Evidence map›Paper›PMID 41322218›Full record

ArticleFrontiers in medicine2025

Longitudinal clinical course, treatment outcomes, and relapse patterns in alopecia areata: a prospective cohort study.

Yan Wenjie, Wang Yue, Wang Mengjiao, Zhao Yumei, Huang Xi

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

5 authors.

Yan WenjieDepartment of Dermatology and Venereology, The First Affiliated Hospital of Guilin Medical University, Guilin, China.
Wang YueThe First Affiliated Hospital of Guilin Medical University, Guilin, China.
Wang MengjiaoDepartment of Dermatology and Venereology, The First Affiliated Hospital of Guilin Medical University, Guilin, China.
Zhao YumeiDepartment of Dermatology and Venereology, The First Affiliated Hospital of Guilin Medical University, Guilin, China.
Huang XiDepartment of Dermatology and Venereology, The First Affiliated Hospital of Guilin Medical University, Guilin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Alopecia areata (AA) is a common autoimmune hair loss disorder with a highly variable course and substantial psychosocial impact. Evidence from long-term prospective cohorts remains limited. To characterize the natural history, treatment outcomes, relapse patterns, quality-of-life changes, and safety profile of AA over 52 weeks in a real-world clinical setting. Methods: In this single-center prospective cohort, 400 patients with AA and 80 healthy controls were followed for 52 weeks, with assessments at weeks 4, 12, 24, 36, and 52. Disease severity was quantified using the Severity of Alopecia Tool (SALT). Primary outcomes included SALT50 and SALT90 achievement at week 24; secondary outcomes were relapse at week 52, patient-reported outcomes [Dermatology Life Quality Index (DLQI), Skindex-16, itch/pain numeric rating scale (NRS)], and safety. An imaging subcohort ( Results: By week 52, 31.8% of patients relapsed, with a median relapse time of 28 weeks. SALT improved over time, with mean scores declining from 38.6 ± 21.7 at baseline to 22.4 ± 17.1 at week 52 ( Conclusion: This prospective cohort provides longitudinal evidence that baseline severity, disease activity, and relapse history are major determinants of response and recurrence in AA. Standardized severity scores, patient-reported outcomes, and imaging biomarkers may improve risk stratification, personalized care, and real-world evaluation of current therapies.

Indexed as

alopecia areataJAK inhibitorsprospective cohortquality of lifeSeverity of Alopecia Tool (SALT)

Identifiers

PMID41322218
PMCPMC12660087

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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.