A randomized, double-blind, placebo-controlled trial of coenzyme Q10 in Huntington disease
Bibliographic record
Abstract
ObjectiveTo test the hypothesis that chronic treatment of early-stage Huntington disease (HD) with high-dose coenzyme Q10 (CoQ) will slow the progressive functional decline of HD.MethodsWe performed a multicenter randomized, double-blind, placebo-controlled trial. Patients with early-stage HD (n = 609) were enrolled at 48 sites in the United States, Canada, and Australia from 2008 to 2012. Patients were randomized to receive either CoQ 2,400 mg/d or matching placebo, then followed for 60 months. The primary outcome variable was the change from baseline to month 60 in Total Functional Capacity score (for patients who survived) combined with time to death (for patients who died) analyzed using a joint-rank analysis approach.ResultsAn interim analysis for futility revealed a conditional power of <5% for the primary analysis, prompting premature conclusion in July 2014. No statistically significant differences were seen between treatment groups for the primary or secondary outcome measures. CoQ was generally safe and well-tolerated throughout the study.ConclusionsThese data do not justify use of CoQ as a treatment to slow functional decline in HD.Clinicaltrialsgov identifierNCT00608881.Classification of evidenceThis article provides Class I evidence that CoQ does not slow the progressive functional decline of patients with HD.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".