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[Establishment and validation of a novel nomogram to predict overall survival after radical nephrectomy].
Xiong, L B; Zou, X P; Ning, K; Luo, X; Peng, Y L; Zhou, Z H; Wang, J; Li, Z; Yu, C P; Dong, P; Guo, S J; Han, H; Zhou, F J; Zhang, Z L.
Affiliation
  • Xiong LB; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Zou XP; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Ning K; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Luo X; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Peng YL; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Zhou ZH; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Wang J; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Li Z; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Yu CP; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Dong P; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Guo SJ; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Han H; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Zhou FJ; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
  • Zhang ZL; Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Zhonghua Zhong Liu Za Zhi ; 45(8): 681-689, 2023 Aug 23.
Article de Zh | MEDLINE | ID: mdl-37580273
ABSTRACT

Objective:

To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups.

Methods:

A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores.

Results:

A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI 0.716-0.823) vs 0.674 (95% CI 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC 0.772/0.734) and SSIGN score (5-/10-year AUC 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group HR=4.33, 95% CI 3.22-5.81, P<0.001; high-risk group vs low-risk group HR=11.95, 95% CI 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI 1.88-3.68, P<0.001).

Conclusions:

Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
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Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Néphrocarcinome / Tumeurs du rein Type d'étude: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limites: Humans Langue: Zh Journal: Zhonghua Zhong Liu Za Zhi Année: 2023 Type de document: Article Pays d'affiliation: Chine

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Néphrocarcinome / Tumeurs du rein Type d'étude: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limites: Humans Langue: Zh Journal: Zhonghua Zhong Liu Za Zhi Année: 2023 Type de document: Article Pays d'affiliation: Chine