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

PURPOSE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSIONS: Time-dependent propensity scores may be useful for pharmacoepidemiologic studies with time-varying exposures when causal pathway confounding is limited.