We previously developed basic and extended models to predict inferior alveolar nerve injuries (IANI) after lower third molar (LM3) removal based on cone-beam computed tomography (CBCT) images. Although these models comprised predictors, including increased age and inferior alveolar canal-related CBCT factors, external validations were lacking. Therefore, this study externally validated these models and compared them with other related models based on their performance. Original and newly validated samples included patients who underwent LM3 removal following CBCT. Subsequently, 39 and 25 patients with IANI, then 457 and 295 randomly selected patients without IANI were chosen of the observed 1573 and 1052 patients, respectively. CBCT- and panoramic radiograph (PAN)-featured models were validated. Then, models' discrimination and calibration abilities were assessed using C-statistics and calibration plots, respectively. Brier scores were also quantified, after which logistic recalibration was achieved to optimize calibration, and a risk calculator was developed. During the external validation, the extended model exhibited the best C-statistic (0.822) and Brier score (0.064), whereas two CBCT- and two PAN-featured models showed lower performances with C-statistics (0.764, 0.706, 0.584, and 0.627) and Brier scores (0.069, 0.074, 0.075, and 0.072). Besides, all models showed a tendency to overpredict its high-risk range. However, recalibration of the extended model resulted in excellent calibration performance. CBCT-featured models, especially the extended model, conclusively showed a superior predictive performance to PAN models. Therefore, the risk calculator on the extended CBCT model is proposed to be a clinical decision-aid tool that preoperatively predicts IANI risk.
Keywords: Cone-beam computed tomography; Inferior alveolar canal; Prediction model; Risk calculator; Third molar surgery; Tooth extraction.
© 2022. The Author(s), under exclusive licence to The Society of The Nippon Dental University.