JMIR Publications

ABSTRACT

Background:

Alopecia is an increasingly recognized adverse event among patients receiving glucagon-like peptide-1 receptor agonists (GLP-1RAs). Although frequently attributed to rapid weight loss–induced telogen effluvium (TE), emerging evidence implicates multiple alopecia phenotypes, agent-specific effects, and metabolic, nutritional, hormonal, and inflammatory pathways. Recommendations for risk assessment, diagnostic classification, prevention, and treatment remain limited.

Objective:

To characterize GLP-1RA–associated alopecia phenotypes, evaluate proposed mechanisms and agent-specific differences, and develop a dermatologist-led management framework.

Methods:

PubMed, Embase, Web of Science, and CINAHL Plus were searched from inception through September 2026 using combinations of “GLP-1 receptor agonist,” individual agent names, “alopecia,” “hair loss,” “telogen effluvium,” “androgenetic alopecia,” “alopecia areata,” and “scarring alopecia.” Eligible primary human studies reported hair-loss incidence, risk, phenotype, predictors, mechanisms, or management among users of GLP-1RAs or dual GIP/GLP-1 receptor agonists. Twenty-four primary studies were included: 4 pharmacovigilance analyses, 3 randomized controlled trials, 10 retrospective cohorts, 1 target-trial emulation, 1 prospective observational study, 1 prospective single-arm pilot study, 1 cross-sectional survey, and 3 case reports. Relevant secondary literature and cited references were reviewed for additional eligible studies. Findings were stratified by alopecia phenotype, agent, diagnostic certainty, and therapeutic implications.

Results:

Across pharmacovigilance analyses, semaglutide demonstrated the most consistent disproportionality signal, whereas findings for tirzepatide varied across studies. Randomized trials of tirzepatide reported higher rates of unspecified alopecia than placebo. Large database studies encompassing up to approximately 1.15 million patients identified associations across telogen effluvium (TE), androgenetic alopecia (AGA), alopecia areata (AA), anagen effluvium, and broader nonscarring alopecia, although findings varied by agent, comparator, and duration of follow-up and relied primarily on administrative diagnostic codes. Associations were most consistently observed for TE, AGA, and broader nonscarring alopecia, whereas most comparative analyses of AA were not significant. Clinical phenotyping was uncommon across the evidence base, with many studies relying on adverse-event reports, claims, or electronic health record codes rather than standardized dermatologic assessment. A cross-sectional survey found self-reported hair loss in 76.0% of participants, with female sex significantly associated with hair loss and severity differing across medications. Clinically characterized reports described semaglutide-associated AA, improvement of insulin resistance–associated AGA with tirzepatide, and improvement of refractory folliculitis decalvans with tirzepatide. Studies of scarring and inflammatory alopecias further showed heterogeneous findings, including increased cicatricial alopecia risk in one comparator analysis, reduced treatment utilization among patients with established scarring alopecias, and clinical response in 58% of a central centrifugal cicatricial alopecia cohort. Based on these findings, a phased framework incorporating baseline assessment, targeted laboratory evaluation, nutritional optimization, early phenotype classification, and diagnosis-directed medical or procedural treatment was proposed.

Conclusions:

GLP-1RA–associated hair loss should not be regarded uniformly as weight loss–induced TE. Current evidence supports a heterogeneous spectrum including TE, AGA, AA, broader nonscarring alopecia, and scarring or inflammatory alopecias, with potentially beneficial effects reported in selected inflammatory phenotypes. Phenotype-directed evaluation may facilitate earlier treatment and prevent unnecessary GLP-1RA discontinuation. Prospective studies incorporating trichoscopy, standardized photography, weight-loss velocity, nutritional biomarkers, and longitudinal hair-density measurements are needed.