Development and validation of a nomogram to predict recurrence for clinical T1/2 clear cell renal cell carcinoma patients after nephrectomy

列线图 医学 肾切除术 肾细胞癌 接收机工作特性 一致性 队列 比例危险模型 泌尿科 外科 曲线下面积 肾透明细胞癌 肿瘤科 内科学
作者
Keruo Wang,Baoyin Guo,Yuanjie Niu,Gang Li
出处
期刊:BMC Surgery [BioMed Central]
卷期号:24 (1)
标识
DOI:10.1186/s12893-024-02487-z
摘要

Abstract Objective To develop and validate a nomogram for predicting recurrence-free survival (RFS) for clinical T1/2 (cT1/2) clear cell renal cell carcinoma (ccRCC) patients after nephrectomy. Methods Clinicopathological and survival data from 1289 cT1/2 ccRCC patients treated at the Second Hospital of Tianjin Medical University between 2017 and 2020 were included. Cox regression analysis was used to identify independent risk factors in 902 and 387 ccRCC patients in the training and validation cohorts, respectively, and construct the nomogram. The performance of the nomogram was assessed through calibration plots, time-dependent receiver operating characteristic (ROC) curves, C-index (concordance-index), and decision curve analysis (DCA). Kaplan-Meier curves were used to evaluate the probability of RFS in patients with different recurrence risks. Results Age, tumor size, surgical approach, Fuhrman grade, and pT3a upstage were identified as independent predictors of RFS. The area under the curve (AUC) for the 3-year and 5-year RFS ROC curves were 0.791 and 0.835 in the training cohort, and 0.860 and 0.880 in the validation cohort. The DCA and calibration plots demonstrated the optimal application and excellent accuracy of the nomogram for predicting 3-year and 5-year RFS. Kaplan-Meier curves revealed significant differences in RFS among the three risk groups in both the training and validation cohorts. Clinically, the developed nomogram provides a more precise tool for risk stratification, enabling tailored postoperative management and surveillance strategies, ultimately aiming to improve patient outcomes. Conclusions We developed a nomogram for predicting RFS in cT1/2 ccRCC patients after nephrectomy with high accuracy. The clinical implementation of this nomogram can significantly enhance clinical decision-making, leading to improved patient outcomes and optimized resource utilization in the management of ccRCC.
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