Nomogram for Predicting Facial Nerve Outcomes After Surgical Resection of Vestibular Schwannoma

Abstract

ObjectiveThe facial nerve (FN) outcomes after vestibular schwannoma surgery seriously affect the social psychology and quality of life of patients. More and more attention has been paid to the protection of FN function. This study aimed to identify significant prognostic factors for FN outcomes after vestibular schwannoma surgery and create a new nomogram for predicting the rates of poor FN outcomes.MethodsData from patients who had undergone operations for vestibular schwannoma between 2015 and 2020 were retrieved retrospectively and patients were divided into good and poor FN outcomes groups according to postoperative nerve function. The nomogram for predicting the risk of poor FN outcomes was constructed from the results of the univariate logistic regression analysis and the multivariate logistic regression analysis of the influencing factors for FN outcomes after surgical resection of vestibular schwannoma.ResultsA total of 392 participants were enrolled. The univariate logistic regression analysis revealed that age, tumor size, cystic features of tumors, cerebrospinal fluid (CSF) cleft sign, tumor adhesion to the nerve, learning curve, and FN position were statistically significant. The multivariate logistic regression analysis showed that age, tumor size, cystic features of tumors, CSF cleft sign, tumor adhesion to the nerve, learning curve, and FN position were independent factors. The nomogram model was constructed according to these indicators. At the last follow-up examination, a good FN outcome was observed in 342 patients (87.2%) and only 50 patients (12.8%) was presented with poor FN function. Application of the nomogram in the validation cohort still gave good discrimination [area under the curve (AUC), 0.806 (95% CI, 0.752–0.861)] and good calibration.ConclusionThis study has presented a reliable and valuable nomogram that can accurately predict the occurrence of poor FN outcomes after surgery in patients. This tool is easy to use and could assist doctors in establishing clinical decision-making for individual patients.