Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China.
Medical Research Center of Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China.
Radiother Oncol. 2019 Mar;132:34-41. doi: 10.1016/j.radonc.2018.11.008. Epub 2018 Dec 21.
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).
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.
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.
The nomogram showed favorable predictive accuracy for CVD among patients with brain necrosis after radiotherapy for NPC and might aid in clinical decision making.
本研究旨在开发并验证一个列线图，以预测鼻咽癌（NPC）放射治疗后脑坏死患者的脑血管疾病（CVD）。
共纳入 346 例符合条件的 NPC 放射治疗后脑坏死患者，分为训练集（n=231）和验证集（n=115）。采用多变量 Cox 比例风险回归模型在训练集中筛选出 CVD 预测的显著变量。然后，基于回归模型建立列线图。采用鉴别度和校准度评估列线图的性能。根据列线图得出的风险评分，所有患者分为高风险或低风险组。此外，采用训练集和验证集联合进行决策曲线分析，以评估列线图的临床实用性。
确定了 4 个显著预测因子：高血压、他汀类药物治疗、高密度脂蛋白血清水平和放射治疗与脑坏死之间的间隔时间。纳入这 4 个预测因子的列线图在训练集上显示出良好的校准度和鉴别度，C 指数为 0.763（95%CI，0.694 至 0.832），在验证集上得到验证（C 指数 0.768；95%CI，0.675 至 0.861）。此外，列线图成功地将患者分为高风险和低风险组。决策曲线表明我们的列线图具有临床实用性。
列线图对 NPC 放射治疗后脑坏死患者的 CVD 具有良好的预测准确性，可能有助于临床决策。
