A cost‐utility analysis comparing CT surveillance, PET‐CT surveillance, and planned postradiation neck dissection for advanced nodal HPV‐positive oropharyngeal cancer
Bibliographic record
Abstract
BACKGROUND: The cost utility of image-guided surveillance using computed tomography (CT) and positron emission tomography (PET)-CT to planned postradiation neck dissection (PRND) was compared for the management of advanced nodal human papillomavirus-positive oropharyngeal cancer following chemoradiation. METHODS: A universal payer perspective was adopted. A Markov model was designed to simulate four treatment approaches with 3-month cycles over a lifetime horizon: 1) CT surveillance, 2) standard PET-CT surveillance, 3) a novel PET-CT approach with repeat PET at 6 months postchemoradiation for equivocal responders, and 4) PRND. Parameters including probabilities of CT nodal progression/resolution, PET avidity, recurrence, and survival were obtained from the literature. Costs were reported in 2019 Canadian dollars and utilities were expressed in quality-adjusted life years (QALYs). Deterministic and probabilistic sensitivity analyses were performed to evaluate model uncertainty. RESULTS: PET-CT surveillance dominated CT surveillance and PRND in the base case scenario, and the novel PET-CT approach was the most cost-effective strategy across a wide range of variables tested in one-way sensitivity analysis. On probabilistic sensitivity analysis, novel PET-CT surveillance was the most cost-effective strategy in 78.1% of model iterations at a willingness-to-pay of $50,000/QALYs. Novel PET-CT surveillance resulted in a 49% lower rate of neck dissection compared with traditional PET-CT, and yielded an incremental benefit of 0.14 QALYs with average cost savings of $1309. CONCLUSIONS: Image-guided surveillance including PET-CT and CT are more cost effective than PRND. The novel PET-CT approach with repeat PET for equivocal responders was the dominant strategy and yielded both higher benefit and lower costs compared with standard PET-CT surveillance.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".