文章：

通过临床评估动态参数增强局部晚期食管癌新辅助免疫化疗肿瘤病理反应预测能力

Enhancing Prediction for Tumor Pathologic Response to Neoadjuvant Immunochemotherapy in Locally Advanced Esophageal Cancer by Dynamic Parameters from Clinical Assessments

原文发布日期：1 September 2023

DOI: 10.3390/cancers15174377

类型: Article

开放获取: 是

英文摘要：

To develop accurate and accessible prediction methods for assessing pathologic response following NICT prior to surgery, we conducted a retrospective study including 137 patients with esophageal squamous cell carcinoma (ESCC) who underwent surgery after two cycles of NICT between January 2019 and March 2022 at our center. We collected clinical parameters to evaluate the dynamic changes in the primary tumor. Univariate and multivariate analyses were performed to determine the correlations between these parameters and the pathologic response of the primary tumor. Subsequently, we constructed prediction models for pCR and MPR using multivariate logistic regression. The MPR prediction Model 2 was internally validated using bootstrapping and externally validated using an independent cohort from our center. The univariate logistic analysis revealed significant differences in clinical parameters reflecting tumor regression among patients with varying pathologic responses. The clinical models based on these assessments demonstrated excellent predictive performance, with the training cohort achieving a C-index of 0.879 for pCR and 0.912 for MPR, while the testing cohort also achieved a C-index of 0.912 for MPR. Notably, the MPR prediction Model 2, with a threshold cut-off of 0.74, exhibited 92.7% specificity and greater than 70% sensitivity, indicating a low rate of underestimating residual tumors. In conclusion, our study demonstrated the high accuracy of clinical assessment-based models in pathologic response prediction, aiding in decision-making regarding organ preservation and radiotherapy adjustments after induction immunochemotherapy.

摘要翻译： 

为开发准确且易于操作的预测方法，用于术前评估新辅助免疫化疗后的病理反应，我们开展了一项回顾性研究，纳入了2019年1月至2022年3月期间在本中心接受两周期新辅助免疫化疗后行手术治疗的137例食管鳞状细胞癌患者。我们收集了临床参数以评估原发肿瘤的动态变化，并通过单因素及多因素分析探究这些参数与原发肿瘤病理反应的相关性。随后，采用多因素逻辑回归构建了病理完全缓解及主要病理缓解的预测模型。其中主要病理缓解预测模型2通过Bootstrap法进行内部验证，并采用本中心独立队列进行外部验证。单因素逻辑分析显示，反映肿瘤退缩的临床参数在不同病理反应患者间存在显著差异。基于这些评估构建的临床模型展现出优异的预测性能：训练队列中病理完全缓解和主要病理缓解的C指数分别达0.879和0.912，而测试队列中主要病理缓解的C指数也达到0.912。值得注意的是，主要病理缓解预测模型2在0.74阈值截断值时表现出92.7%的特异性及超过70%的敏感性，表明其低估残留肿瘤的概率较低。本研究证实基于临床评估的模型在病理反应预测中具有高准确性，有助于指导诱导免疫化疗后的器官保留决策及放疗方案调整。

原文链接：

Enhancing Prediction for Tumor Pathologic Response to Neoadjuvant Immunochemotherapy in Locally Advanced Esophageal Cancer by Dynamic Parameters from Clinical Assessments