A nomogram to predict symptomatic epilepsy in patients with radiation-induced brain necrosis

Author:

Huang Xiaolong,Zhang Xiaoni,Wang Xicheng,Rong Xiaoming,Li Yi,Li Honghong,Jiang Jingru,Cai Jinhua,Zhuo Xiaohuang,Pi Yaxuan,Lin Jinpeng,Chua Melvin L.K.ORCID,Argyriou Andreas A.ORCID,Lattanzi Simona,Simone Charles B.,Glass Jon,Palmer Joshua D.,Chow Edward,Brown Paul D.,Yue Zongwei,Tang Yamei,

Abstract

ObjectiveTo develop and validate a nomogram to predict epilepsy in patients with radiation-induced brain necrosis (RN).MethodsThe nomogram was based on a retrospective analysis of 302 patients who were diagnosed with symptomatic RN from January 2005 to January 2016 in Sun Yat-sen Memorial Hospital using the Cox proportional hazards model. Discrimination of the nomogram was assessed by the concordance index (C index) and the calibration curve. The results were internally validated using bootstrap resampling and externally validated using 128 patients with RN from 2 additional hospitals.ResultsA total of 302 patients with RN with a median follow-up of 3.43 years (interquartile range 2.54–5.45) were included in the training cohort; 65 (21.5%) developed symptomatic epilepsy during follow-up. Seven variables remained significant predictors of epilepsy after multivariable analyses: MRI lesion volume, creatine phosphokinase, the maximum radiation dose to the temporal lobe, RN treatment, history of hypertension and/or diabetes, sex, and total cholesterol level. In the validation cohort, 28 out of 128 (21.9%) patients had epilepsy after RN within a median follow-up of 3.2 years. The nomogram showed comparable discrimination between the training and validation cohort (corrected C index 0.76 [training] vs 0.72 [95% confidence interval 0.62–0.81; validation]).ConclusionOur study developed an easily applied nomogram for the prediction of RN-related epilepsy in a large RN cohort.Classification of evidenceThis study provides Class III evidence that a nomogram predicts post-RN epilepsy.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Neurology (clinical)

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