» Articles » PMID: 30442830

Uptake and Clinical Utility of Multibiomarker Disease Activity Testing in the United States

Overview
Journal J Rheumatol
Specialty Rheumatology
Date 2018 Nov 17
PMID 30442830
Citations 2
Authors
Affiliations
Soon will be listed here.
Abstract

Objective: The clinical utility of the multibiomarker disease activity (MBDA) test for rheumatoid arthritis (RA) management in routine care in the United States has not been thoroughly studied.

Methods: Using 2011-2015 Medicare data, we linked each patient with RA to their MBDA test result. Initiation of a biologic or Janus kinase (JAK) inhibitor in the 6 months following MBDA testing was described. Multivariable adjustment evaluated the likelihood of adding or switching biologic/JAK inhibitor, controlling for potential confounders. For patients with high MBDA scores who added a new RA therapy and were subsequently retested, lack of improvement in the MBDA score was evaluated as a predictor of future RA medication failure, defined by the necessity to change RA medications again.

Results: Among 60,596 RA patients with MBDA testing, the proportion adding or switching biologics/JAK inhibitor among those not already taking a biologic/JAK inhibitor was 9.0% (low MBDA), 11.8% (moderate MBDA), and 19.7% (high MBDA, p < 0.0001). Similarly, among those already taking biologics/JAK inhibitor, the proportions were 5.2%, 8.3%, and 13.5% (p < 0.0001). After multivariable adjustment, referent to those with low disease MBDA scores, the likelihood of switching was 1.51-fold greater (95% CI 1.35-1.69) for patients with moderate MBDA scores, and 2.62 (2.26-3.05) for patients with high MBDA scores. Among those with high MBDA scores who subsequently added a biologic/JAK inhibitor and were retested, lack of improvement in the MBDA score category was associated with likelihood of future RA treatment failure (OR 1.61, 95% CI 1.27-2.03).

Conclusion: The MBDA score was associated with both biologic and JAK inhibitor medication addition/switching and subsequent treatment outcomes.

Citing Articles

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review.

Glaab E, Rauschenberger A, Banzi R, Gerardi C, Garcia P, Demotes J BMJ Open. 2021; 11(12):e053674.

PMID: 34873011 PMC: 8650485. DOI: 10.1136/bmjopen-2021-053674.


Derivation and internal validation of a multi-biomarker-based cardiovascular disease risk prediction score for rheumatoid arthritis patients.

Curtis J, Xie F, Crowson C, Sasso E, Hitraya E, Chin C Arthritis Res Ther. 2020; 22(1):282.

PMID: 33276814 PMC: 7718706. DOI: 10.1186/s13075-020-02355-0.

References
1.
Curtis J, van der Helm-van Mil A, Knevel R, Huizinga T, Haney D, Shen Y . Validation of a novel multibiomarker test to assess rheumatoid arthritis disease activity. Arthritis Care Res (Hoboken). 2012; 64(12):1794-803. PMC: 3508159. DOI: 10.1002/acr.21767. View

2.
Michaud K, Strand V, Shadick N, Degtiar I, Ford K, Michalopoulos S . Outcomes and costs of incorporating a multibiomarker disease activity test in the management of patients with rheumatoid arthritis. Rheumatology (Oxford). 2015; 54(9):1640-9. PMC: 4536857. DOI: 10.1093/rheumatology/kev023. View

3.
Li W, Sasso E, Emerling D, Cavet G, Ford K . Impact of a multi-biomarker disease activity test on rheumatoid arthritis treatment decisions and therapy use. Curr Med Res Opin. 2012; 29(1):85-92. DOI: 10.1185/03007995.2012.753042. View

4.
Yu Z, Lu B, Agosti J, Bitton A, Corrigan C, Fraenkel L . Implementation of Treat-to-Target for Rheumatoid Arthritis in the US: Analysis of Baseline Data From a Randomized Controlled Trial. Arthritis Care Res (Hoboken). 2017; 70(5):801-806. PMC: 5823714. DOI: 10.1002/acr.23343. View

5.
Curtis J, Chen L, Bharat A, Delzell E, Greenberg J, Harrold L . Linkage of a de-identified United States rheumatoid arthritis registry with administrative data to facilitate comparative effectiveness research. Arthritis Care Res (Hoboken). 2014; 66(12):1790-8. PMC: 4245366. DOI: 10.1002/acr.22377. View