Evidence map›Paper›PMID 40014580›Full record

ArticlePloS one2025

Epidemiological landscape of androgenetic alopecia in the US: An All of Us cross-sectional study.

Aditya K Gupta, Tong Wang, Vasiliki Economopoulos

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Aditya K GuptaDivision of Dermatology, Department of Medicine, University of Toronto School of Medicine, Toronto, Ontario, Canada.ORCID 0000-0002-8664-7723
Tong WangMediprobe Research Inc., London, Ontario, Canada.
Vasiliki EconomopoulosMediprobe Research Inc., London, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAndrogenetic alopecia (AGA) is extremely prevalent with a multifactorial etiology. MATERIALS: We conducted a cross-sectional study using the All of US (AoU) dataset Sept 2024 to better understand the epidemiology, social determinants and management of AGA.

resultsMost males were 20-39 years old and females 60-69 years old. Men typically have an earlier onset of AGA than females. Male AGA is generally managed with finasteride; oral minoxidil is prescribed in younger males. Females are prescribed spironolactone and oral minoxidil with finasteride in post-menopausal females. There was very little dutasteride prescribed. Topical minoxidil is available over the counter and was not evaluated. Early in 2011 there were reports of the Post-Finasteride Syndrome (PFS); subsequently, the finasteride prescription rate fell to about 10-20% of the pre-PFS prescription rate. There was increased reporting for AGA in those who drink, have an annual household income ≥$75,000, and those with a higher level of education. There was also higher reporting of female AGA in those with anxiety and depression. Patients with higher income and education may have less pressing medical concerns enabling them to bring their AGA to the physician's attention. Females in whom the AGA affects their anxiety and depression may seek help for the AGA as a way to address their underlying disorder.

conclusionsThis study provides a snapshot of the epidemiology and management of AGA in the USA. AGA is linked to the social determinants of health; addressing the AGA may help better manage the underlying mental and physical state.

Indexed as

AlopeciaAdultAgedCross-Sectional StudiesFemaleFinasterideHumansMaleMiddle AgedMinoxidilUnited StatesYoung AdultFinasterideMinoxidil

Identifiers

PMID40014580
PMCPMC11867384

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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.