Minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis: predictive model based on machine learning

Background: Very few data are available on predictors of minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis (PsA). Such data are crucial, since the therapeutic measures used to change the adverse course of PsA are more likely to succeed if we intervene early. In the pre...

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Autores: Queiro R., Seoane-Mato D., Laiz A., Agirregoikoa E.G., Montilla C., Park H.-S., Pinto-Tasende J.A., Bethencourt Baute J.J., Ibáñez B.J., Toniolo E., Ramírez J., García A.S., Cañete J.D., Juanola X., Fiter J., Gratacós J., Rodriguez-Moreno J., Rosa J.N., Martín A.L., García A.B., Segura P.C., Ferrer A.L., Barrio S.P., Plata Izquierdo A.J., Bustabad S., Guimerá Martín-Neda F.J., Capdevilla E.F., Díaz R.R., Cuervo A., Gibert M.A., Larraz P.T., de la Morena Barrio I., Lanza L.P., Sanchís D.B., Mesquida C.M., Murillo C., Moreno Ramos M.J., Beteta M.D., Guillén P.S.-P., Oliveira L.L., Marco T.N., Cebrián L., de la Cueva Dobao P., Steiner M., Muñoz-Fernández S., Garrido R.V., León M., Rubio E., Jiménez A.M., Fernández-Freire L.R., Luezas J.M., Sánchez-González M.D., Muñoz C.S., Senabre J.M., Rosas J.C., Soler G.S., Mataix Díaz F.J., Nieto-González J.C., González C., Ovalles Bonilla J.G., Rodríguez O.B., Medina F.J.N., Luján D., Ruiz Montesino M.D., Carrizosa Esquivel A.M., Fernández-Carballido C., Martínez-Vidal M.P., Fernández L.G., Jovani V., Alameda R.C., Sabater S.G., Romero I.B., Urruticoechea-Arana A., Torres M.S., Almodóvar R., López Estebaranz J.L., López Montilla M.D., García-Nieto A.V.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau)
Repositorio:r-IIB SANT PAU. Repositorio Institucional de Producción Científica del Instituto de Investigación Biomédica Sant Pau
OAI Identifier:oai:iibsantpau.fundanetsuite.com:p15742
Acceso en línea:https://iibsantpau.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=15742
Access Level:acceso abierto
Palabra clave:adolescent
adult
clinical trial
human
machine learning
multicenter study
pain
psoriatic arthritis
severity of illness index
treatment outcome
Adolescent
Adult
Arthritis, Psoriatic
Humans
Machine Learning
Pain
Severity of Illness Index
Treatment Outcome
Descripción
Sumario:Background: Very few data are available on predictors of minimal disease activity (MDA) in patients with recent-onset psoriatic arthritis (PsA). Such data are crucial, since the therapeutic measures used to change the adverse course of PsA are more likely to succeed if we intervene early. In the present study, we used predictive models based on machine learning to detect variables associated with achieving MDA in patients with recent-onset PsA. Methods: 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. The dataset contained data for the independent variables from the baseline visit and from follow-up visit number 1. These were matched with the outcome measures from follow-up visits 1 and 2, respectively. We trained a random forest–type machine learning algorithm to analyze the association between the outcome measure and the variables selected in the bivariate analysis. In order to understand how the model uses the variables to make its predictions, we applied the SHAP technique. We used a confusion matrix to visualize the performance of the model. Results: The sample comprised 158 patients. 55.5% and 58.3% of the patients had MDA at the first and second follow-up visit, respectively. In our model, the variables with the greatest predictive ability were global pain, impact of the disease (PsAID), patient global assessment of disease, and physical function (HAQ-Disability Index). The percentage of hits in the confusion matrix was 85.94%. Conclusions: A key objective in the management of PsA should be control of pain, which is not always associated with inflammatory burden, and the establishment of measures to better control the various domains of PsA. © 2022, The Author(s).

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