121173 20240319081015.0 doi 10.3390/jcm11154518 sideral 131825 ART-2022-131825 eng Chaparro, María Using Interpretable Machine Learning to Identify Baseline Predictive Factors of Remission and Drug Durability in Crohn’s Disease Patients on Ustekinumab 2022 Access copy available to the general public Unrestricted Ustekinumab has shown efficacy in Crohn’s Disease (CD) patients. To identify patient profiles of those who benefit the most from this treatment would help to position this drug in the therapeutic paradigm of CD and generate hypotheses for future trials. The objective of this analysis was to determine whether baseline patient characteristics are predictive of remission and the drug durability of ustekinumab, and whether its positioning with respect to prior use of biologics has a significant effect after correcting for disease severity and phenotype at baseline using interpretable machine learning. Patients’ data from SUSTAIN, a retrospective multicenter single-arm cohort study, were used. Disease phenotype, baseline laboratory data, and prior treatment characteristics were documented. Clinical remission was defined as the Harvey Bradshaw Index ≤ 4 and was tracked longitudinally. Drug durability was defined as the time until a patient discontinued treatment. A total of 439 participants from 60 centers were included and a total of 20 baseline covariates considered. Less exposure to previous biologics had a positive effect on remission, even after controlling for baseline disease severity using a non-linear, additive, multivariable model. Additionally, age, body mass index, and fecal calprotectin at baseline were found to be statistically significant as independent negative risk factors for both remission and drug survival, with further risk factors identified for remission. info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 3.9 2022 MEDICINE, GENERAL & INTERNAL 58 / 169 = 0.343 2022 Q2 T2 0.935 2022 Medicine (miscellaneous) 2022 Q1 5.4 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Baston-Rey, Iria Fernández Salgado, Estela González García, Javier Ramos, Laura Diz-Lois Palomares, María Teresa Argüelles-Arias, Federico Iglesias Flores, Eva Cabello, Mercedes Rubio Iturria, Saioa Núñez Ortiz, Andrea Charro, Mara Ginard, Daniel Dueñas Sadornil, Carmen Merino Ochoa, Olga Busquets, David Iyo, Eduardo Gutiérrez Casbas, Ana Ramírez de la Piscina, Patricia Boscá-Watts, Marta Maia Arroyo, Maite García, María José Hinojosa, Esther Gordillo, Jordi Martínez Montiel, Pilar Velayos Jiménez, Benito Quílez Ivorra, Cristina Vázquez Morón, Juan María Huguet, José María González-Lama, Yago Muñagorri Santos, Ana Isabel Amo, Víctor Manuel Martín Arranz, María Dolores Bermejo, Fernando Martínez Cadilla, Jesús Rubín de Célix, Cristina Fradejas Salazar, Paola López San Román, Antonio Jiménez, Nuria García-López, Santiago Universidad de Zaragoza (orcid)0000-0003-3970-5457 Figuerola, Anna Jiménez, Itxaso Martínez Cerezo, Francisco José Taxonera, Carlos Varela, Pilar de Francisco, Ruth Monfort, David Molina Arriero, Gema Hernández-Camba, Alejandro García Alonso, Francisco Javier Van Domselaar, Manuel Pajares-Villarroya, Ramón Núñez, Alejandro Rodríguez Moranta, Francisco Marín-Jiménez, Ignacio Robles Alonso, Virginia Martín Rodríguez, María del Mar Camo-Monterde, Patricia García Tercero, Iván Navarro-Llavat, Mercedes García, Lara Arias Hervías Cruz, Daniel Kloss, Sebastian Passey, Alun Novella, Cynthia Vispo, Eugenia Barreiro-de Acosta, Manuel Gisbert, Javier P. 1007 610 Universidad de Zaragoza Dpto. Medicina, Psiqu. y Derm. Area Medicina 11, 15 (2022), 4518 [17 pp.] J. clin.med. Journal of Clinical Medicine 2077-0383 1542141 http://zaguan.unizar.es/record/121173/files/texto_completo.pdf Versión publicada 3347867 http://zaguan.unizar.es/record/121173/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:121173 articulos driver 2024-03-18-15:34:49 ARTICLE