We agree with Schoorel et al. that the area under the receiver–operating characteristics curve (AUC) for the model described in our paper is particularly high after inclusion of scar information. We were careful to state this in our paper: ‘The AUC for our model is perhaps surprisingly high. This may reflect the relatively small number of women in the study.’1. However, we also say in the paper that, even if we interpret this with caution, it suggests that the scar is a major factor in the behavior of the uterus during a trial of labor. We are unable to agree that it is not plausible that the morphology of the scar may be an important predictor of uterine behavior in labor. The main indications for repeat Cesarean section in the failed vaginal birth after Cesarean (VBAC) group in our paper were fetal distress and failure to progress. It is entirely possible that both these factors are exacerbated by poor scar healing, which in turn may be reflected in the morphological features of a scar on ultrasound. Furthermore, a poorly healed scar may impact on decidualization and subsequent placentation and be associated with a greater likelihood of fetal distress in labor. We investigated prospectively the changes in Cesarean section scar dimensions during pregnancy as well as the influence of previous VBAC on those changes2. Schoorel et al. are incorrect in their assertion that this paper contains an analysis relating scar features to the probability of a successful trial of VBAC. It does not. We do comment on residual myometrial thickness (RMT) in the small number of cases of scar rupture or dehiscence. This is because, after peer review of our paper, we were asked by the Editor of the Journal to insert some brief information on the RMT and delta RMT in cases of uterine rupture or dehiscence to give more clinical relevance to the paper, to which we agreed. However, an association between RMT and successful VBAC in the current study was not investigated prior to variable selection. It is also important to note that third-trimester sonographic measurements of the thickness of the lower uterine segment and scar features have been reported as a predictor of vaginal delivery3. Accordingly, this variable would be considered as a possible factor in any predictive model on the basis of expert knowledge and was the basis of our hypothesis when we planned the study. Hence, we used a priori variable selection based on knowledge, which is in agreement with contemporary methodological guidelines. Having published our data on interobserver variability, we are aware that measurements of RMT may impact on the performance of any model that uses this variable; to what extent this occurs will only become apparent when RMT is measured by other examiners4. We are pleased that Schoorel et al. agree with the emphasis we placed in our paper on the importance of external validation of prediction models, which is a vital step before considering the introduction of such models into clinical practice. As we state clearly in the paper: ‘It is important to highlight that whilst this model and approach show promise, external validation in different units and populations is needed before introduction into clinical practice.’ O. Naji†‡, L. Wynants§¶, A. Smith†, Y. Abdallah†‡, C. Stalder†, A. Sayasneh†‡, A. McIndoe†, S. Ghaem-Maghami*‡, S. Van Huffel§¶, B. Van Calster**, D. Timmerman** and T. Bourne†‡** †Obstetrics and Gynaecology Unit, Queen Charlotte's and Chelsea Hospital, Imperial College, London,UK; ‡Institute of Reproductive and Developmental Biology, Imperial College, London, UK; §Department of Electrical Engineering (ESAT-SCD), KU Leuven, Leuven, Belgium; ¶iMinds Future Health Department, KU Leuven–University of Leuven, Leuven, Belgium; **Department of Development and Regeneration, University Hospitals, KU Leuven, Leuven, Belgium *Correspondence. (e-mail: s.ghaem-maghami@imperial.ac.uk)
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