Use of Propensity Score Technique to Account for Exposure-Related Covariates: An Example and Lesson

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Abstract

Background:

In observational research, propensity score techniques can be used to account for baseline differences between compared therapies. Although propensity scores are used increasingly often, their limitations in settings without complete data may not be recognized.

Objectives:

We sought to evaluate the ability of propensity score matching to mitigate confounding by indication in an observational study of the effect of statin therapy on acute myocardial infarction (AMI). Matching was performed at random, and with propensity scores that incorporated a reduced or expanded set of variables.

Research Design/Subjects:

This was a propensity score matched cohort study using members of a health insurer database.

Measures:

Exposure to statin therapy was assessed at the beginning of follow-up with all cohort members being statin initiators or noninitiators, and the outcome of AMI was identified on the basis of claims codes.

Results:

Matching on the basis of the propensity score provided results that are similar in magnitude to randomized clinical trials, suggesting that confounding was mitigated. However, matching on a propensity score created on a reduced set of variables yielded a result that suggested no effect of statin therapy, and demonstrated substantial imbalance on some variables that were not part of the propensity score.

Conclusions:

Propensity score matching can balance with respect to variables not explicitly included in the score, but external data are required to evaluate this.

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