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Predicting Nomogram for Severe Oral Mucositis in Patients with Nasopharyngeal Carcinoma during Intensity-Modulated Radiation Therapy: A Retrospective Cohort Study

Background: Oral mucositis is an acute adverse reaction with high incidence during radiotherapy. Severe oral mucositis can seriously affect patients’ quality of life and compliance with radiotherapy. The aim of this study was to identify the risk factors for severe oral mucositis and to develop a no...

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Autores principales: Liu, Zhibing, Huang, Lulu, Wang, Housheng, Shi, Zhiling, Huang, Yaqin, Liang, Lixing, Wang, Rensheng, Hu, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857735/
https://www.ncbi.nlm.nih.gov/pubmed/36661666
http://dx.doi.org/10.3390/curroncol30010017
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author Liu, Zhibing
Huang, Lulu
Wang, Housheng
Shi, Zhiling
Huang, Yaqin
Liang, Lixing
Wang, Rensheng
Hu, Kai
author_facet Liu, Zhibing
Huang, Lulu
Wang, Housheng
Shi, Zhiling
Huang, Yaqin
Liang, Lixing
Wang, Rensheng
Hu, Kai
author_sort Liu, Zhibing
collection PubMed
description Background: Oral mucositis is an acute adverse reaction with high incidence during radiotherapy. Severe oral mucositis can seriously affect patients’ quality of life and compliance with radiotherapy. The aim of this study was to identify the risk factors for severe oral mucositis and to develop a nomogram for predicting severe oral mucositis in patients with nasopharyngeal carcinoma. Methods: One hundred and ninety patients with nasopharyngeal carcinoma were retrospectively screened in this study. Least absolute shrinkage and selection operator regression and multivariate logistic regression analyses were performed to identify the best predictors of severe oral mucositis. A nomogram was constructed based on the factors. Finally, the discriminative ability of the nomogram was evaluated. Results: Four independent factors predicting severe oral mucositis were identified: age, N stage, the cycle of induction chemotherapy, and dose-volumetric parameter V40 (%) of oral cavity. The area under the receiver of operating characteristic curve of the nomogram was 0.759 (95% confidence interval: 0.691–0.827). Conclusions: A predictive nomogram for severe oral mucositis was established and validated in this study. The nomogram provides a reliable and practical model for clinically predicting the probability of severe oral mucositis in patients with nasopharyngeal carcinoma before intensity-modulated radiation therapy.
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spelling pubmed-98577352023-01-21 Predicting Nomogram for Severe Oral Mucositis in Patients with Nasopharyngeal Carcinoma during Intensity-Modulated Radiation Therapy: A Retrospective Cohort Study Liu, Zhibing Huang, Lulu Wang, Housheng Shi, Zhiling Huang, Yaqin Liang, Lixing Wang, Rensheng Hu, Kai Curr Oncol Article Background: Oral mucositis is an acute adverse reaction with high incidence during radiotherapy. Severe oral mucositis can seriously affect patients’ quality of life and compliance with radiotherapy. The aim of this study was to identify the risk factors for severe oral mucositis and to develop a nomogram for predicting severe oral mucositis in patients with nasopharyngeal carcinoma. Methods: One hundred and ninety patients with nasopharyngeal carcinoma were retrospectively screened in this study. Least absolute shrinkage and selection operator regression and multivariate logistic regression analyses were performed to identify the best predictors of severe oral mucositis. A nomogram was constructed based on the factors. Finally, the discriminative ability of the nomogram was evaluated. Results: Four independent factors predicting severe oral mucositis were identified: age, N stage, the cycle of induction chemotherapy, and dose-volumetric parameter V40 (%) of oral cavity. The area under the receiver of operating characteristic curve of the nomogram was 0.759 (95% confidence interval: 0.691–0.827). Conclusions: A predictive nomogram for severe oral mucositis was established and validated in this study. The nomogram provides a reliable and practical model for clinically predicting the probability of severe oral mucositis in patients with nasopharyngeal carcinoma before intensity-modulated radiation therapy. MDPI 2022-12-23 /pmc/articles/PMC9857735/ /pubmed/36661666 http://dx.doi.org/10.3390/curroncol30010017 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Zhibing
Huang, Lulu
Wang, Housheng
Shi, Zhiling
Huang, Yaqin
Liang, Lixing
Wang, Rensheng
Hu, Kai
Predicting Nomogram for Severe Oral Mucositis in Patients with Nasopharyngeal Carcinoma during Intensity-Modulated Radiation Therapy: A Retrospective Cohort Study
title Predicting Nomogram for Severe Oral Mucositis in Patients with Nasopharyngeal Carcinoma during Intensity-Modulated Radiation Therapy: A Retrospective Cohort Study
title_full Predicting Nomogram for Severe Oral Mucositis in Patients with Nasopharyngeal Carcinoma during Intensity-Modulated Radiation Therapy: A Retrospective Cohort Study
title_fullStr Predicting Nomogram for Severe Oral Mucositis in Patients with Nasopharyngeal Carcinoma during Intensity-Modulated Radiation Therapy: A Retrospective Cohort Study
title_full_unstemmed Predicting Nomogram for Severe Oral Mucositis in Patients with Nasopharyngeal Carcinoma during Intensity-Modulated Radiation Therapy: A Retrospective Cohort Study
title_short Predicting Nomogram for Severe Oral Mucositis in Patients with Nasopharyngeal Carcinoma during Intensity-Modulated Radiation Therapy: A Retrospective Cohort Study
title_sort predicting nomogram for severe oral mucositis in patients with nasopharyngeal carcinoma during intensity-modulated radiation therapy: a retrospective cohort study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857735/
https://www.ncbi.nlm.nih.gov/pubmed/36661666
http://dx.doi.org/10.3390/curroncol30010017
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