Differences Between Marginal Structural Models and Conventional Models in Their Exposure Effect Estimates

Abstract

Marginal structural models were developed to address time-varying confounding in nonrandomized exposure effect studies. It is unclear how estimates from marginal structural models and conventional models might differ in real settings. We systematically reviewed the literature on marginal structural models since 2000. Data to compare marginal structural models and conventional models were obtained from 65 papers reporting 164 exposure-outcome associations. In 58 (40%), estimates differed by at least 20%, and in 18 (11%), the 2 techniques resulted in estimates with opposite interpretations. In 88 papers, marginal structural models were used to analyze real data; only 53 (60%) papers reported the use of stabilized inverse-probability weights and only 28 (32%) reported that they verified that the mean of the stabilized inverse-probability weights was close to 1.0. We found important differences in results from marginal structural models and from conventional models in real studies. Furthermore, reporting of marginal structural models can be improved.