ATX-101 for reduction of submental fat: A phase III randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: ATX-101, an injectable form of deoxycholic acid, causes adipocytolysis when injected subcutaneously into fat. OBJECTIVE: We sought to evaluate the efficacy and safety of ATX-101. METHODS: In this phase III trial (REFINE-2), adults dissatisfied with their moderate or severe submental fat (SMF) were randomized to ATX-101 or placebo. Coprimary end points, evaluated at 12 weeks after last treatment, were composite improvements of 1 or more grades and 2 or more grades in SMF observed on both the validated Clinician- and Patient-Reported SMF Rating Scales. Other end points included magnetic resonance imaging-based assessment of submental volume, assessment of psychological impact of SMF, and additional patient-reported outcomes. RESULTS: Among those treated with ATX-101 or placebo (n = 258/treatment group), 66.5% versus 22.2%, respectively, achieved a composite improvement of 1 or more grades (Mantel-Haenszel risk ratio 2.98; 95% confidence interval 2.31-3.85) and 18.6% versus 3.0% achieved a composite improvement of 2 or more grades in SMF (Mantel-Haenszel risk ratio 6.27; 95% confidence interval 2.91-13.52; P < .001 for both). Those treated with ATX-101 were more likely to achieve submental volume reduction confirmed by magnetic resonance imaging, greater reduction in psychological impact of SMF, and satisfaction with treatment (P < .001 for all). Overall, 85.7% of adverse events in the ATX-101 group and 76.9% in the placebo group were localized to the injection site. LIMITATIONS: Follow-up was limited to 44 weeks. CONCLUSION: ATX-101 is an alternative treatment for SMF reduction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".