Abstract / Summary
Predictive models for estimating successful trial of labor after cesarean delivery (TOLAC) have been developed as tools to support decision-making regarding the choice of TOLAC. This study evaluated the predictive accuracy of an early pregnancy model with that of a delivery admission model for estimating successful initial TOLAC, and explored a simplified delivery admission model. A retrospective cohort study conducted in a single-center in Japan of women with ≥ 1 prior cesarean delivery (CD) between January 2010 and December 2020. Predictive models were developed by adding a known factor associated with vaginal birth after cesarean delivery at the time of admission for delivery, including diabetes mellitus, gestational diabetes mellitus, hypertensive disorders of pregnancy, gestational age, and Bishop score, to an existing early pregnancy model. Receiver operating characteristic (ROC) curves were generated for the four models based on Grobman’s existing models. Internal validation of the prediction model was performed using the bootstrap method. Among 134 cases eligible for initial TOLAC ≥ 37 weeks of gestation, 120 women selected TOLAC, and 14 women underwent elective repeat CD. The areas under the ROCs (AUCs) for Grobman’s early pregnancy and delivery admission models, based on our original dataset, were 0.640 (95% confidence interval [CI]: 0.474–0.805) and 0.836 (95% CI: 0.720–0.951), respectively ( p <.01). The AUCs for the model created by adding the Bishop score at the time of admission for delivery to the existing early pregnancy model was 0.839 (95% CI: 0.753–0.926) and there was a significant difference between Grobman’s early pregnancy and the created models ( p = .0248). The bootstrap optimism-corrected ROC-AUC was 0.758 for this created model. Incorporating the Bishop score at admission for delivery with baseline information obtained during early pregnancy suggests potential utility for predicting successful initial TOLAC. Further development of this prediction model using sufficiently large cohorts, along with external validation, is warranted to confirm its robustness and generalizability. The study was retrospectively registered by the institutional review board of Maizuru Kyosai Hospital Committee (approval number 2025003).