Pregnancy prediction models and eSET criteria for IVF patients - do we need more information?

Purpose: The purpose of the present study was to evaluate statistical prediction models and simple allocation criteria, based on predictors for pregnancy, as tools to identify a good prognosis group in a possible eSET setting. Methods: A pregnancy prediction model based on logistic regression models was generated by analysis of 1675 DET treatment cycles. The model was evaluated and compared to simple eSET allocation criteria. Results: Embryo quality, patient age, and basal FSH were identified as significant predictors (at 5% significance level) of pregnancy. Although comparable to previously generated models, the predictive ability of the present model was relatively poor and practically similar to simple allocation criteria based on age and embryo quality. Conclusions: Existing prediction models, or simple allocation criteria, are limited in identifying good prognosis patients. Future studies of the applicability of improved pregnancy prediction models will need very comprehensive and detailed patient and embryo information.