Guo Qiong-Ya, Zhang Wei, Fu Lin, Hu Shan-Shan, Li Lin
Department of Gastroenterology, Henan Provincial People's Hospital, Zhengzhou 450003, Henan Province, China.
Department of Gastrointestinal Surgery, Henan Provincial People's Hospital, Zhengzhou 450003, Henan Province, China.
World J Gastrointest Oncol. 2025 Jul 15;17(7):105403. doi: 10.4251/wjgo.v17.i7.105403.
Locally advanced rectal cancer (LARC) carries a substantial risk of recurrence, prompting the use of neoadjuvant chemoradiotherapy (nCRT) to improve tumor resectability and long-term outcomes. However, individual treatment responses vary considerably, highlighting the need for robust predictive tools to guide clinical decision-making.
To develop a nomogram model integrating clinical characteristics and biomarkers to predict the likelihood of poor response to nCRT in LARC.
A retrospective analysis was performed on 178 patients with stage II-III LARC treated from January 2021 to December 2023. All patients underwent standardized nCRT followed by total mesorectal excision. Clinical data, inflammatory markers [C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha], and tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 19-9] were collected. Logistic regression was used to identify independent predictors of poor nCRT response. A nomogram was constructed using significant predictors and validated concordance index (C-index), receiver operating characteristic curve, calibration plot, and decision curve analysis (DCA).
A total of 178 patients were enrolled, with 36 (20.2%) achieving a good response and 142 (79.8%) exhibiting a poor response to nCRT. Baseline factors, including age and comorbidities, showed no significant differences. However, poor responders more frequently had lymph node metastasis, advanced tumor node metastasis/T stage, larger tumor diameter, and elevated CRP, IL-6, and CEA levels. Logistic regression confirmed CRP, IL-6, and CEA as independent predictors of poor response. The nomogram demonstrated high accuracy (area under the curve = 0.928), good calibration (Hosmer-Lemeshow = 0.928), and a sensitivity of 88.1% with 82.6% specificity. Internal validation bootstrap resampling ( = 1000) yielded an adjusted C-index of 0.716, and DCA confirmed substantial clinical utility.
A nomogram incorporating serum CRP, IL-6, and CEA accurately predicts poor nCRT response in patients with LARC. This model provides a valuable framework for individualized treatment planning, potentially improving clinical outcomes.
局部晚期直肠癌（LARC）具有较高的复发风险，因此采用新辅助放化疗（nCRT）来提高肿瘤的可切除性和改善长期预后。然而，个体治疗反应差异很大，这凸显了需要强大的预测工具来指导临床决策。
开发一种整合临床特征和生物标志物的列线图模型，以预测LARC患者对nCRT反应不佳的可能性。
对2021年1月至2023年12月期间接受治疗的178例II-III期LARC患者进行回顾性分析。所有患者均接受标准化nCRT，随后进行全直肠系膜切除术。收集临床数据、炎症标志物[C反应蛋白（CRP）、白细胞介素-6（IL-6）、肿瘤坏死因子-α]和肿瘤标志物[癌胚抗原（CEA）、糖类抗原19-9]。采用逻辑回归确定nCRT反应不佳的独立预测因素。使用显著预测因素构建列线图，并通过一致性指数（C指数）、受试者工作特征曲线、校准图和决策曲线分析（DCA）进行验证。
共纳入178例患者，其中36例（20.2%）对nCRT反应良好，142例（79.8%）反应不佳。包括年龄和合并症在内的基线因素无显著差异。然而，反应不佳者更常出现淋巴结转移、肿瘤淋巴结转移/ T分期进展、肿瘤直径较大以及CRP、IL-6和CEA水平升高。逻辑回归证实CRP、IL-6和CEA是反应不佳的独立预测因素。列线图显示出高准确性（曲线下面积 = 0.928）、良好的校准（Hosmer-Lemeshow = 0.928），敏感性为88.1%，特异性为82.6%。通过内部验证的自助重采样（ = 1000）得出调整后的C指数为0.716，DCA证实了其具有显著的临床实用性。
纳入血清CRP、IL-6和CEA的列线图能够准确预测LARC患者对nCRT反应不佳的情况。该模型为个体化治疗方案制定提供了有价值的框架，可能改善临床结局。
