Journal Article

Analytic Strategies to Adjust Confounding using Exposure Propensity Scores and Disease Risk Scores: Nonsteroidal Antiinflammatory Drugs and Short-term Mortality in the Elderly

Til Stürmer, Sebastian Schneeweiss, M. Alan Brookhart, Kenneth J. Rothman, Jerry Avorn and Robert J. Glynn

in American Journal of Epidemiology

Published on behalf of Johns Hopkins Bloomberg School of Public Health

Volume 161, issue 9, pages 891-898
Published in print May 2005 | ISSN: 0002-9262
Published online May 2005 | e-ISSN: 1476-6256 | DOI: http://dx.doi.org/10.1093/aje/kwi106
Analytic Strategies to Adjust Confounding using Exposure Propensity Scores and Disease Risk Scores: Nonsteroidal Antiinflammatory Drugs and Short-term Mortality in the Elderly

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Little is known about optimal application and behavior of exposure propensity scores (EPS) in small studies. In a cohort of 103,133 elderly Medicaid beneficiaries in New Jersey, the effect of nonsteroidal antiinflammatory drug use on 1-year all-cause mortality was assessed (1995–1997) based on the assumption that there is no protective effect and that the preponderance of any observed effect would be confounded. To study the comparative behavior of EPS, disease risk scores, and “conventional” disease models, the authors randomly resampled 1,000 subcohorts of 10,000, 1,000, and 500 persons. The number of variables was limited in disease models, but not EPS and disease risk scores. Estimated EPS were used to adjust for confounding by matching, inverse probability of treatment weighting, stratification, and modeling. The crude rate ratio of death was 0.68 for users of nonsteroidal antiinflammatory drugs. “Conventional” adjustment resulted in a rate ratio of 0.80 (95% confidence interval: 0.77, 0.84). The rate ratio closest to 1 (0.85) was achieved by inverse probability of treatment weighting (95% confidence interval: 0.82, 0.88). With decreasing study size, estimates remained further from the null value, which was most pronounced for inverse probability of treatment weighting (n = 500: rate ratio = 0.72, 95% confidence interval: 0.26, 1.68). In this setting, analytic strategies using EPS or disease risk scores were not generally superior to “conventional” models. Various ways to use EPS and disease risk scores behaved differently with smaller study size.

Keywords: anti-inflammatory agents, non-steroidal; bias (epidemiology); cohort studies; confounding factors (epidemiology); epidemiologic methods; research design; DRS, disease risk score; EPS, exposure propensity score; IPTW, inverse probability of treatment weighting; NSAID, nonsteroidal antiinflammatory drug

Journal Article.  5181 words. 

Subjects: Public Health and Epidemiology

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