“Biomarkers will increasingly help achieve personalized treatment in rheumatology,” he said.
Role of Dependent Variables
Session moderator Gary Firestein, MD, a rheumatologist and professor of medicine at the University of California San Diego, said that in a multi-component test, “the components should be independent. And this is one of the issues that raises a lot of questions about utility here. There are at least three or four different components of the MBDA assays that are dependent variables.” For example, if IL-6 goes down, CRP and other variables are likely to go down, as well.
Dr. van Vollenhoven said the 12 components of the MBDA were chosen out of 180 component candidates in order to find the best correlation with DAS28.
He said it’s difficult to have a composite test that matches up with traditional clinical measures while also remaining distinct from those measures.
“You can say, ‘I want the biomarker that correlates to 100% with the clinical marker—but that doesn’t tell me anything else than what you already know from the clinical marker.’ Or you can have a biomarker that’s completely different from a clinical marker, and you say, ‘Gee, I don’t think I can trust that. That seems such a strange result.’
“You can’t have it both ways.”
Thomas R. Collins is a freelance medical writer based in Florida.
References
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- Fleischmann R, Connolly SE, Maldonado MA, et al. Estimating disease activity using multi-biomarker disease activity scores in patients with rheumatoid arthritis treated with abatacept or adalimumab. Arthritis Rheumatol. 2016 Apr 25.
- Hambardzumyan K, Bolce R, Saevarsdottir S, et al. Pretreatment multi-biomarker disease activity score and radiographic progression in early RA: Results from the SWEFOT trial. Ann Rheum Dis. 2015 Jun;74(6):1102–1109.