Meta-analyses of ataluren randomized controlled trials in nonsense mutation Duchenne muscular dystrophy
Bibliographic record
Abstract
Aim: Assess the totality of efficacy evidence for ataluren in patients with nonsense mutation Duchenne muscular dystrophy (nmDMD). Materials & methods: Data from the two completed randomized controlled trials (ClinicalTrials.gov: NCT00592553; NCT01826487) of ataluren in nmDMD were combined to examine the intent-to-treat (ITT) populations and two patient subgroups (baseline 6-min walk distance [6MWD] ≥300–<400 or <400 m). Meta-analyses examined 6MWD change from baseline to week 48. Results: Statistically significant differences in 6MWD change with ataluren versus placebo were observed across all three meta-analyses. Least-squares mean difference (95% CI): ITT (n = 342), +17.2 (0.2–34.1) m, p = 0.0473; ≥300–<400 m (n = 143), +43.9 (18.2–69.6) m, p = 0.0008; <400 m (n = 216), +27.7 (6.4–49.0) m, p = 0.0109. Conclusion: These meta-analyses support previous evidence for ataluren in slowing disease progression versus placebo in patients with nmDMD over 48 weeks. Treatment benefit was most evident in patients with a baseline 6MWD ≥300–<400 m (the ambulatory transition phase), thereby informing future trial design.
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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 | 0.023 | 0.037 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.052 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".