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A multi-biomarker disease activity score can predict sustained remission in rheumatoid arthritis.

ABSTRACT: BACKGROUND:Reliable assessment of remission is important for the optimal management of rheumatoid arthritis (RA) patients. In this study, we used the multi-biomarker disease activity (MBDA) test to explore the role of biomarkers in predicting point remission and sustained remission. METHODS:RA patients on >?6?months stable therapy in stable low disease activity (DAS28-ESR ??3.2) were assessed every 3?months for 1?year. Baseline, intermittent (IR) and sustained (SR) remission were defined by DAS28-ESR, DAS28-CRP, simple disease activity index (SDAI), clinical disease activity index (CDAI) and ACR/EULAR Boolean criteria. Patients not fulfilling any remission criteria at baseline were classified as 'low disease activity state' (LDAS). Patients not fulfilling any remission criteria over 1?year were classified as 'persistent disease activity' (PDA). MBDA score was measured at baseline/3/6?months. The baseline MBDA score, the 6-month time-integrated MBDA score and MBDA biomarkers were used for analyses. The area under the receiver operating characteristic curve (AUROC) assessed the ability of the MBDA score to discriminate between remission and non-remission. Biomarkers were analysed at baseline using the Mann-Whitney test and over time using the Jonckheere-Terpstra trend test. RESULTS:Of 148 patients, 27% were in the LDAS, 65% DAS28-ESR remission, 51% DAS28-CRP remission, 40% SDAI remission, 43% CDAI remission and 25% ACR/EULAR Boolean remission at baseline. Over 1?year, 9% of patients were classified as PDA. IR and SR were achieved in 42%/47% by DAS28-ESR, 46%/29% by DAS28-CRP, 45%/20% by SDAI, 44%/21% by CDAI and 35%/9% by ACR/EULAR Boolean criteria, respectively. By all remission criteria, baseline MBDA score discriminated baseline remission (AUROCs 0.68-0.75) and IR/SR (AUROCs 0.65-0.74). The 6-month time-integrated MBDA score discriminated IR/SR (AUROCs 0.65-0.79). Baseline MBDA score and concentrations of IL-6, leptin, SAA and CRP were significantly lower in all baseline remission criteria groups vs LDAS. They and the 6-month time-integrated values were lower among patients who achieved IR/SR vs PDA over 1?year. CONCLUSIONS:This study demonstrated that the MBDA score and its biomarkers IL-6, leptin, SAA and CRP differentiated between small differences in disease activity (i.e. between low disease activity and remission states). They were also predictors of remission over 1 year.

SUBMITTER: Ma MHY

PROVIDER: S-EPMC7313155 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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A multi-biomarker disease activity score can predict sustained remission in rheumatoid arthritis.

Ma M H Y MHY Defranoux N N Li W W Sasso E H EH Ibrahim F F Scott D L DL Cope A P AP

Arthritis research & therapy 20200624 1

<h4>Background</h4>Reliable assessment of remission is important for the optimal management of rheumatoid arthritis (RA) patients. In this study, we used the multi-biomarker disease activity (MBDA) test to explore the role of biomarkers in predicting point remission and sustained remission.<h4>Methods</h4>RA patients on > 6 months stable therapy in stable low disease activity (DAS28-ESR ≤ 3.2) were assessed every 3 months for 1 year. Baseline, intermittent (IR) and sustained (SR) remission were ...[more]

PMID: 32580789

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Project description:BACKGROUND: Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. OBJECTIVES: To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. METHODS: Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. RESULTS: 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. CONCLUSION: We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.

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A multi-biomarker disease activity score can predict sustained remission in rheumatoid arthritis.

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A multi-biomarker disease activity score can predict sustained remission in rheumatoid arthritis.

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