Chen Chunyang, Geng Xinyu, Liang Rui, Zhang Dongze, Sun Meiyun, Zhang Guangbo, Hou Jianquan
Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou 215006, People's Republic of China.
Jiangsu Institute of Clinical Immunology, The First Affiliated Hospital of Soochow University, Suzhou 215006, People's Republic of China.
Exp Biol Med (Maywood). 2021 Mar;246(6):729-739. doi: 10.1177/1535370220977107. Epub 2020 Dec 10.
This study built and tested two effective nomograms for the purpose of predicting cancer-specific survival and overall survival of chromophobe renal cell carcinoma (chRCC) patients. Multivariate Cox regression analysis was employed to filter independent prognostic factors predictive of cancer-specific survival and overall survival, and the nomograms were built based on a training set incorporating 2901 chRCC patients in a retrospective study (from 2004 to 2015) downloaded from the surveillance, epidemiology, and end results (SEER) database. The nomograms were verified on a validation cohort of 1934 patients, subsequently the performances of the nomograms were examined according to the receiver operating characteristic curve, calibration curves, the concordance (C-index), and decision curve analysis. The results showed that tumor grade, AJCC and N stages, race, marital status, age, histories of chemotherapy, radiotherapy and surgery were the individual prognostic factors for overall survival, and that AJCC, N and SEER stages, histories of surgery, radiotherapy and chemotherapy, age, tumor grade were individual prognostic factors for cancer-specific survival. According to C-indexes, receiver operating characteristic curves, and decision curve analysis outcomes, the nomograms showed a higher accuracy in predicting overall survival and OSS when compared with TNM stage and SEER stage. All the calibration curves were significantly consistent between predictive and validation sets. In this study, the nomograms, which were validated to be highly accurate and applicable, were built to facilitate individualized predictions of the cancer-specific survival and overall survival to patients diagnosed with chRCC between 2004 and 2015.
本研究构建并测试了两个有效的列线图,用于预测嫌色肾细胞癌(chRCC)患者的癌症特异性生存率和总生存率。采用多变量Cox回归分析来筛选预测癌症特异性生存率和总生存率的独立预后因素,并基于一项回顾性研究中的训练集构建列线图,该训练集纳入了从监测、流行病学和最终结果(SEER)数据库下载的2901例chRCC患者(2004年至2015年)。在1934例患者的验证队列上对列线图进行验证,随后根据受试者工作特征曲线、校准曲线、一致性(C指数)和决策曲线分析来检验列线图的性能。结果显示,肿瘤分级、美国癌症联合委员会(AJCC)和N分期、种族、婚姻状况、年龄、化疗史、放疗史和手术史是总生存率的个体预后因素,而AJCC、N和SEER分期、手术史、放疗史和化疗史、年龄、肿瘤分级是癌症特异性生存率的个体预后因素。根据C指数、受试者工作特征曲线和决策曲线分析结果,与TNM分期和SEER分期相比,列线图在预测总生存率和癌症特异性生存率方面具有更高的准确性。预测集和验证集之间所有校准曲线均显著一致。在本研究中,构建了经验证具有高度准确性和适用性的列线图,以促进对2004年至2015年间诊断为chRCC的患者进行癌症特异性生存率和总生存率的个体化预测。