新辅助免疫化疗联合手术治疗局部晚期食管鳞癌患者病理学完全缓解预测模型

Predictive Model for Pathologic Complete Response to Preoperative Neoadjuvant Immunochemotherapy for Locally Advanced Esophageal Squamous Cell Carcinoma

目的 探究术前新辅助免疫化疗(nICT)联合手术治疗局部晚期食管鳞状细胞癌(ESCC)病理学完全缓解(pCR)的影响因素,构建预测nICT后pCR的列线图模型。方法 回顾性收集2020年2月至2022年4月郑州大学第一附属医院收治的经nICT后接受根治性手术的局部晚期ESCC患者的临床资料。分析pCR的独立影响因素,并建立预测列线图。通过Calibration校准曲线评估模型预测概率与实际结果的一致性,绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC)评价预测模型的区分度,通过决策曲线分析(DCA)评估模型的临床有效性。结果 共纳入131例局部晚期ESCC患者,其中33例(25.20%)达到pCR。多因素logistic分析显示,临床TNM分期、预后营养指数(PNI)、淋巴细胞与单核细胞计数比值(LMR)和癌胚抗原(CEA)是影响nICT后pCR的独立因素。校准曲线表明预测和实际达到pCR的一致性良好,该模型的AUC为0.81(95%CI:0.719~0.896),DCA显示该列线图具有临床应用价值。结论 基于临床TNM分期、PNI、LMR和CEA这4个预测因素构建的列线图模型有助于预测局部晚期ESCC患者nICT后病理学缓解情况,对局部晚期ESCC精准分层并筛选术前nICT受益人群具有重要意义。

Objective To investigate the predictors of pathologic complete response(pCR) after preoperative neoadjuvant immunochemotherapy(nICT) in locally advanced esophageal squamous cell carcinoma(ESCC),and to construct a nomogram model for predicting pCR after nICT.Methods The clinical data of locally advanced ESCC patients who underwent radical surgery after nICT in the First Affiliated Hospital of Zhengzhou University from February 2020 to April 2022 were retrospectively collected.The independent influencing factors of pCR was analyzed,and then a predictive nomogram was established.The Calibration curve was performed to evaluate its consistency from actual results,the area under curve(AUC) of the receiver operating characteristic(ROC) curve to evaluate the prediction discrimination of the model,and the decision curve analysis(DCA) to evaluate its clinical validity.Results A total of 131 patients with locally advanced ESCC were enrolled,among whom 33(25.20%) achieved pCR.Multivariate logistic analysis showed that clinical TNM stage,prognostic nutritional index(PNI),lymphocyte to monocyte ratio(LMR) and carcinoembryonic antigen(CEA) were independent factors for pCR.The calibration curves showed good consistency.The AUC of this model was 0.81(95% CI:0.719-0.896),and DCA showed that the nomogram had clinical application value.Conclusion The model based on the four predictors of clinical TNM stage,PNI,LMR and CEA is helpful for individualized prediction of pCR after nICT in patients with locally advanced ESCC,which is of great significance for distinguishing and selecting suitable locally advanced ESCC patients for neoadjuvant therapy.