Establishment And Validation Of A Recurrence Risk Prediction Model For Refractory Epilepsy After Lobotomy

Objective: To explore the related factors of epilepsy recurrence after lobectomy in patients with refractory epilepsy,To establish a nomogram prediction model for postoperative recurrence risk and verify its reliability.Method: The clinical data of 382 patients with intractable epilepsy who underwent lobectomy at the First Affiliated Hospital of Xinjiang Medical University from January 2012 to December 2021 were retrospectively included in this study,They were randomly divided into modeling group(268 cases)and validation group(114 cases),According to the postoperative recurrence,the patients were divided into recurrence group and non-recurrence group,Univariate and multivariate Logistic regression analysis were used to screen the related factors affecting the recurrence of refractory epilepsy after lobectomy in the modeling group,The nomogram prediction model was drawn,the discrimination was evaluated by the consistency index(C-index),the accuracy was evaluated by the calibration chart,the net benefit rate was evaluated by the decision curve(DCA curve),and the validation group was used for verification.Result: Follow-up results in the modeling group,85 cases had recurrence,183 cases had no recurrence,80 cases had no recurrence and 34 cases had recurrence in the validation group.Multivariate Logistic regression analysis showed that the age at seizure onset,the consistency of MRI,PET-CT,EEG and surgical site,and surgical site were important factors affecting the postoperative recurrence of refractory epilepsy.The C-indexes of the prediction model in the modeling group and the validation group were 0.902 and 0.884,respectively.The model had good discrimination,the calibration curves of the two groups were actually fitted to the ideal curve,with high accuracy,and the decision curve showed a good benefit rate.Conclussion: The prediction model of recurrence risk after lobectomy for refractory epilepsy established in this study can accurately predict the prognosis of patients after surgery,and can provide reference for the treatment and prognosis of patients according to the clinical data of patients.