Identifier to cite or link to this item: http://hdl.handle.net/20.500.13003/18197
Using Interpretable Machine Learning to Identify Baseline Predictive Factors of Remission and Drug Durability in Crohn's Disease Patients on Ustekinumab
StatisticsItem usage statistics
MetadataShow Dublin Core item record
AuthorChaparro, María; 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 Vicens, 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; 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
Document typeresearch article
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.
This item appears in following Docusalut collectionsHospital Universitario Son Espases - HUSE > Comunicación científica
Showing items related by title, author, creator and subject.