BPG is committed to discovery and dissemination of knowledge
Correspondence
Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastrointest Oncol. Apr 15, 2026; 18(4): 114373
Published online Apr 15, 2026. doi: 10.4251/wjgo.v18.i4.114373
Letter to the Editor: Toward better mortality prediction in intensive care unit-admitted colorectal cancer patients
Marco Diaz-Cordova, Ishani Sharma, Kenji Okumura
Marco Diaz-Cordova, Ishani Sharma, Kenji Okumura, Department of Surgery, Westchester Medical Center and New York Medical College, Valhalla, NY 10595, United States
Author contributions: Diaz-Cordova M and Sharma I contributed with writing, editing and literature review; Okumura K provided writing, senior editing, and final revisions of the manuscript.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
Corresponding author: Kenji Okumura, MD, Associate Faculty, Department of Surgery, Westchester Medical Center and New York Medical College, 100 Woods Road, Valhalla, NY 10595, United States. kenji.okumura@wmchealth.org
Received: September 17, 2025
Revised: November 26, 2025
Accepted: January 6, 2026
Published online: April 15, 2026
Processing time: 203 Days and 8.4 Hours
Core Tip

Core Tip: Colorectal cancer remains a leading cause of cancer-related mortality globally. While screening and treatment have increased disease prevalence, reliable predictors of 90-day mortality in intensive care unit-colorectal cancer treated patients are lacking. Prognostic scores such as Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment show potential but require further validation. Additionally, factors like frailty, cancer stage, socioeconomic status, and surgical urgency may influence outcomes/prognosis. Currently, no single tool adequately captures the complexity of prognosis in this population, highlighting the need for prospective studies to develop a more comprehensive and accurate prognostic model.