Clinicopathological and radiological characteristics and prediction of survival in colon cancer

doi:10.4251/wjgo.v17.i2.101516

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Feb 15, 2025 (publication date) through Mar 5, 2026

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World Journal of Gastrointestinal Oncology

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1948-5204

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Gastrointest Oncol. Feb 15, 2025; 17(2): 101516
Published online Feb 15, 2025. doi: 10.4251/wjgo.v17.i2.101516

Clinicopathological and radiological characteristics and prediction of survival in colon cancer

Ashok Kumar, Payal Kaw

Ashok Kumar, Payal Kaw, Department of Surgical Gastroenterology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow 226014, Uttar Pradesh, India

Author contributions: Kumar A conceptualized, supervised, and approved the manuscript; Kaw P reviewed literature and wrote the manuscript.

Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.

Corresponding author: Ashok Kumar, Department of Surgical Gastroenterology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Raebareli Road, Lucknow 226014, Uttar Pradesh, India. doc.ashokgupta@gmail.com

Received: September 17, 2024
Revised: October 14, 2024
Accepted: November 4, 2024
Published online: February 15, 2025
Processing time: 122 Days and 20.2 Hours

Abstract

There are various histological characteristics which have been proposed to predict the survival rate in colon cancer. However, there is no definitive model to accurately predict the survival. Therefore, it is important to find out one model for the prediction of survival in colon cancer which may also include the preoperative, and operative factors in addition to histopathology.

Keywords: Colon cancer; Survival; Predictors; Clinicopathological; Radiological

Core Tip: Although there are several prognostic predictors of colon cancer survival, there are none that are clinically useful. A nomogram developed from various clinical, radiological, and histological parameters can serve as a comprehensive and effective prognostic tool, which can assist clinicians in risk stratification and provide essential guidance for individualized treatment.