Study of prevalence and risk factors of chemotherapy-induced mucositis in gastrointestinal cancer using machine learning models - Research findings

Aug 5, 2026

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Chemotherapy-induced mucositis (CIM) significantly affects clinical outcomes and reduces quality of life in patients with gastrointestinal cancer. This prospective study determines CIM incidence, severity, and risk factors using a machine learning toxicity prediction model (ML-TPM). During winter 2018–2019, 447 chemotherapy patients completed structured questionnaires on demographics, CIM outcomes, and prophylactic measures. CIM occurred in 73.4% of patients; key associations involved gender, number of chemotherapy cycles, platinum-based regimens, and irinotecan, with diarrhea showing additional links to surgical history and probiotics.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages9

Reading Time23 min

AccessFree to download

Objective

Methods

Machine learning toxicity prediction model (ML-TPM)

Results

Cohort characteristics and CIM prevalence

Symptom distribution and treatment discontinuation

Risk-factor associations

Conclusion

Keywords

TYPE Original Research PUBLISHED 28 September 2023 DOI 10.3389/fonc.2023.1138992 OPEN ACCESS EDITED BY Elizabeth S. Fernandes, Pele´ Pequeno Prncipe Research Institute, Brazil REVIEWED BY Reza Shirkoohi, Tehran University of Medical Science, Iran Neha Nanda, Harvard Medical School, United States *CORRESPONDENCE Meng Qiu [qiumeng@wchscu.cn](qiumeng@wchscu.cn) †These authors have contributed equally to this work RECEIVED 06 January 2023 ACCEPTED 30 August 2023 PUBLISHED 28 September 2023 CITATION Huang L, Ye X, Wu F, Wang X and Qiu M (2023) Study of prevalence and risk factors of chemotherapy-induced mucositis in gastrointestinal cancer using machine learning models. Front. Oncol. 13:1138992 . doi: 10.3389/fonc.2023.1138992 COPYRIGHT © 2023 Huang, Ye, Wu, Wang and Qiu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Study of prevalence and risk factors of chemotherapyinduced mucositis in gastrointestinal cancer using machine learning models Lin Huang 1†, Xianhui Ye 2†, Fengqing Wu 3, Xiuyun Wang 3 and Meng Qiu 2* 1 Division of Medical Oncology, Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China, 2 Division of Medical Oncology, Colorectal Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China, 3 Department of Abdominal Cancer, Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China Objective: Chemotherapy-induced mucositis (CIM) signiﬁcantly impacts clinical outcomes and diminishes the quality of life in patients with gastrointestinal cancer. This study aims to prospectively determine the incidence, severity, and underlying risk factors associated with CIM in this patient population. Methods: To achieve this objective, we introduce a novel Machine Learningbased Toxicity Prediction Model (ML-TPM) designed to analyze the risk factors contributing to CIM development in gastrointestinal cancer patients. Within the winter season spanning from December 15th, 2018 to January 14th, 2019, we conducted in-person interviews with patients undergoing chemotherapy for gastrointestinal cancer . These interviews encompassed comprehensive questionnaires pertaining to patient demographics, CIM incidence, severity, and any supplementary prophylactic measures employed. Results: The study encompassed a cohort of 447 participating patients who provided complete questionnaire responses (100%) . Of these, 328 patients (73 . 4%) reported experiencing CIM during the course of their treatment. Notably, CIM-induced complications led to treatment discontinuation in 14 patients (3%) . The most frequently encountered CIM symptoms were diarrhea (41.6%), followed by nausea (37.8%), vomiting (25.1%), abdominal pain (21%), gastritis (10 . 5%), and oral pain (10 . 3%) . Supplementary prophylaxis was administered to approximately 62% of the patients. The analysis revealed signiﬁcant correlations between the overall incidence of CIM and gender (p=0.015), number of chemotherapy cycles exceeding one (p=0.039), utilization of platinum-based regimens (p=0.039), and administration of irinotecan (p=0 . 003) . Speciﬁcally, the incidence of diarrhea exhibited positive correlations with prior surgical history (p=0.037), irinotecan treatment (p=0.021), and probiotics usage (p=0 . 035) . Conversely, diarrhea incidence demonstrated an adverse correlation with platinum-based treatment (p=0 . 026) . Conclusion: In conclusion, this study demonstrates the successful implementation of the ML-TPM model for automating toxicity prediction with Frontiers

FAQs

What is the main objective of the study on chemotherapy-induced mucositis?

The study aims to prospectively determine the incidence, severity, and underlying risk factors for CIM in patients with gastrointestinal cancer receiving chemotherapy.

How was the machine learning approach used to evaluate toxicity risk?

A machine learning-based toxicity prediction model (ML-TPM) was introduced to analyze risk factors contributing to CIM development using questionnaire data from interviewed patients.

Which factors were significantly associated with the incidence of CIM?

Overall CIM incidence correlated with gender, greater than one chemotherapy cycle, use of platinum-based regimens, and administration of irinotecan.

Aug 5, 2026

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