From the Department of Neurology Bioland Laboratory (X.H., X. Zhang, X.R., Y.L., H.L., J.J., J.C., X. Zhuo, X.P., J.L., Z.Y., Y.T.) and Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center (Y.T.), Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University; Guangdong Province Key Laboratory of Brain Function and Disease (Y.T.), Zhongshan School of Medicine, Sun Yat-Sen University; Department of Oncology (X.W.), The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China; Division of Radiation Oncology and Medical Sciences (M.L.K.C.), National Cancer Centre Singapore; Oncology Academic Programme (M.L.K.C.), Duke-NUS Medical School, Singapore; Department of Neurology (A.A.A.), Saint Andrew's State General Hospital of Patras, Greece; Neurological Clinic, Department of Experimental and Clinical Medicine (S.L.), Marche Polytechnic University, Italy; New York Proton Center (C.B.S.), New York; Thomas Jefferson University (J.G.), Philadelphia, PA; Departments of Radiation Oncology (J.D.P.) and Neurosurgery (J.D.P.), The James Cancer Hospital at The Ohio State University Comprehensive Cancer Center, Columbus; Sunnybrook Health Sciences Centre (E.C.), University of Toronto, Canada; and Radiation Oncology (P.D.B.), Mayo Clinic, Rochester, MN.
Neurology. 2020 Sep 8;95(10):e1392-e1403. doi: 10.1212/WNL.0000000000010190. Epub 2020 Jul 6.
To develop and validate a nomogram to predict epilepsy in patients with radiation-induced brain necrosis (RN).
The 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 ( 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.
A 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 index 0.76 [training] vs 0.72 [95% confidence interval 0.62-0.81; validation]).
Our study developed an easily applied nomogram for the prediction of RN-related epilepsy in a large RN cohort.
This study provides Class III evidence that a nomogram predicts post-RN epilepsy.
开发并验证一种列线图，以预测放射性脑坏死（RN）患者的癫痫发作。
该列线图基于 2005 年 1 月至 2016 年 1 月期间在中山大学孙逸仙纪念医院因症状性 RN 而诊断的 302 例患者的回顾性分析，采用 Cox 比例风险模型。通过一致性指数（index）和校准曲线来评估列线图的区分度。通过自举重采样对内进行验证，通过来自另外 2 家医院的 128 例 RN 患者进行外部验证。
共纳入 302 例 RN 患者，中位随访时间为 3.43 年（四分位间距 2.54-5.45），在训练队列中；65 例（21.5%）在随访期间发生症状性癫痫。多变量分析后，有 7 个变量仍然是癫痫的显著预测因素：MRI 病变体积、肌酸磷酸激酶、颞叶最大辐射剂量、RN 治疗、高血压和/或糖尿病史、性别和总胆固醇水平。在验证队列中，128 例患者中有 28 例（21.9%）在 RN 后中位随访 3.2 年内发生癫痫。列线图在训练组和验证组之间显示出相当的区分度（校正 index 0.76[训练]与 0.72[95%置信区间 0.62-0.81；验证]）。
本研究在大型 RN 队列中开发了一种易于应用的列线图，用于预测 RN 相关癫痫。
本研究提供了 III 级证据，表明列线图预测 RN 后癫痫。
