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Cancer Treatment-induced Ulcerative Mucositis Serves As a Significant Predictor of Burden of Illness Including Dysphagia, and Associated Disparities Among Hospitalized Cancer Patients

Overview
Specialties Critical Care
Oncology
Date 2024 Dec 12
PMID 39666090
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Abstract

Background: Our study aims to assess the association between chemotherapy-induced oral ulcerative mucositis (CT-UM) or radiotherapy-induced oral ulcerative mucositis (RT-UM) and the burden of illness (BOI), dysphagia, and disparities among patients with cancers of the oral cavity, lip, and pharynx (CLOP) and hematopoietic stem cell transplant patients (HSCT).

Methods: The study used US national data to investigate the association between UM and the BOI-length of stay (LOS) and dysphagia. The BOI was measured by length of stay (LOS), dysphagia, and associated disparities in these outcomes. This investigation was conducted using generalized linear models (glm).

Results: An analysis was conducted on a sample of 820 patients with CT-UM and 1010 patients with RT-UM, out of a total of 59,710 hospitalized CLOP patients, and 1380 patients with CT-UM from 10,885 total hospitalized HSCT patients. Among, CLOP patients, CT-UM status was associated with increased LOS (Coeff,1.54; 95% CI 1.36 to 1.74) and also associated with a greater likelihood of dysphagia (aOR, 2.11; 95% CI 1.52-2.95). However, among CLOP, RT-UM status was also associated with increased LOS (Coeff, 1.33; 95% CI 1.14-1.55), but there was no association of d RT-UM status and dysphagia (aOR = 1.21; 95% CI 0.84-1.77). Among HSCT patients, CT-UM status was associated with increased LOS and greater likelihood of dysphagia (Coeff, 1.09; 95% CI 1.02-1.16 and aOR = 2.08; 95% CI 1.11-3.9, respectively). Further, UM outcomes disproportionately affect females, Blacks, Hispanics, Medicaid recipients, and those with lower incomes.

Conclusion: The findings highlight the need for more effective methods of screening for and preventing UM in order to decrease BOI, especially in the context of systemic treatments. Additionally, new computational methods including artificial intelligence for mucositis prediction should be the center of future studies.

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