Performance of time-dependent propensity scores: a pharmacoepidemiology case study

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Pharmacoepidemiologic studies of acute effects of episodic exposures often must control for many time-dependent confounders. Marginal structural models permit this and provide unbiased estimates when confounders are on the causal pathway. However, if causal pathway confounding is minimal, analyses with time-dependent propensity scores, calculated for time periods defined by individual drug prescriptions, may have better efficiency. We justify time-dependent propensity scores and compare the performance of these methods in a case study from a previous investigation of the risk of medication toxicity death in current users of propoxyphene and hydrocodone, with both substantial time-dependent confounding and a large number of covariates.


The cohort included Tennessee Medicaid enrollees who filled a qualifying study opioid prescription between 1992 and 2007. We identified 22 time-dependent covariates that accounted for most of the confounding in the original study. We compared analyses with all covariates in the regression model with those based on time-dependent propensity scores and those from marginal structural models.


We identified 489,008 persons with 1,771,295 propoxyphene and 4,088,754 hydrocodone prescriptions. The unadjusted hazard ratio (propoxyphene : hydrocodone) was 0.70 (95%CI, 0.46–1.07). Estimates from inclusion of all covariates in the model, time-dependent propensity score analysis with inverse probability of treatment weighting, and marginal structural models were 1.63 (1.04–2.57), 1.65 (1.01–2.72), and 1.64 (0.83–3.27), respectively. Findings varied little with use of alternative propensity score methods, time origin, or techniques for marginal structural model estimation.


Time-dependent propensity scores may be useful for pharmacoepidemiologic studies with time-varying exposures when causal pathway confounding is limited. Copyright © 2014 John Wiley & Sons, Ltd.

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