A decision tree model for predicting live birth in FMR1 premutation carriers undergoing preimplantation genetic testing for monogenic/single gene defects.

Abstract Research question To determine the optimal patient selection for successful preimplantation genetic testing for women who are fragile X (FMR1) premutation carriers, using a decision tree analysis. This decision support tool enables a comprehensive study of a set of clinical parameters and the expected outcomes. Design A retrospective case–control study analyzing the results of 264 fresh and 21 frozen pre-implantation genetic testing for monogenic disorders (PGT-M) cycles in 64 FMR1 premutation carriers. The primary outcome was live birth per cycle start. The live birth rate was calculated for the ovarian stimulation cycle start. Fresh and frozen embryo transfers from the same cycle were included. Results Remarkably, the decision tree model showed that the number of cytosine guanine (CGG) repeats was only a moderate predictor for live birth, whereas an age younger than 36 was the best predictor for live birth, followed by a collection of 14 or more oocytes. These findings were supported by the results of the logistic regression, which found that only age and oocyte number were significantly associated with live birth. Conclusions The number of CGG repeats is a relatively poor predictor for live birth in PGT-M cycles. FMR1 premutation carriers are not different from non-carriers. Age is the best identifier of live birth, followed by the number of retrieved oocytes.