Two-Year Tumor Outcomes of a Phase 2B, Randomized, Double-Blind Trial of Avasopasem Manganese (GC4419) Versus Placebo to Reduce Severe Oral Mucositis Owing to Concurrent Radiation Therapy and Cisplatin for Head and Neck Cancer
Bibliographic record
Abstract
PURPOSE: Avasopasem manganese (GC4419), an investigational selective dismutase mimetic radioprotector, reduced duration, incidence, and severity of severe oral mucositis (World Health Organization grade 3-4) in a phase 2b, randomized, double-blind trial of patients receiving concurrent cisplatin (cis) and radiation therapy (RT) for head and neck cancer. We report the secondary endpoints of final 1- and 2-year tumor outcomes and exploratory data on trismus and xerostomia. METHODS AND MATERIALS: Patients with locally advanced oral cavity or oropharynx cancer to be treated with definitive or postop cis and RT were randomized to 1 of 3 arms: 30 mg avasopasem, 90 mg avasopasem, or placebo. Pairwise comparisons of Kaplan-Meier estimates (each active arm separately vs placebo) were made for overall survival, progression-free survival, locoregional control, and distant metastasis-free survival. Xerostomia and trismus data were collected at each follow-up visit and analyzed for trends by post-RT timepoint and treatment group. RESULTS: At a median follow-up for the entire cohort of 25.5 months (25th-75th percentile, 24.6-26.2 months; range, 0.2-31.9 months), Kaplan-Meier estimates of 1- and 2-year overall survival, progression-free survival, locoregional control, and distant metastasis-free survival were not statistically different. No trends were apparent in xerostomia or trismus data. CONCLUSIONS: Avasopasem does not lead to statistically different tumor control outcomes when used concurrently with cis and RT for head and neck cancer. There was no detectable effect on trismus or xerostomia.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".