Empirical evidence of bias in infertility research: overestimation of treatment effect in crossover trials using pregnancy as the outcome measure

Abstract

Objective: To determine whether crossover trials with simple pooling of data over different study periods leads to a different estimate of treatment effect compared with parallel group trials in infertility research using pregnancy as the outcome measure.

Design: An observational study using nine overviews that included trials with both crossover and parallel group designs. These overviews comprised 17 crossover and 17 parallel group trials. In total, there were 5,291 outcomes including 775 pregnancies. The association between study design and treatment effect estimate was analyzed using multiple logistic regression, controlling for differences in the therapeutic interventions and variations in the methodological quality of the trials.

Setting: Infertile patients in an academic research environment.

Patients: Infertile patients undergoing treatment efficacy evaluation in controlled trials.

Interventions: Random allocation to a variety of treatments including clomiphene citrate, hCG, IUI, tamoxifen, and bromocriptine.

Main outcome measure: Estimate of bias between study designs, based on the interaction of study design and treatment in the logistic regression model.

Results: Crossover trials produced a larger average estimate of treatment effect compared with trials with a parallel group design, overestimating the odds ratio by 74% (95% confidence interval, 2% to 197%).

Conclusion: The use of a crossover design for evaluating infertility treatments with outcomes that prevent patients from completing later phases of the trial should be avoided because it leads to exaggerated estimates of treatment effect and may result in erroneous inferences and clinical decisions. Furthermore, the type of study design should be taken into account when assessing the methodological quality of therapy trials in infertility.