Osteoradionecrosis in head and neck cancer patients: Risk factors and comparison of grading systems.
Bibliographic record
Abstract
e18057 Background: We aimed to identify the incidence and risk factors for osteoradionecrosis (ORN) in head and neck cancer (HNC) patients. We also compared frequency of severity scores across different ORN grading systems. Methods: Retrospective review was conducted for HNC patients who were managed at our institution (2011-2018) with curative-intent definitive, pre- or post-operative intensity-modulated radiation therapy (IMRT) with 45Gy, and underwent pre-IMRT dental evaluation. Jaw ORN was defined based on: 1) clinical signs (exposed bone, bone spicules, sequestra, infection and fistula), 2) radiological finding (abnormal bone pattern, radiographic sequestra and pathological fracture), and 3) treatment required and response to therapy, either conservative (chlorhexidine rinse, antibiotics, PENTOCLO, and hyperbaric oxygen) or surgical (sequestrectomy, debridement, and jaw resection). ORN events were retrospectively graded using 6 different grading systems. Pre-IMRT periodontal condition (PC) was classified by universal multi-dimensional staging system based on number of teeth and bone loss (stages 0 to IV). Multivariable analysis (MVA) using logistic regression was applied to identify risk factors of ORN. Results: A total of 2735 HNC patients were included; median age 61 years, 30% (n = 807) current/ex-smokers, 72% (n = 1914) had moderate to severe PC (stage II-IV), 53% (n = 1459) oral cavity/oropharynx (OC/OP) primary tumor. The median IMRT dose was 70Gy/35 fractions, 43% (n = 1170) received concurrent chemotherapy, and 37% (n = 1006) underwent surgery. A total of 227 patients (8.3%) developed ORN. There was discrepancy in different grading system for capturing and reporting the degree of severity (i.e. grade) of ORN (table). On MVA, risk factors for ORN were: current/ex-smoker (OR 1.5, 95% CI: 1.12-2, p< 0.01), stage II-IV PC (OR 1.7, 95% CI: 1.17-2.36, p< 0.01), primary OC/OP tumor (OR 4.4, 95% CI: 3.08-6.29, p< 0.001], and IMRT dose prescription ≥60Gy (OR 3.5, 95%CI: 1.11-11.33, p< 0.01). Conclusions: ORN is relatively uncommon in HNC patients, however it can be under-reported by different grading systems. Risk factors for ORN were: smoking history, pre-IMRT poor PC condition, OC/OP primary tumor, and higher dose (≥60Gy) IMRT.[Table: see text]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".