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.

本研究建立并测试了两个有效的列线图，用于预测嫌色细胞肾细胞癌 (chRCC) 患者的癌症特异性存活率和总体存活率。采用多变量 Cox 回归分析来过滤预测癌症特异性生存率和总生存率的独立预后因素，列线图是基于从监测下载的回顾性研究（2004 年至 2015 年）中包含 2901 名 chRCC 患者的训练集构建的，流行病学和最终结果 (SEER) 数据库。列线图在 1934 名患者的验证队列中进行了验证，随后根据受试者工作特征曲线、校准曲线、一致性（C 指数）和决策曲线分析检查了列线图的性能。结果显示，肿瘤分级，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体生存的个体预后因素，而 AJCC、N 和 SEER 分期、手术史、放化疗史、年龄、肿瘤分级是癌症特异性生存的个体预后因素。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期和 OSS 方面显示出更高的准确性。所有校准曲线在预测集和验证集之间显着一致。在这项研究中，列线图被验证为高度准确和适用，