Systematic literature review of patient-reported outcome measures used in assessment and measurement of sleep disorders in chronic obstructive pulmonary disease

Introduction

Sleep problems are a common and important, but poorly understood and under-researched, aspect of chronic obstructive pulmonary disease (COPD). After breathlessness and fatigue, sleep disturbance is considered to be the third most common symptom experienced by people with respiratory disease¹ and is also predictive of exacerbations, respiratory-related emergency hospital visits, and all-cause mortality.² Insomnia describes any reported difficulty a person has with sleep³ and has four elements: difficulties falling asleep, interrupted sleep, trouble staying asleep, and still feeling tired and worn out even after a usual amount of sleep.^3–5 Around 10% of the adult population is affected by insomnia, but the occurrence is much higher in people with COPD, where estimates range between 16% and 75%.⁶ The benefits of sleep are well known, and long-term interruption of normal sleeping patterns has a detrimental impact on physical, emotional, and social functioning, and is also associated with anxiety, depression, bodily pain, and a wide variety of pre-existing chronic medical conditions.⁴ In addition to insomnia, narcolepsy (suddenly falling asleep at inappropriate times), restless legs syndrome, and obstructive sleep apnea are the most common sleep disorders found in the general population,⁶ and people with COPD are disproportionately affected. Restless legs syndrome involves a need to move the legs, usually at night-time, is associated with marked sleep disturbance, and affects 7%–14% of the general population and 29% of patients with COPD.^7,8 Obstructive sleep apnea is the periodic interruption of airflow in the upper airway during sleep and affects 3%–7% of the general population⁹ and 25%–29% of people with COPD.10 A summary of the occurrence of four common sleep disorders in COPD populations is provided in Table 1.^8,11–13

Table 1 Summary of the occurrence of common sleep disorders in COPD populations Abbreviation: COPD, chronic obstructive pulmonary disease.

Given the importance of sleep disorders in COPD, being able to accurately classify their nature and severity is important in the management of COPD. Although self-reported sleep disorders are associated with COPD symptoms and poorer health-related quality of life,¹⁴ their relationship with traditional diagnostic markers of lung function (such as forced expiratory volume in one second, forced vital capacity, and oxygen saturation) is weak.¹⁵ This emphasizes the need for clinical instruments to accurately assess the impact of the disease and its treatment on a patient’s health and well-being through patient-reported outcome measures (PROMs)^16,17 as well as recording changes in physiological function.

Many of the instruments that have measured sleep disturbance in epidemiological studies were originally developed for people with a range of psychological conditions and/or pre-existing sleeping disorders.^18,19 However, the validity of these measures cannot be assumed to transfer between clinical populations.¹⁹ Thus, the aim of this review was to identify and evaluate the suitability of published measures of sleep disturbance for use in people with COPD in order to make recommendations for best practice for clinical and research purposes. Our objectives were to:

• Identify which patient-reported outcome sleep measures have been used in people with COPD
• Identify which instruments have been developed and validated specifically for people with COPD
• Summarize the evidence for reliability and validity of sleep instruments in COPD patients
• Examine associations with sleep disturbance recorded by sleep instruments used in clinical studies of COPD patients.

Materials and methods

Ethical approval was not needed to undertake this review, which was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.²⁰

Search strategy

In this study, we conducted a systematic computerized literature review designed to identify all PROMs concerned with sleep problems experienced by people with COPD. The search included all instruments that had been developed and validated in people with COPD as well as generic instruments that had been developed for use in other disease areas and then administered to adult COPD patients.

Stage 1: Identification of sleep outcome measures used in COPD

The first stage of the search was to identify sleep outcome measures that had been used in COPD. This was conducted using EMBASE, MEDLINE, and PsycINFO electronic databases for all years up to May 2014 using both key words, ie, the Medical Subject Headings (MeSH) “COPD” AND “sleep” and expanded to include all recognized subheadings. All titles, abstracts, and full texts from the identified papers were examined by the lead author (APG) for reference to specific sleep instruments or data indicating that at least one sleep outcome measure had been used. A list of sleep outcome measures was then produced. The reference lists and citations of selected articles were also searched to identify any additional sleep PROMs not found by the electronic database search.

Stage 2: Selection and evaluation of sleep instruments used in COPD

A SCOPUS database search was carried out on each of the detected sleep outcome measures to identify all publications in which the original paper had been cited. The search included the following related terms:

1. Construct-related terms: sleep problems
2. Population terms: COPD patients (in the title, abstract, text, or reference section)
3. Outcome-related terms: development, validation, or psychometric properties of sleep PROMs designed specifically for people with COPD. Sleep outcome measures not specifically designed for people with COPD but used in a COPD patient group whether psychometric data were reported or not
4. Method-related terms: instrument* OR measure* OR question* OR scale OR assess
5. Quality assessment terms: valid* or reliab* or evaluat* OR psychometric.

We also screened the reference lists and citations of included articles to identify additional relevant publications.

Eligibility criteria

To be included in the review, all identified articles had to meet the following inclusion criteria: the article described PROMs that either had been specifically designed and validated for use in patients with COPD or included a generic instrument that had been administered to COPD patients; information on at least one measurement property of the outcome measure was reported; the study sample consisted of adults with a clinical diagnosis of COPD; a full text of the original publication was published electronically, in English, in a peer-reviewed journal.

Articles were excluded if reference to COPD and/or sleep only appeared in the text or reference section. Similarly, we excluded all articles with mixed study samples where the results from COPD patients were not reported separately. Review articles, protocols, and case studies were also excluded. Two investigators (APG and JY) read independently all titles, abstracts, and full texts of all the retrieved articles to determine which were eligible for review. Any disagreements were resolved at a consensus meeting.

Methodological quality assessment

The COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) checklist²¹ is a standardized tool for evaluating the methodological quality of PROMs. COSMIN checklists are used to evaluate the measurement properties of instruments in terms of their internal consistency, reliability, measurement error, content validity, structural validity, hypothesis testing, cross-cultural validity, criterion validity, and responsiveness to change. As it was anticipated that the number of PROMs that had been developed and validated for use in COPD populations was likely to be very small, rather than using the full COSMIN checklist we used four PROM characteristics recommended by the US Food and Drug Administration²² to evaluate the measurement properties of identified sleep PROM instruments in relation to their use in COPD patients, ie, conceptual and measurement model, reliability, validity, and responsiveness to change.

Conceptual model

Identified articles were examined for descriptions of concepts contained within the instrument, including the rationale and process for deriving scale scores from raw scores, identifying and dealing with floor and ceiling effects, and scale variability.

Reliability

Articles were scrutinized for estimates of reliability, including inter-item correlations, test-retest repeatability, internal consistency, and/or kappa statistics.

Validity

Any reference to content, construct, and criterion-related validity were noted. When considering construct validity, we also recorded methods to differentiate between people with different levels of lung function or disease severity, such as the Global Initiative for Chronic Obstructive Lung Disease staging system that classifies people with COPD according to the results of pulmonary tests. Where available, we also collected data regarding the relationships between sleep outcome instruments and other established COPD outcome measures (such as the St George’s Respiratory Questionnaire,²³ the Medical Research Council Dyspnea scale,²⁴ and routine clinical tests). Any analyses intended to examine dimensionality using factor analysis or Rasch analysis were noted, along with any assessments of differential item functioning that evaluated group differences in PROM item responses.

Responsiveness to change

All data relating to the ability of the instrument to detect changes over time in terms of sleep disturbance were noted. Where correlations between changes in scores of two measures are reported, these had to relate to predefined hypotheses.

Results

The stage 1 database search identified articles referring to COPD and sleep (Medline 804, EMBASE 2,314, and PsycINFO 59) from which one COPD-specific and six non-disease-specific sleep instruments were identified (Table 2).^25–31 In stage 2, the SCOPUS search found 10,602 articles citing any of the seven sleep outcome measures, 270 of which referred to COPD. After applying the exclusion criteria, 44 manuscripts were selected for review (Figure 1). Nearly 90% of the reviewed publications either used the Pittsburgh Sleep Quality Index (PSQI;³⁰ 19/44, 43.1%) or the Epworth Sleepiness Scale (ESS; 20/44, 45.5%).²⁸ The 19-item PSQI measures sleep quality in seven domains and the ESS assesses the likelihood of a person dozing off or falling asleep in eight common life situations. Most studies involved patients with moderate-severe COPD recruited from hospital outpatient or specialist respiratory clinics.

Table 2 Number of papers found and excluded or included in the review Abbreviation: COPD, chronic obstructive pulmonary disease.

Figure 1 Flow diagram showing the total number of studies screened, assessed for eligibility and included in the review. Abbreviation: COPD, chronic obstructive pulmonary disease.

COPD-specific sleep outcome measures

After assessing the methodological properties of the identified PROMs, only one instrument appeared to have been developed and validated for use in COPD patients, ie, the COPD and Asthma Sleep Impact Scale (CASIS).²⁵

The CASIS is a seven-item measure of sleep impairment during the previous week. Five items relate to disturbance falling asleep or staying awake during the day. The remaining two items concern sleep quality. The items are scored on a five-point scale ranging from 0 if the item never applies, to 4 if the item applies very often. A total raw score is produced from the sum of the seven individual scores which is then linearly transformed to a 0–100 total scale score. A mean CASIS score of 43.3±24.7 was reported in patients with mild COPD. The results of the original psychometric testing of the CASIS (Table 3), showed that the scale had good internal consistency (Cronbach’s alpha 0.91), test-retest reproducibility (intraclass coefficient 0.84), and concurrent validity (correlated with the St George’s Respiratory Questionnaire, r<=0.68).

Table 3 Psychometric properties of COPD and Asthma Sleep Impact Scale Abbreviations: COPD, chronic obstructive pulmonary disease; CASIS, COPD and Asthma Sleep Impact Scale; ICC, intra-class correlation coefficient; SGRQ, St George’s Respiratory Questionnaire.

None of the non-disease-specific sleep scales reported any tests of reliability or validity to justify their use in the COPD population. Significant associations were observed in only 8/20 (40%) of studies where the ESS was compared with other COPD-related outcome measures. For example, the prevalence of daytime sleepiness (ESS >10) was significantly greater in patients diagnosed with insomnia.¹¹ Compared with people who had obstructive sleep apnea/hypopnea syndrome, COPD patients were more likely to be affected by daytime sleepiness.³² Significant differences in mean ESS scores were observed between patients with COPD and restless legs syndrome compared with controls who had restless legs syndrome.³³ However, no differences in daytime sleepiness were observed in a study that compared use of temazepam between COPD patients and controls.³⁴ Similarly, no significant differences in ESS scores were detected in patients with and without restless legs syndrome³⁵ (Table 4).

Table 4 Summary of studies that used the Epworth Sleepiness Scale Abbreviations: AHI, apnea-hypopnea index; BD, bronchodilator; BMI, body mass index; CI, confidence interval; OR, odds ratio; COPD, chronic obstructive pulmonary disease; RLS, restless legs syndrome; SDB, sleep-disordered breathing; CBT, cognitive behavioral therapy; OSAHS, obstructive sleep apnea/hypopnea syndrome; mMRC, modified Medical Research Council Dyspnoea scale; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; GOLD, Global initiative for chronic Obstructive Lung Disease; SpO2, oxygen saturation; ESS, Epworth Sleepiness Scale; SE, standard error; pO2, oxygen partial pressure; paO2, arterial oxygen tension; IQR, interquartile range; TB90%, time spent with saturation below 90%; SF-36, Short-Form 36 Health Survey; nCPAP, nasal continuous positive airway pressure; SD, standard deviation; OSA, obstructive sleep apnea.

For the PSQI, significant associations were noted in 11/19 (57.9%) of the relevant studies. PSQI scores were found to be significantly higher in patients with restless legs syndrome.³⁶ PSQI total scores also correlated with total scores from the St George’s Respiratory Questionnaire^37,14 and the Fatigue Severity Scale.³⁵ In contrast, no correlation was observed between PSQI and St George’s Respiratory Questionnaire scores in an investigation of factors affecting health status in COPD patients with comorbid anxiety or depression.³⁸ Further, although significant PSQI score reductions were observed in patients receiving a course of cognitive behavioral therapy (where the primary outcome was insomnia),³⁹ no reductions in pre- and post-sleep quality were observed in a randomized controlled trial that compared cognitive behavioral therapy with usual care, where sleep was a secondary outcome measure to anxiety and depression⁴⁰ (Table 5).

Table 5 Summary of papers that used the Pittsburgh Sleep Quality Index Abbreviations: BMI, body mass index; CI, confidence interval; COPD, chronic obstructive pulmonary disease; RLS, restless legs syndrome; mMRC, modified Medical Research Council Dyspnea scale; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; GOLD, Global initiative for chronic Obstructive Lung Disease; IQR, interquartile range; nCPAP, nasal continuous positive airway pressure; PR, pulmonary rehabilitation; RR, relative risk; BD, bronchodilator; CBT, cognitive behavioral therapy; SD, standard deviation; NPPV, noninvasive positive pressure ventilation; PaCO2, partial pressure of carbon dioxide; HRQoL, health-related quality of life; PSQI, Pittsburgh Sleep Quality Index; OPO, overnight pulse oximetry; SGRQ, St George’s Respiratory Questionnaire; CESD, Center for Epidemiologic Studies-Depression.

Table 6 shows the papers that used the four remaining generic outcome measures in studies of COPD patients.^33,35,41,42 With so few studies, there are currently insufficient data to evaluate the utility of these instruments; however, in one study,³³ International Restless Leg Study Group scores correlated significantly with ESS scores.

Table 6 Summary of articles using generic sleep measures Abbreviations: BNSQ, Basic Nordic Sleep Questionnaire; COPD, chronic obstructive pulmonary disease; PLM, periodic limb movement; SDQ, Sleep Disorders Questionnaire; PSY, psychiatric sleep disorder; RLS, restless leg syndrome; IRLSG, International Restless Leg Study Group; SA, sleep apnea; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; OSA, obstructive sleep apnea; mMRC, modified Medical Research Council Dyspnea scale; GOLD, Global initiative for chronic Obstructive Lung Disease; SaO2, arterial oxygen saturation; ESS, Epworth Sleepiness Scale; PaCO2, partial pressure of carbon dioxide; PaO2; hypercapnia PaCO.

Although the results provide some evidence of the validity of measures of sleep disturbance in people with COPD, none of the above sleep measures were specifically evaluated for people with COPD. Similarly, we did not find any articles that provided data on test-retest, intrarater, or inter-rater reliability or responsiveness to change among COPD patient groups.

The point estimates of sleep disturbance from clinical studies of COPD patients using the ESS and the PSQI are shown on Tables 4 and 5. In 13/15 of the studies using the ESS, the mean/median scores were less than 10, ie, below the accepted cutoff value for excessive daytime sleepiness.²⁸ Most of the observed PSQI scores were above 5, ie, above the cutoff value representing poor quality sleep.³⁰ Point and upper and lower quartile estimates for the ESS and PSQI are displayed on Figures 2 and 3.

Figure 2 Point estimates and variability in studies that used the ESS. Abbreviation: ESS, Epworth Sleepiness Scale.

Figure 3 Point estimates and variability in studies that used the PSQI. Abbreviation: PSQI, Pittsburgh Sleep Quality Index.

Discussion

Sleep disturbances are an important problem that can seriously impact on physical and mental well-being as well as quality of life for people with COPD. This review identified seven outcome measures that have been used in COPD populations but none has been sufficiently validated to satisfy US Food and Drug Administration requirements to support labeling claims in medical product development. Only one measure, the CASIS, included item response theory modeling when evaluating the psychometric evaluation of the instrument. Incorporating item response theory is now considered to be an essential component in the design and validation of all PROMs.¹⁹

The majority of sleep studies in COPD have relied on two general measures of sleep dysfunction, the ESS and the PSQI, and although both of these instruments have been extensively used in a variety of clinical populations, neither has been validated for use in COPD patients.

As far as we are aware, this is the first systematic review of sleep measures in COPD. A strength of this study was the comprehensiveness of our literature search. We believe that we have identified all of the main PROMs of sleep disorders that have been used in COPD populations. Nevertheless, as we did not search all electronic databases or carry out a hand search, there is the possibility that we may have missed some relevant articles, particularly those that appeared in non-English language journals. However, by cross-checking the reference lists of all included papers and that of a recent systematic review of instruments designed to measure sleep dysfunction in adults,¹⁵ we believe we have minimized the loss of any important papers.

The review identified only one PROM, ie, the CASIS, which has been specifically designed and validated for use in COPD patients. In each item of the CASIS, patients are advised to “[…] think about the impact of breathing problems/COPD/asthma on your sleep during the past week […]” Most items, however, are general in nature and relate to the frequency of symptoms such as falling asleep, staying awake, and waking up feeling rested. Only one item relates specifically to breathing problems, ie, shortness of breath, coughing, and chest tightness. Further, as these symptoms are all contained within the same item, it is not possible to differentiate patients who may have different severity of symptoms; for example, between patients who wake up at night only with shortness of breath or wake up with both shortness of breath and coughing. Since the publication of the original paper, the CASIS has not been used in any intervention studies, so further evidence is needed to confirm the utility of this instrument in guiding the clinical management of COPD patients and in research.

This review has highlighted the current reliance of sleep research on generic sleep measures and the paucity of disease-specific instruments currently available to assess the patient’s experience of sleep in relation to COPD. By definition, generic measures tend to cover broad aspects such as functional status and perceptions and are more likely to identify aspects that are not disease-related. Because instruments validated in one population may not perform well in specific populations under investigation, separate validation of generic measures in each population is recommended.⁴³ Similarly, given that disease-specific measures are generally more responsive to change, outcomes based solely on generic measures are unlikely to detect treatment-related improvements.⁴⁴ These deficiencies could call into question findings from previous research on the impact of sleep problems in COPD. The need for validated COPD-specific sleep outcome measures was emphasized in an expert panel meeting held in 2011.⁴⁵ While appreciating the multifactorial nature of sleep disturbance in COPD, the panel highlighted the need for an instrument to classify patients according to their night or daytime symptoms, which is not possible using existing PROMs for sleep. Development work on new COPD sleep PROMs to address these limitations is currently being carried out by the authors of this review.

Conclusion

This review highlights the complexity of sleep assessment, the inadequacy of non-disease-specific measures to capture problems experienced by people with COPD, and the absence of robust and validated methods of assessing and classifying symptoms associated with disrupted sleep in COPD. In studies using non-disease-specific sleep measures, there is a pressing need for these to be validated with COPD populations and/or for new disease-specific PROMs to be developed.

Acknowledgment

This partnership received financial support from the Knowledge Transfer Partnerships (KTP) program. The project was also supported by the UK Medical Research Council. KTP aims to help businesses to improve their competitiveness and productivity through the better use of knowledge, technology, and skills that reside within the UK knowledge base. KTP is funded by the Technology Strategy Board along with other government funding organizations.

Author contributions

All authors contributed to the design of the review. APG carried out the literature searches, produced draft manuscripts for review, and edited the manuscript prior to submission. JY read and verified the suitability of the articles for review and also participated in consensus meetings. ST provided guidance and editorial support during preparation of the review. All authors contributed and approved the final version of the manuscript. ST and JY are guarantors of the paper, taking responsibility for the integrity of the work as a whole from inception to the published article.

Disclosure

The authors report no conflicts of interest in this work.

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