Suppr超能文献

可切除食管鳞状细胞癌新辅助治疗后的病理完全缓解:内镜特征及意义

Pathologic complete response after neoadjuvant therapy for resectable esophageal squamous cell carcinoma: Endoscopic characteristics and implications.

作者信息

Yuan Peng, Liu Zongchao, Dai Liang, Yan Yan, Wu Yaya, Chen Keneng, Li Wenqing, Wu Qi

机构信息

State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Department of Endoscopy, Peking University Cancer Hospital & Institute, Beijing 100142, China.

Department of Cancer Epidemiology, State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Peking University Cancer Hospital & Institute, Beijing 100142, China.

出版信息

Endosc Int Open. 2025 Jul 23;13:a26255884. doi: 10.1055/a-2625-5884. eCollection 2025.

Abstract

BACKGROUND AND STUDY AIMS

This study aimed to identify endoscopic characteristics and develop predictive models for detecting a pathologic complete response (pCR) after neoadjuvant therapy in patients with esophageal squamous cell carcinoma (ESCC).

PATIENS AND METHODS

This study enrolled 220 patients including a retrospective cohort (n = 158) and a prospective cohort (n = 62), from May 2018 to March 2023 with ESCC who received neoadjuvant chemoimmunotherapy (nCIT) or neoadjuvant chemotherapy (nCT) followed by surgery. Predictive capability of the endoscopic characteristics for pCR was developed and validated using machine learning.

RESULTS

All patients underwent endoscopic examinations before surgery but after neoadjuvant therapy. Cohort I was divided into a training set (n = 112) and an internal validation set (n = 46) at a 7:3 ratio. Seven endoscopic features were assessed: scarring; intraepithelial papillary capillary loop (IPCL) type B; depressed mucosa post-tumor disappearance; eroding mucosal changes with an uneven surface; nonsuperficial neoplastic lesions; protruded changes; and presence of cancer cells in biopsy specimens. Using these characteristics as predictors, a multivariate logistic regression model was trained to predict pCR. For further validation, data from prospective Cohorts II and III were incorporated. The model achieved 96.43% accuracy (95% confidence interval [CI] 91.11%-99.02%) in the training set, 93.48% (95% CI 82.10%-98.63%) for internal validation of Cohort I, and 96.77% (95% CI 88.83%-99.61%) in the prospective validation set.

CONCLUSIONS

Endoscopic characteristics are significant predictors of pCR in patients with ESCC receiving nCIT or nCT. The predictive model demonstrated high accuracy in both derivation and validation cohorts.

摘要

背景与研究目的

本研究旨在确定食管鳞状细胞癌(ESCC)患者新辅助治疗后病理完全缓解(pCR)的内镜特征并建立预测模型。

患者与方法

本研究纳入了220例患者,包括一个回顾性队列(n = 158)和一个前瞻性队列(n = 62),这些患者在2018年5月至2023年3月期间患有ESCC,接受了新辅助化疗免疫治疗(nCIT)或新辅助化疗(nCT),随后接受手术。使用机器学习开发并验证内镜特征对pCR的预测能力。

结果

所有患者在新辅助治疗后但手术前均接受了内镜检查。队列I以7:3的比例分为训练集(n = 112)和内部验证集(n = 46)。评估了七个内镜特征:瘢痕形成;上皮内乳头样毛细血管袢(IPCL)B型;肿瘤消失后黏膜凹陷;表面不平的糜烂性黏膜改变;非浅表性肿瘤病变;突出改变;以及活检标本中癌细胞的存在。以这些特征作为预测因子,训练了一个多变量逻辑回归模型来预测pCR。为了进一步验证,纳入了前瞻性队列II和III的数据。该模型在训练集中的准确率为96.43%(95%置信区间[CI] 91.11%-99.02%),在队列I的内部验证中为93.48%(95% CI 82.10%-98.63%),在前瞻性验证集中为96.77%(95% CI 88.83%-99.61%)。

结论

内镜特征是接受nCIT或nCT的ESCC患者pCR的重要预测因子。该预测模型在推导队列和验证队列中均显示出高准确率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b74b/12303029/986807a5e752/10-1055-a-2625-5884_26298922.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验