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

cris.virtualsource.author-orcid657eb181-3137-4b10-9226-937f459da4de
cris.virtualsource.author-orcid2b25a84b-cb6c-4513-841c-40f6bf102199
datacite.rightsopen.access
dc.contributor.authorNielsen, Mia-Louise
dc.contributor.authorPetersen, Troels C
dc.contributor.authorMaul, Lara Valeska
dc.contributor.authorThyssen, Jacob P
dc.contributor.authorThomsen, Simon F
dc.contributor.authorWu, Jashin J
dc.contributor.authorNavarini, Alexander A
dc.contributor.authorKündig, Thomas
dc.contributor.authorYawalkar, Nikhil
dc.contributor.authorSchlapbach, Christoph
dc.contributor.authorBoehncke, Wolf-Henning
dc.contributor.authorConrad, Curdin
dc.contributor.authorCozzio, Antonio
dc.contributor.authorMicheroli, Raphael
dc.contributor.authorErik Kristensen, Lars
dc.contributor.authorEgeberg, Alexander
dc.contributor.authorMaul, Julia-Tatjana
dc.date.accessioned2024-11-13T08:08:01Z
dc.date.available2024-11-13T08:08:01Z
dc.date.issued2024-04
dc.description.abstractBackground 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 ( = .01).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.
dc.description.sponsorshipClinic of Dermatology
dc.identifier.doi10.48620/76184
dc.identifier.pmid39295895
dc.identifier.publisherDOI10.1177/24755303231217492
dc.identifier.urihttps://boris-portal.unibe.ch/handle/20.500.12422/103400
dc.language.isoen
dc.publisherSAGE Publications
dc.relation.ispartofJournal of Psoriasis and Psoriatic Arthritis
dc.relation.issn2475-5303
dc.subjectclassification
dc.subjectmachine learning
dc.subjectpredictive models
dc.subjectpsoriasis
dc.subjectpsoriatic arthritis
dc.subjectreal word
dc.subjectregistry
dc.subjectstatistics
dc.subject.ddc600 - Technology::610 - Medicine & health
dc.titlePredicting Psoriatic Arthritis in Psoriasis Patients - A Swiss Registry Study.
dc.typearticle
dspace.entity.typePublication
dspace.file.typetext
oaire.citation.endPage50
oaire.citation.issue2
oaire.citation.startPage41
oaire.citation.volume9
oairecerif.author.affiliationClinic of Dermatology
oairecerif.author.affiliationClinic of Dermatology
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unibe.description.ispublishedpub
unibe.refereedtrue
unibe.subtype.articlejournal

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