Opioid therapy vs. Multimodal analgesia in head and neck cancer (OPTIMAL-HN): Results of a randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Radiation-induced mucositis (RIM) pain confers substantial morbidity for head and neck cancer (HNC) patients undergoing radiotherapy (RT) or chemoradiotherapy (CRT). With no well-established standard treatment, OPTIMAL-HN aimed to demonstrate the non-inferiority of multimodal analgesia (MMA; analgesic medications with different mechanisms of action) to opioid analgesia alone. METHODS: OPTIMAL-HN (ClinicalTrials.gov identifier: NCT04221165) was an open-label, non-inferiority, randomized clinical trial. We enrolled HNC patients receiving curative-intent RT/CRT and experiencing moderate ≥ 4/10 RIM pain. We randomized 1:1, stratified by RT vs. CRT, to opioids alone (standard arm) or MMA (pregabalin, acetaminophen, naproxen, and opioids if required). The primary endpoint was mean pain score (range: 0-10) during the last week of RT. Secondary endpoints included mean weekly opioid use, duration of opioid requirement, quality of life, weight loss, and toxicity. All analyses were pre-specified, including testing for superiority if non-inferiority was demonstrated. RESULTS: Forty-nine patients were enrolled, 25 in the opioid analgesia arm and 24 in the MMA arm. Median follow-up was 4.2 months. The primary endpoint, mean pain score during the last 7 days of RT, was 5.1 (95 % confidence interval [CI]: 4.1-6.1) in the opioid arm and 4.9 (95 % CI: 3.8-5.9) in the MMA arm (non-inferiority p = 0.039, superiority p = 0.72). Analyzing all pain scores from enrollment to 6-weeks post-RT, MMA demonstrated both non-inferiority and superiority compared to opioids alone (non-inferiority p = 0.0024, superiority p < 0.001). One patient in the MMA arm was admitted with acute kidney injury, possibly related to the analgesic regimen. Arms were similar for all other secondary endpoints. CONCLUSIONS: MMA demonstrates non-inferiority to opioid analgesia alone in managing RIM pain during the last week of RT and superiority when analyzing the post-RT time period. MMA should, therefore, be considered an effective mode of analgesia for HNC patients receiving RT.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".