Proton pump inhibitors and risk of all-cause and cause-specific mortality: A cohort study.

AIM: To investigate the association between proton pump inhibitors (PPIs) and both all-cause and cause-specific mortality. METHODS: We conducted a cohort study using the UK Clinical Practice Research Datalink GOLD database. We compared 733 885 new users of PPIs to 124 410 new users of H2 receptor antagonists (H2Ras). In a secondary analysis we compared 689 602 PPI new users to 1 361 245 nonusers of acid suppression therapy matched on age, sex and calendar year. Hazard ratios for all-cause and cause-specific mortality were estimated using propensity score (PS) weighted Cox models. RESULTS: PPI prescription was associated with increased risk of all-cause mortality, with hazard ratios decreasing considerably by increasing adjustment (unadjusted hazard ratio [HR] 1.65, 95% confidence interval [CI] 1.62-1.69; PS-weighted HR 1.38, 95% CI 1.33-1.44; high-dimensional PS-weighted HR 1.31, 95% CI 1.26-1.37). Short-term associations were observed with mortality from causes where a causal short-term association is unexpected (eg, lung cancer mortality: PS-weighted HR at 6 months 1.77, 95% CI 1.39-2.25). Adjusted hazard ratios were substantially higher when compared to nonusers (PS-weighted HR all-cause mortality 1.96, 95% CI 1.94-1.99) rather than H2RA users. CONCLUSIONS: PPI prescription was strongly associated with all-cause and cause-specific mortality. However, the change in hazard ratios (a) by increasing adjustment and (b) between comparator groups indicates that residual confounding is likely to explain the association between poor health outcomes and PPI use, and fully accounting for this using observational data may not be possible.

Application of High-Dimensional Propensity Score Methods to the National Health and Aging Trends Study.

BACKGROUND: High-dimensional propensity scoring (HDPS) is a method for empirically identifying potential confounders within large healthcare databases such as administrative claims data. However, this method has not yet been applied to large national health surveys such as the National Health and Aging Trends Study (NHATS), an ongoing nationally representative survey of older adults in the United States and important resource in gerontology research. METHODS: In this Research Practice article, we present an overview of HDPS and describe the specific data transformation steps and analytic considerations needed to apply it to national health surveys. We applied HDPS within NHATS to investigate the association between self-reported visual difficulty and incident dementia, comparing HDPS to conventional confounder selection methods. RESULTS: Among 7 207 dementia-free NHATS Wave 1 respondents, 528 (7.3%) had self-reported visual difficulty. In an unadjusted discrete time proportional hazards model accounting for the complex survey design of NHATS, self-reported visual difficulty was strongly associated with incident dementia (odds ratio [OR] 2.34, 95% confidence interval [CI]: 1.95-2.81). After adjustment for standard investigator-selected covariates via inverse probability weighting, the magnitude of this association decreased, but evidence of an association remained (OR 1.44, 95% CI: 1.11-1.85). Adding 75 HDPS-prioritized variables to the investigator-selected propensity score model resulted in further attenuation of the association between visual impairment and dementia (OR 0.94, 95% CI: 0.70-1.23). CONCLUSIONS: HDPS can be successfully applied to national health surveys such as NHATS and may improve confounder adjustment. We hope developing this framework will encourage future consideration of HDPS in this setting.