[Propensity score: A credible alternative to randomization?]

In clinical research, the reference method to evaluate treatment benefit without bias is the randomized trial. Unfortunately, it is not always possible to realize one, as for example in surgery or for particular observational studies. In these cases, Rosenbaum and Rubin introduced in 1983 a new methodology: the calculation of a propensity score. When several treatments are compared, this calculation enables to take into account confusion bias using a score that synthesizes the influence on treatment choice of clinical parameters evaluated before. This article describes how to build this score, to estimate its validity, and how to use it: as a new variable into a multivariate analysis, as a matching criterion, or as a stratification parameter. Examples are given to illustrate each case and point out the limitations of such a methodology. This approach, although innovative and useful, cannot reach the level of evidence of randomized clinical trials: simulations have demonstrated this fact in several situations. On the other hand, it can be compared to standard multivariate analysis which permits in a non-randomized context, to limit evaluation bias of treatments by adjusting on potential confusion factors. Some guidelines are given in the last chapter to help researchers decide whether to use a propensity score or a standard multivariate analysis.