Establishment of a prediction model for postoperative progression-free survival in patients with renal cell carcinoma
10.3969/j.issn.1009-8291.2024.10.011
- VernacularTitle:肾细胞癌患者术后无进展生存期预测模型的建立
- Author:
Huafeng LI
1
,
2
;
Zhenlong WANG
3
;
Hongyi ZHANG
1
;
Zihe PENG
3
;
Chenyue WANG
1
;
Yao DONG
3
;
Haibin ZHOU
1
,
2
Author Information
1. Department of Urology, The First Affiliated Hospital of Xi'an Medical University, Xi'an 710077
2. Department of Urology, The First Affiliated Hospital of Xi'an Medical University, Xi'an 710077
3. Department of Urology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China
- Publication Type:Journal Article
- Keywords:
renal cell carcinoma;
nomogram;
prediction model;
progression-free survival;
UISS;
SSIGN;
Leibovich
- From:
Journal of Modern Urology
2024;29(10):892-897
- CountryChina
- Language:Chinese
-
Abstract:
[Objective] To analyze factors influencing the postoperative progression-free survival (PFS) in patients with renal cell carcinoma (RCC), construct a nomogram model for predicting PFS, and compare it with other predictive models. [Methods] A retrospective analysis was conducted on the general and clinical data of 263 RCC patients who underwent surgery at the Department of Urology, the Second Affiliated Hospital of Xi'an Jiaotong University, during Apr.2014 and Nov.2021.Patients were divided into the progression group (n=34) and non-progression group (n=229). The data of the two groups were analyzed to identify prognostic variables associated with PFS, and a nomogram model was constructed.The performance of this model was compared with that of the University of California, Los Angeles Integrated Staging System (UISS) score, tumor staging, tumor size, tumor pathological grade, and tumor necrosis scoring system (SSIGN score), and Leibovich score by plotting receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC). Calibration curve of the nomogram was used to validate the model's performance, and K-fold cross-validation was employed to assess its external validity. [Results] Multivariate Cox regression analysis revealed that age (HR=2.255, 95%CI: 1.032-4.926), T stage (HR=5.766, 95%CI: 2.351-14.142), pathological grade (HR=3.100, 95%CI: 1.445-6.651), and pathological necrosis (HR=2.656, 95%CI: 1.253-5.629) were independent risk factors of PFS (P<0.05). The nomogram model based on these four independent variables had AUCs (95%CI) of 0.750 (0.630-0.870), 0.803 (0.705-0.902), and 0.847 (0.757-0.937) for 1, 3, and 5 years, respectively, which were higher than those of UISS score, SSIGN score, and Leibovich score.The calibration curve of the nomogram showed good consistency between predicted and actual probabilities.In K-fold cross-validation, the average AUCs of the nomogram at 1, 3, and 5 years were 0.761, 0.808, and 0.842, indicating good external validity of the nomogram. [Conclusion] The nomogram based on age, T stage, pathological grade and pathological necrosis can accurately predict the risk of postoperative PFS in RCC patients at 1, 3, and 5 years, which can aid clinicians in the early identification of high-risk progression.
