Machine learning prediction and explanatory models of serious infections in patients with rheumatoid arthritis treated with tofacitinib.

Journal: Arthritis research & therapy
PMID: 39192350

Abstract

BACKGROUND: Patients with rheumatoid arthritis (RA) have an increased risk of developing serious infections (SIs) vs. individuals without RA; efforts to predict SIs in this patient group are ongoing. We assessed the ability of different machine learning modeling approaches to predict SIs using baseline data from the tofacitinib RA clinical trials program.

Authors

  • Merete Lund Hetland
    Copenhagen Center for Arthritis Research (COPECARE), Center for Rheumatology and Spine Diseases, Centre of Head and Orthopaedics, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark.
  • Anja Strangfeld
    Epidemiology and Health Services Research, German Rheumatism Research Centre (DRFZ), Berlin, Germany.
  • Gianluca Bonfanti
    Engineering Ingegneria Informatica, Milan, Italy.
  • Dimitrios Soudis
    Pfizer Hellas S.A, Thessaloniki, Greece.
  • J Jasper Deuring
    Pfizer, Rotterdam, The Netherlands. Jasper.Deuring@Pfizer.com.
  • Roger A Edwards
    Health Services Consulting Corporation, Boxborough, MA, USA.

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