Abstract:

Objective: To predict the 3-year cancer-specific survival (CSS) of patients with non-metastatic T_3a renal cell carcinoma after surgery. Methods: A total of 336 patients with pathologically confirmed T_3a N0-1M0 renal cell carcinoma (RCC) who underwent surgical treatment at the Department of Urology, Peking University Third Hospital from March 2013 to February 2021 were retrospectively collected. The patients were randomly divided into a training cohort of 268 cases and an internal validation cohort of 68 cases at an 4 ∶ 1 ratio. Using two-way Lasso regression, variables were selected to construct a nomogram for predicting the 3-year cancer-specific survival (CSS) of the patients with T_3aN0-1M0 RCC. Performance assessment of the nomogram included evaluation of discrimination and calibration ability, as well as clinical utility using measures such as the concordance index (C-index), time-dependent area under the receiver operating characteristic curve [time-dependent area under the curve (AUC)], calibration curve, and decision curve analysis (DCA). Risk stratification was determined based on the nomogram scores, and Kaplan-Meier survival analysis and Log-rank tests were employed to compare progression-free survival (PFS) and cancer-specific survival (CSS) among the patients in the different risk groups. Results: Based on the Lasso regression screening results, the nomogram was constructed with five variables: tumor maximum diameter, histological grading, sarcomatoid differentiation, T_3a feature, and lymph node metastasis. The baseline data of the training and validation sets showed no statistical differences (P>0.05). The consistency indices of the column diagram were found to be 0.808 (0.708- 0.907) and 0.903 (0.838-0.969) for the training and internal validation sets, respectively. The AUC values for 3-year cancer-specific survival were 0.843 (0.725-0.961) and 0.923 (0.844-1.002) for the two sets. Calibration curves of both sets demonstrated a high level of consistency between the actual CSS and predicted probability. The decision curve analysis (DCA) curves indicated that the column diagram had a favorable net benefit in clinical practice. A total of 336 patients were included in the study, with 35 cancer-specific deaths and 69 postoperative recurrences. According to the line chart, the patients were divided into low-risk group (scoring 0-117) and high-risk group (scoring 119-284). Within the low-risk group, there were 16 tumor-specific deaths out of 282 cases and 36 postoperative recurrences out of 282 cases. In the high-risk group, there were 19 tumor-specific deaths out of 54 cases and 33 post-operative recurrences out of 54 cases. There were significant differences in progression-free survival (PFS) and cancer-specific survival (CSS) between the low-risk and high-risk groups (P < 0.000 1). Conclusion: A nomogram model predicting the 3-year CSS of non-metastatic T_3a renal cell carcinoma patients was successfully constructed and validated in this study. This nomogram can assist clinicians in accurately assessing the long-term prognosis of such patients.

Key words: Renal cell carcinoma, Nomograms, Prognosis