Evidence map›Paper›PMID 39295895›Full record

ArticleJournal of psoriasis and psoriatic arthritis2024

Predicting Psoriatic Arthritis in Psoriasis Patients - A Swiss Registry Study.

Mia-Louise Nielsen, Troels C Petersen, Lara Valeska Maul, Jacob P Thyssen, Simon F Thomsen, Jashin J Wu, Alexander A Navarini, Thomas Kündig, Nikhil Yawalkar, Christoph Schlapbach and 7 more

Abstract read
In one paragraph

Article in Journal of psoriasis and psoriatic arthritis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

17 authors.

Mia-Louise NielsenDepartment of Dermatology, Bispebjerg Hospital, University of Copenhagen, Copenhagen, Denmark.ORCID https://orcid.org/0000-0002-1562-8568
Troels C PetersenNiels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
Lara Valeska MaulDepartment of Dermatology, University Hospital Basel, Basel, Switzerland.
Jacob P ThyssenDepartment of Dermatology, Bispebjerg Hospital, University of Copenhagen, Copenhagen, Denmark.
Simon F ThomsenDepartment of Dermatology, Bispebjerg Hospital, University of Copenhagen, Copenhagen, Denmark.
Jashin J WuDepartment of Dermatology, University of Miami Miller School of Medicine, Miami, FL, USA.
Alexander A NavariniDepartment of Dermatology, University Hospital Basel, Basel, Switzerland.
Thomas KündigFaculty of Medicine, University of Zürich, Zürich, Switzerland.
Nikhil YawalkarDepartment of Dermatology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Christoph SchlapbachDepartment of Dermatology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Wolf-Henning BoehnckeDivision of Dermatology and Venereology, Geneva University Hospitals, Geneva, Switzerland.
Curdin ConradDepartment of Dermatology, CHUV University Hospital and University of Lausanne (UNIL), Lausanne, Switzerland.
Antonio CozzioDepartment of Dermatology, Venereology and Allergy, Cantonal Hospital St. Gallen, St. Gallen, Switzerland.
Raphael MicheroliDepartment of Rheumatology, University Hospital Zürich, Zürich, Switzerland.
Lars Erik KristensenThe Parker Institute, Bispebjerg and Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.
Alexander EgebergDepartment of Dermatology, Bispebjerg Hospital, University of Copenhagen, Copenhagen, Denmark.
Julia-Tatjana MaulFaculty of Medicine, University of Zürich, Zürich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Psoriatic arthritis (PsA) is a prevalent comorbidity among patients with psoriasis, heavily contributing to their burden of disease, usually diagnosed several years after the diagnosis of psoriasis. Objectives: To investigate the predictability of psoriatic arthritis in patients with psoriasis and to identify important predictors. Methods: Data from the Swiss Dermatology Network on Targeted Therapies (SDNTT) involving patients treated for psoriasis were utilized. A combination of gradient-boosted decision trees and mixed models was used to classify patients based on their diagnosis of PsA or its absence. The variables with the highest predictive power were identified. Time to PsA diagnosis was visualized with the Kaplan-Meier method and the relationship between severity of psoriasis and PsA was explored through quantile regression. Results: A diagnosis of psoriatic arthritis was registered at baseline of 407 (29.5%) treatment series. 516 patients had no registration of PsA, 257 patients had PsA at inclusion, and 91 patients were diagnosed with PsA after inclusion. The model's AUROCs was up to 73.7%, and variables with the highest discriminatory power were age, PASI, physical well-being, and severity of nail psoriasis. Among patients who developed PsA after inclusion, significantly more first treatment series were classified in the PsA-group, compared to those with no PsA registration. PASI was significantly correlated with the median burden/severity of PsA ( Conclusions: Distinguishing between patients with and without PsA based on clinical characteristics is feasible and even predicting future diagnoses of PsA is possible. Patients at higher risk can be identified using important predictors of PsA.

Indexed as

classificationmachine learningpredictive modelspsoriasispsoriatic arthritisreal wordregistrystatistics

Identifiers

PMID39295895
PMCPMC11361495

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.