Improvements in Submental Contour up to 3 Years After ATX-101: Efficacy and Safety Follow-Up of the Phase 3 REFINE Trials
Bibliographic record
Abstract
BACKGROUND: ATX-101 (deoxycholic acid) significantly reduced submental fat (SMF) severity in two 24-week Phase 3 studies (REFINE-1 and REFINE-2). OBJECTIVES: The aim of this study was to evaluate the durability of effect and long-term safety of ATX-101. METHODS: REFINE study patients who maintained ≥1-grade improvement on the Clinician-Reported SMF Rating Scale (CR-1 responders) 12 weeks after their last REFINE treatment were eligible for enrollment in this multicenter, double-blind, nontreatment, long-term, follow-up study (NCT02163902). The primary endpoint was CR-1 response at Years 1, 2, and 3. Patient-reported satisfaction, psychological impact, and adverse events were monitored. RESULTS: In total, 224 patients (ATX-101, n = 113; placebo, n = 111) were enrolled. Maintenance of CR-1 response was significantly better in the ATX-101 group than in the placebo group at Year 1 (86.4% vs 56.8%; P < 0.001), Year 2 (90.6% vs 73.8%; P = 0.014), and Year 3 (82.4% vs 65.0%; P = 0.03). Most (74%) ATX-101‒treated patients satisfied at 12 weeks remained satisfied at Year 3. Significant reductions from baseline in psychological impact scores were sustained through Year 3 (P < 0.001). No new treatment-related adverse events were reported. CONCLUSIONS: Improvements in submental contour achieved with ATX-101 are maintained for 3 years in most patients. No new safety signals emerged.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".