• Benjamin S Harris, R Phillips Heine, Jinyoung Park, Keturah R Faurot, Maeve K Hopkins, Andrew J Rivara, Hanna R Kemeny, Chad A Grotegut, and J Eric Jelovsek.
• Department of Obstetrics and Gynecology, Duke University Health System, Durham, NC. Electronic address: benjamin.harris@duke.edu.
• Am. J. Obstet. Gynecol. 2019 May 1; 220 (5): 492.e1-492.e7.

BackgroundThe use of trial of labor after cesarean delivery calculators in the prediction of successful vaginal birth after cesarean delivery gives physicians an evidence-based tool to assist with patient counseling and risk stratification. Before deployment of prediction models for routine care at an institutional level, it is recommended to test their performance initially in the institution's target population. This allows the institution to understand not only the overall accuracy of the model for the intended population but also to comprehend where the accuracy of the model is most limited when predicting across the range of predictions (calibration).ObjectiveThe purpose of this study was to compare 3 models that predict successful vaginal birth after cesarean delivery with the use of a single tertiary referral cohort before continuous model deployment in the electronic medical record.Study DesignAll cesarean births for failed trial of labor after cesarean delivery and successful vaginal birth after cesarean delivery at an academic health system between May 2013 and March 2016 were reviewed. Women with a history of 1 previous cesarean birth who underwent a trial of labor with a term (≥37 weeks gestation), cephalic, and singleton gestation were included. Women with antepartum intrauterine fetal death or fetal anomalies were excluded. The probability of successful vaginal birth after cesarean delivery was calculated with the use of 3 prediction models: Grobman 2007, Grobman 2009, and Metz 2013 and compared with actual vaginal birth after cesarean delivery success. Each model's performance was measured with the use of concordance indices, Brier scores, and calibration plots. Decision curve analysis identified the range of threshold probabilities for which the best prediction model would be of clinical value.ResultsFour hundred four women met the eligibility criteria. The observed rate of successful vaginal birth after cesarean delivery was 75% (305/404). Concordance indices were 0.717 (95% confidence interval, 0.659-0.778), 0.703 (95% confidence interval, 0.647-0.758), and 0.727 (95% confidence interval, 0.669-0.779), respectively. Brier scores were 0.172, 0.205, and 0.179, respectively. Calibration demonstrated that Grobman 2007 and Metz vaginal birth after cesarean delivery models were most accurate when predicted probabilities were >60% and were beneficial for counseling women who did not desire to have vaginal birth after cesarean delivery but had a predicted success rates of 60-90%. The models underpredicted actual probabilities when predicting success at <60%. The Grobman 2007 and Metz vaginal birth after cesarean delivery models provided greatest net benefit between threshold probabilities of 60-90% but did not provide a net benefit with lower predicted probabilities of success compared with a strategy of recommending vaginal birth after cesarean delivery for all women .ConclusionWhen 3 commonly used vaginal birth after cesarean delivery prediction models are compared in the same population, there are differences in performance that may affect an institution's choice of which model to use.Copyright © 2019 Elsevier Inc. All rights reserved.

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