Publication Name	World Journal of Clinical Oncology
Manuscript ID	109554
Country	China

Category	Gastroenterology & Hepatology
Manuscript Type	Editorial
Article Title	Modified predictive model incorporating the waist-to-hip ratio for advanced colorectal neoplasia: A step toward precision screening
Manuscript Source	Invited Manuscript
All Author List	Zong-Xian Zhao and Zong-Ju Hu
Funding Agency and Grant Number
Corresponding Author	Zong-Ju Hu, Department of Anorectal Surgery, Fuyang People’s Hospital, No. 501 Sanqing Road, Yingzhou District, Fuyang 236000, Anhui Province, China. hzj130123@126.com
Key Words	Advanced colorectal neoplasia; Abdominal obesity; Colorectal cancer screening; Risk scoring model; Waist-to-hip ratio
Core Tip	The new Asia-Pacific Colorectal Screening model, by incorporating the waist-to-hip ratio (WHR), better captures the metabolic risks driven by visceral fat and significantly improves the prediction accuracy. A high WHR (> 0.9 for men; > 0.85 for women) increases the risk of advanced colorectal neoplasms by 46%, enabling high-risk subgroups to receive prioritized colonoscopy. Future research should be expanded to multi-regional cohorts and incorporate more biomarkers (such as percentage of body fat, blood lipid and blood glucose levels), laboratory (stool DNA, polygenic risk scores, circulating tumor DNA) and imaging indicators (computed tomography-measured visceral fat area) to optimize the model.
Citation	Zhao ZX, Hu ZJ. Modified predictive model incorporating the waist-to-hip ratio for advanced colorectal neoplasia: A step toward precision screening. World J Clin Oncol 2025; In press

Received	2025-05-15 06:55
Peer-Review Started	2025-05-15 06:58
To Make the First Decision
Return for Revision	2025-06-04 01:59
Revised	2025-06-13 02:39
Second Decision	2025-07-09 02:39
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-07-09 08:21
Articles in Press	2025-07-09 08:21
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2218-4333 (online)
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