BACKGROUND:

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.

METHODS:

We systematically reviewed the literature on marginal structural models since 2000.

RESULTS:

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.

CONCLUSIONS:

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.