ArticleInternational journal of radiation oncology, biology, physics2026
Multi-institutional Normal Tissue Complication Probability (NTCP) Prediction Model for Mandibular Osteoradionecrosis: Results from the PREDMORN Study.
Article in International journal of radiation oncology, biology, physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Personalized Prevention of Osteoradionecrosis of the Jaws: From Clinical Risk Profiling and Site-Specific Dosimetry to Artificial Intelligence and Individualized Treatment-Effect Estimation.Journal of personalized medicine · 2026Review
- Clinical and dosimetric dataset of time-to-event normal tissue complication probability for osteoradionecrosis.Scientific data · 2026Article
- Beyond the dose-volume histogram: a critical appraisal of normal tissue complication probability modelling for osteoradionecrosis of the jaw and a strategic framework for clinical translation.Frontiers in oncology · 2026Article
- Radiation-specific Automated Dosimetric dental, Mandible, and maxilla Annotation for Predicting Periodontal Problems (RADMAP): A semi-automated tool for dosimetric oral risk communication and osteoradionecrosis assessment.medRxiv : the preprint server for health sciences · 2025Article
- Data-centric artificial intelligence and cancer research: construction of a real-world head and neck treatment data repository.ESMO real world data and digital oncology · 2025Article
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Authors and funding
32 authors.
Funding
Abstract
purposeMandibular osteoradionecrosis (ORN) is a severe late complication affecting patients with head and neck cancer (HNC) treated with radiation therapy (RT) that significantly impacts patients' quality of life and can require costly interventions. Although radiation dose is a key factor, other clinical and demographic risk factors also influence ORN development. Previous predictive models have primarily been single-institutional, limiting their generalizability. In this first analysis from the PREDMORN Consortium, we have aimed to reproduce existing statistical association and modeling analyses on the largest and most diverse mandibular ORN cohort worldwide to allow comparison with previous studies. METHODS AND MATERIALS: This retrospective multi-institutional study included 3928 patients with HNC (622 ORN cases) from 8 institutions. Clinical, demographic, and dosimetric variables were analyzed to develop a prediction model (any grade ORN vs no ORN) using forward stepwise logistic regression with correlation-based variable preselection. The ORN normal tissue complication probability (NTCP) model was developed on 80% of data from 6 institutions, tested on the remaining unseen 20%, and externally validated on a matched cohort (58 patients, 19 ORN cases) and a large population-based cohort (2687 patients, 215 ORN cases).
resultsKey predictors of ORN were D
conclusionsThe PREDMORN NTCP model is the largest multi-institutional effort to date aimed at predicting ORN risk in patients with HNC using real-world data. The model demonstrated good generalizability when externally validated to a large population-based cohort. Our observations align with current guidelines and corroborate findings from smaller single-institution studies.
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