老年食管鳞癌放化疗联合抗PD-1抗体疗效研究
基于241例老年食管鳞癌患者,比较放化疗联合抗PD-1抗体与单纯放化疗的疗效与安全性,显示联合治疗未显著改善生存。

基本信息
资源简介
老年食管鳞癌放化疗联合抗PD-1抗体疗效研究
【数据集背景】
本数据集源站标题为《Adding anti-PD-1 antibody to definitive chemoradiotherapy in elderly patients with esophageal squamous cell carcinoma: higher intensity does not equate to better outcomes》。配套论文《Adding anti-PD-1 antibody to definitive chemoradiotherapy in elderly patients with esophageal squamous cell carcinoma: higher intensity does not equate to better outcomes》发表于 Annals of Medicine(2026),DOI:10.1080/07853890.2026.2622762。项目资助方:This work was supported by grants from the Basic and Applied Basic Research Foundation of Guangdong Province (2025A1515010951).。源站首次发布:2026-02-02。
【数据内容】
源站原始描述:The benefit of adding anti-PD-1 antibodies to definitive chemoradiotherapy (dCRT) in elderly patients with esophageal squamous cell carcinoma (ESCC) remains uncertain. This study evaluated its efficacy and safety versus dCRT alone. We retrospectively analyzed the patients aged ≥ 70 years with ESCC treated at three academic centers from 2009 to 2023. All patients received first-line dCRT and the study group additionally received anti-PD-1 antibodies (IO group). Propensity score matching (PSM) was…
【数据结构与技术规格】
文件数 2 个,合计 13.43 MB。iann_a_2622762_sm1835.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,38.49 KB。数据集 DOI:10.6084/m9.figshare.31230188.v1。
【主题与分类】
源站学科分类:Medicine、Immunology、Biological Sciences not elsewhere classified、Cancer。主题标签:Esophageal cancer、radiotherapy、anti-PD-1 antibody、chemotherapy、elderly patients。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://tandf.figshare.com/articles/dataset/Adding_anti-PD-1_antibody_to_definitive_chemoradiotherapy_in_elderly_patients_with_esophageal_squamous_cell_carcinoma_higher_intensity_does_not_equate_to_better_outcomes/31230188
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Adding anti-PD-1 antibody to definitive chemoradiotherapy in elderly patients with esophageal squamous cell carcinoma: higher intensity does not equate to better outcomes. Taylor & Francis. Cen, Peiying; Chen, Biqi; Zhou, Wenxi; Cheng, Qi; Li, Zimeng; Yi, Chen; et al
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。




