The propensity score in the analysis of therapeutic studies

A method for reducing bias in observational studies proposed by ROSENBAUM and RUBIN (1983, 1984) is discussed with a view to applications in studies designed to compare two treatments. The data are stratified on a function of covariates, called the propensity score. The propensity score is the conditional probability of receiving a specific treatment given a set of observed covariates. Some insight into how this kind of stratification works in theory is given. Within strata, the treatment groups are comparable with respect to the distribution of covariates incorporated into the score: hence a corresponding stratified analysis can be considered. The method is different from other strategies in that the subclasses are not intended to comprise patients with similar prognosis. In practice, estimated grouped scores are used. Problems concerning the interpretation of the proposed stratified approach are illustrated by an application in oncology, and the results are compared to those from an analysis in a standard regression model.