consequently their shared variances,

408

were typically lower than the corresponding correlations between these measures and A-IQOLS

409

scores, at both baseline and follow-up. Treatment step (2-6) and the number of asthma medical vis-

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its were not correlated with QOLS scores.

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QOLS scores were significantly (p < 0.0001), but only weakly correlated28 with A-IQOLS scores (r = -0.39 at baseline), with only approximately 15% common variance. The correlation between QOLS scores and depression (PHQ-9) and QOLS (r = -0.52 at

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baseline; p < 0.0001) was slightly greater than that between the PHQ-9 and A-IQOLS (r = 0.45),

415

but this difference was not statistically significant.34 QOLS sensitivity to changes in asthma status. In contrast to the strong associations between

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changes in asthma status measures and changes in A-IQOLS scores between baseline and follow-

418

up, changes in asthma status measure were not significantly correlated with changes in QOLS

419

scores (Table 5). Similarly, the correlation between changes in A-IQOLS scores and changes in

420

QOLS scores was very weak (r = -0.15) and not statistically significant (p = 0.07), at least for the

421

relatively small changes observed between test and retest. Changes in depression (PHQ-9 scores),

422

however, were significantly correlated with changes in QOLS scores (p = 0.053).

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DISCUSSION The A-IQOLS has strong content validity -- it directly queries the patient about the effects of their asthma on a comprehensive set of dimensions of individuals’ quality of life whose continued

426

relevance is supported by the present results. Its scores proved to be reliable (i.e., to discriminate

427

well between patients with differing asthma status, to have an appropriate-size SEM determined in a

428

test-retest study), and to have strong convergent validity. Its scores and score changes were signifi-

429

cantly correlated, in the expected directions, with scores and score changes in other asthma out-

430

comes measures but not so highly correlated as to compromise its divergent/discriminant validity.

431

The relatively low shared variances indicate that A-IQOLS scores provide unique information not

432

provided by other asthma measures. Many of those measures, long included in the asthma outcome

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measurement toolbox, continue to be useful, but are not adequate proxies for a measure of the pa-

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tient’s perception of how their asthma and its treatment are affecting their quality of life.

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The relatively new Impact of Asthma on Quality of Life Scale (IAQLS)35 consists of

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items drawn from the National Institutes of Health’s Patient–Reported Outcome Measurement

437

Information System (PROMIS®) database.36 PROMIS supports development of efficient, pre-

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cise, valid, responsive adult and child reported measures of health status in specific health do-

439

mains (http://www.nihpromis.org/about/missionvisiongoals), and addresses many limitations of

440

existing generic and disease-specific health status measures. While the IAQLS may provide a

441

better measure of asthma patients’ functional status, like earlier measures, it does not directly

442

assess the patient’s perception of the impact of asthma on their life. Hence, contrary to its de-

443

veloper’s claim, it is not responsive to the central recommendation of the 2010 NIH AOW with

444

regard to quality of life measures.

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Potential research uses of the A-IQOLS In asthma research the A-IQOLS may be used to characterize study populations at baseline. A-IQOLS scores, reflecting the patients’ perception of disease impact, also may have explanatory

449

use in treatment adherence research. Importantly, a measure of patient perception of the effects of

450

asthma and its treatment could provide an important secondary and, in some cases, potentially a

451

primary outcome measure in trials of asthma therapy. In patients with moderately severe or severe

452

asthma, where both the disease and its treatment may have significant negative effects, assessment

453

of the patient’s perspective may be of even greater importance and may help ensure a more com-

454

plete evaluation of therapeutic benefits than is provided by physiological, symptom, or functional

455

status measures.

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Potential research uses of the QOLS

The QOLS can be administered to any adult, regardless of health status. However, unlike

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other generic measures widely used in health research (e.g., the SF-1237 or the EuroQol-5D,38)

460

which assess symptoms, mood, and functional limitations that have diverse etiology and high

461

prevalence in the general population (e.g., pain), the QOLS measures the individual’s perception

462

of their quality of life. The present study found that, while QOLS scores are reliable and are sig-

463

nificantly correlated with A-IQOLS scores, the perceived negative effect of asthma on dimensions

464

of an individual’s quality of life (A-IQOLS scores) shares only 15% variance with how well the in-

465

dividual feels their needs and wants are being satisfied (QOLS scores), and score changes in A-

466

IQOLS and QOLS scores share only 2% common variance. Further, in asthma patients, QOLS

467

scores are somewhat less strongly correlated with other asthma outcomes measures than are A-

468

IQOLS scores. This suggests that, for many if not most asthma patients, their overall quality of life

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is less dependent on their asthma than on other factors. An individuals’ quality of life has many

470

influences, historically and at any given point in time. A health problem is just one such poten-

471

tial influence. It appears that a measure, such as the A-IQOLS, which asks the patient to evalu-

472

ate the impact of a specific disease on their quality of life, is a more direct, sensitive, and appro-

473

priate approach than inferring impact from changes or differences in a generic measure such as

474

the QOLS. However, this does not mean that the QOLS has no appropriate clinical or behavioral

475

research use. On the contrary, it is a reliable and valid measure and may be particularly useful as

476

a generic QoL measure for characterizing and comparing study populations, as a measure of QoL

477

when that construct is potentially a mediator or moderator of other outcomes, and as a primary or

478

secondary outcome in studies of special populations such as those with multiple chronic diseases

479

or diseases that are very severe and/or life-limiting.

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Clinical use of the A-IQOLS and QOLS.

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The present study identified the minimal within-person score changes on the A-IQOLS and the QOLS that represent true change. This information is critical to their potential clinical use.

484

They provide standardized measures of the patients’ perception of their QoL and of the negative

485

effects of asthma on their QoL using a common conceptual framework. Both are brief, both can be

486

completed on paper or electronically at home or in the clinic waiting room, and scoring is

487

straightforward -- features that make their clinical use more feasible. For example, patients

488

whose asthma is not as well controlled as it might be, but who feel asthma is having little negative

489

effect (low A-IQOLS score), may be making personal choices about medication use or their activi-

490

ties that are satisfactory for them, and may not want or warrant escalation of treatment to improve

491

asthma control. Other patients with poorly controlled asthma may regard their asthma as having

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only a small negative effect because other circumstances, situations, or health conditions are having

493

a much greater negative effect. This circumstance, if revealed to clinicians by A-IQOLS and/or

494

QOLS scores and ratings, and used in conjunction with other clinical information, may prove useful

495

in clinical management. Given the current state of knowledge, choosing the appropriate response

496

to a patient’s A-IQOLS or QOLS results would be a matter of clinician judgement. Further re-

497

search is needed to determine whether the summary scores and/or the individual dimension ratings

498

can play a useful role in informing clinical management decisions and care.

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In both research and practice, a disease-specific instrument such as the A-IQOLS and a generic instrument such as the QOLS can be used separately or together. A disease-specific in-

501

strument appears most useful in patients with a single significant chronic disease or a small

502

number of relatively distinct conditions. When rating the negative effect of a disease, it is to be

503

expected that some patients will incorrectly attribute symptoms, functional limitations, and side

504

effects to the disease when they actually result from another cause (e.g., shortness of breath may

505

result from asthma and/or obesity and physical deconditioning). Conversely, patients may not

506

recognize certain symptoms or side effects as being due to asthma or its treatment. However,

507

such perceptions, accurate or not, may influence patients’ disease management. Further, this is

508

not unique to the A-IQOLS. The same potential confusions exist in patient-reported symptoms,

509

functional limitations, and medication side effects on asthma-related health status measures, and

510

other self-report measures.

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The QOLS may have an additional unique role to play in research and clinical practice

513

involving patients with multiple chronic conditions (MCC) and/or a severe or life-limiting condi-

514

tions. In such circumstances, the goals of medical treatment are appropriately aimed at maintain-

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ing, and if possible enhancing, the patient’s overall QoL. For that purpose, the QOLS has poten-

516

tial advantages over both disease-specific measures such as the A-IQOLS and generic measures

517

such as the SF-12 or EuroQoL. Further, with disease progression may come a shift or narrowing

518

in the areas of life that are most important to the individual, which the QOLS is uniquely able to

519

accommodate. Further research is needed on the relative merits of the QOLS in patients with

520

multiple, severe, and/or life-limiting conditions.

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Limitations

523

The present study was intentionally broadly representative of asthma patients in its racial/ethnic

524

and sex distribution, and heterogeneous in level of treatment intensity and asthma severity. It

525

was not, however, designed to be representative in socioeconomic status, education, or source of

526

health care. Participants also were drawn from a single health care system, although not a

527

closed/single insurer system -- many PAMF patients also receive care from non-PAMF primary

528

or specialty care providers.

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More importantly, the sample size is too small to determine the psychometric properties of the A-IQOLS and QOLS in specific patient subgroups, e.g., those with very low levels of education,

531

particular racial or ethnic groups, or those with severe asthma. However, several other clinical tri-

532

als of asthma treatment are underway that will support key sub-group analyses (to determine the

533

generalizability of use of the instruments) and will include analyses of follow-up data from clini-

534

cal trials of asthma treatment (to determine sensitivity to treatment effects, which will further

535

inform power and sample size estimates for future clinical trials.

536 537

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Finally, the present sample is too small to properly assess the incremental value of weighting individuals’ responses on the A-IQOLS and/or QOLS scales by their personal Im-

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portance ratings when computing summary scores. Typically, such weighting strategies have not

539

proven to be useful, have significant computational disadvantages in scoring,33 and require collec-

540

tion of additional information, such as on the present Importance scale, in order to calculate appro-

541

priate weights. It is likely that ratings on the A-IQOLS and QOLS already take into account the im-

542

portance of dimensions to the individual. However, the issue of importance-weighting inevitably

543

arises with regard to instruments of this type, and will be addressed in our analysis of data from oth-

544

er studies now underway.

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Future directions

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The A-IQOLS is a model for a potential family of IQOLS measures to assess the quality of life impact of other diseases, conditions, and treatments. Such measures are straightforward to

549

create and are relevant to assessing the quality of life impact of virtually any health condition or

550

treatment. They would utilize the same rating scale as the A-IQOLS, but the stem question

551

would specify whatever disease or condition was of interest. The use of a common rating scale

552

permits direct comparison of the negative effects of different diseases and treatments on quality

553

of life and may also support cost benefit studies. For some purposes a bi-directional scale (both

554

positive and negative effects) might also be used.

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Conclusions

The Asthma Impact on Quality of Life Scale (A-IQOLS) is a reliable and valid measure

558

of patients’ perception of the impact of asthma on their quality of life, providing unique infor-

559

mation not provided by other asthma self-report measures that assess patient’s symptoms and

560

functional status. Further study is needed to understand the performance of this measure in par-

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ticular patient subgroups, its sensitivity to the effects of different therapeutic interventions, and

562

its value in clinical care. The success of the IQOLS approach in asthma suggests that this type of

563

measure may be useful in other diseases as well. The Flanagan QOLS is a reliable and valid

564

measure of patients’ perception of whether their needs and wants are being satisfied and yields a

565

score that represents their perceived quality of life. While less sensitive than the A-IQOLS to

566

changes in asthma status, it has potential value in characterizing study populations and as an

567

outcome measure in research involving persons with severe, multiple, or life-limiting conditions.

568

Both the A-IQOLS and QOLS appear to be useful in clinical research and potentially useful in

569

clinical care.

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Funding source: National Heart, Lung and Blood Institute (R01HL119845, PI: SWilson)

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Acknowledgments: The authors gratefully acknowledge the contributions of Nicholas Vesom

574

to the conduct of the test-retest study, as well as the contributions of the study participants and

575

staff of the Palo Alto Medical Foundation Mountain View’s Allergy and Pulmonology services

576

where patient assessment occurred. We also acknowledge the expert review and helpful sugges-

577

tions on this manuscript by Lauress L. Wise, PhD. Ultimately, responsibility for the research

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and for this report rests solely with the authors.

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Johns Hopkins University. Long-acting Beta Agonist Step Down Study (LASST). In: Clin-

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icalTrials.gov [Internet]. Bethesda (MD): National Library of Medicine (US). 2000- [cited

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2016 Apr 22]. Available from: http://clinicaltrials.gov/show/ NCT01437995 NLM Identifi-

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er: NCT01437995.

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Johns Hopkins University. Effect of Positive Airway Pressure on Reducing Airway Reactivity in Patients With Asthma (CPAP). In: ClinicalTrials.gov [Internet]. Bethesda (MD):

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National Library of Medicine (US). 2000- [cited 2016 Apr 22]. Available from:

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http://clinicaltrials.gov/show/ NCT01629823 NLM Identifier: NCT01629823.

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41. Sarikonda K, Sheshadri A, Koch T, Kozlowski J, Wilson B, Schechtman K, et al. Predictors Of Bronchial Thermoplasty Response In Patients With Severe Refractory Asthma. Am J

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Respir Crit Care Med 2014;A2429–A2429.

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42.

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Washington University School of Medicine. A Prospective Observational Study of Biopredictors of Bronchial Thermoplasty Response in Patients With Severe Refractory Asthma

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(BTR Study) (BTR). In: ClinicalTrials.gov [Internet]. Bethesda (MD): National Library of

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Medicine (US). 2000- [cited 2016 Apr 22]. Available from:

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https://clinicaltrials.gov/show/NCT01185275 NLM Identifier: NCT01185275.

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Table 1. Baseline characteristics of test-retest study participants, n=147.

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Characteristic Age, years 18-44 years old 45-59 years old 60-70 years old Sex

95 (64.6) 52 (35.4)

White/Caucasian Black/African American Asian American Indian/Alaska Native

111 (75.5) 22 (15.0) 12 (8.2) 2 (1.4)

Hispanic Non-Hispanic

17 (11.6) 130 (88.4)

≤ High school Some college College or above

7 (4.8) 43 (29.3) 97 (66.0)

Employed Unemployed Homemaker/Student/Retired Disabled, unable to work

109 (74.1) 9 (6.1) 23 (15.6) 6 (4.1)

<$75,000 ≥$75,000

35 (23.8) 112 (76.2)

<5 years of age 5 years of age - puberty† Puberty - 17.9 years of age

24 (16.3) 33 (22.4) 16 (10.9)

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Female Male

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Race

Annual family income

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Employment status

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Education

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Ethnicity

N (%) or Mean ± SD (Range) 49.1 ± 12.3 (21-70) 51 (34.7) 61 (41.5) 35 (23.8)

Asthma onset age (self-report)

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Characteristic ≥18 years of age ‡

Yes No

140 (95.2) 7 (4.8)

Current smoker Ex-smoker Never smoker

5 (3.4) 30 (20.4) 112 (76.2)

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Aeroallergen(s) reported among asthma triggers

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Smoker

BMI, kg/m2

2

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Normal weight (18.5 to 24.9 kg/m ) Overweight (25 to 29.9 kg/m2) Obese (≥30 kg/m2) Berlin Questionnaire (Obstructive Sleep Apnea risk)

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Low Risk High Risk

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No. asthma exacerbations requiring OCS§ (12 mos. preceding enrollment)

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31.5 ± 7.9 (19.2-63.2) 26 (17.7) 52 (35.4) 69 (46.9) 74 (50.3) 73 (49.7)

0 1 >1

0.4 ± 0.8 (0-5) 106 (72.1) 29 (19.7) 12 (8.2)

0 1 >1

1.58 ± 1.95 47 (32.0) 48 (32.7) 52(35.4)

No. asthma-related outpatient medical visitsǁ (12 mos. preceding enrollment)

Treatment step*

N (%) or Mean ± SD (Range) 74 (50.3)

Step 2 Step 3 Step 4 Step 5 Step 6

15 (10.2) 23 (15.6) 61 (41.5) 47 (32.0) 1 (0.7)

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Treatment step definitions available http://www.ncbi.nlm.nih.gov/books/NBK7222/. Step 2 = Low-dose inhaled corticosteroid (ICS) or alternative (Cromolyn, LTRA, Nedocromil, or Theophylline); Step 3 = Low-dose (ICS) + long-acting inhaled beta2-agonist (LABA), or Medium-dose ICS, or alternative (Low-dose (ICS) + either LTRA, Theophylline, or Zileuton); Step 4 = Medium-dose (ICS) + LABA or alternative (Medium-dose (ICS) + either LTRA, Theophylline, or Zileuton); Step 5 = High-dose (ICS) + LABA ± Omalizumab for patients who have allergies; Step 6 = High-dose (ICS) + LABA + oral corticosteroid ± Omalizumab for patients who have allergies. † Puberty was defined as starting at age 12 for girls, age 14 for boys. ‡ Aeroallergens included pollen, house dust mites, cats, dogs, cockroaches, and molds. § OCS (oral corticosteroid) prescription of at least three days for an asthma-related diagnosis code: asthma (ICD9 493.x) cough (ICD9 786.2) bronchitis (ICD9 490), upper respiratory infection (ICD( 465.9), bronchospasm (ICD9 519.11); or wheezing (ICD9 786.07), given that all patients had underlying asthma. Courses of OCS separated by >7 days were treated as separate exacerbations. See Asthma outcomes: Exacerbations. Fuhlbrigge, A., et al. J Allergy Clin Immunol, 2012:129(3);S34-S48. ǁ Outpatient office and Urgent Care Clinic visits with asthma diagnosis code (ICD9 493.x) within 12 mos. preceding enrollment. Does not include hospital emergency department visits.

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Table 2. Comparison of clinical characteristics of participants at baseline (test) and follow-up (retest), n=147. Baseline Follow-up N (%) or N (%) or Mean ± SD Mean ± SD Clinical Characteristic (Range) (Range) p 87.8 ± 18.5 87.1 ± 18.2 FEV1 Percent Predicted, pre(37.0-151.0) (38.0-131.0) bronchodilator‡ 0.27 19.0 ± 3.9 19.8 ± 3.7 ACT (10.0-25.0) (9.0-25.0) 0.003 80 (54.4) 92 (62.6) Well-controlled (20-25) <0.0001 33 (22.4) 33 (22.4) Poorly controlled (16-19) 34 (23.1) 22 (15.0) Very poorly controlled (5-15) 0.8 ± 0.2 0.9 ± 0.1 § ASUI (0.2-1.0) (0.3-1.0) 0.001 13.9 ± 12.1 11.3 ± 11.0 Marks AQLQǁ (0-65) (0-44) <0.0001 5.4 ± 1.1 5.7 ± 1.0 Juniper Mini-AQLQ: Total Score¶ (2.9-6.9) (2.9-7.0) <0.0001 5.2 ± 1.2 5.6 ± 1.1 Mini-AQLQ: Symptom Score** (2.2-7.0) (2.2-7.0) <0.0001 4.1 ± 4.1 3.1 ± 3.5 PHQ-9†† (Depression) (0-20) (0-15) <0.0001 No. asthma-related OCS prescriptions 0.03 ± 0.18 0.04 ± 0.20 (4 wks. preceding enrollment)‡‡ (0-1) (0-1) 0.76 No. asthma-related medical visits§§ (4 0.10 ± 0.29 0.14 ± 0.46 wks. preceding enrollment) (0-1) (0-4) 0.32 1.35 ± 0.45 1.25 ± 0.34 A-IQOLS* (1.00-3.94) (1.00-3.00) 0.002 3.73 ± 0.76 3.63 ± 0.74 QOLS† (1.18-4.94) (1.19-5.00) 0.06

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Abbreviations: A-IQOLS, Asthma Impact on Quality of Life Scale; QOLS, Flanagan Quality of Life Scale; FEV1, forced expiratory volume in one second; ACT, Asthma Control Test; ASUI, Asthma Symptom Utility Index; Marks AQLQ Asthma Quality of Life Questionnaire; Mini-AQLQ, Juniper mini-Asthma Quality of Life Questionnaire, total score and symptom sub-scale; PHQ-9, Patient Health Questionnaire. * Possible range, 1-No negative effect at all to 5-Extremely negative effect. † Possible range, 1-Not at all well satisfied to 5-Very well satisfied. ‡ Sample size, n=146. § Possible range, 0-Worst possible symptoms to 1-Best state/no symptoms. Sample size, n=146. ǁ Possible range, 0-Less impact on functional status to 80-Very severe impact on functional status. ¶ Possible range, 1-Totally limited to 7-Not at all limited ** Possible range, 1-Symptoms all of the time to 7-Symptoms none of the time. †† Possible range, 0-No symptoms to 27-Major depression, severe. ‡‡ OCS (oral corticosteroid) prescription of at least 3 days for an asthma-related diagnosis code (asthma, ICD9 493.x; cough, ICD9 786.2; bronchitis, ICD9 490; upper respiratory infection, ICD( 465.9; bronchospasm, ICD9 519.11; or wheezing, CD9 786.07) within 4 weeks preceding enrollment. Courses of OCS separated by >7 days were treated as separate exacerbations. See Asthma outcomes: Exacerbations. Fuhlbrigge, A., et al. J Allergy Clin Immunol, 2012:129(3);S34-S48. McNemar exact test. §§ Outpatient office and Urgent Care Clinic visits with asthma diagnosis code (ICD9 493.x) within 4 weeks preceding enrollment. Does not include hospital emergency department visits. McNemar exact test.

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Table 3. Relative and population-independent reliabilities of the A-IQOLS and Flanagan QOLS, n=147. Relative reliability Follow-up Mean ±SD

A-IQOLS

1.35 ±0.45

QOLS

3.73 ±0.76

MeanAll (of B and F)

Between subject SDdiff

t

p

r

ICC

Mean diff. (Bias)

1.25 ±0.34

0.58

0.56

-0.10

1.30

0.37

-3.23

<0.002

3.63 ±0.74

0.67

0.67

-0.10

3.68

0.61

-1.89

0.06

95% LOA (95% CI) LB -0.83 (-0.94, -0.73) -1.29 (-1.46, -1.12)

95% LOA (95% CI) UB

SEM

SEM %

CR

WSV

0.63 (0.53, 0.74)

0.07

±0.27

20.34

±0.73

1.10 (0.93, 1.27)

0.19

±0.43

11.71

±1.19

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Baseline Mean ±SD

Population- independent reliability

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Definitions: SD= Standard Deviation; r= Pearson’s correlation coefficient; ICC= Intraclass Correlation Coefficient; t= t-value from paired t-test; p= p-value for paired t-test; LOA= Limits of Agreement; CI= Confidence Interval; L/UB= Lower/Upper Bound; WSV = within subject variance from two-way repeated-measure analysis of variance; SEM (Standard Error of Measurement)= √WSV; SEM%= SEM/MeanAll X 100; CR1= Coefficient of Repeatability= 2.77 x SEM. 1 Vaz, Sharmila, Torbjörn Falkmer, Anne Elizabeth Passmore, Richard Parsons, and Pantelis Andreou. 2013. “The Case for Using the Repeatability Coefficient When Calculating Test-Retest Reliability.” PloS One 8 (9): e73990. doi:10.1371/journal.pone.0073990.

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Table 4. Correlations and shared variances between A-IQOLS, QOLS, and other clinical characteristics, at baseline and at follow-up, n=147. A-IQOLS (n=147) QOLS (n=147) Follow-up Baseline Follow-up Baseline p -

R2 -

r* -

p -

R2 -

r* -0.39

p <.0001

R2 0.15

r* -0.40

p <.0001

0.03 -0.50 -0.51 0.74 -0.63 -0.58 0.45 0.10$ 0.15$

0.74 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.24 0.06

<0.01 0.25 0.26 0.55 0.39 0.33 0.20 0.01 0.02

-0.004 -0.53 -0.52 0.72 -0.65 -0.60 0.53 0.21$ 0.14$

0.96 <.0001 <.0001 <.0001 <.0001 <.0001 <.0001 0.01 0.10

<0.01 0.28 0.27 0.52 0.42 0.36 0.28 0.04 0.02

0.08 0.24 0.32 -0.48 0.41 0.38 -0.52 0.08$ -0.04$

0.35 0.004 <.0001 <.0001 <.0001 <.0001 <.0001 0.36 0.67

0.0060 0.06 0.10 0.23 0.16 0.15 0.27 0.006 0.0001

0.14 0.26 0.26 -0.41 0.32 0.29 -0.54 -0.19$ -0.05$

0.09 0.02 0.002 0.07 0.001 0.07 <0.001 0.17 <.0001 0.10 0.0003 0.09 <.0001 0.30 0.02 0.04 0.53 <0.01

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r* -

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Clinical Characteristic A-IQOLS FEV1 Percent Predicted, prebronchodilator† ACT ASUI† Marks AQLQ Juniper Mini-AQLQ: Total Score Symptom Score PHQ-9 No. of exacerbations requiring OCS ‡ No. of asthma-related medical visitsǁ

R2 0.16

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Abbreviations: A-IQOLS, Asthma Impact on Quality of Life Scale; QOLS, Flanagan Quality of Life Scale; FEV1, forced expiratory volume in one second; ACT, Asthma Control Test; ASUI, Asthma Symptom Utility Index; Marks AQLQ, Asthma Quality of Life Questionnaire; Mini-AQLQ, Juniper mini-Asthma Quality of Life Questionnaire, total score and symptom sub-scale; PHQ-9, Patient Health Questionnaire. * r=Pearson product-moment correlation † Sample size, n=146. ‡ OCS (oral corticosteroid) prescription of at least 3 days for an asthma-related diagnosis code (asthma, ICD9 493.x; cough, ICD9 786.2; bronchitis, ICD9 490; upper respiratory infection, ICD( 465.9; bronchospasm, ICD9 519.11; or wheezing, CD9 786.07) within 4 weeks prior to enrollment. Courses of OCS separated by >7 days were treated as separate exacerbations. See Asthma outcomes: Exacerbations. Fuhlbrigge, A., et al. J Allergy Clin Immunol, 2012:129(3);S34-S48. $ Spearman Rank-Order Correlation. ǁ Outpatient office visit or Urgent Care Clinic visit with asthma-related diagnosis code (ICD9 493.x) within 4 weeks preceding baseline and follow-up assessments. Does not include hospital emergency department visits.

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Table 5. Correlations between baseline-to-follow-up changes in asthma status measures and changes in A-IQOLS and QOLS scores, with estimates of shared variance, n=147. Change in Association with change in Association with change in Characteristic A-IQOLS Score QOLS Score * 2 * Clinical Characteristics Mean ± SD r p R r p R2 FEV1 Percent Predicted, pre-0.74 ± 8.06 0.10 0.22 0.01 -0.08 0.32 0.01 bronchodilator † 0.79 ± 3.16 ACT -0.40 <0.0001 0.16 -0.07 0.40 0.005 ‡ 0.04 ± 0.15 ASUI -0.33 <0.0001 0.11 -0.02 0.77 0.001 -2.59 ± 7.02 Marks AQLQ 0.52 <0.0001 0.27 -0.005 0.96 <0.01 0.28 ± 0.78 Mini-AQLQ: Total Score -0.55 <0.0001 0.30 0.07 0.38 0.01 0.36 ± 0.93 Mini-AQLQ: Symptom Score -0.45 <0.0001 0.20 0.06 0.49 0.003 -1.03 ± 2.96 PHQ-9 0.20 0.01 0.04 -0.16 0.053 0.03 § ǁ ǁ No. exacerbations requiring OCS 0.01 ± 0.27 0.10 0.24 0.01 0.01 0.89 <0.01 ¶ ǁ ǁ No. asthma-related medical visits 0.04 ± 0.49 0.11 0.20 0.01 -0.07 0.41 <0.01 -0.10 ± 0.37 A-IQOLS -0.15 0.07 0.02 -0.10 ± 0.61 QOLS

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Abbreviations: A-IQOLS, Asthma Impact on Quality of Life Scale; QOLS, Flanagan Quality of Life Scale; FEV1, forced expiratory volume in one second; ACT, Asthma Control Test; ASUI, Asthma Symptom Utility Index; Marks AQLQ, Asthma Quality of Life Questionnaire; Mini-AQLQ, Juniper mini-Asthma Quality of Life Questionnaire, total score and symptom sub-scale; PHQ-9, Patient Health Questionnaire. * r=Pearson product-moment correlation † Sample size, n=146. ‡ Sample size, n=146. § OCS (oral corticosteroid) prescription of at least 3 days for an asthma-related diagnosis code (asthma, ICD9 493.x; cough, ICD9 786.2; bronchitis, ICD9 490; upper respiratory infection, ICD( 465.9; bronchospasm, ICD9 519.11; or wheezing, CD9 786.07) within 4 weeks preceding enrollment. Courses of OCS separated by >7 days were treated as separate exacerbations. See Asthma outcomes: Exacerbations. Fuhlbrigge, A., et al. J Allergy Clin Immunol, 2012:129(3);S34-S48. ǁ Spearman Rank-Order Correlation. ¶ Outpatient office visit or Urgent Care Clinic visit with asthma diagnosis code (ICD9 493.x) within 4 weeks preceding enrollment. Does not include hospital emergency department visits.

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Figure 1. Flanagan’s Dimensions of Quality of Life.1

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1. Material comforts - things like a desirable home, good food, possessions, conveniences, an increasing income, and security for the future. 2. Health and personal safely – being physically fit and vigorous, free from anxiety and distress, and avoiding bodily harm. 3. Relationships with your parents, brothers, sisters, and other relatives communicating, visiting, and doing things with, understanding, and helping and being helped by your relatives. 4. Having and raising children - being a parent and helping, teaching, and caring for your children. 5. Close relationship with a husband, wife, or partner 6. Close friends - sharing activities, interests, and views; being accepted, visiting, giving and receiving help, love, trust, support, guidance. 7. Helping and encouraging others - adults or children other than relatives or close friends. These can be your own efforts or efforts as a member of a church, club, or volunteer group. 8. Participation in activities relating to local and national government and public affairs. 9. Learning, attending school, improving your understanding, or gaining additional knowledge. 10. Understanding yourself - knowing your assets and limitations, knowing what life is all about and making decisions on major life activities. For some people, this includes religious or spiritual experiences; for others, it is developing an attitude toward life or a philosophy. 11. Independence2 - doing for yourself: being able to take care of and make decisions about your daily needs, personal care, where you live, and your financial affairs. 12. Work in a job or at home that is interesting, rewarding, and worthwhile. 13. Expressing yourself in a creative manner in music, art, writing, photography, practical activities, or in leisure time activities. 14. Socializing - meeting other people, doing things with them, and hosting or attending parties or other social gatherings. 15. Reading, listening to music, or observing sporting events or entertainment. 16. Participation in active recreation such as playing sports, traveling and sightseeing, playing games or cards, singing, dancing, playing an instrument, acting, and other such activities.

1 2

Flanagan JC. A research approach to improving our quality of life. Am Psychol 1978;33:138. Added to the original Flanagan dimensions by Burckhardt CS, et al. Res Nurs Health. 1989;21:347-354.

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ONLINE SUPPLEMENT

Historical Background, Instrument Development and Pilot Testing (supplement)

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Pilot test versions. Detailed descriptions of the 15 Flanagan dimensions of QoL were already available,1 as were shorter summaries.2 To create the A-IQOLS, very slight

modifications were made (e.g., to ensure that the dimension Close relationship with a husband,

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wife, or partner was inclusive of spouses and partners without regard to gender). A 16th

dimension, Independence, was added as suggested by Burckhardt et al., based on their findings

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regarding the importance of that dimension in persons with chronic health conditions.3 The root question was stated as follows: “Over the past four weeks, how much did your asthma negatively affect your life in each of the following areas?” The respondent was asked to “Consider the effects of the asthma itself, the asthma medications you use, and anything you did

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to avoid, treat, or get medical care for asthma symptoms.” A 5-point, unidirectional Likert-type scale was selected, ranging from 1 = No negative effect at all, 2 = Slightly negative effect, 3 = Moderately negative effect, 4 = Very negative effect, to 5 = Extremely negative effect.

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Flanagan’s quality of life Importance questionnaire (above)1 and his QOLS (above) also were used in the present study in asthma patients, with the addition of the 16th dimension and the

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small wording changes noted above. The root question in the QOLS is: “At this time, how well are your needs and wants being satisfied in each of the following areas?” In his earliest version Flanagan used the phrase “how well are your needs and wants being met in each of the following areas?” Later, he substituted “satisfied” for “met,” which is the wording we chose. Neither version asked how satisfied the individual was with their life, but how well their needs and wants were being satisfied, using five scale points: 1 = Not at all Well Satisfied, 2 = Only Slightly Well Satisfied, 3 = Moderately Well Satisfied, 4 = Well Satisfied, 5 = Very Well Satisfied. The

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QOLS was administered to thousands of participants in research on Vietnam veterans and on national samples of adults.1,2,4 Burckhardt and colleagues also used the Flanagan dimensions in their clinical research.5–7

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However, in addition to adding a 16th dimension, Independence, they made other changes. Their root question asked for a rating of “…how satisfied you are at this time.” The verbal anchors used a “Delighted-Terrible” scale with the following 7 anchors: “1 = terrible”, “2 = unhappy”, “3

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= mostly dissatisfied”, “4 = mixed”, ‘5 = mostly satisfied”, “6 = pleased”, “and “7 = delighted.” These anchors are not responsive to the question posed to the respondent, not all grammatically

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consistent or psychologically equidistant, and not clearly related to a single underlying construct. The scoring algorithm also was modified. Despite these major changes, they referred to their measure as the “Flanagan QOLS,” which has introduced confusion in the literature. We chose to use the final root question, numeric response scale, verbal response anchors, and scoring of

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original Flanagan’s QOLS but included Burckhardt’s additional dimension in order to potentially include it in the A-IQOLS score if its importance was endorsed by patients.

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Pilot testing. Shortly after recruitment began for the DASH for Asthma trial,8 the AIQOLS, Flanagan’s QOLS, and QoL Importance scale, were added to that study’s data collection

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protocol and administered at baseline and follow-up to 88 of the 90 DASH enrollees (Kaiser Health Care System asthma patients in the San Francisco Bay Area). The pilot test sample averaged 51.5 years of age; was 50.6% White, 11.5% African American, 31.0% Asian, and 6.9% some other race; 14.8% were Hispanic; 8.0% had no more than a high school diploma; 45.5% a high school diploma but no baccalaureate degree, and the remaining 46.5% a college degree.

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The DASH clinical coordinators requested clarification of what respondents should do if they felt that some dimension did not apply to them (e.g., they had no living relatives, no spouse/partner, no children, and/or did not engage in an activity). The Administration

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Instructions (above) were modified to cover such circumstances and encourage ratings on all 16 dimensions on both the A-IQOLS and QOLS. The clinical coordinators also reported that none of the patients, including those who had a high school education or less (n = 8) and those who

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were African American or Hispanic (n = 22), had questions about the rating scale or meaning of the quality of life dimensions.

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The A-IQOLS and QOLS each required approximately 3-4 minutes to complete, and the Importance scale approximately 2-3 minutes. Within individuals, responses varied across the dimensions. On average, the reported impact of asthma was somewhat more negative on certain dimensions (Health and Safety, Active Recreation, and dimensions related to relationships with

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other adults) than on others, which was expected and suggests that the dimensions were being discriminated from each other in an appropriate manner. No significant changes in the AIQOLS, QOLS, or Importance questionnaire appeared necessary based on the results of the

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Table S1: Percentages of AQOLIS-TR participants rating each of the 16 dimensions as personally Important or Very Important, n=147. Male (n=52) 21-30

30-39

40-49

50-59

n=5

n=11

n=7

n=17

60-70

21-30

30-39

40-49

50-59

60-70

n=12

n=6

n=12

n=22

n=32

n=23

n=147

83

83

83

82

88

74

83

100 75

83 50

100 83

95 86

91 75

83 83

94 79

71

92

50

83

68

75

91

73

88 76

92 83

83 83

100 92

86 95

72 84

74 83

84 84

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Component

Overall Sample

Female (n=95)

Material comforts

80

91

86

82

2. 3.

Health and personal safety Relationships with relatives

100 80

100 73

100 71

100 88

4.

Having and raising children

0

45

86

5. 6.

Close relationship with husband, wife, or partner Close friends

80 80

100 91

86 57

7.

Helping and encouraging others

60

91

57

47

75

100

92

91

81

87

80

18

14

29

17

33

17

27

19

35

23

73 64

43 57

53 76

83 100

83 100

75 100

73 100

44 84

57 91

63 88

100

86

100

100

100

100

100

100

100

99

100 40

100 82

86 29

94 59

83 92

100 67

100 58

95 73

88 72

74 78

90 69

60

64

43

29

67

83

58

77

56

83

63

60 80

82 64

43 57

71 76

83 75

50 83

58 58

91 59

75 63

100 83

78 69

100 100

11. Independence

80

12. Work that is interesting, rewarding, and worthwhile 13. Expressing yourself in a creative manner 14. Socializing

0

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Participating in activities related to local/national government and public affairs 9. Learning, attending school, improving understanding 10. Understanding yourself

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8.

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15. Reading, listening to music, or observing events/entertainment 16. Participation in active recreation

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Table S2. Baseline A-IQOLS and QOLS scores by baseline characteristics of AQOLIS-TR participants, n=147. A-IQOLS QOLS Mean ± SD Mean ± SD p P (Range) (Range) Characteristic Overall 1.35 ± 0.45 3.73 ± 0.76 (1.00-3.94) (1.19-4.94) Age, years 1.37 ± 0.41 3.73 ± 0.77 18-44 years old 0.93 0.91 (1.00-2.75) (1.44-4.94) 1.34 ± 0.48 3.75 ± 0.76 45-59 years old (1.00-3.94) (2.00-4.94) 1.36 ± 0.48 3.68 ± 0.77 60-70 years old (1.00-2.81) (1.19-4.88) Sex 1.39 ± 0.50 3.77 ± 0.76 Female 0.18 0.33 (1.00-3.94) (1.19-4.94) 1.29 ± 0.33 3.64 ± 0.76 Male (1.00-2.31) (2.13-4.94) Race 1.35 ± 0.44 3.67 ± 0.75 White/Caucasian 0.91 0.52 (1.00-3.94) (1.19-4.94) 1.39 ± 0.54 3.91 ± 0.88 Black/African American (1.00-2.81) (2.31-4.94) 1.31 ± 0.50 3.83 ± 0.68 Asian (1.00-2.75) (2.81-4.81) American Indian/Alaska 1.19 ± 0.09 3.97 ± 0.57 Native (1.13-1.25) (3.56-4.38) Ethnicity 1.44 ± 0.70 3.34 ± 0.93 Hispanic 0.40 0.03 (1.00-3.94) (1.19-4.94) 1.34 ± 0.41 3.78 ± 0.73 Non-Hispanic (1.00-2.81) (1.44-4.94) Education 1.39 ± 0.65 3.63 ± 0.92 ≤ High school 0.97 0.55 (1.00-2.81) (2.06-4.94) 1.35 ± 0.31 3.63 ± 0.81 Some college (1.00-2.19) (1.44-4.94) 1.35 ± 0.49 3.78 ± 0.73 College or above (1.00-3.94) (1.19-4.94) Employment status 1.37 ± 0.47 3.67 ± 0.78 Employed 0.72 0.47 (1.00-3.94) (1.19-4.94) 1.30 ± 0.30 4.01 ± 0.53 Unemployed (1.00-1.94) (3.31-4.81)

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Disabled, unable to work Annual family income <$75,000 ≥$75,000

1.53 ± 0.50 (1.00-2.81) 1.30 ± 0.42 (1.00-3.94)

0.008

Asthma onset age (self-report)

5 years of age to puberty† Puberty to 17.9 years of age ≥18 years of age

1.35 ± 0.32 (1.00-2.19) 1.24 ± 0.40 (1.00-2.75) 1.36 ± 0.28 (1.00-1.81) 1.40 ± 0.53 (1.00-3.94)

Aeroallergen(s) as asthma triggers (self-report)‡

1.36 ± 0.46 (1.00-3.94) 1.13 ± 0.17 No (1.00-1.50)

TE D

Yes

Smoker

1.29 ± 0.30 (1.00-1.69) 1.34 ± 0.57 (1.00-3.94) 1.36 ± 0.43 (1.00-2.81)

0.19

0.94

EP

Current smoker

0.44

Ex-smoker

AC C

Never smoker

3.46 ± 0.79 (1.44-4.94) 3.81 ± 0.73 (1.19-4.94)

3.73 ± 0.68 (2.38-4.94) 3.80 ± 0.77 (1.44-4.94) 3.98 ± 0.71 (2.88-4.94) 3.64 ± 0.79 (1.19-4.94)

0.01

0.36

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<5 years of age

P

RI PT

Homemaker/Student/Retired

p

QOLS Mean ± SD (Range) 3.86 ± 0.71 (2.38-4.94) 3.79 ± 0.94 (2.44-4.88)

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Characteristic

A-IQOLS Mean ± SD (Range) 1.27 ± 0.39 (1.00-2.81) 1.46 ± 0.66 (1.00-2.75)

3.72 ± 0.77 (1.19-4.94) 3.79 ± 0.61 (2.88-4.81)

4.04 ± 0.52 (3.62-4.94) 3.48 ± 0.89 (1.19-4.94) 3.78 ± 0.72 (1.44-4.94)

0.81

0.10

BMI, kg/m2

Normal (18.5 to 24.9 kg/m2) Overweight (25 to29.9 kg/m2) Obese (≥30 kg/m2)

1.32 ± 0.47 (1.00-2.75) 1.26 ± 0.35 (1.00-2.81) 1.43 ± 0.50 (1.00-3.94)

0.11

3.81 ± 0.77 (2.44-4.94) 3.89 ± 0.55 (2.88-4.94) 3.57 ± 0.86 (1.19-4.94)

0.06

Berlin Questionnaire (Obstructive Sleep Apnea risk) Low Risk

1.26 ± 0.36 (1.00-2.75)

0.01

3.92 ± 0.66 (2.44-4.94)

0.002

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Characteristic High Risk

A-IQOLS Mean ± SD (Range) 1.45 ± 0.52 (1.00-3.94)

QOLS Mean ± SD (Range) 3.53 ± 0.81 (1.19-4.94)

p

Step 4 Step 5 Step 6 ACT Well-controlled (20-25) Poorly controlled (16-19)

No. asthma exacerbations requiring OCS§ (12 mos. preceding enrollment)

1.15 ± 0.20 (1.00-2.06) 1.45 ± 0.57 (1.00-3.94) 1.73 ± 0.50 (1.00-2.81)

TE D

Very poorly controlled (5-15)

0

1.31 ± 0.39 (1.00-2.81) 1.34 ± 0.39 (1.00-2.75) 1.78 ± 0.82 (1.06-3.94)

<0.0001

0.003

EP

1

0.07

>1

AC C

Asthma-related medical visitsǁ (12 mos. preceding enrollment)

*

0 1 >1

3.52 ± 0.79 (2.38-4.94) 3.79 ± 0.65 (2.38-4.81) 3.66 ± 0.77 (1.19-4.94) 3.88 ± 0.70 (2.00-4.94) 3.62 ± 1.22 (1.44-4.81)

1.35 ± 0.43 (1.00-2.75) 1.27 ± 0.37 (1.00-2.81) 1.43 ± 0.53 (1.00-3.94)

0.47

SC

Step 3

1.25 ± 0.24 (1.00-1.81) 1.24 ± 0.32 (1.00-2.31) 1.34 ± 0.41 (1.00-2.81) 1.39 ± 0.56 (1.00-3.94) 1.78 ± 0.61 (1.25-2.75)

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Step 2

RI PT

Asthma Treatment Step*

P

0.22

3.86 ± 0.72 (1.19-4.94) 3.72 ± 0.82 (1.44-4.94) 3.43 ± 0.74 (2.06-4.88)

3.77 ± 0.74 (1.19-4.94) 3.68 ± 0.66 (2.31-4.88) 3.50 ± 1.10 (1.44-4.81)

3.69 ± 0.77 (1.19-4.94) 3.84 ± 0.68 (2.38-4.94) 3.65 ± 0.82 (1.44-4.94)

0.02

0.48

0.42

Treatment step information available http://www.ncbi.nlm.nih.gov/books/NBK7222/ Step 2 = Low-dose inhaled corticosteroid (ICS) or alternative (Cromolyn, LTRA, Nedocromil, or Theophylline); Step 3 = Low-dose ICS + long-acting inhaled beta2-agonist (LABA) or Medium-dose ICS or alternative (Low-dose ICS + either LTRA, Theophylline, or Zileuton); Step 4 = Medium-dose ICS + LABA, or alternative (Medium-dose ICS + either LTRA, Theophylline, or Zileuton); Step 5 = High-dose

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EP

TE D

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ICS + LABA ± Omalizumab for patients with allergies; Step 6 = High-dose ICS + LABA + oral corticosteroid ± Omalizumab for patients with allergies. † Puberty was defined as starting at age 12 for girls and age 14 for boys. ‡ Aeroallergens included pollen, house dust mites, cats, dogs, cockroaches, and molds. § OCS (oral corticosteroid) prescription of at least three days for an asthma-related diagnosis code: asthma (ICD9 493.x), cough (ICD9 786.2), bronchitis (ICD9 490), upper respiratory infection (ICD,( 465.9), bronchospasm (ICD9 519.11), or wheezing (ICD9 786.07), given that all patients had underlying asthma. Courses of OCS separated by >7 days were treated as separate exacerbations. See Fuhlbrigge, A., et al. Asthma outcomes: Exacerbations. J Allergy Clin Immunol, 2012:129(3); S34-S48. ǁ Outpatient office and Urgent Care Clinic visits with asthma diagnosis code (ICD9 493.x) within 12 mos. preceding enrollment. Does not include hospital emergency department visits.

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Table S3. Relative and population-independent reliability and related characteristics of other measures, n=147. Relative reliability indices

r*

FEV1 Percent Predicted, prebronchodilator*

87.8±18.5

87.0±18.2

ACT

19.0±3.9

ASUI*

Absolute reliability indices

MeanAll (of B and F)

Between subject SDDIFF

t

0.90

0.90

-0.7

87.4

8.1

-1.11

19.8±3.7

0.65

0.65

0.79

19.4

3.2

0.82±0.17

0.86±0.13

0.49

0.48

0.04

0.84

0.15

3.28

0.001

Marks AQLQ

13.9±12.1

11.3±11.0

0.82

0.81

-2.6

12.6

7.0

-4.47

<0.0001

Mini-AQLQ: Total Score

5.4±1.1

5.7±1.0

0.73

0.73

0.28

5.5

0.78

4.32

<0.0001

Mini-AQLQ: Symptom Score

5.2±1.2

5.6±1.1

0.69

0.69

0.36

5.4

0.93

4.68

<0.0001

PHQ-9

4.1±4.1

3.1±3.5

0.71

0.70

3.6

2.9

-4.23

<0.0001

p

0.27

SC 3.03

M AN U

TE D

AC C

-1.0

95% LOA (LB) -16.53 (-18.80, -14.27) -5.41 (-6.29, -4.52) -0.26 (-0.30, -0.21) -16.36 (-18.32, -14.39) -1.25 (-1.47, -1.03) -1.46 (-1.72, -1.2) -6.84 (-7.67, -6.01)

RI PT

ICC+

Mean diff (Bias)

EP

Baseline Mean ±SD

Followup Mean ±SD

0.003

95% LOA (UB) 15.05 (12.79, 17.32) 6.98 (6.10, 7.87) 0.34 (0.30, 0.38) 11.17 (9.21, 13.14) 1.81 (1.59, 2.03) 2.17 (1.92, 2.43) 4.78 (3.95, 5.61)

Within subject variance

SEM

SEM %

CR

32.46

5.70

6.52

15.79

4.99

2.23

11.52

6.19

0.01

0.11

12.87

0.30

24.66

4.97

39.30

13.77

0.30

0.55

9.96

1.53

0.43

0.66

12.14

1.82

4.39

2.10

58.69

5.81

Definitions: SD= Standard Deviation; r= Pearson’s correlation coefficient; ICC= Intraclass Correlation Coefficient; t= t-value from paired t-test; p= p-value for paired t-test; LOA= Limits of Agreement; CI= Confidence Interval; L/UB= Lower/Upper Bound; SEM (Standard Error of Measurement)= √WMS, where WMS= mean square error term from ANOVA; SEM%= SEM/MnAll X 100; CR= Coefficient of Repeatability= 2.77 x SEM. Abbreviations: FEV1, forced expiratory volume in one second; ACT, Asthma Control Test; ASUI, Asthma Symptom Utility Index; Marks AQLQ, Asthma Quality of Life Questionnaire; Mini-AQLQ, Juniper Mini-Asthma Quality of Life Questionnaire; PHQ-9, Patient Health Questionnaire * Sample size, n=146.

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Table S4. Internal consistency reliability (Cronbach’s alpha) of self-report measures, n=147. Baseline Follow-up α α Clinical Characteristic 0.93 0.91 A-IQOLS 0.93 0.93 QOLS 0.81 0.80 ACT 0.94 0.94 Marks AQLQ 0.93 0.93 Juniper Mini-AQLQ: Total Score 0.87 0.86 Mini-AQLQ: Symptom Score 0.83 0.87 PHQ-9

AC C

EP

TE D

M AN U

Abbreviations: A-IQOLS, Asthma Impact on Quality of Life Scale; QOLS, Flanagan Quality of Life Scale; ACT, Asthma Control Test; Marks AQLQ, Asthma Quality of Life Questionnaire; Mini-AQLQ, Juniper mini-Asthma Quality of Life Questionnaire, total score and symptom sub-scale; PHQ-9, Patient Health Questionnaire.

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1.

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2.

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8. Ma J, Strub P, Lavori PW, Buist AS, Camargo CA, Nadeau KC, et al. DASH for asthma: A pilot study of the DASH diet in not-wellcontrolled adult asthma. Contemp Clin Trials 2013;35:55–67.