Online Supplement. Relationship Between OSA Clinical Phenotypes and CPAP Treatment Outcomes

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1 Relationship Between OSA Clinical Phenotypes and CPAP Treatment Outcomes Frédéric Gagnadoux, MD, PhD; Marc Le Vaillant, PhD; Audrey Paris, MD, PhD; Thierry Pigeanne, MD; Laurence Leclair-Visonneau, MD; Acya Bizieux-Thaminy, MD; Claire Alizon, MD; Marie-Pierre Humeau, MD; Xuan-Lan Nguyen, MD; Béatrice Rouault, MD; Wojciech Trzepizur, MD, PhD; Nicole Meslier, MD; on behalf of the Institut de Recherche en Santé Respiratoire des Pays de la Loire Sleep Cohort Group* CHEST 2016; 149(1): AMERICAN COLLEGE OF CHEST PHYSICIANS. Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details. DOI: /j.chest

2 e-appendix 1. ABBREVIATIONS: AHI: apnea-hypopnea index; CVD: cardiovascular diseases; CPAP: continuous positive airway pressure; EDS: Excessive daytime sleepiness; ESS: Epworth Sleepiness Scale; HR-QOL: Health-related quality of life; PSG: polysomnography; QD2A: 13-item self-rated Pichot depression scale; SDB: sleep-disordered breathing METHODS Design and study population This prospective cohort study was conducted on the Institut de Recherche en Santé Respiratoire des Pays de la Loire [IRSR] sleep cohort. Since 15 May 2007, consecutive patients 18 years investigated for clinical suspicion of OSA in 7 centres from the West of France are eligible for inclusion in the IRSR sleep cohort. Approval was obtained from the University of Angers ethics committee and from the "Comité Consultative sur le Traitement de l Information en matière de Recherche dans le domaine de la Santé [C.C.T.I.R.S.] (07.207bis). The database is anonymous and complies with the restrictive requirements of the "Commission Nationale Informatique et Liberté [C.N.I.L.], the French information technology, and personal data protection authority. All patients included in the IRSR sleep cohort gave their written informed consent. Between 15 May 2007 and 1 st December 2014, patients from the IRSR sleep cohort with an AHI 15, indicating moderate-to-severe OSA, were included in the cross-sectional cluster analysis to identify phenotypes. Patients in whom CPAP had been prescribed for at least 6 months with available follow-up data on CPAP adherence, daytime sleepiness and quality of life were included in the analysis of CPAP outcomes. Baseline assessment Questionnaires The following sleep-related symptoms were considered to be present when they occurred at least 3 times a week: loud snoring, stopped breathing during sleep, unrested upon waking, headache upon waking. A complaint of insomnia was recorded when patients reported frequent difficulty falling asleep and/or difficulty staying asleep and/or early final awakening. Excessive daytime sleepiness (EDS) was defined by an Epworth Sleepiness Score (ESS)>10 1. Symptoms of depression were defined by a QD2A depression score 7 2,3. Health-related quality of life (HR- QOL) was assessed using the Outcomes Study 36-item short-form (SF-36) 4. Socioeconomic status (SES) was described by the following variables: marital status (married or living as a couple / living alone); employment status (employed full time or part time / retired /

3 unemployed); and educational attainment as determined by the age at which the patient left full-time education ( 18 / >18 years) 5. Assessment of co morbidities Obesity was defined by a body mass index (BMI) 30 kg/m 2. Hypertension (HTN) and diabetes were defined as a physician diagnosis combined with treatment with appropriate medication. Co morbid cardiovascular disease (CVD) was defined as a physician diagnosis of 1 of the following CVD: ischaemic heart disease, cardiac arrhythmia, congestive heart failure and stroke. Sleep recordings OSA was diagnosed by overnight polysomnography (PSG) or overnight respiratory recording. Overnight PSG was performed with continuous recording of the following channels: electroencephalogram, electrooculogram, chin electromyogram, arterial oxygen saturation, nasal-oral airflow (pressure cannula and tracheal sounds), electrocardiogram, chest and abdominal wall motion, and body position. Overnight respiratory recordings were performed with continuous recording of arterial oxygen saturation, nasal-oral airflow, chest and abdominal wall motion, and body position. Respiratory events were scored manually using recommended criteria 6. CPAP initiation and follow-up According to French guidelines, CPAP was prescribed in patients with OSA symptoms and either an apnea-hypopnea index (AHI) 30 or an AHI between 15 and <30 with severe EDS and/or severe CVD co morbidities. At 6 months, patients were reviewed in the outpatient clinic by the sleep specialist and filled in the ESS and SF-36 questionnaire. Objective data concerning CPAP adherence were downloaded from the internal memory of the device. Statistical analysis Latent class analysis (LCA) was conducted to identify OSA clusters. LCA is a statistical method for finding subgroups of related cases from multivariate discrete data based on the patterns of their associated variables 7,8. Thirteen clinically relevant dichotomized variables were entered in the LCA, including demographic and anthropometric data, sleep-related symptoms, complaint of insomnia, EDS, depressive symptoms and co morbidities. The most appropriate number of clusters was determined by examining commonly used criteria, including the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), the sample size-adjusted BIC (SSABIC), the Lo-Mendell-Rubin Likelihood Ratio Test (LMR-LRT), and the entropy 7. To graphically display the OSA clusters identified by LCA, we plotted the prevalence of each variable in each cluster on a colour intensity scale spanning from yellow (prevalence of 0) to red

4 (prevalence of 100) 7. The relative relevance of each variable to the separation into clusters was evaluated by using Chi 2 values. Differences among clusters with regards to SES and sleep recordings data were also examined using Chi-squared test or ANOVA, as appropriate. To validate the clinical relevance of OSA clusters identified by LCA, treatment outcomes were compared across clusters in the subgroup of patients in whom CPAP had been prescribed for at least 6 months with available follow-up data. The profile of the distribution of the variables across the clusters identified by LCA was compared in the total sample and in the CPAP follow-up subgroup, and the individual agreement in the assigned cluster was tested by means of Kappa statistics. The primary outcome variable was the success of CPAP treatment at 6 months followup, as defined by mean daily use of the device 4h and either a decrease in ESS 4 points in patients with baseline value 11 and/or an increase of at least 7 points in the energy/vitality component score of the SF-36 questionnaire regardless of baseline ESS value. A logistic regression procedure was conducted to model the association between OSA clusters and the success of CPAP treatment at 6 months follow-up. Unadjusted and adjusted odds ratio (OR) (95 confidence intervals [CI]) for CPAP treatment success according to OSA cluster were calculated. To adjust for potential confounders, the following covariates that are likely to interfere with CPAP outcomes were progressively entered in the multivariate logistic regression analysis: SES, AHI and ESS. All statistical analyses were performed with SAS software (SAS/STAT Package by SAS Institute Inc., Cary, NC, USA) and MPlus V.7.2 for LCA. A 2-tailed p value < 0.05 was considered significant. RESULTS A flow diagram is presented in e-figure 1. On 1 st December 2014, 9,907 patients had been enrolled in the IRSR sleep cohort and 3,924 of them had an AHI value < 15. A total of 5,983 patients with moderate-to-severe OSA were included in the cross-sectional analysis. Among 4,224 patients in whom CPAP had been prescribed for at least 6 months, 401 had no available CPAP adherence data at 6 months and 733 had missing follow-up data regarding EDS and/or HR-QOL; 3,090 patients were therefore included in the CPAP outcomes analysis. As expected, patients included in the CPAP outcomes analysis had slightly more severe disease than the entire baseline cohort in terms of symptoms, AHI and co morbidities (e-table 1).

5 e-table 2 shows the distribution of the 13 variables across the 5 OSA clusters in the entire baseline population. As shown in e-table 3, significant differences were observed between distinct OSA clusters regarding SES and sleep recording data. e-figure 1: Flow diagram of subjects during the study. IRSR, Institut de Recherche en Santé Respiratoire des Pays de la Loire; OSA, obstructive sleep apnoea; AHI, apnoea-hypopnoea index.

6 e-table 1: Comparison of the entire baseline population with the CPAP follow-up population Variables Entire baseline population (n=5,983) CPAP follow-up population (n=3,090) p value Age, years 60.1 (12.9) 60.9 (12.3) < Female, BMI, kg/m (6.7) 32.3 (6.6) < Epworth sleepiness 9.9 (5.0) 10.3 (5.0) < score QD2A depression score 3.7 (3.4) 3.8 (3.4) SF-36 energy/vitality 47.2 (20.7) 46.3 (20.7) score AHI 41.0 (20.4) 44.6 (20.4) < Comorbidities HTN, CVD, Diabetes, Results expressed as mean (standard deviation) unless otherwise indicated. BMI, body mass index; AHI, apnoea-hypopnoea index; HTN, hypertension; CVD, cardiovascular disease

7 e-table 2: Description of the five obstructive sleep apnea clusters in the entire baseline population (n=5,983) All (n=5,9 83) 1 (n=848 ) Cluste r 2 (n=90 0) 3 (n=1,0 90) 4 (n=1,9 19) 5 (n=1,2 27) Chi 2 value s Obesity, Age>65 years, ,44 8 Female, ,08 9 Complaint of insomnia, Loud snoring, Stopped breathing, Unrested upon waking, ,32 3 Headache upon waking, Depressive symptoms, , EDS, ,08 5 HTN, ,50 7 CVD, ,43 0 Diabetes, ,03 5 EDS, excessive daytime sleepiness; HTN, hypertension; CVD, cardiovascular disease *Chi 2 values corresponded to the sum of the squared difference between observed and expected data, divided by the expected data in all possible categories

8 e-table 3: Differences in socioeconomic status and sleep recordings data across the five obstructive sleep apnoea clusters (n=5,983) 1 (n=848) 2 (n=900) 3 (n=1,090) 4 (n=1,919) 5 (n=1,227) p value Socioeconomic status Married or < living as a couple, Left full-time < education < 18 years, Employment status Employed, < Retired, Other, Sleep recording data AHI, events (19.9) 46.2 (20.5) 41.4 (22.7) 37.9 (19.2) 42.5 (19.4) < Mean SaO (2.6) 91.6 (2.7) 92.5 (2.9) 92.9 (2.2) 91.7 (2.5) < ODI, < events -1 (22.2) (23.7) (26.2) (22.1) (22.0) Time with SaO 2 <90, 17.5 (23.3) 21.3 (22.1) 13.9 (20.8) 10.2 (16.6) 20.7 (22.9) < Total sleep time, min N3 sleep*, REM sleep*, Arousal index*, events (83.1) 22.8 (9.7) 17.1 (7.0) 29.9 (15.2) (74.0) 20.0 (9.9) 16.7 (7.0) 35.5 (18.8) (70.4) (75.8) (88.7) < (9.3) 21.2 (8.8) 22.0 (10.3) (7.4) 19.1 (6.9) 18.1 (7.0) < (17.0) 33.3 (16.8) 34.0 (17.1) AHI, apnea-hypopnea index; SaO 2, oxygen saturation; ODI, oxygen desaturation index; Data are expressed as mean (SD) or percentages; * data available for 2,103 patients

9 The distribution of the 13 variables across the 5 OSA clusters identified by LCA in the CPAP follow-up population is described in e-figure e-figure 2: Prevalence of each variable according to the clusters identified by Latent Class Analysis in patients include in the CPAP outcomes analysis (n=3,090). Each coloured line represents a variable with prevalence ranging from 0 (yellow) to 100 (red). Only slight although statistically significant differences were observed between clusters regarding CPAP adherence at 6 months with 75.8 to 85.5 of patients using CPAP at least 4 hours per night in clusters 3 and 5, respectively (e-table 4). Overall, 42.3 of patients met the criterion for success of CPAP treatment with marked differences between clusters. The lowest and highest rates of CPAP treatment success were observed in cluster 5 (25.7) and cluster 3 (57.6), respectively.

10 e-table 4: CPAP treatment outcomes across the five obstructive sleep apnoea clusters CPAP adherence Daily CPAP use, h Daily CPAP use 4h, Reduction in EDS*, Improvemen t of QOL**, CPAP treatment success 1 (n=455 ) Cluste r 2 (n=49 9) Cluste r 3 (n=61 5) 4 (n=905 ) Cluste r 5 (n=61 6) Whole (n=3,0 90) p value 5.8 (2.1) 5.9 (2.1) 5.5 (2.0) 5.6 (2.0) 6.0 (1.9) 5.7 (2.0) < < < < Data are expressed as mean (SD) or percentages; EDS, Excessive daytime sleepiness; QOL, quality of life * Decrease in Epworth score of at least 4 points in patients with baseline value 11 ** Increase of at least 7 points in the energy/vitality component score of the SF-36 questionnaire regardless of baseline Epworth score

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