Objective Quantitative assessment of disease activity in rheumatoid arthritis (RA) is important for patient management, and additional objective information may aid rheumatologists in clinical decision-making. We validated a recently-developed multi-biomarker disease activity (MBDA) test relative to clinical disease activity in diverse RA cohorts. Methods Serum samples were obtained from the InFoRM, BRASS, and Leiden Early Arthritis Clinic cohorts. Levels of 12 biomarkers were measured and combined according to a pre-specified algorithm to generate the composite MBDA score. The relationship of the MBDA score to clinical disease activity was characterized separately in seropositive and seronegative patients using Pearson correlations and area under the receiver operator characteristic curve (AUROC) to discriminate between patients with low and moderate/high disease activity. Associations between changes in MBDA score and clinical responses 6–12 weeks after initiation of anti-TNF or methotrexate treatment were evaluated by AUROC. Results The MBDA score was significantly associated with DAS28-CRP in both seropositive (AUROC=0.77; P<0.001) and seronegative patients (AUROC=0.70; P<0.001). In subgroups based on age, sex, body-mass index, and treatment, the MBDA score was associated with DAS28-CRP (P<0.05) in all seropositive and most seronegative subgroups. Changes in MBDA score at 6–12 weeks could discriminate both ACR50 responses (P=0.03) and DAS28-CRP improvement (P=0.002). Changes in MBDA score at 2 weeks were also associated with subsequent DAS28-CRP response (P=0.02). Conclusion Our findings establish the criterion and discriminant validity of a novel multi-biomarker test as an objective measure of RA disease activity to aid in the management of RA patients.
BackgroundDisease 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.ObjectivesTo develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis.MethodsCandidate 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.Results130 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.ConclusionWe 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.
Although diabetes is a risk factor for sepsis, once established, the outcome of severe sepsis does not appear to be significantly influenced by the presence of diabetes. In nondiabetic patients, however, admission hyperglycemia is associated with an increased mortality.
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