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Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model

PURPOSE: Osteoradionecrosis of the jaw (ORN) can manifest in varying severity. The aim of this study is to identify ORN risk factors and develop a novel classification to depict the severity of ORN. METHODS: Consecutive head-and-neck cancer (HNC) patients treated with curative-intent IMRT (≥ 45Gy) i...

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Autores principales: Watson, Erin E, Hueniken, Katrina, Lee, Junhyung, Huang, Sophie H, Maghrabi A, Amr El, Xu, Wei, Moreno, Amy C, Tsai, C. Jillian, Hahn, Ezra, McPartlin, Andrew J, Yao, Christopher MKL, Goldstein, David P, De Almeida, John R, Waldon, John N, Fuller, Clifton David, Hope, Andrew J, Ruggiero, Salvatore L, Glogauer, Michael, Hosni, Ali A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516072/
https://www.ncbi.nlm.nih.gov/pubmed/37745576
http://dx.doi.org/10.1101/2023.09.12.23295454
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author Watson, Erin E
Hueniken, Katrina
Lee, Junhyung
Huang, Sophie H
Maghrabi A, Amr El
Xu, Wei
Moreno, Amy C
Tsai, C. Jillian
Hahn, Ezra
McPartlin, Andrew J
Yao, Christopher MKL
Goldstein, David P
De Almeida, John R
Waldon, John N
Fuller, Clifton David
Hope, Andrew J
Ruggiero, Salvatore L
Glogauer, Michael
Hosni, Ali A
author_facet Watson, Erin E
Hueniken, Katrina
Lee, Junhyung
Huang, Sophie H
Maghrabi A, Amr El
Xu, Wei
Moreno, Amy C
Tsai, C. Jillian
Hahn, Ezra
McPartlin, Andrew J
Yao, Christopher MKL
Goldstein, David P
De Almeida, John R
Waldon, John N
Fuller, Clifton David
Hope, Andrew J
Ruggiero, Salvatore L
Glogauer, Michael
Hosni, Ali A
author_sort Watson, Erin E
collection PubMed
description PURPOSE: Osteoradionecrosis of the jaw (ORN) can manifest in varying severity. The aim of this study is to identify ORN risk factors and develop a novel classification to depict the severity of ORN. METHODS: Consecutive head-and-neck cancer (HNC) patients treated with curative-intent IMRT (≥ 45Gy) in 2011–2018 were included. Occurrence of ORN was identified from in-house prospective dental and clinical databases and charts. Multivariable logistic regression model was used to identify risk factors and stratify patients into high-risk and low-risk groups. A novel ORN classification system was developed to depict ORN severity by modifying existing systems and incorporating expert opinion. The performance of the novel system was compared to fifteen existing systems for their ability to identify and predict serious ORN event (jaw fracture or requiring jaw resection). RESULTS: ORN was identified in 219 out of 2732 (8%) consecutive HNC patients. Factors associated with high-risk of ORN were: oral-cavity or oropharyngeal primaries, received IMRT dose ≥60Gy, current/ex-smokers, and/or stage III-IV periodontal disease. The ORN rate for high-risk vs low-risk patients was 12.7% vs 3.1% (p<0.001) with an area-under-the-receiver-operating-curve (AUC) of 0.71. Existing ORN systems overclassified serious ORN events and failed to recognize maxillary ORN. A novel ORN classification system, RadORN, was proposed based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. This system detected serious ORN events in 5.7% of patients and statistically outperformed existing systems. CONCLUSION: We identified risk factors for ORN, and proposed a novel ORN classification system based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. It outperformed existing systems in depicting the seriousness of ORN, and may facilitate clinical care and clinical trials.
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spelling pubmed-105160722023-09-23 Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model Watson, Erin E Hueniken, Katrina Lee, Junhyung Huang, Sophie H Maghrabi A, Amr El Xu, Wei Moreno, Amy C Tsai, C. Jillian Hahn, Ezra McPartlin, Andrew J Yao, Christopher MKL Goldstein, David P De Almeida, John R Waldon, John N Fuller, Clifton David Hope, Andrew J Ruggiero, Salvatore L Glogauer, Michael Hosni, Ali A medRxiv Article PURPOSE: Osteoradionecrosis of the jaw (ORN) can manifest in varying severity. The aim of this study is to identify ORN risk factors and develop a novel classification to depict the severity of ORN. METHODS: Consecutive head-and-neck cancer (HNC) patients treated with curative-intent IMRT (≥ 45Gy) in 2011–2018 were included. Occurrence of ORN was identified from in-house prospective dental and clinical databases and charts. Multivariable logistic regression model was used to identify risk factors and stratify patients into high-risk and low-risk groups. A novel ORN classification system was developed to depict ORN severity by modifying existing systems and incorporating expert opinion. The performance of the novel system was compared to fifteen existing systems for their ability to identify and predict serious ORN event (jaw fracture or requiring jaw resection). RESULTS: ORN was identified in 219 out of 2732 (8%) consecutive HNC patients. Factors associated with high-risk of ORN were: oral-cavity or oropharyngeal primaries, received IMRT dose ≥60Gy, current/ex-smokers, and/or stage III-IV periodontal disease. The ORN rate for high-risk vs low-risk patients was 12.7% vs 3.1% (p<0.001) with an area-under-the-receiver-operating-curve (AUC) of 0.71. Existing ORN systems overclassified serious ORN events and failed to recognize maxillary ORN. A novel ORN classification system, RadORN, was proposed based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. This system detected serious ORN events in 5.7% of patients and statistically outperformed existing systems. CONCLUSION: We identified risk factors for ORN, and proposed a novel ORN classification system based on vertical extent of bone necrosis and presence/absence of exposed bone/fistula. It outperformed existing systems in depicting the seriousness of ORN, and may facilitate clinical care and clinical trials. Cold Spring Harbor Laboratory 2023-09-13 /pmc/articles/PMC10516072/ /pubmed/37745576 http://dx.doi.org/10.1101/2023.09.12.23295454 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Watson, Erin E
Hueniken, Katrina
Lee, Junhyung
Huang, Sophie H
Maghrabi A, Amr El
Xu, Wei
Moreno, Amy C
Tsai, C. Jillian
Hahn, Ezra
McPartlin, Andrew J
Yao, Christopher MKL
Goldstein, David P
De Almeida, John R
Waldon, John N
Fuller, Clifton David
Hope, Andrew J
Ruggiero, Salvatore L
Glogauer, Michael
Hosni, Ali A
Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model
title Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model
title_full Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model
title_fullStr Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model
title_full_unstemmed Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model
title_short Development and Standardization of a Classification System for Osteoradionecrosis: Implementation of a Risk-Based Model
title_sort development and standardization of a classification system for osteoradionecrosis: implementation of a risk-based model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10516072/
https://www.ncbi.nlm.nih.gov/pubmed/37745576
http://dx.doi.org/10.1101/2023.09.12.23295454
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