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Meta-Analysis
. 2019 Nov;71(11):1459-1472.
doi: 10.1002/acr.23785.

Correlation of the Multi-Biomarker Disease Activity Score With Rheumatoid Arthritis Disease Activity Measures: A Systematic Review and Meta-Analysis

Tate M Johnson  1 , Kyle A Register  2 , Cynthia M Schmidt  3 , James R O'Dell  1 , Ted R Mikuls  1 , Kaleb Michaud  4 , Bryant R England  1
Affiliations
Meta-Analysis

Correlation of the Multi-Biomarker Disease Activity Score With Rheumatoid Arthritis Disease Activity Measures: A Systematic Review and Meta-Analysis

Tate M Johnson et al. Arthritis Care Res (Hoboken). 2019 Nov.

Abstract

Objective: There are conflicting reports on the validity of the multi-biomarker disease activity (MBDA) score for assessing rheumatoid arthritis (RA) disease activity. Our aim was to perform a systematic review of the MBDA and a meta-analysis of the correlation between the MBDA and other RA disease activity measures.

Methods: A systematic review was performed by searching Medline, Embase, Scopus, Google Scholar, and the Cochrane Library from inception to March 7, 2017. Study details, MBDA performance, and study quality were assessed by independent reviewers. Correlations of the MBDA with composite RA disease activity measures were pooled using random-effects meta-analyses.

Results: A total of 22 studies were identified in the systematic review, of which 8 (n = 3,242 assays) reported correlations of the MBDA with RA disease activity measures. Pooling results from these 8 studies in the meta-analysis, the MBDA demonstrated modest correlations with the Disease Activity Score in 28 joints using the C-reactive protein level (DAS28-CRP; r = 0.41, 95% confidence interval [95% CI] 0.36-0.46) and the Disease Activity Score using the erythrocyte sedimentation rate (DAS28-ESR; r = 0.48, 95% CI 0.38-0.58), with weaker correlations observed with the Simplified Disease Activity Index (SDAI; r = 0.35, 95% CI 0.26-0.43), Clinical Disease Activity Index (CDAI; r = 0.26, 95% CI 0.19-0.33), and Routine Assessment of Patient Index Data 3 (RAPID3; r = 0.23, 95% CI 0.19-0.27). Correlations between change in MBDA and change in disease activity measures ranged from r = 0.53 for the DAS28-ESR to r = 0.26 for the CDAI.

Conclusion: The MBDA demonstrates moderate convergent validity with the DAS28-CRP and the DAS28-ESR but weaker correlations with the SDAI, CDAI, and RAPID3. While it appears to complement existing RA disease activity measures, further assessment of the performance characteristics of the MBDA is warranted.

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Figures

Figure 1.
Figure 1.. Flow diagram of study selection.
Search strategy identified 718 articles with 470 remaining after removing duplicates. After title and abstract review, 121 full text manuscripts were reviewed with 22 fulfilling criteria for inclusion into the systematic review and 8 further fulfilling criteria for inclusion in meta-analysis.
Figure 2.
Figure 2.. Correlation of the multi-biomarker disease activity score with rheumatoid arthritis disease activity measures.
Forest plots demonstrating the correlation of the multi-biomarker disease activity score with RA disease activity measures including (A) DAS28-CRP, (B) SDAI, (C) CDAI, and (D) RAPID3. Studies assessing correlation at multiple time points are modeled separately for meta-analysis. *Patients with initial follow-up at 6 weeks and again at 12 weeks if adequate treatment response not obtained in the BRASS and NESTED cohorts (Curtis 2012).
Figure 3.
Figure 3.. Correlation of the change in multi-biomarker disease activity score with change in rheumatoid arthritis disease activity measures over time.
Forest plots demonstrating correlation of change in multi-biomarker disease activity score with change in RA disease activity measures including (A) DAS28-CRP, (B) SDAI, (C) CDAI, (D) RAPID3. Studies assessing correlation at multiple follow up points are modeled separately for meta-analysis. *Patients followed up initially at 6 weeks, and again at 12 weeks if adequate treatment response not obtained in the BRASS and NESTED cohorts (Curtis 2012).
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Comment in

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