Comparative Efficacy of Minoxidil and 5‐Alpha Reductase Inhibitors Monotherapy for Male Pattern Hair Loss: Network Meta‐Analysis Study of Current Empirical Evidence
Bibliographic record
Abstract
BACKGROUND: Treatment options for male androgenetic alopecia (AGA) range from pharmacologic agents-such as minoxidil, finasteride, and dutasteride-to newer procedural and experimental therapies. AIMS: We determined the relative effect of the various dosages and administrative routes of minoxidil, finasteride and dutasteride through network meta-analysis (NMA) of relevant outcome measures. METHODS: We conducted a systematic review to identify eligible studies. Our NMAs included studies that investigated monotherapy with minoxidil, finasteride, and dutasteride of any dosage and route on the following 5 outcomes: 24- and 48-week changes in total and terminal hair density, and 24-week change in independent observer assessment (IOA). We assessed evidence quality and performed sensitivity and node-splitting analyses of inconsistency. Each NMA produced estimates for pairwise relative effects and surface under the cumulative ranking curve (SUCRA) values. RESULTS: Our search found 33 eligible studies across which 19 comparators (18 interventions and 1 control) were identified. The active comparators included minoxidil (oral, topical, sublingual), finasteride (oral, topical, mesotherapy) and dutasteride (oral, mesotherapy). The control node amalgamated placebo and vehicle arms. CONCLUSIONS: We found dutasteride 0.5 mg/day to be the most effective option. Among FDA-approved treatments, topical minoxidil 5% was the most effective topical monotherapy, while finasteride 1 mg/day was the most effective oral option. Dutasteride mesotherapy appears significantly less effective than oral administration (0.5 mg/day).
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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 | 0.027 | 0.065 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.041 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".