The impact of monotherapies for male androgenetic alopecia: A network meta‐analysis study
Bibliographic record
Abstract
BACKGROUND: The evidence base pertaining to the efficacy of monotherapies for androgenetic alopecia (AGA), the most common form of hair loss, is ever expanding-and this warrants a formal comparison therapies' effect on a frequent basis. AIMS: The objective of the current study was to determine the comparative effect of relevant monotherapies for male AGA. PATIENTS/METHODS: Our aim was achieved by conducting Bayesian network meta-analysis (NMA), under a random effects model, for two outcomes: 6-month change in (1) total and (2) terminal hair density in adult (i.e., aged 18 years and above) men with AGA; these analyses were preceded by a systematic search of the peer-reviewed literature for suitable data. Interventions' surface under the cumulative ranking curve (SUCRA) and pairwise relative effects (quantified as mean differences) were estimated through the NMAs. RESULTS: We determined the comparative effect of 20 active comparators and a control (i.e., placebo/vehicle). "Dutasteride 0.5 mg once daily for 24 weeks" was ranked the most effective in terms of 6-month change in (1) total hair density (SUCRA = 87%) and terminal hair density (SUCRA = 98%). Our results showed that interventions' effectiveness can be dose dependent. CONCLUSIONS: Our updated analyses of the up-to-date evidence regarding monotherapies for male AGA showed that the oral form of 5-alpha reductase inhibitors are more effective than oral minoxidil and other newer agents like Botox, microneedling, and photobiomodulation. Our findings can better inform clinical decision making and design of future research studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".