Cure Rates of Control Interventions in Randomized Trials of Onychomycosis Treatments
Bibliographic record
Abstract
BACKGROUND: The efficacy of antifungals for onychomycosis has been determined in randomized controlled trials (RCTs); interestingly, their control arms have demonstrated some therapeutic effects. These controls constitute either placebos (inert pills) or vehicles (all but the antifungal component of the creams). We sought to determine whether RCT controls exhibited statistically relevant efficacy rates (ie, beyond the placebo effect), whether oral and topical controls differed in their efficacies, and whether the efficacy rates of the controls correlated with those of the active comparator associated with that control. METHODS: All RCTs of oral and topical monotherapies for dermatophyte toenail onychomycosis were identified through a systematic literature search. For the meta-analyses of cure rates, the double arcsine transformation was used. The N - 1 χ2 test was used to determine whether the cure rates significantly differed between topical and oral controls. Correlation was investigated using Kendall rank correlation tests. RESULTS: The pooled mycological, complete, and clinical cure rates of the control interventions (19 trials) were 9%, 1%, and 6%, respectively. The pooled efficacy rates for oral and topical controls were as follows: mycological cure rate, 7% and 12% (P = .0016); complete cure rate, 1% for both; and clinical cure rate, 4% and 8%, respectively (P = .0033). For oral RCTs, the respective cure rates of the active therapies were not correlated with controls. However, for topical RCTs, as the mycological and clinical cure rates of the active therapy increased, so did those of the topical vehicle associated with the active therapy in question, and vice versa. CONCLUSIONS: The topical vehicle cure rates were often higher than the oral placebo cure rates, likely due to the presence of nonantifungal chemicals (eg, moisturizers, urea) with antifungal and debriding properties, which are not present in oral controls.
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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 | 0.317 | 0.485 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.006 |
| 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".