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

• Published in: BMC surgery 2024-06, Vol.24 (1), p.196-11, Article 196
• Main Authors: Wang, Keruo, Guo, Baoyin, Niu, Yuanjie, Li, Gang
• Format: Article
• Language: English
• Subjects: Adult; Aged; Calibration; Carcinoma, Renal cell; Carcinoma, Renal Cell - pathology; Carcinoma, Renal Cell - surgery; Clear cell renal cell carcinoma; Clear cell-type renal cell carcinoma; Decision making; Diseases; Female; Humans; Inclusion; Kidney cancer; Kidney Neoplasms - pathology; Kidney Neoplasms - surgery; Male; Medical colleges; Medical prognosis; Medical research; Medicine, Experimental; Metastasis; Middle Aged; Neoplasm Recurrence, Local - diagnosis; Neoplasm Recurrence, Local - epidemiology; Neoplasm Staging; Nephrectomy; Nephrectomy - methods; Nomogram; Nomograms; Patients; Recurrence-free survival; Regression analysis; Relapse; Resource utilization; Retrospective Studies; Risk analysis; Risk Factors; Risk groups; ROC Curve; Statistical analysis; Survival; Survival analysis; Training; Validation; Variables
• ISSN: 1471-2482; 1471-2482
• DOI: 10.1186/s12893-024-02487-z

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. 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. 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. 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.