Can Biomarkers already guide treatment decisions?

A post-hoc analysis of a trial in RA patients shows that biomarkers may help to identify patients at risk for progression and thus enable individualised treatment decisions.

C-reactive protein, autoantibodies and clinical disease activity are excellent predictors

A post-hoc analysis of a trial in RA patients shows that biomarkers may help to identify patients at risk for progression and thus enable individualised treatment decisions.

Treatment decisions in rheumatology became increasingly complex during the previous decades. According to Ronald van Vollenhoven, rheumatologist at the Department of Medicine, Solna (Sweden) biomarkers could offer the best solution to the dilemma how to treat patients. “Since 20 years we say the biomarkers are right around the corner – I try to convince you that this will indeed be the case in the next years” said van Vollenhoven. Even today, everybody uses biomarkers in rheumatology e.g. f C reactive protein. “However, we do hope for more sophisticated biomarkers that could guide treatment”, stated van Vollenhoven. A promising example is a labrogate commercially marketed, multimarker disease activity panel that assays levels of 12 biomarkers. In a post hoc analysis of 235 patients with early rheumatoid arthritis enrolled in the SWEFOT trial it showed prognostic value: Those patients with a low or moderate MBDA score had only a 3% risk for radiographic progression, whereas 21% of patients with high scores on this multibiomarker disease activity panel at baseline had radiographic progression of their rheumatoid arthritis during the following year.

“We have an interesting test, and we wanted to know, whether it makes sense to treat high risk patients according to the MBDA score more aggressively”, said van Vollenhoven.

MBDA predicts treatment response

The primary endpoint of the SWEFOT trial was the percentage of EULAR good response after 12 months: 25% of the study population reached this goal with a triple therapy of conventional disease modifying drugs (methotrexate (MTX), sulfasalazine (SSZ) and hydroxychloroquine (HCQ)) and 39% with MTX in combination with a TNF-Blockers – not a very impressive result. However, when data from patients with high MBDA scores at baseline were analysed the difference was striking: Only 38% of patients with high MBDA scores gained the primary endpoint with the triple therapy compared to 61% with a TNF-Blocker. “The test helps us to identify patients, who do a lot better with a TNF-Blocker”; said van Vollenhoven. In patients with low MBDA scores it was vice versa: They benefited more from the triple combination.

The MBDA is an example of the potential of biomarkers to guide treatment decisions and to identify a subset of patients, which particularly benefit from biologicals. “Biomarkers will increasingly help achieve personalized treatment in rheumatology”, concluded van Vollenhofen. Josef Smolen, Director of the university clinic AKH Vienna (Austria), is far less optimistic: “I am very fond of biomarker research but despite many efforts, research into new biomarker has been disappointing and has not surpassed what we have known for ages: That C-reactive protein and autoantibodies as well as clinical disease activity are excellent predictors on all accounts”, he said in the discussion.

Van Vollenhofen R. Biomarkers are critical for our future. Abstract SP0129, presented on the 12th of June, 2016 Annual EULAR Meeting.

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