Toward Individualized Prediction of Response to Methotrexate in Early Rheumatoid Arthritis: A Pharmacogenomics-Driven Machine Learning Approach.
Elena MyasoedovaArjun P AthreyaCynthia S CrowsonJohn M DavisKenneth J WarringtonRobert C WalchakErin CarlsonKrishna R KalariTim BongartzPaul P TakRonald F van VollenhovenLeonid PadyukovPaul EmeryAnn W MorganLiewei WangRichard M WeinshilboumEric L Mattesonnull nullPublished in: Arthritis care & research (2022)
Pharmacogenomic biomarkers combined with baseline DAS28 scores can be useful in predicting response to methotrexate in patients with early RA. Applying ML to predict treatment response holds promise for guiding effective RA treatment choices, including timely escalation of RA therapies.