Evidence map›Paper›PMID 41710524›Full record

ArticleClinical, cosmetic and investigational dermatology2026

Trichoscopic Features, Clinical Correlates, and Risk Prediction in Female Pattern Hair Loss: A Retrospective Case-Control Study.

Boquan Long, Qi Long, Weitian Pan, Siqi Chen, Zhiming Ye, Hongwei Guo

Abstract read
In one paragraph

Article in Clinical, cosmetic and investigational dermatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Boquan LongDepartment of Dermatology, The second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, People's Republic of China.
Qi LongDepartment of Dermatology, The second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, People's Republic of China.
Weitian PanThe First Clinical College, Guangdong Medical University, Zhanjiang, Guangdong, People's Republic of China.
Siqi ChenDepartment of Dermatology, The second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, People's Republic of China.
Zhiming YeDepartment of Dermatology, The second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, People's Republic of China.ORCID 0009-0000-7747-0826
Hongwei GuoDepartment of Dermatology, Zhanjiang Central Hospital, Guangdong Medical University (Central People's Hospital of Zhanjiang), Zhanjiang, Guangdong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Female Pattern Hair Loss (FPHL) is often confused with another condition called Chronic telogen effluvium (CTE). Trichoscopy plays an increasingly prominent role in the diagnosis and prognosis of hair disorders. Objective: This study investigated the clinical manifestations and trichoscopic features of FPHL to identify correlations and to develop a nomogram model to predict the risk of FPHL. Methods: A retrospective case-control study was conducted, including 151 FPHL patients (cases) and 151 CTE patients (controls). Clinical and trichoscopic data were analyzed to identify independent risk factors for FPHL and to establish a predictive nomogram model. Results: The findings suggested that AGA family history (P<0.05) and earlier onset of hair loss ( Conclusion: The nomogram model based on our data is effective in predicting FPHL risk, which could help optimize disease management.

Indexed as

female pattern hair lossnomogram modelrisk factorstrichoscopy

Identifiers

PMID41710524
PMCPMC12911958

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.