Liu Qiang, Kong Xiangyi, Wang Zhongzhao, Wang Xiangyu, Zhang Wenxiang, Ai Bolun, Gao Ran, Fang Yi, Wang Jing
Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Front Oncol. 2021 Apr 29;11:642677. doi: 10.3389/fonc.2021.642677. eCollection 2021.
Nomogram prognostic models could greatly facilitate risk stratification and treatment strategies for cancer patients. We developed and validated a new nomogram prognostic model, named NCCBM, for breast cancer patients with brain metastasis (BCBM) using a large BCBM cohort from the SEER (Surveillance, Epidemiology, and End Results) database. Clinical data for 975 patients diagnosed from 2011 to 2014 were used to develop the nomogram prognostic model. The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index) and calibration curve. The results were validated using an independent cohort of 542 BCBM patients diagnosed from 2014 to 2015. The following variables were selected in the final prognostic model: age, race, surgery, radiation therapy, chemotherapy, laterality, grade, molecular subtype, and extracranial metastatic sites. The C-index for the model described here was 0.69 (95% CI, 0.67 to 0.71). The calibration curve for probability of survival showed good agreement between prediction by nomogram and actual observation. The model was validated in an independent validation cohort with a C-index of 0.70 (95% CI, 0.68 to 0.73). We developed and validated a nomogram prognostic model for BCBM patients, and the proposed nomogram resulted in good performance.
列线图预后模型可以极大地促进癌症患者的风险分层和治疗策略。我们使用来自监测、流行病学和最终结果(SEER)数据库的大型脑转移乳腺癌(BCBM)队列,开发并验证了一种名为NCCBM的新列线图预后模型,用于脑转移乳腺癌患者。2011年至2014年诊断的975例患者的临床数据用于开发列线图预后模型。列线图的预测准确性和判别能力通过一致性指数(C指数)和校准曲线来确定。结果使用2014年至2015年诊断的542例BCBM患者的独立队列进行验证。最终的预后模型中选择了以下变量:年龄、种族、手术、放射治疗、化疗、患侧、分级、分子亚型和颅外转移部位。此处描述的模型的C指数为0.69(95%CI,0.67至0.71)。生存概率的校准曲线显示列线图预测与实际观察之间具有良好的一致性。该模型在独立验证队列中得到验证,C指数为0.70(95%CI,0.68至0.73)。我们为BCBM患者开发并验证了列线图预后模型,所提出的列线图表现良好。