Department of Urology, People's Hospital of Putuo District, School of Medicine, Tongji University, Shanghai.
Department of Urology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai.
Int Braz J Urol. 2021 Mar-Apr;47(2):333-349. doi: 10.1590/S1677-5538.IBJU.2020.0195.
Increased attention has been focused on the survival of renal cell carcinoma (RCC) patients with bone metastasis. This study proposed to establish and evaluate a nomogram for predicting the overall survival (OS) and cancer-specific survival (CSS) of RCC patients with bone metastasis.
RCC patients with bone metastasis between 2010 and 2015 were captured from the surveillance, epidemiology and end results (SEER) database. Univariate and multivariate cox regressions were performed to assess the effects of clinical variables on OS and CSS. The nomogram based on the Cox hazards regression model was developed. Concordance index (C-index) and calibration curve were performed to evaluate the accuracy of nomogram models, receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were conducted to assess the predict performance.
A total of 2.471 eligible patients were enrolled in this study. The patients were assigned to primary (n=1.672) and validation (n=799) cohorts randomly. The 1-, 2-, and 3-year OS and CSS nomogram models were constructed based on age at diagnosis, sex, marital status, pathological grade, T-stage, N-stage, brain/liver/lung metastasis, surgery, radiotherapy and chemotherapy. The c for OS and CSS prediction was 0.730 (95% confidence interval [CI]: 0.719-0.741) and 0.714 (95%CI:0.702-0.726). The calibration curves showed significant agreement between nomogram models and actual observations. ROC and DCA indicated nomograms had better predict performance.
The nomograms for predicting prognosis provided an accurate prediction of OS and CSS in RCC patients with bone metastasis, and contributed clinicians to optimize individualized treatment plans.
人们越来越关注伴有骨转移的肾细胞癌（RCC）患者的生存情况。本研究旨在建立并评估一种预测伴有骨转移的 RCC 患者总生存（OS）和癌症特异性生存（CSS）的列线图。
从监测、流行病学和最终结果（SEER）数据库中捕获了 2010 年至 2015 年间伴有骨转移的 RCC 患者。采用单变量和多变量 cox 回归分析评估临床变量对 OS 和 CSS 的影响。基于 Cox 风险回归模型建立了列线图。采用一致性指数（C-index）和校准曲线评估列线图模型的准确性，采用接受者操作特征（ROC）曲线和决策曲线分析（DCA）评估预测性能。
本研究共纳入 2471 例符合条件的患者。患者被随机分为原始队列（n=1672）和验证队列（n=799）。根据诊断时的年龄、性别、婚姻状况、病理分级、T 分期、N 分期、脑/肝/肺转移、手术、放疗和化疗，构建了用于预测 OS 和 CSS 的 1、2 和 3 年列线图模型。OS 和 CSS 预测的 C 指数分别为 0.730（95%置信区间[CI]：0.719-0.741）和 0.714（95%CI：0.702-0.726）。校准曲线显示列线图模型与实际观察结果之间存在显著一致性。ROC 和 DCA 表明列线图具有更好的预测性能。
预测预后的列线图为伴有骨转移的 RCC 患者提供了 OS 和 CSS 的准确预测，有助于临床医生优化个体化治疗计划。
