[一种预测根治性肾切除术后总生存率的新nomogram建立与验证]。

Q3 Medicine
L B Xiong, X P Zou, K Ning, X Luo, Y L Peng, Z H Zhou, J Wang, Z Li, C P Yu, P Dong, S J Guo, H Han, F J Zhou, Z L Zhang
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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. <b>Results:</b> 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 <i>P</i><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% <i>CI:</i> 0.716-0.823) vs 0.674 (95% <i>CI:</i> 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 <i>P</i><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 (<i>P</i><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. 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引用次数: 0

摘要

目的:建立非转移性肾癌根治性肾切除术(RN)患者5年、10年、15年总生存期(OS)的nomogram预后模型,并将模型结果与单纯病理分期、国外常用的Karakiewicz nomogram评分和Mayo Clinic分期、大小、分级和坏死(SSIGN)评分进行比较,并将患者分为不同的预后风险亚组。方法:回顾性分析中山大学肿瘤中心1999 ~ 2020年收治的1246例非转移性肾细胞癌患者的临床资料。采用多变量Cox回归分析筛选影响预后的变量建立nomogram,采用bootstrap随机抽样进行内部验证。采用时间-接收者工作特征曲线(ROC)、校准曲线和临床决策曲线分析(DCA)对nomogram进行评价。通过曲线下面积(AUC)比较nomogram与纯病理分期、Karakiewicz nomogram及SSIGN评分的预测效果。最后,根据nomogram评分将患者分为不同的风险亚组。结果:本研究共纳入1246例接受RN治疗的患者。多因素Cox回归分析显示,年龄、吸烟史、病理核分级、肉瘤样分化、肿瘤坏死、病理T、N分期是影响RN患者预后的独立因素(PCI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)。校正曲线显示,sysuc模型预测的生存率与实际生存率接近,而临床DCA显示,sysuc nomogram在一定概率范围内具有优势。在纳入857例详细病理核分期患者的ROC分析中,nomogram(5 /10年AUC: 0.823/0.804)比单纯病理分期(5 /10年AUC: 0.771 /0.658)、Karakiewicz nomogram(5 /10年AUC: 0.772/0.734)和SSIGN评分(5 /10年AUC: 0.792/0.750)预测RN患者5 /10年OS(所有PPHR=4.33, 95% CI: 3.22-5.81, PHR=11.95, 95% CI: 8.29-17.24, PHR=2.63, 95% CI: 1.88-3.68, p)具有更大的AUC(5 /10年AUC: 0.823/0.804)和更好的判别能力。年龄、吸烟史、病理核分级、肉瘤样分化、肿瘤坏死、病理分期是肾移植术后非转移性肾癌患者预后的独立因素。基于这些独立预后因素的SYSUCC nomogram比单纯的病理分期、Karakiewicz nomogram和SSIGN评分更能预测患者术后5年、10年和15年的OS。此外,SYSUCC nomogram具有良好的辨别性、一致性、风险分层性和临床应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Establishment and validation of a novel nomogram to predict overall survival after radical nephrectomy].

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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中华肿瘤杂志
中华肿瘤杂志 Medicine-Medicine (all)
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1.40
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