Obstructive Sleep Apnea on the I have no disclosures. Job: A 2-Way - PDF document

3/10/18 Disclosures Obstructive Sleep Apnea on the • I have no disclosures. Job: A 2-Way Street Daniel Schwartz, MA MSc Emerging and Re-emerging Occupational and Environmental Exposure and Disease March 10 2018 Roadmap Obstructive Sleep Apnea and Occupation • Involves a decrease or stoppage of airflow despite ongoing efforts to • Occupation as a Risk Factor for OSA, Motivations and Research breathe during sleep. Questions • Well-defined risk factors – BMI, smoking, alcohol – each of which have • Understanding Meta-Analysis occupational associations. • Stealth disease that can go undetected; high prevalence, probably under • Meta-Prevalence of OSA in Commercial Drivers reported • Meta-Analysis of Association Between Organic Solvent Exposure and • 4% in middle-aged men • 2% in middle aged women OSA • Research objectives • Limitations, Sources of Bias, and Discussion 1. Provide quantitative estimates of risk and association between occupational factors and OSA • Questions 2. Provide synthesis of the occupational literature on OSA, including the risks of commercial driving, and risks related to organic solvent exposure. 1

3/10/18 What is meta-analysis? Fixed Effects Model • Set of quantitative, statistical • Assumes all study estimates are of a single underlying effect. procedures used to systematically aggregate and combine the results of • Observed differences in measured effects are generated due to previous research. sampling error. • Can increase statistical power and precision in measuring a treatment • Better terminology – “common effect” model. effect. • With an infinitely large sample for all studies, between-study • A means of identifying data gaps, and differences would disappear. exploring sources of heterogeneity from multiple sources. • Heterogeneity (I 2 ) statistic • Applicable to both • Measures the % variability due to between-study variability rather than observational/epidemiological data, within-study sampling error. and trial data. Riley, 2011 http://library.downstate.edu/EBM2/2700.htm Invoking a Fixed Effects Model Fixed Effects Model Assumptions Heterogeneity test I 2 STUDY 3 STUDY 1 STUDY 2 Significant? If NOT data are more consistent with fixed effects model. STUDY 1 STUDY 2 STUDY 3 2

3/10/18 Assigning study weights in a fixed effects model Random Effects Model • Assumes the true treatment/exposure effect is different from study to study. • Inverse variance method • Pooled estimates capture the average treatment effect. STUDY 1 STUDY 2 STUDY 3 • I.e., larger, more precise • Accounts for between-study differences in measurement AND error estimates receive greater due to chance. Even if samples are infinitely large (eliminating weight variability due to chance), the observed study effects would vary because of real differences in treatment/exposure effects . • Default model when large heterogeneity exists (i.e., high I 2 ) between studies, and corresponding CI will be wider, i.e., claims of significance are more conservative. Weight i = 1/(standard error) 2 Bigby, 2014 Riley, 2011 FIXED EFFECTS MODEL RANDOM EFFECTS MODEL Study weighting in a random effects model Study estimates measure a common Study estimates measure different underlying treatment effect. Pooled estimate treatment effects ; pooled estimate estimates one single effect. estimates the average of these effects . OVERALL MEAN OVERALL MEAN • Inverse variance method • Within-study variance • Between-study from the overall treatment/exposure effect STUDY 2 mean STUDY 1 STUDY 3 σ STUDY 1 σ STUDY 2 σ STUDY 3 σ STUDY 1 σ STUDY 2 σ STUDY 3 Sources of variability – within-study error Sources of variability - within- and between- Weight i = 1/(T 2 + standard error i2 ) study error Weight i = 1/(T 2 + standard error i2 ) Weight i = 1/(standard error i ) 2 Bigby, 2014 3

3/10/18 Commercial Driver Meta-Prevalence Analysis Spectrum of Obstructive Sleep Apnea • Embase/PubMed query à June 2016 “Drivers” AND “sleep” AND “apnea” • • “Commercial” AND “driver” AND “sleep” AND “apnea” Apneas • Major inclusion criteria • Polysomnography-confirmed OSA • Major exclusion criteria Respiratory effort Hypopneas • OSA defined by paper survey of symptoms related arousals • Prevalence estimates based on pre-screened populations selecting for symptomatic patients • Case reports, conference papers, abstracts 12-channel Polysomnography Apnea-Hypopnea Index (AHI) • A measure of OSA severity using 12-channel polysomnography. • Count of the average # apneas + # hypopneas per hour • Apnea = complete cessation of airflow during sleep >= 10 s • Hypopnea = reduction in airflow, variably defined • AHI is a reproducible measurement of OSA severity , and is predictive of cardiovascular risk • Hypopneas without apneas lead to similar expression of OSA, but are harder to measure and defined differently • AASM 2001 • Recommended - Abnormal respiratory event >= 10 sec with >=30% reduction of airflow AND >=4% oxygen desaturation. • Alternative - >=50% reduction in nasal pressure signal excursions AND associated with >=3% desaturation or arousal • Sleep Heart Health Study – stricter cut-off for desaturation >=4% http://healthysleep.med.harvard.edu/sleep-apnea/diagnosing-osa/testing 4

3/10/18 AHI is Predictive of Cardiovascular Risk Commercial Driver Meta-Prevalence Analysis • Sleep Heart Health Study • 18 full-text articles eligible • Graded association between AHI and HTN >140/90 • Defined OSA cut-offs • AHI >5 mild disease • AHI >15 moderate-severe • Study size range from N = 32 to N = 2342 • High heterogeneity warranted use of a random effects model Even mild OSA is associated with a significantly elevated risk of hypertension after adjustments for relevant confounder variables Nieto et al., 2000 Schwartz et al 2017 There is a significant burden of even mild OSA amongst the commercial driver Commercial Drivers – Pooled Prevalence population AHI>5 AHI>15 AHI 5-14.9 ~ 28.6% Other pooled estimates among the adult male population, mild OSA AHI>5 è 22% 41% (95% CI 26-56%) 15% (95% CI 12-19%) (Franklin and Lindberg, 2015) Nieto et al., 2000 Schwartz et al 2017 5

3/10/18 Solvent Exposure and OSA Meta-Analysis Solvent Exposure and OSA Meta-Analysis • Meta-analysis to determine summary relative risk rather than • 541 abstracts screened; 7 full-text papers eligible. prevalence. • All bibliography title-reviewed leading to • Similar search strategy as earlier à “occupational AND exposure AND inclusion of 1 additional article. sleep AND apnea” • 8 full-text articles meeting criteria. • Confounder adjusted and matched results • Major inclusion criteria selected over unadjusted. • Summaries of risk including relative risk (RR), odds ratio (OR), standardized • Age incidence ratios (SIR) with respect to solvent exposure and OSA risk. • BMI • Smoking • Risk estimates for occupations characterized by solvent exposure (dry • Sex cleaning, painting, print shop work, etc). • High heterogeneity prompting use of • OSA definable by sleep study, or ICD-based diagnostic code of OSA. random effects model. • Major exclusion criteria • Diverse methods of OSA definition; diverse study designs including case-control, and • Abstracts, reviews, commentaries, case reports population-based designs . Solvent Exposure and OSA Meta-Analysis Random Effect Summary Relative Risk 2.38 (95% CI 0.89 – 6.32) Heterogeneity statistic I 2 93.9% Schwartz et al 2017 6