Department of Urology, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Department of Urology, Beijing Anzhen Hospital, Capital Medical University, Beijing, People's Republic of China.
Urol Oncol. 2021 Dec;39(12):835.e19-835.e27. doi: 10.1016/j.urolonc.2021.06.014. Epub 2021 Oct 4.
To establish a nomogram for the prediction of postoperative cancer-specific survival (CSS) in patients with nonmetastatic T3a renal cell carcinoma (RCC).
The Surveillance, Epidemiology, and End Results database were searched for patients with pT3aN0-1M0 RCC between 2010 and 2018. The patients were randomly stratified into the training and verification group (7:3 ratio). Using Cox regression analysis, the predictors for the CSS in the training group were integrated to establish the nomogram for predicting the 3-year and 5-year CSS. Harrell's concordance index (C-index), time-dependent receiver operating characteristic curve, decision curve analysis, and Kaplan-Meier survival analysis were used to evaluate the nomogram performance.
A total of 5,791 pT3aN0-1M0 RCC cases with eligible data were selected from the Surveillance, Epidemiology, and End Results database. Age, tumor size, surgery type, Fuhrman grade, histological type, sarcomatoid, N stage, and invasion patterns were identified as the significant predictors for CSS to establish the nomogram. The C-indices of the nomogram were 0.774 (95% CI: 0.753-0.795) and 0.777 (95% CI: 0.745-0.809) for the training and verification group, respectively. The calibration of the nomogram revealed consistency between the predicted and observed survival. The area under the 3-year and 5-year CSS receiver operating characteristic curves were 0.773 and 0.786 in the training group, respectively. Decision curve analysis showed the optimal application of the model in clinical decision-making. According to the cutoff values of prognostic indices, patients with low-risk showed better CSS than those with high-risk in both training and verification groups (both P< 0.0001).
The current nomogram could effectively predict the CSS of patients with nonmetastatic T3a RCC, and could be used to identify patients who might need a compact interval of follow-up and postoperative adjuvant systemic treatment. The limitations included the retrospective nature, absence of external validation, and several unmeasured variables related to the selection bias of surgery type. The results should be interpreted with caution.
建立一个列线图，用于预测非转移性 T3a 期肾细胞癌（RCC）患者的术后癌症特异性生存（CSS）。
从 2010 年至 2018 年，在监测、流行病学和最终结果数据库中搜索 pT3aN0-1M0RCC 患者。患者被随机分层到训练和验证组（比例为 7:3）。使用 Cox 回归分析，将训练组中 CSS 的预测因子整合到建立预测 3 年和 5 年 CSS 的列线图中。Harrell 的一致性指数（C 指数）、时间依赖性接受者操作特征曲线、决策曲线分析和 Kaplan-Meier 生存分析用于评估列线图的性能。
从监测、流行病学和最终结果数据库中选择了 5791 例符合条件的 pT3aN0-1M0RCC 病例。年龄、肿瘤大小、手术类型、Fuhrman 分级、组织学类型、肉瘤样、N 分期和浸润模式被确定为 CSS 的显著预测因子，以建立列线图。列线图在训练组和验证组的 C 指数分别为 0.774（95%CI：0.753-0.795）和 0.777（95%CI：0.745-0.809）。列线图的校准显示预测与观察到的生存之间具有一致性。在训练组中，3 年和 5 年 CSS 接收器操作特征曲线下的面积分别为 0.773 和 0.786。决策曲线分析表明该模型在临床决策中的最佳应用。根据预后指标的截断值，低风险患者在训练组和验证组的 CSS 均优于高风险患者（均 P<0.0001）。
目前的列线图可以有效地预测非转移性 T3aRCC 患者的 CSS，可用于识别可能需要紧凑随访间隔和术后辅助全身治疗的患者。该研究存在一定的局限性，包括回顾性研究、缺乏外部验证以及与手术类型选择偏倚相关的几个未测量变量。因此，结果应谨慎解释。
