Abstract
High-dimensional propensity score (hd-PS) adjustment has been proposed as a tool to improve control for confounding in pharmacoepidemiological studies using longitudinal claims databases. We investigated whether hd-PS matching improved confounding by indication in a study of Cox-2 inhibitors (coxibs) and traditional nonsteroidal anti-inflammatory drugs (tNSAIDs) and their association with the risk of upper gastrointestinal complications (UGIC). In a cohort study of new users of coxibs and tNSAIDs we compared the effectiveness of these drugs to reduce UGIC using hd-PS matching and conventional propensity score (PS) matching in the German Pharmacoepidemiological Research Database. The unadjusted rate ratio (RR) of UGIC for coxib users versus tNSAID users was 1.21 [95 % confidence interval (CI) 0.91-1.61]. The conventional PS matched cohort based on 79 investigator-identified covariates resulted in a RR of 0.84 (0.56-1.26). The use of the hd-PS algorithm based on 900 empirical covariates further decreased the RR to 0.62 (0.43-0.91). A comparison of hd-PS matching versus conventional PS matching resulted in improved point estimates for studying an intended treatment effect of coxibs versus tNSAIDs when benchmarked against results from randomized controlled trials.
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