Publication Name	World Journal of Gastrointestinal Oncology
Manuscript ID	101379
Country	China

Received	2024-09-12 09:45
Peer-Review Started	2024-09-12 09:45
To Make the First Decision
Return for Revision	2024-10-28 07:59
Revised	2024-11-04 14:42
Second Decision	2024-11-21 02:42
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-11-22 13:27
Articles in Press	2024-11-22 13:27
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-12-17 09:09
Publish the Manuscript Online	2025-01-18 08:12

ISSN	1948-5204 (online)
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Category	Gastroenterology & Hepatology
Manuscript Type	Letter to the Editor
Article Title	Advancements and challenges in esophageal carcinoma prognostic models: A comprehensive review and future directions
Manuscript Source	Invited Manuscript
All Author List	Jia Chen and Qi-Chang Xing
ORCID	Author(s) ORCID Number Qi-Chang Xing http://orcid.org/0000-0001-7186-8841
Funding Agency and Grant Number	Funding Agency Grant Number Scientific Research Program of Hunan Provincial Health Commission B202313018450
Corresponding Author	Qi-Chang Xing, Department of Clinical Pharmacy, Xiangtan Central Hospital, No. 120 Heping Road, Xiangtan 411100, Hunan Province, China. 67324457@qq.com
Key Words	Predictive model; Machine learning; Esophageal carcinoma; Survival rate; Factors
Core Tip	Clinical prediction model has great development space and practical value in the medical field. Despite significant efforts to explore the prognosis of esophageal carcinoma, current prognostic models remain imperfect. Traditional predictive models, such as Cox proportional hazards regression and logistic regression, are widely used but often lack effective evaluation mechanisms to determine their optimal performance. Moreover, due to limitations in sample size and predictive factors, the reproducibility of these models is poor, which severely restricts their broad application in clinical practice. Therefore, it is necessary to further explore and select more appropriate analytical methods to construct more accurate and reliable predictive models, thereby better serving clinical needs.
Publish Date	2025-01-18 08:12
Citation	<p>Chen J, Xing QC. Advancements and challenges in esophageal carcinoma prognostic models: A comprehensive review and future directions. <i>World J Gastrointest Oncol</i> 2025; 17(2): 101379</p>
URL	https://www.wjgnet.com/1948-5204/full/v17/i2/101379.htm
DOI	https://dx.doi.org/10.4251/wjgo.v17.i2.101379

Full Article (PDF)	WJGO-17-101379-with-cover.pdf
Manuscript File	101379_Auto_Edited_100522.docx
Answering Reviewers	101379-answering-reviewers.pdf
Audio Core Tip	101379-audio.m4a
Conflict-of-Interest Disclosure Form	101379-conflict-of-interest-statement.pdf
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Non-Native Speakers of English Editing Certificate	101379-non-native-speakers.pdf
Peer-review Report	101379-peer-reviews.pdf
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Scientific Editor Work List	101379-scientific-editor-work-list.pdf
CrossCheck Report	101379-crosscheck-report.pdf