Meta‐Analysis of Randomized, Controlled Trials Comparing Particular Doses of Griseofulvin and Terbinafine for the Treatment of Tinea Capitis
Bibliographic record
Abstract
Two oral antifungal agents, griseofulvin and terbinafine, have regulatory approval in the United States, but it is unknown whether one has superior overall efficacy. Genus-specific differences in efficacy are believed to exist for the two agents. It is not clear at what doses and durations of treatment these differences apply. The goals of this meta-analysis were to determine whether a statistically significant difference in efficacy exists between these agents at a given dose and duration of each in tinea capitis infections overall and to determine whether a genus-specific difference in efficacy exists for these two treatments at a given dose and duration of each. We performed a literature search for clinically and methodologically similar randomized controlled trials comparing 8 weeks of griseofulvin (6.25-12.5 mg/kg/day) to 4 weeks of terbinafine (3.125-6.25 mg/kg/day) in the treatment of tinea capitis. A meta-analysis was performed using the Mantel-Haenszel method and random effects model; results were expressed as odds ratios with 95% confidence intervals. Meta-analysis of randomized controlled trials did not show a significant difference in the overall efficacy of the two drugs at the doses specified, but specific efficacy differences were observed based on the infectious species. For tinea capitis caused by Microsporum spp., griseofulvin is superior (p = 0.04), whereas terbinafine is superior for Trichophyton spp. infection (p = 0.04). Our results support species-specific differences in treatment efficacy between griseofulvin and terbinafine and provide a clinical context in which this knowledge may be applied.
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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 | 0.028 | 0.060 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.071 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| 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".