Validation of a Vaginal Birth After Cesarean Delivery Prediction Model Without Race and Ethnicity in Individuals With Two Prior Cesarean Deliveries

Abstract

Previous models for prediction of vaginal birth after cesarean (VBAC) relied on race and ethnicity, raising concern for bias. In response, the Maternal-Fetal Medicine Units Network (MFMU) created a new prediction model without race and ethnicity for individuals with one prior cesarean delivery. We performed a secondary analysis of the MFMU Cesarean Registry database to evaluate whether the MFMU VBAC prediction model without race and ethnicity could accurately predict VBAC for individuals with two prior cesarean deliveries. Overall, 353 individuals were included and 252 (71%) had VBAC. An area under the curve for the receiver operating curve of 0.74 (95% CI, 0.69–0.80) was reported for the predicted probabilities for VBAC, indicating that the model can be used for prediction of VBAC in this population.