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. Author manuscript; available in PMC: 2016 Apr 1.
Published in final edited form as: Qual Life Res. 2014 Oct 12;24(4):999–1009. doi: 10.1007/s11136-014-0818-1

Correlation of Promis Scales and Clinical Measures Among Chronic Obstructive Pulmonary Disease Patients With and Without Exacerbations

Debra E Irwin 1, Charles A Atwood Jr 2, Ron D Hays 3, Karen Spritzer 3, Honghu Liu 4, James F Donohue 5, Nancy Kline Leidy 6, Susan E Yount 7, Darren A DeWalt 8
PMCID: PMC4369165  NIHMSID: NIHMS634904  PMID: 25307510

Abstract

Purpose

The Patient-Reported Outcomes Measurement Information System (PROMIS®) initiative was developed to advance the methodology of PROs applicable to chronic diseases. Chronic obstructive pulmonary disease (COPD) is a progressive chronic disease associated with poor health. This study was designed to examine the correlation of PROMIS health-related quality of life (HRQOL) scales and clinical measures among COPD patients.

Methods

A cross-sectional analysis was conducted comparing patients who were stable (n = 100) with those currently experiencing a COPD exacerbation (n=85). All PROMIS measures for adults available at the time of the study (2008), disease-targeted and other HRQOL instruments, health literacy, percent predicted FEV1, and a 6-minute walk distance were assessed when patients were considered clinically stable.

Results

Stable COPD patients reported significantly (p≤0.05) better health-related quality of life on PROMIS domains than patients experiencing an exacerbation. PROMIS domain scores were significantly (p≤0.01) correlated with each of legacy measures. Six-minute walk scores were most highly correlated with the PROMIS physical function domain scores (r=0.53) followed by the fatigue (r=-0.26), social (r=0.24) and to a lesser extent depression (r=-0.23) and anxiety (r=-0.22) domain scores. Percent predicted FEV1 score was significantly associated with PROMIS physical function scores (r=0.27).

Conclusion

This study provides support for the validity of the PROMIS measures in COPD patients.

Keywords: patient-reported outcomes, health-related quality of life, chronic obstructive pulmonary disease

Introduction

Clinical measures are critically important but may not reflect the day-to-day functioning and well-being of patients with chronic diseases. The Patient Reported Outcomes Measurement Information System (PROMIS®) initiative of the National Institutes of Health (NIH) was developed to advance methodology and the application of patient-reported outcomes (PROs) among patients with chronic diseases for use in research and clinical practice [1].

Chronic Obstructive Pulmonary Disease (COPD) is a progressive disease characterized by airflow limitation that is not fully reversible [4]. It is a prevalent condition that ranks in the top 5 for leading causes of death worldwide and in the top 3 in the U.S. [2,3]. COPD is characterized by episodes of exacerbation that require acute therapies and sometimes hospitalization that are associated with declines in health-related quality of life (HRQOL) [5].

COPD represents a potentially informative target condition for evaluating the validity of the PROMIS instruments for several reasons. Stable COPD is associated with relatively poor health status across many areas covered by PROMIS instruments, including depression, anxiety, fatigue, mobility, activities of daily living (ADLs), and social activities, with significant declines seen in several of these domains during acute exacerbations of the condition [9-13]. One study examined the most important HRQOL domains from the COPD patient perspective and these patients identified several relevant PROMIS domains including fatigue, physical functioning, social roles and social activities to be most relevant for their condition [36]. Another study demonstrated that stable COPD patients with more severe lung function had significantly worse PROMIS physical function and social role domain scores [37]. Across studies, several different HRQOL instruments including generic and COPD-targeted measures have been used to evaluate the impact of COPD on HRQOL. Most COPD specific measures correlate weakly with clinical measures such as FEV1 [32-35, 37]. Therefore, the best instrument and the relative sensitivity of generic versus condition-targeted measures is not generally agreed upon in the literature [5-8]. Since PROMIS instruments are designed to be applicable to a range of chronic illnesses, they allow for comparisons across a variety of chronic health conditions and studies. Hence, the relative validity of PROMIS instruments compared to existing COPD specific instruments is important to document.

This aim of this study was to examine the validity of PROMIS scales in a cross-sectional comparison of stable patients with COPD and patients with a recent exacerbation. Specifically, the validity is evaluated by: 1) exploring the correlations of the PROMIS scales with clinical indices such as Forced Expiratory Volume in 1 Second (FEV1) and 6-minute walk assessments; 2) evaluating the correlations of PROMIS scales with established COPD-targeted instruments and 3) comparing PROMIS scale scores between stable COPD patients and patients experiencing an exacerbation.

Materials and Methods

Participants

Patients were eligible for inclusion in the study if they met the following criteria:

  1. had an established clinical history of COPD in accordance with the Global Initiative for Chronic Obstructive Lung Disease (GOLD) definition. [14,15]

  2. had at least a 10 pack/year history of smoking

  3. were 40 years or older

  4. read and spoke English

  5. had access to and be able to communicate using a touch tone telephone

  6. were able to see and interact with a computer screen, mouse, and keyboard.

Two groups of patients with a clinical diagnosis of COPD were eligible for enrollment: 1) patients with a stable COPD diagnosis, and 2) patients currently experiencing a COPD exacerbation. For those enrolled in the stable group (n=100), the patient needed to be exacerbation-free for a minimum of 2 months prior to enrollment. For those enrolled into the exacerbation group (n=85), treatment for an exacerbation may have started no more than 3 days prior to the day of enrollment for patients recruited in the outpatient setting and no more than 6 days prior to the day of enrollment for patients recruited in the in-patient setting. An exacerbation was defined as a sustained worsening of COPD symptoms from stable state from normal day-to-day variations. Criteria for an exacerbation included that it was acute in onset, necessitated a change in regular medication [4], and required treatment with antibiotics, corticosteroids, hospitalization or a combination of these events [16,17].

Patients were excluded from participation if they had any concurrent medical or psychiatric condition that may have precluded participation in this study or completion of self-administered questionnaires (e.g., moderate to severe dementia and/or severe, uncontrolled schizophrenia), had a history of asthma without co-existent COPD as the primary diagnosis, or were experiencing a current heart failure exacerbation.

Participants were recruited from outpatient clinics and hospitals at 4 research sites (University of North Carolina Health System, NorthShore University Health System, Pittsburgh VA Medical Center, and Durham VA Medical Center). The study was conducted in accordance with the amended Declaration of Helsinki and was approved by the Institutional Review Board (IRB) at each site. At the time of enrollment, eligible participants gave written informed consent and began the baseline assessment.

Study Procedures

For those who were stable at enrollment, the baseline assessment included a questionnaire, literacy assessment, percent predicted FEV1, and a 6-minute walk test. For those in exacerbation at enrollment, the questionnaire was administered at baseline and the clinical measures (FEV1 and a 6-minute walk test) along with the literacy assessment were administered when the patient was deemed stable (approximately 3 months after exacerbation). This was done because it was difficult for the exacerbators to complete these measurements during the time of exacerbation. In addition, all of the analysis involving the clinical measures (FEV1 And 6-minute walk test) utilized data obtained when the patients were deemed stable (see Data Analysis section). The questionnaire collected information on demographics, comorbid conditions, COPD history (symptoms, duration of diagnosis as well as the number of exacerbations, hospitalizations, and emergency room (ER) visits during past year) and health-related quality of life (HRQOL). Participants self-reported their responses on laptop computers in the clinic or in the hospital. Research assistants reviewed the clinical chart to abstract variables including clinical characteristics, body mass index (BMI) and COPD medications.

Study Measures

One goal of the study was to evaluate the associations between the clinical assessments (percent-predicted FEV1 and 6-minute walk) and the HRQOL measures. The measures are summarized in Table 1. Included were the PROMIS adult health domains (www.nihpromis.org) and several targeted “legacy” measures: St. Georges Respiratory Questionnaire (SGRQ), Modified Medical Research Council (MMRC) Dyspnea Scale, Functional Assessment of Chronic Illness Therapy (FACIT) Dyspnea Scale, EXAcerbations of Chronic pulmonary disease Tool – Patient Reported Outcome (EXACT-PRO)), and the Pittsburgh Sleep Quality Index (PSQI) [18-24, 38]. These measures were chosen because they are some of the most commonly used HRQOL measures in COPD clinical trials and observational studies. The MMRC and FACIT Dyspnea scales assess the impact of dyspnea on activities of daily living and physical functioning. The SGRQ is a HRQOL questionnaire designed for patients with chronic airflow limitation and evaluates three domains: 1) symptoms 2) activities that exacerbate symptoms and 3) areas of disease impact such as employment, panic, stigmatization, need for medications, side effects of medications, expectations and being in control of health as well as disturbances of daily life. The EXACT-PRO measures COPD symptoms and manifestations of exacerbations. Pittsburgh Sleep Quality Index evaluates sleep quality and disturbances. Version 1.0 of the PROMIS items were used and these PROMIS items can be found by accessing www.nihpromis.org. The analysis for this manuscript is cross-sectional and included the initial assessment day for the EXACT-PRO. Due to the quantity of data, the longitudinal data collected from the EXACT-PRO diaries and the other PRO measures will be the subject of another manuscript. Literacy was assessed using the Short Test of Functional Health Literacy in Adults (S-TOFHLA) [27].

Table 1. Study Measures.

Assessment Mode of Administration Patients with Exacerbation Stable Patients

Demographic data forma Self-administered X X

Clinical data formb Chart abstraction X X

Literacy assessmentc,g Interviewer-administered X X

PROMIS 1.0 Itemsd Self-administered
Physical function CAT/SF X X
Pain interference CAT/SF X X
Pain behavior CAT/SF X X
Fatigue CAT/SF X X
Anxiety CAT/SF X X
Depression CAT/SF X X
Anger CAT/SF X X
Social Roles CAT/SF X X
Discretionary Social Activities CAT/SF X X
Global Health items X X

Legacy Instruments e Self-administered
SGRQ X X
PSQI X X
MMRC Dyspnea X X
FACIT-Dyspnea X X
Exact-PRO Daily Diary Self-administeredf Xf Xf

Clinical Assessments In-person assessment
FEV1 measurements X c X
6 minute walk X c X
a

gender, birthdate, race, ethnicity, smoking history, comorbid conditions, current COPD symptoms, COPD history (type of COPD, current medications, duration of disease, number of exacerbation and associated hospitalizations and emergency room visits during the past 12 months)

b

body mass index (BMI), COPD history (type of COPD, current medications, lung function values past 2 years)

c

These measures were performed at baseline visit unless patient was experiencing an exacerbation or feeling too ill during their baseline enrollment visit, in which case they were performed when the patient was deemed in a stable state. Forced Expiratory Volume in 1 Second (FEV1) was measured via portable spirometry.

d

CAT=computer administered items; SF=short forms

e

SGRQ=St. George's Respiratory Questionnaire; Modified Medical Research Council (MMRC) Dyspnea Scale; Functional Assessment of Chronic Illness Therapy (FACIT) Dyspnea Scale; PSQI=Pittsburgh Sleep Quality Index; Exact-PRO= EXAcerbations of Chronic pulmonary disease Tool – Patient Reported Outcome

f

administered via computer at baseline visit and then during follow-up via Interactive Voice Response via phone daily

g

Short Test of Functional Health Literacy in Adults (S-TOFHLA)

We anticipated that all of the legacy instruments would be significantly correlated with the PROMIS domain scales. Specifically, the PROMIS physical function and social health (discretionary social activities and social roles) would be the most strongly correlated for the SGRQ, FACIT and MMRC instruments as these had been indicated in another study [37]. Because these PROMIS domains (physical functioning and social health) are scored so that a higher score represents better health, we hypothesized negative correlations with the legacy measures.

A 6-minute walk assessment and percent predicted FEV1 measurements were performed at the baseline visit unless the patient was experiencing an exacerbation or feeling too ill, in which case these measures were performed when the patient was deemed stable. The 6-minute walk test measured the distance in meters that a participant is able to walk in a 6-minute time span [25, 26]. Portable spirometry was used to estimate FEV1 using the American Thoracic Society criteria [4].

Scoring of HRQOL Measures

PROMIS 1.0 measures administered assess physical function, pain interference, pain behavior, fatigue, anxiety, depression, anger, social roles (SR – satisfaction with participation in social roles), discretionary social activities (DSA – satisfaction with participation in discretionary social activities) and global health (Table 1). PROMIS measures can be administered via static short forms (SF) (SF number of items: physical function = 10, pain interference = 6, pain behavior = 7, fatigue = 7, anxiety = 7, depression = 8, anger = 8, social roles = 7, discretionary social activities = 7, and global health = 10) or by computer adaptive testing (CAT). For CAT administration, the next item to be administered is based on the participant's prior responses and items are administered until the reliability of measurement meets a target threshold (e.g., 0.90). The PROMIS CAT parameters (www.assessmentcenter.net) were used to administer the CAT. Any remaining SF items that had not yet been administered were presented after the CAT was completed. Scores from the CAT and SF (all items) were calculated using item response theory (IRT) parameters allowing a CAT score and a SF score for each participant on the same underlying metric. PROMIS scores are scored on a T-metric with 50 representing the mean and 10 the standard deviation in the U. S. general population. For PROMIS domains of anger, anxiety, depression, fatigue, pain behavior and pain interference, higher scores indicate worse health and for domains of physical function, DSA, SR, and global health (physical and mental), higher scores indicate better health.

The SGRQ contains 3 domains (symptoms, activity, and impacts) and a summary score on a 0-100 scale with 100 representing the worst HRQOL [18, 38]. The MMRC scale is scored on a scale of 0 to 4 (0=not troubled with breathlessness except with strenuous exercise; to 4=too breathless to leave the house or breathless when dressing or undressing) [19]. To perform correlation analysis, the MMRC score was linearly transformed to a 0-100 possible range (1=0; 2=25; 3=50; 4=75; 5=100) for some analyses. This was done by subtracting 1 from the original MMRC score and multiplying it by 25. The FACIT-Dyspnea Scale consists of 20 items that assess dyspnea severity (10 items) and related functional limitations (10 items). Lower scores reflect less severity or difficulty completing a task [20]. The PSQI is scored on a 0-21 scale with higher scores representing worse sleep quality [24]. The EXACT-PRO Daily Dairy total score is computed across the 14 items and has a possible range of 0 to 100, with higher values indicating a more severe condition [21-23]. The S-TOFHLA was scored according to published guidelines and literacy was classified as adequate for those individuals scoring range of 23 to 36 and inadequate for those scoring 0-22 [27].

Data Analysis

A cross-sectional analysis was performed using the baseline evaluations unless otherwise specified. Preliminary data were analyzed using descriptive and graphical methods wherever applicable, to facilitate interpretation of the data. Data was summarized using descriptive statistics (e.g., means and standard deviation for continuous and ordinal variables; count and frequency for categorical variables) for demographic variables and all HRQOL and clinical measures. All item responses were examined using measures of central tendency (mean, median), and spread (standard deviation, range), and response category frequencies. Correlations between PROMIS and legacy measures as well as between PROMIS and clinical measures were estimated. Only the correlations between PROMIS administered by CAT and legacy measures are presented as there were no significant differences noted when examining the correlations between PROMIS SF and legacy measures. PROMIS IRT-calibrated person parameters were used for correlations. As noted earlier, 6-minute walk and FEV1 percent predicted scores were collected when all patients were deemed stable. The relationship between HRQL (PROMIS and legacy) scores and clinical measures (6MWT and FEV1) used the HRQOL assessed at the time the patients were deemed stable. In other words, these correlations (PROMIS with clinical measures) were performed at baseline for stable patients. For patients experiencing an exacerbation, the PROMIS and clinical measures were collected when the patient was deemed stable, which may have been up to 3 months after the baseline visit.

A two-sample t-test was used to compare scores on the PROMIS domains between the two COPD groups (stable versus in an exacerbation). Pearson correlation coefficients of the PROMIS measures with clinical measures and the HRQOL legacy measures were computed.

Results

The stable COPD patients did not differ substantially from the COPD patients enrolled during an exacerbation on BMI, smoking history, percent-predicted FEV1, ability to walk greater than 300 meters on 6-minute walk assessment, literacy, gender, race, and presence of comorbid conditions. However, exacerbators were significantly younger and had been diagnosed for shorter periods of time than stable patients. In addition, the exacerbators reported significantly more COPD related hospitalizations, emergency room (ER) visits and exacerbations during the past 12 months. Not surprisingly, the exacerbators reported significantly more COPD symptoms and exacerbation-related medications (antibiotics as well as systemic steroids)(Table 2).

Table 2. Baseline Demographic and Clinical Characteristics of Enrolled Patients.

Characteristic Stable (n=100) Exacerbation (n=85)

mean (sd) range mean (sd) range p-value

BMI 31.10 (8.5) 18-65 32.10 (11.1) 16-79 n.s.
Smoking Pack Year History 46.48 (27.3) 10-156 48.99 (34.5) 10-180 n.s.

% (n) % (n) p-value

Percent Predicted FEV1

>= 80 5(4) 3(2) n.s.
50-79 42(35) 39(27) n.s.
30-49 39(33) 33(23) n.s.
< 30 14(12) 25(17) n.s.

6 Minute Walk

>300 m 55(46) 43(17) n.s.

Literacy

Adequate 93 (91) 88 (59) n.s.

Age Category

40-49 years 2(2) 9(8) <0.01
50-59 years 28(28) 44(37)
60-69 years 37(37) 29(25)
70+ years 33(33) 18(15)

Gender

Female 43(43) 51(43) n.s.

Race

White 75(75) 73(60) n.s.

Comorbidities

Hypertension 60(56) 62(50) n.s.
Angina 13(12) 30(24) <0.01
CAD 21(20) 25(20) n.s.
CHF 18(17) 19(15) n.s.
MI 20(19) 21(17) n.s.
Liver diagnosis 10(9) 8(6) n.s.
Kidney diagnosis 3(3) 3(2) n.s.
Asthma 29(27) 44(35) 0.03
Diabetes 34(32) 31(25) n.s.
Depression 37(35) 44(35) n.s.
Anxiety 33(31) 48(38) 0.05
Sleep Disorder 30(28) 44(36) 0.04
Cancer 24(23) 26(21) n.s.

Length of COPD Diagnosis

<1 yr 4(4) 17(14) 0.03
1-3 yrs 23(23) 24(20)
3-5 yrs 15(15) 17(14)
>5 yrs 57(56) 43(36)

Exacerbations last 12 Months

0 68(67) 7(6) <0.01
1 17(17) 28(24)
2 to 5 13(13) 54(46)
≥6 2(2) 11(9)

COPD Hospitalizations last 12 Months

0 87(84) 15(13) <0.01
1 9(9) 46(39)
2 to 5 4(4) 36(30)
≥6 0(0) 2(2)

COPD ER Visits last 12 Months

0 83(81) 41(35) <0.01
1 9(9) 27(23)
2 to 5 7(7) 29(25)
≥6 1(1) 2(2)

Current COPD Symptoms

SOB worsening 19(19) 80(68) <0.01
Cough worsening 15(15) 61(52) <0.01
Increase sputum/mucous 20(20) 61(51) <0.01
Fever 1(1) 29(25) <0.01
Faster Breathing 11(11) 66(56) <.001
Wheezing 20(20) 78(65) <.001
Other 8(8) 31(26) <0.01

COPD Medications

Antibiotics 1(1) 24(20) <0.01
Beta agonists 96(94) 96(80) n.s.
Inhaled steroids 60(59) 63(52) n.s.
Systemic steroids 3(3) 48(40) <0.01
Anticholinergenics 74(72) 77(64) n.s.

n.s.=not significant; NA=not applicable

Table 3 shows the mean PROMIS scores by COPD exacerbation status at enrollment. For all domains the stable patients reported significantly better PROMIS scores, whether administered via CAT or SF. Similarly, the stable patients reported significantly better HRQOL on all of the legacy instruments. PROMIS short form scores were significantly correlated (P<0.001) with CAT scores for all domains (physical function r=0.89; pain interference r=0.95; pain behavior r=0.97; fatigue r=0.88; anxiety r=0.94; depression r=0.85; anger r=0.98, social roles r=0.97; discretionary social activities r=0.95).

Table 3. Mean PROMIS SF, CAT and Legacy Instrument Scores by COPD Exacerbation Status at Enrollment.

Stable (n=100) Exacerbation (n=85)

PROMIS SF+ mean (sd) mean (sd) p-value

Anger 50 (9) 53 (10) <0.01
Anxiety 53 (10) 60 (8) <0.01
Depression 51 (8) 57 (9) <0.01
Fatigue 55 (9) 63 (8) <0.01
Pain Behavior 53 (11) 57 (10) <0.01
Pain Interference 57 (10) 61 (9) <0.01
Physical Function 37 (6) 34 (7) <0.01
Discretionary Social Activities 46 (8) 42 (8) <0.01
Social Roles 44 (9) 38 (9) <0.01
Global Physical 40 (8) 35 (8) <0.01
Global Mental 45 (9) 43 (9) 0.07

PROMIS CAT+ mean (sd) mean (sd) p-value

Anger 50 (10) 53 (10) 0.02
Anxiety 54 (9) 62 (8) <0.01
Depression 51 (9) 57 (9) <0.01
Fatigue 56 (9) 65 (8) <0.01
Pain Behavior 54 (9) 56 (9) 0.05
Pain Interference 57 (10) 61 (10) <0.01
Physical Function 38 (6) 35 (7) <0.01
Discretionary Social Activities 45 (9) 41 (9) <0.01
Social Roles 43 (9) 39 (9) <0.01

Legacy Instruments* + mean (sd) mean (sd) p-value

FACIT - Dyspnea

Dyspnea 51 (9) 58 (11) <0.01
Functional Limitations 50 (8) 55 (10) 0.0019

SGRQ

Symptoms 53 (22) 76 (15) <0.01
Activities 66 (20) 81 (18) <0.01
Impact 38 (19) 58 (17) <0.01
Total 49 (18) 68 (15) <0.01

PSQI

8 (5) 9 (4) 0.02

EXACT PRO - Day 1

30 (13) 45 (10) <0.01

MMRC - dyspnea

38 (26) 58 (30) <0.01
+

CAT=computer administered items; SF=short forms;

*

SGRQ=St. George's Respiratory Questionnaire; Modified Medical Research Council (MMRC) Dyspnea Scale; FunctionalAssessment of Chronic Illness Therapy (FACIT) Dyspnea Scale; PSQI=Pittsburgh Sleep Quality Index; Exact-PRO= EXAcerbations of Chronic pulmonary disease Tool– Patient Reported Outcome

All of the PROMIS measures (using CAT) were significantly correlated with the legacy instruments except for the PROMIS pain domain measures (Pain Behavior and Pain Interference) and the MMRC (Table 4). These results did not differ for PROMIS SF (data not shown). Six-minute walk scores were most highly correlated with the PROMIS physical function scores, followed by the fatigue, social domains (SR and DSA), and to a lesser extent anxiety and depression (Table 5). (Similar correlations were found for PROMIS SF and CAT.) Percent-predicted FEV1 scores were significantly correlated with PROMIS physical function scores (SF and CAT) as well as with FACIT, MMRC and SGRQ (Activities and Total) scores (Table 5).

Table 4. Product-moment Correlations of PROMIS CAT and Legacy Instruments when Participants are Stable.

PROMIS CAT FACIT -
Dyspnea
FACIT -
Functional
Limitations
SGRQ -
Symptoms
SGRQ -
Activities
SGRQ -
Impacts
SGRQ -
Total
PSQI EXACT
-PRO
Day 1
MMRC-
Dyspnea

Anger (n= 125) 0.31+ 0.37+ 0.35+ 0.36+ 0.51+ 0.49+ 0.41+ 0.48+ 0.27+
Anxiety (n=125) 0.40+ 0.42+ 0.52+ 0.41+ 0.57+ 0.57+ 0.48+ 0.58+ 0.30+
Depression (n=126) 0.40+ 0.41+ 0.46+ 0.41+ 0.55+ 0.55+ 0.40+ 0.55+ 0.33+
Fatigue (n=124) 0.63+ 0.66+ 0.57+ 0.60+ 0.67+ 0.72+ 0.50+ 0.62+ 0.39+
Pain Behavior (n=125) 0.44+ 0.47+ 0.45+ 0.42+ 0.51+ 0.53+ 0.52+ 0.47+ 0.11
Pain Interference (n=125) 0.43+ 0.44+ 0.43+ 0.38+ 0.51+ 0.52+ 0.49+ 0.46+ 0.14
Physical Function (n=124) -0.78+ -0.74+ -0.37+ -0.77+ -0.56+ -0.67+ -0.29+ -0.53+ -0.55+
Discretionary Social Activities (n=126) -0.54+ -0.60+ -0.47+ -0.56+ -0.58+ -0.63+ -0.43+ -0.48+ -0.36+
Social Roles (n=126) -0.57+ -0.62+ -0.53+ -0.56+ -0.60+ -0.65+ -0.47+ -0.49+ -0.38+
+

p≤0.01

CAT=computer administered items; SF=short forms; SGRQ=St. George's Respiratory Questionnaire; Modified Medical Research Council (MMRC) Dyspnea Scale; Functional Assessment of Chronic Illness Therapy (FACIT) Dyspnea Scale; PSQI=Pittsburgh Sleep Quality Index; Exact-PRO= EXAcerbations of Chronic pulmonary disease Tool– Patient Reported Outcome

Table 5. Product-moment Correlations of PROMIS SF, CAT and Legacy Instruments with 6 Minute Walk and Percent Predicted FEV1 when Participants are Stable.

PROMIS SF* 6 Minute Walk % Predicted FEV1

r p-value n r p-value**

Anger -0.15 0.10 121 -0.08 0.37 128
Anxiety -0.22 0.01 122 0.01 0.93 129
Depression -0.23 0.01 122 -0.08 0.36 129
Fatigue -0.26 <0.01 122 -0.11 0.20 128
Pain Behavior -0.18 0.05 122 0.14 0.11 129
Pain Interference -0.24 <0.01 122 0.09 0.31 129
Physical Function 0.53 <0.01 122 0.27 <0.01 129
Discretionary Social Activities 0.21 0.02 121 0.11 0.21 127
Social Roles 0.31 <0.01 121 0.17 0.06 128

PROMIS CAT* 6 Minute Walk % Predicted FEV1

r* p** n r* P** n

Anger -0.18 0.06 115 -0.05 0.60 121
Anxiety -0.21 0.02 115 -0.01 0.94 121
Depression -0.17 0.06 115 -0.10 0.28 121
Fatigue -0.20 0.03 114 -0.11 0.21 120
Pain Behavior -0.14 0.13 115 0.15 0.09 121
Pain Interference -0.15 0.11 115 0.13 0.16 121
Physical Function 0.57 <0.01 114 0.34 <0.01 120
Discretionary Social Activities 0.24 0.01 115 0.11 0.25 121
Social Roles 0.24 0.01 115 0.15 0.10 121

Legacy Instruments+ 6 Minute Walk % Predicted FEV1

r* p** n r* P** n

FACIT - Dyspnea

Dyspnea -0.50 <0.01 112 -0.31 <0.01 115
Functional Limitations -0.50 <0.01 108 -0.27 <0.01 111

SGRQ

Symptoms -0.09 0.33 121 -0.06 128
Activities -0.41 <0.01 120 -0.25 <0.01 127
Impacts -0.20 0.03 119 -0.17 0.06 127
Total -0.27 <0.01 119 -0.20 0.03 127

PSQI

-0.17 106 0.10 113

EXACT-PRO Day 1

-0.33 110 -0.16 120

MMRC - Dyspnea

-0.39 <0.01 122 -0.21 0.02 128
*

CAT=computer administered items; SF=short forms;

+

SGRQ=St. George's Respiratory Questionnaire; Modified Medical Research Council (MMRC) Dyspnea Scale; Functional Assessment of Chronic Illness Therapy (FACIT) Dyspnea Scale; PSQI=Pittsburgh Sleep Quality Index; Exact-PRO= EXAcerbations of Chronic pulmonary disease Tool – Patient Reported Outcome

Discussion

Only a couple of studies have evaluated PROMIS instruments among COPD patients. One prior cross-sectional study showed PROMIS scores to be worse for those with COPD than those without it [28]. This study used self-reported chronic disease status including COPD, did not include any assessment of clinical diagnosis and COPD specific results were not reported in detail. Another recent study noted that PROMIS physical function and social activity scores decreased with level of lung function measured by GOLD grade [37]. The present study is unique in comparing PROMIS scores between stable and exacerbating COPD patients. Exacerbators reported significantly worse HRQOL on all domains. This study is also one of the first studies to examine the correlations between PROMIS scores and clinical indices.

The results of this study for the PROMIS measures were similar whether the administration was done using a static short-form or CAT. The availability of PROMIS instruments in both CAT and short-form offers researchers flexibility in administration formats. CAT administration offers the advantage of minimal participant burden without sacrificing measurement precision but requires a computer for administration. Short-forms can be accomplished via paper and pencil and thus, does not require a computer for administration [39]. Both were developed with rigorous qualitative and quantitative methodology and offer the advantages of comparability across conditions, reliability, validity and precision.

Several studies have now confirmed that COPD patients experiencing an exacerbation report significantly poorer HRQOL than stable COPD patients using either generic or disease-targeted measures [5-8]. The results for the disease-targeted measures administered in this study were similar to those previously reported [5-8]. The magnitude of score differences between stable and exacerbating patients for the disease-specific measures is substantially greater than for the PROMIS measures. This is not unexpected since the disease-specific measures would be most likely to demonstrate differences between these two populations as compared to a generic measure. Exacerbations of COPD have been reported to lead to substantial reductions in HRQOL [29, 30]. In addition, some studies have found that patients with worse HRQOL scores on disease-targeted measures are more likely to be hospitalized and less likely to survive [29, 30].

Patients with COPD often have several other chronic illnesses. Because it is difficult for patients to attribute their symptoms to one disease or treatment versus another, generic HRQOL measures may be easier to complete [31]. In this study, comparable findings were presented for generic and disease-targeted measures. PROMIS scores were significantly correlated with the disease specific legacy instruments. Similar to other reported results [37], this study found moderate correlations between the PROMIS domain scores and the FACIT-Dyspnea (correlation coefficients range 0.31 – 0.78) and mMRC dyspnea (correlation coefficients range from 0.11 – 0.55). In addition, the largest correlations with the 6-minute walk test were similar for the SGRQ Activities (r = -0.41), the FACIT-Dyspnea and Functional Limitations (r = -0.50) and the PROMIS Physical Function (r=0.57) domain scores.

The correlations between FEV1 and HRQOL tended to be small in magnitude and similar to those reported in another study correlating FEV1 with PROMIS measures [37]. There is a sizable literature reflecting the relatively weak correlations of disease-targeted and generic HRQL instruments with clinical measures, similar to those found in this study. A recent meta analysis reported weighted correlations of -0.29 between SGRQ total score and FEV1 and -0.34 between SGRQ total score and 6-minute walk [32]. Similarly, weak correlations have been noted between generic HRQOL instruments scores and FEV1 assessments (range for SF-36 physical functioning summary (PCS) r=0.06 to 0.38, and SF-36 mental health summary (MCS) 0.09 to 0.25) [33-35].

One limitation of this study was the small sample size at each site that recruited patients; hence, clinical site-specific analyses were not feasible. All study sites underwent extensive three-day training on a standardized study protocol to ensure consistent implementation for patient recruitment, enrollment and study procedures and to minimize variability among sites. Another limitation was that differential item functioning for the two study groups (stable and exacerbation patients) was not examined. In addition, for some of the analyses a subset of the study patients were utilized due to the fact that not patients completed these measures when they were in a stable state. Moreover, the analyses reported here do not address longitudinal changes in COPD status; hence, it is difficult to determine whether some of the differences seen between stable and exacerbating patients are really due to the exacerbation or just different underlying disease severity. These issues will be addressed more completely in future manuscripts that incorporate longitudinal components of this study.

Conclusion

The study provides support for the validity of the PROMIS measures and found that they performed similarly to legacy measures targeting the impact of COPD on HRQOL. Because the PROMIS instruments are designed to be applicable to a range of chronic illnesses, they offer some advantages over disease-targeted instruments by allowing for comparisons across a variety of chronic health conditions and studies.

Acknowledgments

This work was supported by the National Institutes of Health [Grants U01AR052181 and U01AR052177]. The Patient-Reported Outcomes Measurement Information System (PROMIS) is an NIH Roadmap initiative to develop a computerized system measuring PROs in respondents with a wide range of chronic diseases and demographic characterics. PROMIS II was funded by cooperative agreements with a Statistical Center (Northwestern University, PI: David Cella, PhD, 1U54AR057951), a Technology Center (Northwestern University, PI: Richard C. Gershon, PhD, 1U54AR057943), a Network Center (American Institutes for Research, PI: Susan (San) D. Keller, PhD, 1U54AR057926) and thirteen Primary Research Sites which may include more than one institution (State University of New York, Stony Brook, PIs: Joan E. Broderick, PhD and Arthur A. Stone, PhD, 1U01AR057948; University of Washington, Seattle, PIs: Heidi M. Crane, MD, MPH, Paul K. Crane, MD, MPH, and Donald L. Patrick, PhD, 1U01AR057954; University of Washington, Seattle, PIs: Dagmar Amtmann, PhD and Karon Cook, PhD, 1U01AR052171; University of North Carolina, Chapel Hill, PI: Darren A. DeWalt, MD, MPH, 2U01AR052181; Children's Hospital of Philadelphia, PI: Christopher B. Forrest, MD, PhD, 1U01AR057956; Stanford University, PI: James F. Fries, MD, 2U01AR052158; Boston University, PIs: Stephen M. Haley, PhD and David Scott Tulsky, PhD (University of Michigan, Ann Arbor), 1U01AR057929; University of California, Los Angeles, PIs: Dinesh Khanna, MD and Brennan Spiegel, MD, MSHS, 1U01AR057936; University of Pittsburgh, PI: Paul A. Pilkonis, PhD, 2U01AR052155; Georgetown University, PIs: Carol. M. Moinpour, PhD (Fred Hutchinson Cancer Research Center, Seattle) and Arnold L. Potosky, PhD, U01AR057971; Children's Hospital Medical Center, Cincinnati, PI: Esi M. Morgan DeWitt, MD, MSCE, 1U01AR057940; University of Maryland, Baltimore, PI: Lisa M. Shulman, MD, 1U01AR057967; and Duke University, PI: Kevin P. Weinfurt, PhD, 2U01AR052186). NIH Science Officers on this project have included Deborah Ader, PhD, Vanessa Ameen, MD, Susan Czajkowski, PhD, Basil Eldadah, MD, PhD, Lawrence Fine, MD, DrPH, Lawrence Fox, MD, PhD, Lynne Haverkos, MD, MPH, Thomas Hilton, PhD, Laura Lee Johnson, PhD, Michael Kozak, PhD, Peter Lyster, PhD, Donald Mattison, MD, Claudia Moy, PhD, Louis Quatrano, PhD, Bryce Reeve, PhD, William Riley, PhD, Ashley Wilder Smith, PhD, MPH, Susana Serrate-Sztein,MD, Ellen Werner, PhD and James Witter, MD, PhD. This manuscript was reviewed by PROMIS reviewers before submission for external peer review. See the Web site at www.nihpromis.org for additional information on the PROMIS initiative.

Abbreviations

ADL

activities of daily living

BMI

body mass index

CAT

computerized adaptive testing

COPD

chronic obstructive pulmonary disease

DSA

discretionary social activities

ER

emergency room

EXACT-PRO

EXAcerbations of Chronic pulmonary disease Tool – Patient Reported Outcomes

FACIT

Functional Assessment of Chronic Illness Therapy

FEV1

forced expiratory volume in 1 second

GOLD

Global Initiative for Chronic Obstructive Lung Disease

HRQOL

health-related quality of life

IRB

Institutional Review Board

IRT

item response theory

NIH

National Institutes of Health

MRC

Medical Research Council Dyspnea Scale

PRO

patient reported outcomes

PROMIS

Patient Reported Outcomes Measurement Information System

PSQI

Pittsburgh Sleep Quality Index

SGRQ

St. George's Respiratory Questionnaire

SR

social roles

s-TOFLHA

Short Test of Functional Health Literacy in Adults

Footnotes

Declarations of Conflicsts of Interest: DEI – no conflict of interest; CA - no conflict of interest; RH - no conflict of interest; KS - no conflict of interest; HL - no conflict of interest; JD - no conflict of interest; NKL - no conflict of interest; SY- no conflict of interest; DAD - no conflict of interest.

Contributor Information

Debra E. Irwin, Email: dirwin@email.unc.edu.

Charles A. Atwood, Jr., Email: atwoodcw@upmc.edu.

Ron D. Hays, Email: drhays@ucla.edu.

Karen Spritzer, Email: spritzer@ucla.edu.

Honghu Liu, Email: hhliu@mednet.ucla.edu.

James F. Donohue, Email: james_donohue@med.unc.edu.

Nancy Kline Leidy, Email: nancy.leidy@unitedbiosource.com.

Susan E. Yount, Email: s-yount@northwestern.edu.

Darren A. DeWalt, Email: darren_dewalt@med.unc.edu.

References

  • 1.Ader DN. Developing the Patient-Reported Outcomes Measurement Information System (PROMIS) Medical Care. 2007;45(Suppl 1):S1–S2. doi: 10.1097/01.mlr.0000258615.42478.55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.World Health Organization. [Accessed August 2014]; http://www.who.int/features/qa/18/en/ and http://www.who.int/mediacentre/factsheets/fs310/en/
  • 3.Center for Disease Control. [Accessed August 2014]; http://www.cdc.gov/nchs/fastats/lcod.htm/
  • 4.American Thoracic Society. [Accessed August 2014]; http://http://www.thoracic.org/statements/ and http://www.thoracic.org/clinical/copdguidelines/resources/copddoc.pdf.
  • 5.Schmier JK, Halpern MT, Higashi MK, Bakst A. The quality of life impact of acute exacerbations of chronic bronchitis (AECB): a literature review. Qual Life Res Mar. 2005;14(2):329–347. doi: 10.1007/s11136-004-0625-1. [DOI] [PubMed] [Google Scholar]
  • 6.Doll H, Grey-Amante P, Duprat-Lomon I, Sagnier PP, Thate-Waschke I, Lorenz J, Rychlik R, Pfeil T. Quality of life in acute exacerbation of chronic bronchitis: results from a German population study. Respir Med Jan. 2002;96(1):39–51. doi: 10.1053/rmed.2001.1208. [DOI] [PubMed] [Google Scholar]
  • 7.Doll H, Duprat-Lomon I, Ammerman E, Sagnier PP. Validity of the St George's respiratory questionnaire at acute exacerbation of chronic bronchitis: Comparison with the Nottingham health profile. Quality of Life Research. 2003;V12(2):117–132. doi: 10.1023/a:1022280532276. [DOI] [PubMed] [Google Scholar]
  • 8.Paterson C, Langan CE, McKaig GA, Anderson PM, Maclaine GD, Rose LB, Walker SJ, Campbell MJ. Assessing patient outcomes in acute exacerbations of chronic bronchitis: The measure your medical outcome profile (MYMOP), medical outcomes study 6-item general health survey (MOS-6A) and EuroQol (EQ-5D) Quality of Life Research. 2000;V9(5):521–527. doi: 10.1023/a:1008930521566. [DOI] [PubMed] [Google Scholar]
  • 9.Yohannes AM, Roomi J, Baldwin RC, Connolly MJ. Depression in elderly outpatients with disabling chronic obstructive pulmonary disease. Age Ageing. 1998 Mar 1;27(2):155–160. doi: 10.1093/ageing/27.2.155. 1998. [DOI] [PubMed] [Google Scholar]
  • 10.Wamboldt FS. Anxiety and depression in COPD: a call (and need) for further research. Copd Jun. 2005;2(2):199–201. [PubMed] [Google Scholar]
  • 11.Kapella MC, Larson JL, Patel MK, Covey MK, Berry JK. Subjective fatigue, influencing variables, and consequences in chronic obstructive pulmonary disease. Nurs Res. 2006 Jan-Feb;55(1):10–17. doi: 10.1097/00006199-200601000-00002. [DOI] [PubMed] [Google Scholar]
  • 12.Guyatt GH, Berman LB, Townsend M, Pugsley SO, Chambers LW. A measure of quality of life for clinical trials in chronic lung disease. Thorax Oct. 1987;42(10):773–778. doi: 10.1136/thx.42.10.773. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Reardon JZ, Lareau SC, ZuWallack R. Functional Status and Quality of Life in Chronic Obstructive Pulmonary Disease. The American Journal of Medicine. 2006;119(10, Supplement 1):32–37. doi: 10.1016/j.amjmed.2006.08.005. [DOI] [PubMed] [Google Scholar]
  • 14.Pauwels RA, Buist AS, Calverley PMA, Jenkins CR, Hurd SS. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease . NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) Workshop Summary. Am J Respir Crit Care Med. 2001 Apr 1;163(5):1256–1276. doi: 10.1164/ajrccm.163.5.2101039. 2001. [DOI] [PubMed] [Google Scholar]
  • 15.Rabe KF, Hurd S, Anzueto A, Barnes PJ, Buist SA, Calverley P, Fukuchi Y, Jenkins C, Rodriguez-Roisin R, van Weel C, Zielinski J. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2007 Sep 15;176(6):532–555. doi: 10.1164/rccm.200703-456SO. [DOI] [PubMed] [Google Scholar]
  • 16.Vestbo J. The TORCH (towards a revolution in COPD health) survival study protocol. Eur Respir J Aug. 2004;24(2):206–210. doi: 10.1183/09031936.04.00120603. [DOI] [PubMed] [Google Scholar]
  • 17.Calverley P, Pauwels R, Vestbo J, Jones P, Pride N, Gulsvik A, Anderson J, Maden C. Combined salmeterol and fluticasone in the treatment of chronic obstructive pulmonary disease: a randomised controlled trial. Lancet. 2003 Feb 8;361(9356):449–456. doi: 10.1016/S0140-6736(03)12459-2. [DOI] [PubMed] [Google Scholar]
  • 18.St. George's Respiratory Questionnaire website. Accessed August 2014 http://www.healthstatus.sgul.ac.uk/SGRQ_download/SGRQ%20Manual%20June%202009.pdf.
  • 19.Bestalib JC, Paula EA, Garroda R, Garnhamma R, Jones PW, Wedzicha JA. Usefulness of the Medical Research Council (MRC) dyspnoea scale as measure of disability in patients with chronic obstructive pulmonary disease. Thorax. 1999;54:581–586. doi: 10.1136/thx.54.7.581. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Hinchcliff M, Beaumont JL, Thavarajah K, Varga J, Chung A, Podlusky S, Carns M, Chang RW, Cella D. Validity of two new patient-reported outcome measures in systemic sclerosis: Patient-Reported Outcomes Measurement Information System 29-item Health Profile and Functional Assessment of Chronic Illness Therapy-Dyspnea short form. Arthritis Care Res (Hoboken) 2011 Nov;63(11):1620–1628. doi: 10.1002/acr.20591. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Leidy NK, Wilcox T, Jones PW, Murray L, Winnette R, Howard K, Petrillo J, Powers J, Sethi S, the EXACT-PRO Study Group Development of the EXAcerbations of Chronic Obstructive Pulmonary Disease Tool (EXACT): A Patient-Reported Outcome Measure. Value in Health. 2010;13(8):965–975. doi: 10.1111/j.1524-4733.2010.00772.x. [DOI] [PubMed] [Google Scholar]
  • 22.Leidy NK, Wilcox T, Jones PW, Roberts L, Powers J, Sethi S, the EXACT-PRO Study Group Standardizing measurement of COPD exacerbations: Reliability and validity of a patient-reported diary. American Journal of Respiratory and Critical Care Medicine. 2010 Sep 2; doi: 10.1164/rccm.201005-0762OC. In press. Epub. [DOI] [PubMed] [Google Scholar]
  • 23.Jones PW, Chen WH, Wilcox T, Sethi S, Leidy NK, for the EXACT-PRO Study Group Characterizing and quantifying the symptomatic features of COPD exacerbations. Chest. 2010 Nov 11; doi: 10.1378/chest.10-1240. In press. Epub ahead of print. [DOI] [PubMed] [Google Scholar]
  • 24.Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Research. 1989;28:193–213. doi: 10.1016/0165-1781(89)90047-4. [DOI] [PubMed] [Google Scholar]
  • 25.Reybrouck T. Clinical Usefulness and Limitations of the 6-Minute Walk Test in Patients With Cardiovascular or Pulmonary Disease. Chest. 2003;123:325–327. doi: 10.1378/chest.123.2.325. [DOI] [PubMed] [Google Scholar]
  • 26.Ingle L, Rigmy AS, Carroll S, Butterly R, King RF, Cooke CB, Cleland JGJF, Clark AL. Prognostic value of the 6 min walk test and self-perceived symptom severity in older patients with chronic heart failure. European Heart Journal. 2007 doi: 10.1093/eurheartj/ehl527. http://eurheartj.oxfordjournals.org/cgi/content/abstract/ehl527v1. [DOI] [PubMed]
  • 27.Baker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J. Development of a brief test to measure functional health literacy. Patient Educ Couns. 1999;38:33–42. doi: 10.1016/s0738-3991(98)00116-5. [DOI] [PubMed] [Google Scholar]
  • 28.Rothrock NE, Hays RD, Spritzer K, Yount SE, Riley W, Cella D. Relative to the general US population, chronic diseases are associated with poorer health-related quality of life as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) J Clin Epi. 2010;63:1195–1204. doi: 10.1016/j.jclinepi.2010.04.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Fan VS, Curtis JR, Tu SP, McDonell MB, Fihn DS. Using quality of life to predict hospitalization and mortality in patients with obstructive lung diseases. Chest. 2002;122(2):429–436. doi: 10.1378/chest.122.2.429. [DOI] [PubMed] [Google Scholar]
  • 30.Almagro P, Calbo E, Ochoa de Echaguen A, Barreiro B, Quintana S, Heredia JL, Garau J. Mortality after hospitalization for COPD. Chest. 2002;121(5):1441–1448. doi: 10.1378/chest.121.5.1441. [DOI] [PubMed] [Google Scholar]
  • 31.Yeo J, Karimova G, Bansal S. Co-morbidity in older patients with COPD – its impact on health service utilization and quality of life, a community study. Age and Ageing. 2006;35:33–37. doi: 10.1093/ageing/afj002. [DOI] [PubMed] [Google Scholar]
  • 32.Tsiligianni I, Kocks J, Tzanakis N, Siafakas N, van der Molen T. Factors that influence disease-specific quality of life or health status in patients with COPD: a systematic review and meta-analysis of Pearson correlations. Prim Care Respir J. 2011;20(3):257–268. doi: 10.4104/pcrj.2011.00029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Kaplan RM, Ries AL, Reilly J, Mohsenifar Z. Measurement of health-related quality of life in the national emphysema treatment trial. Chest. 2004;126(3):781–789. doi: 10.1378/chest.126.3.781. [DOI] [PubMed] [Google Scholar]
  • 34.Pereira EDB, Pinto R, Alcantara M, Medeiros M. Influence of respiratory runction parameters on the quality of life of COPD patients. J Bras Pneumol. 2009;35(8):730–736. doi: 10.1590/s1806-37132009000800003. [DOI] [PubMed] [Google Scholar]
  • 35.Pickard AS, Yang Y, Lee TA. Comparison of health-related quality of life measures in chronic obstructive pulmonary disease. Health and Qual Life Outcomes. 2011;9(26) doi: 10.1186/1477-7525-9-26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Paap MCS, Bode C, Lenferink LIM, Groen LC, Terwee CB, Ahmed S, Eilayyan O, van der Palen J. Identirying key domains of health-related quality of life for patients with chronic obstructive pulmonary disease: the patient perspective. Health Qual Life Outcomes. 2014;12:106. doi: 10.1186/s12955-014-0106-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Lin FJ, Pickard AS, Krishnan JA, Joo MJ, Au DH, Carson SS, Gillespie S, Henderson AG, Lindenauer PK, McBurnie MA, Mulaski RA, Naureckas ET, Vollmer WM, Lee TA, CONCERT Consortium Measuring health-related quality of life in chronic obstructive pulmonary disease: properties of the EQ-5D-%L and PROMIS-43 short form. BMC Med Res Meth. 2014;14:78. doi: 10.1186/1471-2288-14-78. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Meguro M, Barley EA, Spencer S, Jones PW. Development and validation of an improved COPD-specific version of the St George's Respiratory Questionnaire. Chest. 2006;132:456–463. doi: 10.1378/chest.06-0702. [DOI] [PubMed] [Google Scholar]
  • 39.Cella D, Gershon R, Lai JS, Choi S. The future of outcomes measurement: item banking, tailored short-forms, and computerized adaptive assessment. Qual Life Res. 2007;16(Suppl1):131–141. doi: 10.1007/s11136-007-9204-6. [DOI] [PubMed] [Google Scholar]

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