Preprint
Mandibular dose-volume predicts time-to-osteoradionecrosis in an actuarial normal-tissue complication probability (NTCP) model: External validation of right-censored clinico-dosimetric and competing risk application across international multi-institutional observational cohorts and online graphical user interface clinical support tool assessment
medRxiv : the preprint server for health sciences
Cold Spring Harbor Laboratory
08/20/2024
DOI: 10.1101/2024.08.20.24312311
PMCID: PMC11370531
PMID: 39228724
Abstract
Existing studies on osteoradionecrosis of the jaw (ORNJ) have primarily used cross-sectional data, assessing risk factors at a single time point. Determining the time-to-event profile of ORNJ has important implications to monitor oral health in head and neck cancer (HNC) long-term survivors.BackgroundExisting studies on osteoradionecrosis of the jaw (ORNJ) have primarily used cross-sectional data, assessing risk factors at a single time point. Determining the time-to-event profile of ORNJ has important implications to monitor oral health in head and neck cancer (HNC) long-term survivors.Demographic, clinical and dosimetric data were retrospectively obtained for a clinical observational cohort of 1129 patients with HNC treated with radiotherapy (RT) at The University of Texas MD Anderson Cancer Center. ORNJ was diagnosed in 198 patients (18%). A multivariable logistic regression analysis with forward stepwise variable selection identified significant predictors for ORNJ. These predictors were then used to train a Weibull Accelerated Failure Time (AFT) model, which was externally validated using an independent cohort of 265 patients (92 ORNJ cases and 173 controls) treated at Guy's and St. Thomas' Hospitals.MethodsDemographic, clinical and dosimetric data were retrospectively obtained for a clinical observational cohort of 1129 patients with HNC treated with radiotherapy (RT) at The University of Texas MD Anderson Cancer Center. ORNJ was diagnosed in 198 patients (18%). A multivariable logistic regression analysis with forward stepwise variable selection identified significant predictors for ORNJ. These predictors were then used to train a Weibull Accelerated Failure Time (AFT) model, which was externally validated using an independent cohort of 265 patients (92 ORNJ cases and 173 controls) treated at Guy's and St. Thomas' Hospitals.Our model identified that each unit increase in D25% is significantly associated with a 12% shorter time to ORNJ (Adjusted Time Ratio [ATR] 0·88, p<0·005); pre-RT dental extractions was associated to a 27% faster (ATR 0·73, p=0·13) onset of ORNJ; male patients experienced a 38% shorter time to ORNJ (ATR 0·62, p = 0·11). The model demonstrated strong internal calibration (integrated Brier score of 0·133, D-calibration p-value 0.998) and optimal discrimination at 72 months (Harrell's C-index of 0·72). The model also showed good generalization to the independent cohort, despite a slight drop in performance.FindingsOur model identified that each unit increase in D25% is significantly associated with a 12% shorter time to ORNJ (Adjusted Time Ratio [ATR] 0·88, p<0·005); pre-RT dental extractions was associated to a 27% faster (ATR 0·73, p=0·13) onset of ORNJ; male patients experienced a 38% shorter time to ORNJ (ATR 0·62, p = 0·11). The model demonstrated strong internal calibration (integrated Brier score of 0·133, D-calibration p-value 0.998) and optimal discrimination at 72 months (Harrell's C-index of 0·72). The model also showed good generalization to the independent cohort, despite a slight drop in performance.This study is the first to demonstrate a direct relationship between radiation dose and the time to ORNJ onset, providing a novel characterization of the impact of delivered dose not only on the probability of a late effect (ORNJ), but the conditional risk during survivorship.InterpretationThis study is the first to demonstrate a direct relationship between radiation dose and the time to ORNJ onset, providing a novel characterization of the impact of delivered dose not only on the probability of a late effect (ORNJ), but the conditional risk during survivorship.This work was supported by various funding sources including NIH, NIDCR, NCI, NAPT, NASA, BCM, Affirmed Pharma, CRUK, KWF Dutch Cancer Society, NWO ZonMw, and the Apache Corporation.FundingThis work was supported by various funding sources including NIH, NIDCR, NCI, NAPT, NASA, BCM, Affirmed Pharma, CRUK, KWF Dutch Cancer Society, NWO ZonMw, and the Apache Corporation.
Details
- Title: Subtitle
- Mandibular dose-volume predicts time-to-osteoradionecrosis in an actuarial normal-tissue complication probability (NTCP) model: External validation of right-censored clinico-dosimetric and competing risk application across international multi-institutional observational cohorts and online graphical user interface clinical support tool assessment
- Creators
- Laia Humbert-VidanSerageldin Kamel - The University of Texas MD Anderson Cancer CenterAndrew Wentzel - University of Illinois ChicagoZaphanlene Kaffey - The University of Texas MD Anderson Cancer CenterMoamen AbdelaalKyle B SpierNatalie A West - The University of Texas MD Anderson Cancer CenterG Elisabeta Marai - University of Illinois ChicagoGuadalupe Canahuate - University of IowaXinhua Zhang - University of Illinois ChicagoMelissa M Chen - The University of Texas MD Anderson Cancer CenterKareem A Wahid - The University of Texas MD Anderson Cancer CenterJillian Rigert - The University of Texas MD Anderson Cancer CenterSeyedmohammadhossein Hosseinian - North Carolina State UniversityAndrew J Schaefer - Rice UniversityKristy K Brock - The University of Texas MD Anderson Cancer CenterMark Chambers - The University of Texas MD Anderson Cancer CenterAdegbenga O Otun - The University of Texas MD Anderson Cancer CenterRuth Aponte-WessonVinod Patel - Guy's and St Thomas' NHS Foundation TrustAndrew Hope - Princess Margaret Cancer CentreJack Phan - The University of Texas MD Anderson Cancer CenterAdam S Garden - The University of Texas MD Anderson Cancer CenterSteven J Frank - The University of Texas MD Anderson Cancer CenterWilliam H Morrison - The University of Texas MD Anderson Cancer CenterMichael T Spiotto - The University of Texas MD Anderson Cancer CenterDavid Rosenthal - The University of Texas MD Anderson Cancer CenterAnna Lee - The University of Texas MD Anderson Cancer CenterRenjie He - The University of Texas MD Anderson Cancer CenterMohamed A Naser - The University of Texas MD Anderson Cancer CenterErin Watson - Princess Margaret Cancer CentreKatherine A Hutcheson - The University of Texas MD Anderson Cancer CenterAbdallah S R MohamedVlad C Sandulache - Baylor College of MedicineLisanne V van Dijk - University Medical Center GroningenAmy C Moreno - The University of Texas MD Anderson Cancer CenterTeresa Guerrero UrbanoStephen Y Lai - The University of Texas MD Anderson Cancer CenterClifton D Fuller - The University of Texas MD Anderson Cancer Center
- Resource Type
- Preprint
- Publication Details
- medRxiv : the preprint server for health sciences
- DOI
- 10.1101/2024.08.20.24312311
- PMID
- 39228724
- PMCID
- PMC11370531
- Publisher
- Cold Spring Harbor Laboratory
- Language
- English
- Date posted
- 08/20/2024
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984701658802771
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