Treatment Interruption and Outcomes in Head and Neck Cancer
Bibliographic record
Abstract
Importance: Historical evidence demonstrated that delays or interruptions in radiotherapy (RT) are associated with poorer oncologic outcomes in head and neck squamous cell carcinoma (HNSCC). Substantial concerns arose during the COVID-19 pandemic, when treatment schedules were frequently disrupted. Objective: To determine the association of RT interruptions with locoregional failure (LRF) and overall survival (OS). Design, Setting, and Participants: This retrospective review and secondary analysis of 3 randomized clinical trials (NRG/RTOG 0129, 0522, and 1016) included patients enrolled in the trials who were treated with RT. Patients with HNSCC were grouped as (1) p16-positive oropharynx (p16+ OPSCC) and (2) p16-negative oropharynx and all other subsites regardless of p16 status (called locally advanced HNSCC [LAHNSCC])). Cox proportional hazards models were fit to assess the association of an RT interruption (binary model) and length of RT interruption (continuous model) with LRF and OS. Exposures: Presence of RT interruption. Main Outcomes and Measures: LRF and OS. Results: There were 1549 patients (200 female patients [12.9%]; mean [SD] age, 57 [6] years; 1048 p16+ OPSCC [67.7%]; 501 LAHNSCC [32.3%]) who were included in the binary model; 439 (28.3%) had RT interruption. There were 1083 patients (69.9%) with available length of RT interruption (continuous model). A binary RT interruption was associated with hazard ratios (HRs) of 1.04 (95% CI, 0.90-1.36) for LRF and 1.22 (95% CI, 0.99-1.50) for OS. As a continuous predictor, each 7-day interruption corresponded to HRs of 1.45 (95% CI, 1.12-1.89) for LRF and 1.41 (95% CI, 1.07-1.86) for OS. Analyses did not indicate effect modification by p16 status, and results are presented from models that estimated the effect of RT interruption across both groups. Using covariate-adjusted predictions from models that included clinical and tumor characteristics, a mean 7-day interruption in RT was associated with a 3-year LRF decrement of 4.1% in p16+ OPSCC and 9.1% in LAHNSCC. Predicted 3-year LRF detriment due to RT interruption ranged from 2.0% for a patient with non-T4, non-N3, p16+ OPSCC to 11.2% for a patients with LAHNSCC with a T4N3 p16-negative cancer. Conclusions and Relevance: The secondary analysis suggests that RT treatment interruptions may be negatively associated with LRF and OS in HNSCC, but the magnitude of the association varies depending on p16 status and clinical characteristics. While treatment interruptions should globally be discouraged, patients with LAHNSCC or higher-stage disease may be most affected. Trial Registration: ClinicalTrials.gov Identifiers: NCT00047008; NCT00265941; NCT01302834.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".