Vectra® DA

Rheumatoid arthritis (RA) has high prevalence (1.5 million adult cases in the US) and high median annual healthcare costs ($4,677 for RA patients vs. $1,229 for non-RA patients).

RA can be treated with two types of disease modifying anti-rheumatic drugs (DMARDs): traditional non-biologic DMARDs (appropriate with low RA disease activity) and biologic DMARDs (appropriate with high RA disease activity). Biologic DMARDs lead to decreased mean disease activity, hospitalization, sick leave, and work-related disability in RA patients, but cause significant increase in treatment costs.

Although significant clinical advances have been made in RA over the last two decades, challenges remain in optimizing treatment decisions, which add unnecessary healthcare costs and increase burden on payers. For the most part, clinicians do not use formal measures of disease activity and when they do, the measures used are made up of subjective components, such as the DAS28, CDAI, SDAI, and RAPID3*, and measure on-going efficacy of different therapy selections.

There is a need for objective measures of disease activity that provide a comprehensive understanding of disease progression at the patient level, taking into account RA disease heterogeneity, while minimizing the impact on the physician’s time. Vectra® DA fulfills this unmet need by combining multiple serum biomarkers into a single score that can help physicians characterize disease activity in patients, assess response to treatment, identify risk of joint damage, and potentially guide second line treatment after methotrexate and inform tapering decisions for patients in stable remission.+ Use of Vectra DA may help avoid unnecessary drug exposure and expenditure, potentially creating overall savings for physicians, patients, and payers.

* DAS28: 28-Joint Disease Activity Score, CDAI: Clinical Disease Activity Index, SDAI: Simplified Disease Activity Index, RAPID3: Routine Assessment of Patient Index Data.
+ This test is not intended or validated to diagnose RA, to predict response to specific therapies or classes of therapies, or to guide therapy taper or withdrawal.