Repository logo
  • English
  • 中文
Log In
Have you forgotten your password?
  1. Home
  2. College of Public Health / 公共衛生學院
  3. Epidemiology and Preventive Medicine / 流行病學與預防醫學研究所
  4. Predicting Colon Cancer-Specific Survival for the Asian Population Using National Cancer Registry Data from Taiwan
 
  • Details

Predicting Colon Cancer-Specific Survival for the Asian Population Using National Cancer Registry Data from Taiwan

Journal
Annals of Surgical Oncology
Journal Volume
29
Journal Issue
2
Pages
853-863
Date Issued
2022
Author(s)
Chan H.-C.
Huang C.-C.
Huang C.-C.
Amrita Chattopadhyay  
Yeh K.-H.
WEN-CHUNG LEE  
CHUN-JU CHIANG  
Lee H.-Y.
Cheng S.H.-C.
TZU-PIN LU  
DOI
10.1245/s10434-021-10646-2
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113407576&doi=10.1245%2fs10434-021-10646-2&partnerID=40&md5=46363c071510cb7546ab6528de16176f
https://scholars.lib.ntu.edu.tw/handle/123456789/605026
Abstract
Colon cancer is the third most incident and life-threatening cancer in Taiwan. A comprehensive survival prediction system would greatly benefit clinical practice in this area. This study was designed to develop an accurate prognostic model for colon cancer patients by using clinicopathological variables obtained from the Taiwan Cancer Registry database. We analyzed 20,218 colon cancer patients from the Taiwan Cancer Registry database, who were diagnosed between 2007 and 2015, were followed up until December 31, 2017, and had undergone curative surgery. We proposed two prognostic models, with different combinations of predictors. The first model used only traditional clinical features. The second model included several colon cancer site-specific factors (circumferential resection margin, perineural invasion, obstruction, and perforation), in addition to the traditional features. Both prediction models were developed by using a Cox proportional hazards model. Furthermore, we investigated whether race is a significant predictor of survival in colon cancer patients by using Model 1 on the Surveillance, Epidemiology, and End Results (SEER) cancer registry dataset. The proposed models displayed a robust prediction performance (all Harrell's c-index >0.8). For both the calibration and validation steps, the differences between the predicted and observed mortality were mostly less than 5%. The prediction model (Model 1) is an effective predictor of survival regardless of the ethnic background of patients and can potentially help to provide better prediction of colon cancer-specific survival outcomes, thus allowing physicians to improve treatment plans.
SDGs

[SDGs]SDG3

[SDGs]SDG5

Publisher
Springer Science and Business Media Deutschland GmbH
Type
journal article

臺大位居世界頂尖大學之列,為永久珍藏及向國際展現本校豐碩的研究成果及學術能量,圖書館整合機構典藏(NTUR)與學術庫(AH)不同功能平台,成為臺大學術典藏NTU scholars。期能整合研究能量、促進交流合作、保存學術產出、推廣研究成果。

To permanently archive and promote researcher profiles and scholarly works, Library integrates the services of “NTU Repository” with “Academic Hub” to form NTU Scholars.

總館學科館員 (Main Library)
醫學圖書館學科館員 (Medical Library)
社會科學院辜振甫紀念圖書館學科館員 (Social Sciences Library)

開放取用是從使用者角度提升資訊取用性的社會運動,應用在學術研究上是透過將研究著作公開供使用者自由取閱,以促進學術傳播及因應期刊訂購費用逐年攀升。同時可加速研究發展、提升研究影響力,NTU Scholars即為本校的開放取用典藏(OA Archive)平台。(點選深入了解OA)

  • 請確認所上傳的全文是原創的內容,若該文件包含部分內容的版權非匯入者所有,或由第三方贊助與合作完成,請確認該版權所有者及第三方同意提供此授權。
    Please represent that the submission is your original work, and that you have the right to grant the rights to upload.
  • 若欲上傳已出版的全文電子檔,可使用Open policy finder網站查詢,以確認出版單位之版權政策。
    Please use Open policy finder to find a summary of permissions that are normally given as part of each publisher's copyright transfer agreement.
  • 網站簡介 (Quickstart Guide)
  • 使用手冊 (Instruction Manual)
  • 線上預約服務 (Booking Service)
  • 方案一:臺灣大學計算機中心帳號登入
    (With C&INC Email Account)
  • 方案二:ORCID帳號登入 (With ORCID)
  • 方案一:定期更新ORCID者,以ID匯入 (Search for identifier (ORCID))
  • 方案二:自行建檔 (Default mode Submission)
  • 方案三:學科館員協助匯入 (Email worklist to subject librarians)

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science