SynthesisFrontiers in medicine2022
Hair regrowth treatment efficacy and resistance in androgenetic alopecia: A systematic review and continuous Bayesian network meta-analysis.
Synthesis in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
- Hair Growth-Promoting Activity of a Biorenovated Esculetin Complex Through Modulation of Dermal Papilla Cell Function and Hair Follicle Cycling.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Alopecia management from a comparative perspective: pharmacological and pharmaceutical insights in humans, dogs, and cats.Frontiers in veterinary science · 2026Review
- A Novel, Drinkable Food Supplement Formulation Reduces Hair Shedding and Increases the Percentage of Anagen Scalp Hair Follicles in Females with Hair Loss.Journal of clinical medicine · 2025Article
- Synergistic effects of mesenchymal stem cell secretome and Wnt10b on hair follicle regeneration in a 3D bioengineering model: a preclinical study.Stem cell research & therapy · 2025Article
- Topical minoxidil effectiveness in enhancing facial aesthetics: A systematic review and meta-analysis.Journal of family medicine and primary care · 2025Review
- Novel Strategies for Androgenetic Alopecia Therapy: Integrating Multifunctional Plant Extracts with Nanotechnology for Advanced Cutaneous Drug Delivery.Pharmaceutics · 2025Review
- Research Trends and Hotspots in Female Pattern Hair Loss: A Bibliometric Study.Journal of cosmetic dermatology · 2025Article
- (7E)-7,8-Dehydroheliobuphthalmin fromInternational journal of molecular sciences · 2025Article
- Article
- Reprofiling synthetic glucocorticoid-induced leucine zipper fusion peptide as a novel and effective hair growth promoter.Archives of dermatological research · 2024Article
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Authors and funding
14 authors at 9 institutions in 8 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Androgenetic alopecia (AGA) affects almost half the population, and several treatments intending to regenerate a normal scalp hair phenotype are used. This is the first study comparing treatment efficacy response and resistance using standardized continuous outcomes. Objective: To systematically compare the relative efficacy of treatments used for terminal hair (TH) regrowth in women and men with AGA. Methods: A systematic literature review was conducted (from inception to August 11, 2021) to identify randomized, Placebo-controlled trials with ≥ 20 patients and reporting changes in TH density after 24 weeks. Efficacy was analyzed by sex at 12 and 24 weeks using Bayesian network meta-analysis (B-NMA) and compared to frequentist and continuous outcomes profiles. Results: The search identified 2,314 unique articles. Ninety-eight were included for full-text review, and 17 articles met the inclusion criteria for data extraction and analyses. Eligible treatments included ALRV5XR, Dutasteride 0.5 mg/day, Finasteride 1 mg/day, low-level laser comb treatment (LLLT), Minoxidil 2% and 5%, Nutrafol, and Viviscal. At 24 weeks, the B-NMA regrowth efficacy in TH/cm Conclusion: Some TH regrowth can be expected from most AGA treatments with less variability in women than men. Responses to drug treatments were rapid, showing strong early efficacy followed by the greatest resistance effects from flatlining to loss of regrowth after 12-16 weeks. Finasteride, Minoxidil 2% and Viviscal in men were not statistically different from Placebo. LLLT appeared more efficacious than pharmaceuticals. The natural product formulation ALRV5XR showed better efficacy in all tested parameters without signs of treatment resistance (see Graphical abstract). Systematic review registration: www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42021268040, identifier CRD42021268040.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.