A nomogram for the prediction of cerebrovascular disease among patients with brain necrosis after radiotherapy for nasopharyngeal carcinoma. (March 2019)

• Record Type: Journal Article
• Authors: Cai, Jinhua; Cheng, Jinping; Li, Honghong; Lin, Wei-Jye; Li, Yi; Zhuo, Xiaohuang; Huang, Xiaolong; Simone, Charles B.; Aronow, Wilbert S.; Chow, Edward L.W.; Tang, Yamei
• Is Part Of: Radiotherapy and oncology. Volume 132(2019)
• Page Start: 34
• Page End: 41
• Publication Date: 2019-03
• Subjects: ASCVD atherosclerotic cardiovascular disease -- CAS carotid stenosis -- CFS cerebrovascular disease-free survival -- CI confidence interval -- C-index concordance index -- CVD cerebrovascular disease -- DCA decision curve analysis -- IRB interval between radiotherapy and brain necrosis -- HDL high-density lipoprotein -- IMRT intensity-modulated radiation therapy -- IQR interquartile range -- NPC nasopharyngeal carcinoma -- TIA transient ischemic attack; Brain necrosis -- Radiotherapy -- Cerebrovascular disease -- Carotid stenosis -- Nomogram; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2018.11.008
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: A nomogram to predict cerebrovascular disease in brain necrosis after radiotherapy. The nomogram shows favorable discrimination and calibration. The nomogram is capable to stratify patients into high- and low-risk groups. This reliable and easy-to-use predictive tool may aid in clinical decision making. Abstract: Background and purpose: This study sought to develop and validate a nomogram to predict cerebrovascular disease (CVD) among patients with brain necrosis after radiotherapy for nasopharyngeal carcinoma (NPC). Materials and methods: A total of 346 eligible patients with brain necrosis after radiotherapy for NPC were divided into a training set ( n = 231) and a validation set ( n = 115). A multivariate Cox proportional hazards regression model was used to select the significant variables for CVD prediction in the training set. Then, a nomogram was developed based on the regression model. The performance of the nomogram was assessed with respect to discrimination and calibration. All patients were classified into high- or low-risk groups based on the risk scores derived from the nomogram. Moreover, a decision curve analysis was performed with the combined training and validation sets to evaluate the clinical usefulness of the nomogram. Results: Four significant predictors were identified: hypertension, statin treatment, serum level of high-density lipoprotein, and interval between radiotherapy and brain necrosis. The nomogram incorporating these four predictors showed favorable calibration and discrimination regarding the training set, with a C-index of 0.763 (95% CI, 0.694 to 0.832), which was confirmed using the validation set (C-index 0.768; 95% CI, 0.675 to 0.861). Furthermore, the nomogram successfully stratified patients into high- and low-risk groups. The decision curve indicated that our nomogram was clinically useful. Conclusion: The nomogram showed favorable predictive accuracy for CVD among patients with brain necrosis after radiotherapy for NPC and might aid in clinical decision making.