Efficacy of non‐surgical treatments for androgenetic alopecia: a systematic review and network meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Androgenetic alopecia, or male/female pattern baldness, is the most common type of progressive hair loss disorder. The aim of this study was to review recent advances in non-surgical treatments for androgenetic alopecia and identify the most effective treatments. A network meta-analysis (NMA) was conducted of the available literature of the six most common non-surgical treatment options for treating androgenetic alopecia in both men and women; dutasteride 0.5 mg, finasteride 1 mg, low-level laser therapy (LLLT), minoxidil 2%, minoxidil 5% and platelet-rich plasma (PRP). Seventy-eight studies met the inclusion criteria, and 22 studies had the data necessary for a network meta-analysis. Relative effects show LLLT as the superior treatment. Relative effects show PRP, finasteride 1 mg (male), finasteride 1 mg (female), minoxidil 5%, minoxidil 2% and dutasteride (male) are approximately equivalent in mean change hair count following treatment. Minoxidil 5% and minoxidil 2% reported the most drug-related adverse events (n = 45 and n = 23, respectively). The quality of evidence of minoxidil 2% vs. minoxidil 5% was high; minoxidil 5% vs. placebo was moderate; dutasteride (male) vs. placebo, finasteride (female) vs. placebo, minoxidil 2% vs. placebo and minoxidil 5% vs. LLLT was low; and finasteride (male) vs. placebo, LLLT vs. sham, PRP vs. placebo and finasteride vs. minoxidil 2% was very low. Results of this NMA indicate the emergence of novel, non-hormonal therapies as effective treatments for hair loss; however, the quality of evidence is generally low. High-quality randomized controlled trials and head-to-head trials are required to support these findings and aid in the development of more standardized protocols, particularly for PRP. Regardless, this analysis may aid physicians in clinical decision-making and highlight the variety of non-surgical hair restoration options for patients.
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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) | 0.008 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it