Related Experiment Video
Updated: Sep 18, 2025
Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition
Published on: March 11, 2021
Defining the optimal radiation thresholds for Stratifying jaw osteoradionecrosis risk in head and neck cancer
Mohammad Moharrami1, Erin Watson1, Shao Hui Huang2
1Faculty of Dentistry, University of Toronto, Toronto, ON, Canada; Department of Dental Oncology, Princess Margaret Cancer Centre, Toronto, ON, Canada.
Purpose:
Osteoradionecrosis (ORN) of the jaw is a serious complication following radiation therapy (RT) for head and neck cancer (HNC). This study aimed to establish optimal thresholds for dose-volume histogram (DVH) parameters to differentiate between low- and high-risk HNC groups for developing ORN while accounting for the competing risk of death.
Methods:
A retrospective cohort of HNC patients treated with curative-intent RT between 2011 and 2018 was analyzed. ORN was defined as a binary outcome, with ClinRad grades ≥ 1 considered positive. Maximally selected rank statistics were employed to determine the optimal DVH cutoff points, with risk group discrimination assessed using Gray's statistics and the cumulative incidence function (CIF). Adjusted cause-specific hazard ratios (csHR) and sub-distribution hazard ratios (sdHR) were calculated using Cox proportional hazards and Fine-Gray models for dichotomized DVH parameters, controlling for established ORN risk factors.
Results:
Among 2,466 patients, 183 developed ORN. A threshold for D10cc of 59.2 Gy (95 % CI: 56.1-60.6) was identified as the most discriminative parameter, producing significantly different CIF curves between risk groups. Adjusted regression analyses demonstrated that dichotomized D10cc was significantly associated with ORN, with a csHR of 2.54 (95 % CI: 1.80-3.58) and a sdHR of 2.27 (95 % CI: 1.59-3.25). Additionally, periodontal condition, primary tumor site, and dental insurance coverage were significant predictors in all multivariable models.
Conclusions:
The identification of clinically relevant DVH thresholds improves risk stratification for ORN. Integrating these thresholds into pre- and post-RT treatment planning may enhance evidence-based clinical decision-making and ultimately improve patient outcomes.
