Evidence map›Paper›PMID 37041707›Full record

ArticleAnnals of dermatology2023

Clinical Characteristics of Psoriasis for Initiation of Biologic Therapy: A Cluster Analysis.

Yul Hee Kim, Seung Il Kim, Bumhee Park, Eun-So Lee

Abstract read
In one paragraph

Article in Annals of dermatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Psoriasis Area and Severity Index (PASI) Objectivisation by Flow Cytometry Analysis of Major Lymphocytes Subsets.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2023
    Article
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

4 authors.

Yul Hee KimDepartment of Dermatology, Ajou University School of Medicine, Suwon, Korea.ORCID https://orcid.org/0000-0003-3589-8896
Seung Il KimOffice of Biostatics, Medical Research Collaborating Center, Ajou Research Institute for Innovative Medicine, Ajou University Medical Center, Suwon, Korea.ORCID https://orcid.org/0000-0002-6902-791X
Bumhee ParkOffice of Biostatics, Medical Research Collaborating Center, Ajou Research Institute for Innovative Medicine, Ajou University Medical Center, Suwon, Korea.ORCID https://orcid.org/0000-0002-5271-1571
Eun-So LeeDepartment of Dermatology, Ajou University School of Medicine, Suwon, Korea. esl@ajou.ac.kr.ORCID https://orcid.org/0000-0003-0232-7704

Funding

Korea Health Industry Development Institute HI16C0992
6 · The paper itself

Abstract

backgroundPsoriasis is a complex and heterogeneous disease that widely affects a patient's life. Biological therapy is usually prescribed in patients with severe psoriasis that do not respond to conventional treatment. However, data on the specific patient characteristics receiving biologics are still unavailable.

objectiveTo classify patients with psoriasis into subgroups with distinct phenotypes through cluster analysis, and to evaluate the differences between the clusters to predict disease prognosis by examining the response to biological therapy.

methodsThe clinical characteristics of the patients with psoriasis were investigated and categorized using hierarchical cluster analysis. After clustering, the clinical characteristics of the patients were compared and the initiation of treatment with biologics according to the clusters were evaluated.

resultsA total of 361 patients with psoriasis were classified into two clusters using 16 distinct clinical phenotypes. Group 1 (n=202) consisted of male smokers and alcohol users with higher psoriasis area and severity index (PASI), older age of onset, higher body mass index, and comorbidities including psoriatic arthritis, hypertension, and diabetes when compared to group 2 (n=159). Group 1 had a significantly higher probability of biological treatment initiation than group 2 (

conclusionCluster analysis classified patients with psoriasis into two subgroups according to their clinical characteristics. Predicting the disease prognosis using a combination of specific clinical parameters may aid in the management of the disease.

Indexed as

Biological therapyCluster analysisPsoriasis

Identifiers

PMID37041707
PMCPMC10112364

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