Predicción de la respuesta al tratamiento en pacientes con artritis reumatoide utilizando un modelo basado en machine learning

Abstract

Rheumatoid arthritis (RA) is a chronic inflammatory, autoimmune and disabling disease. Response to treatment or sustained remission are the main goals in the management of these patients; however, a significant number of patients do not respond to treatment. Therefore, predicting the achievement of response or remission is essential for patient management, since it allows considering the gradual decrease in the use of therapies, helping to avoid potential negative outcomes at the joint level and unwanted side effects; in addition to contributing to the reduction of the high costs of the type of therapies used in RA. Objective. To identify the predictive variables of the response to treatment or remission in patients with rheumatoid arthritis treated between 2018 and 2022 in a Care Center for Rheumatoid Arthritis.