Epidemiology
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Adjusting for large numbers of covariates ascertained from patients' health care claims data may improve control of confounding, as these variables may collectively be proxies for unobserved factors. Here, we develop and test an algorithm that empirically identifies candidate covariates, prioritizes covariates, and integrates them into a propensity-score-based confounder adjustment model. ⋯ In typical pharmacoepidemiologic studies, the proposed high-dimensional propensity score resulted in improved effect estimates compared with adjustment limited to predefined covariates, when benchmarked against results expected from randomized trials.
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Oseltamivir is a neuraminidase inhibitor that inhibits influenza virus proliferation, and is used as an antiviral drug against influenza A and B viruses. Recently, concerns have been raised about hallucinations, delirium, and abnormal activity after administration of oseltamivir for treatment of infection with influenza virus. A large epidemiologic study was conducted in Japan in the winter of 2006-2007 to assess the relationship between oseltamivir intake and adverse behaviors, and an interim report was released on 10 July 2008. ⋯ However, the analytic method used in the study was flawed. A correct analysis (based on person-time) shows a rate ratio of 1.57 (95% confidence interval = 1.34-1.83). This example clearly illustrates the importance of person-time in the analysis of cohort studies.