Machine learning identifies patients with RA most likely to benefit from sarilumab

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Sumary of Machine learning identifies patients with RA most likely to benefit from sarilumab:

  • A model using machine learning was able to ascertain a simple selection rule to identify which patients with rheumatoid arthritis would benefit most from sarilumab, according to a speaker at the 2020 ACR Convergence Annual Meeting..
  • “Despite the existence of guidelines for DMARD treatment of RA, a more individualized approach to treatment is needed to maximize efficacy while minimizing risk of adverse events,”.
  • “At the moment, we are facing a trial and error approach with RA treatment because we do not have a way of predicting which patient will respond to which treatment..
  • “This study, through machine learning, looked at different predictors of response to sarilumab, to see what patients may benefit the most from treatment with sarilumab,”.
  • “These findings could help physicians make better informed decisions, especially when it comes to their decision making when considering sarilumab for their patients.”.
  • Adobe Stock “In phase 3 trials, sarilumab, an IL-6 receptor inhibitor approved for treatment of moderate to severe RA, has been shown to be superior to both placebo — in the MOBILITY and TARGET clinical trials — and the TNF-alpha inhibitor adalimumab — in the MONARCH clinical trial,”.
  • “However, the characteristics of patients who are most likely to benefit from sarilumab treatment remain poorly understood.”.
  • Regeneron, Sanofi) or adalimumab (Humira, AbbVie) for RA, Choy and colleagues drew data from the sarilumab clinical development program..
  • Using a decision-tree classification approach, and the Generalized, Unbiased, Interaction Detection and Estimation (GUIDE) algorithm, the researchers built predictive models based on the American College of Rheumatology response criteria at week 24 among participants from the MOBILITY trial..
  • Choy and colleagues identified 17 categorical and 25 continuous baseline variables as candidate predictors, chosen based on subject matter expertise..
  • The researchers validated the resulting rule using independent data sets from the MOBILITY, TARGET and MONARCH trials — which included 1,197, 546 and 369 participants, respectively — as well as on the tocilizumab-calibrator study ASCERTAIN, which included 202 total participants..
  • Among the 42 candidate variables, the combined presence of anti-citrullinated protein antibodies and a CRP level of more than 12.3 mg/L was identified as a predictor — or rule — of better treatment outcomes with sarilumab…

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