Generation and validation of a revised classification for oesophageal and junctional adenocarcinoma

Author:

Peters C J12,Hardwick R H2,Vowler S L3,Fitzgerald R C14

Affiliation:

1. Medical Research Council (MRC) Cancer Cell Unit, Hutchison/MRC Research Centre, Cambridge, UK

2. Cambridge Oesophago-Gastric Centre, Addenbrooke's Hospital, Cambridge, UK

3. Bioinformatics Core, Cancer Research UK Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK

4. Department of Gastroenterology, Addenbrooke's Hospital, Cambridge, UK

Abstract

Abstract Background Oesophageal adenocarcinoma is the commonest oesophageal malignancy in the West, but is staged using a system designed for squamous cell carcinoma. The aim was to develop and validate a staging system for oesophageal and junctional adenocarcinoma. Methods Patients with oesophageal adenocarcinoma (Siewert types I and II) undergoing oesophagectomy with curative intent were randomly assigned to generation (313 patients) and validation (131) data sets. Outcome in the generation data set was associated with histopathological features; a revised node (N) classification was derived using recursive partitioning and tested on the validation data set. Results A revised N classification based on number of involved lymph nodes (N0, none; N1, one to five; N2, six or more) was prognostically significant (P < 0·001). Patients with involved nodes on both sides of the diaphragm, regardless of number, had the same outcome as the N2 group. When applied to the validation data set, the revised classification (including nodal number and location) provided greater discrimination between node-positive patients than the existing system (P < 0·001). Conclusion A revised N classification based on number and location of involved lymph nodes provides improved prognostic power and incorporates features that may be useful before surgery in clinical management decisions.

Publisher

Oxford University Press (OUP)

Subject

Surgery

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3