BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
9/5/2025 6:36:18 AM | Browse: 506 | Download: 628
 |
Received |
|
2025-05-20 07:07 |
 |
Peer-Review Started |
|
2025-05-20 07:07 |
 |
First Decision by Editorial Office Director |
|
2025-06-10 08:36 |
 |
Return for Revision |
|
2025-06-10 08:36 |
 |
Revised |
|
2025-07-05 19:28 |
 |
Publication Fee Transferred |
|
|
 |
Second Decision by Editor |
|
2025-08-11 02:49 |
 |
Second Decision by Editor-in-Chief |
|
|
 |
Final Decision by Editorial Office Director |
|
2025-08-13 09:25 |
 |
Articles in Press |
|
2025-08-13 09:25 |
 |
Edit the Manuscript by Language Editor |
|
|
 |
Typeset the Manuscript |
|
2025-08-29 01:03 |
 |
Publish the Manuscript Online |
|
2025-09-05 06:36 |
| ISSN |
1007-9327 (print) and 2219-2840 (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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Prospective Study |
| Article Title |
Serum homocysteine-based traffic light triage colonoscopy screening in colorectal cancer at-risk patients: A prospective cohort study
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Francisco Xavier Cano, José María Duque, Lucia Seoane, Miguel Puga-Tejada, Alejandra Espinoza de los Monteros, Pablo Bermeo, Eduardo Junquera, Daniel Pérez, Jimmy Martin-Delgado, Monica Santelli, Carla Pérez and Francisco Javier Pérez Rivera |
| ORCID |
|
| Funding Agency and Grant Number |
|
| Corresponding Author |
Francisco Xavier Cano, Doctorate Student, MD, Professor, Researcher, Instituto de Investigación e Innovación en Salud Integral, Universidad Católica de Santiago de Guayaquil, Av. Pdte. Carlos Julio Arosemena Tola, Guayaquil 090615, Guayas, Ecuador. francisco.cano@cu.ucsg.edu.ec |
| Key Words |
Homocysteine; Predictive value of a test; Colonoscopy; Colorectal cancer; Cancer screening |
| Core Tip |
In this study, we propose a traffic-light triage model based on serum homocysteine levels, sex, and age to prioritize colonoscopy after a positive fecal occult blood test. A green light (≤ 12 micromoles per liter in both sexes) indicates low risk and allows colonoscopy within three months. A yellow light (12-15 micromoles) in men suggests high-risk polyps and requires colonoscopy within one month. In women, the same range is already associated with adenocarcinoma and warrants immediate intervention. A red light (> 15 micromoles) in either sex is strongly associated with cancer and indicates the need for urgent colonoscopy. |
| Publish Date |
2025-09-05 06:36 |
| Citation |
Cano FX, Duque JM, Seoane L, Puga-Tejada M, Espinoza de los Monteros A, Bermeo P, Junquera E, Pérez D, Martin-Delgado J, Santelli M, Pérez C, Pérez Rivera FJ. Serum homocysteine-based traffic light triage colonoscopy screening in colorectal cancer at-risk patients: A prospective cohort study. World J Gastroenterol 2025; 31(34): 109718
|
| URL |
https://www.wjgnet.com/1007-9327/full/v31/i34/109718.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v31.i34.109718 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.