Severe Disease in Patients With Recent-Onset Psoriatic Arthritis. Prediction Model Based on Machine Learning

To identify patient- and disease-related characteristics that make it possible to predict higher disease severity in recent-onset PsA. We performed a multicenter observational prospective study (2-year follow-up, regular annual visits). The study population comprised patients aged ≥ 18 years who ful...

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Bibliographic Details
Authors: Queiro, Ruben|||0000-0002-8418-7145, Seoane-Mato, Daniel|||0000-0001-5430-039X, Laiz, Ana|||0000-0002-2820-4801, Galíndez Agirregoikoa, Eva, Montilla, Carlos, Park, Hye S.|||0000-0002-4972-9527, Pinto Tasende, Jose A., Bethencourt Baute, Juan José|||0000-0002-9382-9234, Joven Ibáñez, Beatriz, Toniolo, Elide|||0000-0002-8327-4861, Ramírez, Julio, Pruenza García-Hinojosa, Cristina
Format: article
Publication Date:2022
Country:España
Institution:Universitat Autònoma de Barcelona
Repository:Dipòsit Digital de Documents de la UAB
Language:English
OAI Identifier:oai:ddd.uab.cat:286342
Online Access:https://ddd.uab.cat/record/286342
https://dx.doi.org/urn:doi:10.3389/fmed.2022.891863
Access Level:Open access
Keyword:Global pain
Machine learning
Perianal psoriasis
Prediction model
Recent-onset psoriatic arthritis
Severe disease
Description
Summary:To identify patient- and disease-related characteristics that make it possible to predict higher disease severity in recent-onset PsA. We performed a multicenter observational prospective study (2-year follow-up, regular annual visits). The study population comprised patients aged ≥ 18 years who fulfilled the CASPAR criteria and less than 2 years since the onset of symptoms. Severe disease was defined at each visit as fulfillment of at least 1 of the following criteria: need for systemic treatment, Health Assessment Questionnaire (HAQ).

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