Efficacy of Cetirizine 1% Versus Minoxidil 5% Topical Solution in the Treatment of Male Alopecia: A Randomized, Single-blind Controlled Study
Bibliographic record
Abstract
PURPOSE: Prostaglandins play a pivotal role in modulating hair growth cycle. Prostaglandin F2α and prostaglandin E have stimulating and prostaglandin D has inhibitory effects on hair follicle. Cetirizine inhibits release of prostaglandin D2 and stimulates the release of prostaglandin E2. In the present study, the efficacy and safety of twice daily application of topical cetirizine 1% versus minoxidil 5% solutions for 16 weeks were compared in male androgenetic alopecia (AGA). METHODS: Forty men, aged 18 to 49 years, were randomly divided into two equal groups to apply either cetirizine 1% or minoxidil 5% solutions. The study was divided into two phases, a 16-week treatment phase either with cetirizine or minoxidil (anagen phase), followed by an 8-week drug-free (telogen phase) with a follow-up when patients used placebo. Efficacy outcomes included the change in total hair density, vellus and terminal hair density, hair diameter and the percentage of hair in anagen and telogen phases from baseline in 16 and 24 weeks. RESULTS: After 16 weeks, we observed a significant increase in total and vellus hair density in both minoxidil and cetirizine groups, but the improvement was much higher in the minoxidil group. The percentage of hair in the anagen phase also increased in both groups after 16 weeks of treatment, but then diminished after 8 weeks of placebo consumption. No significant adverse reactions associated with the administration of cetirizine solution were reported. CONCLUSION: Cetirizine 1% solution was effective in hair growth without any complications for treatment of male AGA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".