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新辅助直肠肿瘤退缩分级综合评分作为局部晚期直肠癌患者新辅助放化疗后无病生存的替代终点。

Neoadjuvant rectal-tumor regression grade combined score as surrogate endpoint for disease-free survival in locally advanced rectal cancer patients after neoadjuvant chemoradiotherapy.

作者信息

Zhang Weili, Sun Hui, Yang Rong, Xie Xiaolin, Liao Leen, Wang Weifeng, Wang Ruowei, Wu Xiaojun, Lu Zhenhai, Pan Zhizhong, Lin Feifei, Shao Lingdong, Peng Jianhong

机构信息

Department of Colorectal Surgery, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangzhou, 510060, P. R. China.

Department of Medical Oncology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, P. R. China.

出版信息

Oncologist. 2025 Jun 4;30(6). doi: 10.1093/oncolo/oyaf124.

Abstract

BACKGROUND

Existing prognostic models, such as tumor regression grade (TRG) and neoadjuvant rectal (NAR) score, have been validated as important indicators for assessing the efficacy of neoadjuvant therapy in locally advanced rectal cancer (LARC) and predicting disease-free survival (DFS). However, both models have inherent limitations in prognostic prediction. This study aims to construct a composite NAR-TRG score to predict DFS in LARC patients treated with chemoradiotherapy (CRT) followed by radical surgery.

PATIENTS AND METHODS

A total of 952 consecutive LARC patients between December 2010 and July 2018 at Sun Yat-sen University Cancer Center and Fujian Cancer Hospital, were enrolled in this study. After calculating the NAR score, patients were categorized into NAR low, medium, and high groups; TRG was dichotomized into TRG low and high groups; the NAR-TRG combined score was then determined based on both NAR and TRG groupings. Survival outcomes were analyzed using Kaplan-Meier, Cox regression. Nomograms were developed to forecast patient DFS, with the area under the curve values of time-dependent receiver operating characteristic (timeROC) and c-index utilized to assess the accuracy and reliability of the nomograms.

RESULTS

Significant differences in 5-year DFS were observed among the NAR-TRG score from 1 to 3 (91.4% vs 79.9% vs 72.3%, P < .001). NAR-TRG score was identified as an independent predictor of DFS in multivariate analysis (HR = 1.577, 95% CI: 1.298-1.915, P < .001). The comparison of timeROC AUCs revealed that the NAR-TRG score consistently outperformed both the NAR score and TRG group at various time points (Main cohort: NAR-TRG score vs TRG, P = .002; NAR-TRG score vs NAR, P = .002; Validation cohort: NAR-TRG score vs TRG, P = .003; NAR-TRG score vs NAR, P = .002). The nomogram model including the NAR-TRG score demonstrated a superior c-index and area under the timeROC for DFS compared to models excluding the NAR-TRG score both in the main cohort and validation cohort.

CONCLUSIONS

The NAR-TRG score effectively stratifies LARC patients receiving neoadjuvant CRT, which can serve as a surrogate endpoint for DFS, contributing to the optimization of decisions related to postoperative therapy and subsequent follow-up strategies.

摘要

背景

现有的预后模型,如肿瘤退缩分级(TRG)和新辅助直肠癌(NAR)评分,已被证实是评估局部晚期直肠癌(LARC)新辅助治疗疗效及预测无病生存期(DFS)的重要指标。然而,这两种模型在预后预测方面都存在固有局限性。本研究旨在构建一个复合NAR-TRG评分,以预测接受放化疗(CRT)后行根治性手术的LARC患者的DFS。

患者与方法

2010年12月至2018年7月期间,中山大学肿瘤防治中心和福建省肿瘤医院共纳入952例连续的LARC患者。计算NAR评分后,将患者分为NAR低、中、高组;TRG分为TRG低和高组;然后根据NAR和TRG分组确定NAR-TRG综合评分。采用Kaplan-Meier法和Cox回归分析生存结局。绘制列线图以预测患者的DFS,利用时间依赖性受试者工作特征曲线(timeROC)下面积值和c指数评估列线图的准确性和可靠性。

结果

NAR-TRG评分1至3分的患者5年DFS存在显著差异(91.4%对79.9%对72.3%,P<0.001)。多因素分析显示NAR-TRG评分是DFS的独立预测因素(HR=1.577,95%CI:1.298-1.915,P<0.001)。timeROC曲线下面积比较显示,在各个时间点NAR-TRG评分均优于NAR评分和TRG组(主要队列:NAR-TRG评分对TRG,P=0.002;NAR-TRG评分对NAR,P=0.002;验证队列:NAR-TRG评分对TRG, P=0.003;NAR-TRG评分对NAR,P=0.002)。在主要队列和验证队列中,包含NAR-TRG评分的列线图模型在DFS的c指数和timeROC曲线下面积方面均优于不包含NAR-TRG评分的模型。

结论

NAR-TRG评分有效地对接受新辅助CRT的LARC患者进行了分层,可作为DFS的替代终点,有助于优化术后治疗及后续随访策略相关决策。

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