Publication Name	World Journal of Gastrointestinal Oncology
Manuscript ID	102459
Country	China

Received	2024-10-21 03:33
Peer-Review Started	2024-10-21 03:33
To Make the First Decision
Return for Revision	2025-02-06 21:38
Revised	2025-02-17 14:09
Second Decision	2025-03-10 02:37
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-03-10 08:12
Articles in Press	2025-03-10 08:12
Publication Fee Transferred	2025-02-19 01:02
Edit the Manuscript by Language Editor
Typeset the Manuscript	2025-04-08 02:25
Publish the Manuscript Online	2025-05-15 10:28

ISSN	1948-5204 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Copyright	© The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher	Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website	http://www.wjgnet.com

Category	Research & Experimental Medicine
Manuscript Type	Retrospective Study
Article Title	Development and validation of machine learning nomograms for predicting survival in stage IV pancreatic cancer: A retrospective study
Manuscript Source	Unsolicited Manuscript
All Author List	Kun Huang, Zhu Chen, Xin-Zhu Yuan, Yun-Shen He, Xiang Lan and Chen-You Du
ORCID	Author(s) ORCID Number Xiang Lan http://orcid.org/0009-0004-5016-1301
Funding Agency and Grant Number	Funding Agency Grant Number Mianyang Health and Health Committee 2023 Scientific Research Project 202309 Chengdu University of Traditional Chinese Medicine University-Hospital Joint Innovation Fund LH202402010 Mianyang Chinese Medicine Association 2024 Traditional Chinese Medicine Inheritance and Innovation Science and Technology Project MYSZYYXH-202426
Corresponding Author	Xiang Lan, MD, Professor, Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuanjiagang, Yuzhong District, Chongqing 400000, China. lanxiangkeyan@163.com
Key Words	Stage IV pancreatic ductal adenocarcinoma; Prognosis; Surveillance Epidemiology, and End Results Program; Machine learning; Cancer survival; Prognostic model
Core Tip	This study develops and validates a machine learning-based nomogram to predict survival in patients with stage IV pancreatic ductal adenocarcinoma. Using data from the Surveillance, Epidemiology, and End Results program, the model integrates prognostic factors and demonstrates high accuracy in predicting cancer-specific survival and overall survival at various time points. This nomogram offers a personalized approach to survival prediction, potentially guiding clinical decision-making and treatment strategies for advanced pancreatic cancer patients.
Publish Date	2025-05-15 10:28
Citation	<p>Huang K, Chen Z, Yuan XZ, He YS, Lan X, Du CY. Development and validation of machine learning nomograms for predicting survival in stage IV pancreatic cancer: A retrospective study. <i>World J Gastrointest Oncol</i> 2025; 17(5): 102459</p>
URL	https://www.wjgnet.com/1948-5204/full/v17/i5/102459.htm
DOI	https://dx.doi.org/10.4251/wjgo.v17.i5.102459

Full Article (PDF)	WJGO-17-102459-with-cover.pdf
Manuscript File	102459_Auto_Edited_011114.docx
Answering Reviewers	102459-answering-reviewers.pdf
Audio Core Tip	102459-audio.wav
Biostatistics Review Certificate	102459-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form	102459-conflict-of-interest-statement.pdf
Copyright License Agreement	102459-copyright-assignment.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	102459-foundation-statement.pdf
Signed Informed Consent Form(s) or Document(s)	102459-informed-consent-statement.pdf
Institutional Review Board Approval Form or Document	102459-institutional-review-board-statement.pdf
Non-Native Speakers of English Editing Certificate	102459-non-native-speakers.pdf
Peer-review Report	102459-peer-reviews.pdf
Scientific Misconduct Check	102459-scientific-misconduct-check.png
Scientific Editor Work List	102459-scientific-editor-work-list.pdf
CrossCheck Report	102459-crosscheck-report.pdf