Jinpeng Lin, Yamei Tang, Zongwei Yue, Paul D Brown, Edward Chow, Joshua D Palmer, Jon Glass, Charles B Simone, Simona Lattanzi, Andreas A Argyriou, Melvin L K Chua, Xiaolong Huang, Yaxuan Pi, Xiaohuang Zhuo, Jinhua Cai, Jingru Jiang, Honghong Li, Yi Li, Xiaoming Rong, Xicheng Wang, Xiaoni Zhang
Journal: Neurology 2020;95(10):e1392-e1403
PMID: 32631922
OBJECTIVE
To develop and validate a nomogram to predict epilepsy in patients with radiation-induced brain necrosis (RN).
METHODS
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.
RESULTS
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]).
CONCLUSION
Our study developed an easily applied nomogram for the prediction of RN-related epilepsy in a large RN cohort.
CLASSIFICATION OF EVIDENCE
This study provides Class III evidence that a nomogram predicts post-RN epilepsy.
© 2020 American Academy of Neurology.
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