Stratification of Stage II Colon Cancer Using Recurrence Prediction Value

Author:

Mizuno Shodai1,Shigeta Kohei1,Kato Yujin1,Okui Jun12,Morita Satoru1,Sonal Swati3,Goldstone Robert3,Berger David3,Al-Masri Rama4,Al-Masri Mahmoud4,Tajima Yuki5,Kikuchi Hiroto5,Hirata Akira5,Nakadai Jumpei6,Baba Hideo6,Sugiura Kiyoaki7,Hoshino Go7,Seo Yuki7,Makino Akitsugu8,Suzumura Hirofumi8,Suzuki Yoshiyuki9,Adachi Yoko9,Shimada Takehiro9,Kondo Takayuki10,Matsui Shimpei1,Seishima Ryo1,Okabayashi Koji1,Kitagawa Yuko1,Kunitake Hiroko3

Affiliation:

1. Department of Surgery, Keio University School of Medicine, Tokyo, Japan

2. Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan

3. General and Gastrointestinal Surgery, Massachusetts General Hospital, MA, USA

4. Department of Surgery, King Hussein Cancer Center, Amman, Jordan

5. Department of Surgery, Hiratsuka City Hospital, Kanagawa, Japan

6. Department of Surgery, Saitama City Hospital, Saitama, Japan

7. Department of Surgery, Japan Red Cross Ashikaga Hospital, Tochigi, Japan

8. Department of Surgery, Saiseikai Utsunomiya Hospital, Tochigi, Japan

9. Department of Surgery, National Hospital Organization Tokyo Medical Center, Tokyo, Japan

10. Department of Surgery, Kawasaki Municipal Hospital, Kanagawa, Japan

Abstract

Objective: To create a recurrence prediction value (RPV) of high-risk factor and identify the patients with high risk of cancer recurrence. Summary Background Data: There are several high-risk factors known to lead to poor outcomes. Weighting each high-risk factor based on their association with increased risk of cancer recurrence can provide a more precise understanding of risk of recurrence. Methods: We performed a multi-institutional international retrospective analysis of patients with Stage II colon cancer patients who underwent surgery from 2010 to 2020. Patient data from a multi-institutional database were used as the Training data, and data from a completely separate international database from two countries were used as the Validation data. The primary endpoint was recurrence-free survival (RFS). Results: A total of 739 patients were included from Training data. To validate the feasibility of RPV, 467 patients were included from Validation data. Training data patients were divided into RPV low (n = 564) and RPV high (n = 175). Multivariate analysis revealed that risk of recurrence was significantly higher in the RPV high than the RPV low (Hazard ratio (HR) 2.628; 95% confidence interval (CI) 1.887-3.660; P < 0.001). Validation data patients were divided into two groups (RPV low, n = 420) and RPV high (n = 47). Multivariate analysis revealed that risk of recurrence was significantly higher in the RPV high than the RPV low (HR 3.053; 95% CI 1.962-4.750; P < 0.001). Conclusions: RPV can identify Stage II colon cancer patients with high risk of cancer recurrence world-wide.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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