Evidence map›Paper›PMID 37745576›Full record

ArticlemedRxiv : the preprint server for health sciences2023

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

Erin E Watson, Katrina Hueniken, Junhyung Lee, Sophie H Huang, Amr El Maghrabi A, Wei Xu, Amy C Moreno, C Jillian Tsai, Ezra Hahn, Andrew J McPartlin and 9 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors at 5 institutions in 2 countries.

Erin E WatsonDepartment of Dental Oncology, Princess Margaret Cancer Centre.
Katrina HuenikenDepartment of Biostatistics, University Health Network.
Junhyung LeeDepartment of Dental Oncology, Princess Margaret Cancer Centre.
Sophie H HuangDepartment of Radiation Oncology, Princess Margaret Cancer Centre; University of Toronto.
Amr El Maghrabi ADepartment of Dental Oncology, Princess Margaret Cancer Centre.
Wei XuDepartment of Biostatistics, University Health Network.
Amy C MorenoThe University of Texas MD Anderson Cancer Center, Department of Radiaion Oncology.
C Jillian TsaiDepartment of Radiation Oncology, Princess Margaret Cancer Centre; University of Toronto.
Ezra HahnDepartment of Radiation Oncology, Princess Margaret Cancer Centre; University of Toronto.
Andrew J McPartlinDepartment of Radiation Oncology, Princess Margaret Cancer Centre; University of Toronto.
Christopher Mkl YaoDepartment of Otolaryngology - Head & Neck Surgery, University Health Network; University of Toronto.
David P GoldsteinDepartment of Otolaryngology - Head & Neck Surgery, University Health Network; University of Toronto.
John R De AlmeidaDepartment of Otolaryngology - Head & Neck Surgery, University Health Network; University of Toronto.
John N WaldonDepartment of Radiation Oncology, Princess Margaret Cancer Centre; University of Toronto.
Clifton David FullerThe University of Texas MD Anderson Cancer Center, Department of Radiaion Oncology.
Andrew J HopeDepartment of Radiation Oncology, Princess Margaret Cancer Centre; University of Toronto.
Salvatore L RuggieroDepartment of Oral and Maxillofacial Surgery, Stony Brook University.
Michael GlogauerFaculty of Dentistry, University of Toronto.
Ali A HosniDepartment of Radiation Oncology, Princess Margaret Cancer Centre; University of Toronto.
University of Toronto · CAUniversity Health Network · CAPrincess Margaret Cancer Centre · CAThe University of Texas MD Anderson Cancer Center · USHofstra University · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Establish Objective Clinical Outcome Measures for Mandibular OsteoradionecrosisR01DE025248 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LAI, STEPHEN Y · 2016 to 2020
$2.9M
Longitudinal Spatial-Nonspatial Decision Support for Competing Outcomes in Head and Neck Cancer TherapyR01CA258827 · NCI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI CANAHUATE, GUADALUPE, FULLER, CLIFTON DAVID · 2021 to 2025
$2.9M
Quantitative Imaging Biomarker Prospective Validation of Dynamic Contrast-Enhanced MRI as a Metric of Orodental Injury After Radiotherapy (QI-ProVE-MRI)U01DE032168 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Clifton David Fuller, STEPHEN Y LAI · 2023 to 2026
$2.8M
Provider and Patient-generated Remote Oro-Dental Health Electronic Data Capture for Algorithmic Longitudinal Evaluation and Risk-Assessment (PROHEALER)K01DE030524 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MORENO, AMY CATHERINE · 2022 to 2024
$479k
Radiation-specific Automated Dental Dose Distributions via Machine-learning based Mapping for Accurate Predictions of (Peri)odontal Problems (RADMAP)R21DE031082 · NIDCR · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MORENO, AMY CATHERINE · 2021 to 2022
$452k
NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA258827NIDCR NIH HHS K01 DE030524NIDCR NIH HHS R01 DE025248NIDCR NIH HHS R21 DE031082NIDCR NIH HHS U01 DE032168
6 · The paper itself

Abstract

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.

Identifiers

PMID37745576
PMCPMC10516072
OpenAlexW4386698727

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.