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Prediction of radiographic progression (RP) in early rheumatoid arthritis (eRA) would be very useful for optimal choice among available therapies. We evaluated a multi-biomarker disease activity (MBDA) score, based on 12 serum biomarkers as a baseline predictor for 1-year RP in eRA. Baseline disease activity score based on erythrocyte sedimentation rate (DAS28-ESR), disease activity score based on C-reactive protein (DAS28-CRP), CRP, MBDA scores and DAS28-ESR at 3 months were analysed for 235 patients with eRA from the Swedish Farmacotherapy (SWEFOT) clinical trial. RP was defined as an increase in the Van der Heijde-modified Sharp score by more than five points over 1 year. Associations between baseline disease activity measures, the MBDA score, and 1-year RP were evaluated using univariate and multivariate logistic regression, adjusted for potential confounders. Among 235 patients with eRA, 5 had low and 29 moderate MBDA scores at baseline. None of the former and only one of the latter group (3.4%) had RP during 1 year, while the proportion of patients with RP among those with high MBDA score was 20.9% (p=0.021). Among patients with low/moderate CRP, moderate DAS28-CRP or moderate DAS28-ESR at baseline, progression occurred in 14%, 15%, 14% and 15%, respectively. MBDA score was an independent predictor of RP as a continuous (OR=1.05, 95% CI 1.02 to 1.08) and dichotomised variable (high versus low/moderate, OR=3.86, 95% CI 1.04 to 14.26). In patients with eRA, the MBDA score at baseline was a strong independent predictor of 1-year RP. These results suggest that when choosing initial treatment in eRA the MBDA test may be clinically useful to identify a subgroup of patients at low risk of RP. WHO database at the Karolinska Institute: CT20080004; and clinicaltrials.gov: NCT00764725.

Successfully stopping or reducing treatment for patients with rheumatoid arthritis (RA) in low disease activity (LDA) may improve cost-effectiveness of care. We evaluated the multi-biomarker disease activity (MBDA) score as a predictor of disease relapse after discontinuation of TNF inhibitor (TNFi) treatment. 439 RA patients who were randomized to stop TNFi treatment in the POET study were analyzed post-hoc. Three indicators of disease relapse were assessed over 12 months: 1) restarting TNFi treatment, 2) escalation of any DMARD therapy and 3) physician-reported flare. MBDA score was assessed at baseline. Associations between MBDA score and disease relapse were examined using univariate analysis and multivariate logistic regression. At baseline, 50.1%, 35.3% and 14.6% of patients had low (<30), moderate (30-44) or high (>44) MBDA scores. Within 12 months, 49.9% of patients had restarted TNFi medication, 59.0% had escalation of any DMARD and 57.2% had ≥1 physician-reported flare. MBDA score was associated with each indicator of relapse. At least one indicator of relapse was observed in 59.5%, 68.4% and 81.3% of patients with low, moderate or high MBDA scores, respectively (P = 0.004). Adjusted for baseline DAS28-ESR, disease duration, BMI and erosions, high MBDA scores were associated with increased risk for restarting TNFi treatment (OR = 1.85, 95% CI 1.00-3.40), DMARD escalation (OR = 1.99, 95% CI 1.01-3.94) and physician-reported flare (OR = 2.00, 95% 1.06-3.77). For RA patients with stable LDA who stopped TNFi, a high baseline MBDA score was independently predictive of disease relapse within 12 months. The MBDA score may be useful for identifying patients at risk of relapse after TNFi discontinuation.

Variability exists in the assessment of disease activity in rheumatoid arthritis (RA) patients that may affect quality of care. To measure the impact on quality of care of a Multi-Biomarker Disease Activity (MBDA) test that quantitatively assesses RA disease activity. Board-certified rheumatologists without prior experience with the MBDA test (N = 81) were randomized into an intervention or control group as part of a longitudinal randomized-control study. All physicians were asked to care for three simulated RA patients, using Clinical Performance and Value (CPV™) vignettes, in a before and after design. CPV™ vignettes have been validated to assess the quality of clinical practice and identify variation in care. The vignettes covered all domains of a regular patient visit; scores were determined as a percentage of explicit predefined criteria completed. Three vignettes, representing typical RA cases, were administered each round. In the first round, no physician received information about the MBDA test. In the second round, only physicians in the intervention group were given educational materials about the test and hypothetical test results for each of the simulated patients. The outcome measures were the overall quality of care, disease assessment and treatment. The overall quality scores in the intervention group improved by 3 percent (p = 0.02) post-intervention compared with baseline, versus no change in the control group. The greatest benefit in the intervention group was to the quality of disease activity assessment and treatment decisions, which improved by 12 percent (p<0.01) compared with no significant change in the control group. The intervention was associated with more appropriate use of biologic and/or combination DMARDs in the co-morbidity case type (p<0.01). Based on these results, use of the MBDA test improved the assessment and treatment decisions for simulated cases of RA and may prove useful for rheumatologists in clinical practice.

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. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. 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. 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. 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.

There is a broad and growing interest in Bioelectronic Medicine, a dynamic field that continues to generate new approaches in disease treatment. The fourth bioelectronic medicine summit “Technology targeting molecular mechanisms” took place on September 23 and 24, 2020. This virtual meeting was hosted by the Feinstein Institutes for Medical Research, Northwell Health. The summit called international attention to Bioelectronic Medicine as a platform for new developments in science, technology, and healthcare. The meeting was an arena for exchanging new ideas and seeding potential collaborations involving teams in academia and industry. The summit provided a forum for leaders in the field to discuss current progress, challenges, and future developments in Bioelectronic Medicine. The main topics discussed at the summit are outlined here.

The Laser Interferometer Space Antenna (LISA) has two scientific objectives of cosmological focus: to probe the expansion rate of the universe, and to understand stochastic gravitational-wave backgrounds and their implications for early universe and particle physics, from the MeV to the Planck scale. However, the range of potential cosmological applications of gravitational-wave observations extends well beyond these two objectives. This publication presents a summary of the state of the art in LISA cosmology, theory and methods, and identifies new opportunities to use gravitational-wave observations by LISA to probe the universe.

We assessed the effect of influenza vaccination on plasma levels of human immunodeficiency virus type 1 (HIV-1) RNA and the impact of age, plasma HIV-1 RNA level, CD4 cell count, and anti-HIV therapy on immune response. Forty-nine adults (mean age, 38.7 years; mean CD4 cell count ±SD, 190 ± 169/mL; mean plasma HIV-1 RNA level ± SD, 154,616 ± 317,192 copies/mL) were immunized. Elevations of ⩾0.48 log in plasma HIV-1 RNA levels occurred in two (4%) of 49 subjects within 4 weeks of vaccination. A fourfold or greater increase in antibody titer occurred in 13 (45%) of 29 subjects, correlating directly with CD4 cell count (P = .002) and inversely with plasma HIV-1 RNA level (P = .034). By multivariate analysis, CD4 cell count was a stronger predictor of antibody response than was plasma HIV-1 RNA level. We conclude that increases in plasma HIV-1 RNA levels following influenza vaccination are rare and transient and that antibody response is impaired with CD4 cell counts of <100/mL and plasma HIV-1 RNA levels of >100,000 copies/mL. Prospective trials are needed to evaluate the impact of highly active therapy on immune response after vaccination.

PurposeWe assessed the impact of adjustment of the multi-biomarker disease activity score (MBDA) for age, sex, and leptin, over the range of age and adiposity, and assessed relationships with clinical disease activity.MethodsPatients with RA, ages 18–75 years, were recruited from clinical practices and completed whole-body DXA to quantify fat mass indices (FMI, kg/m2). FMI Z-scores were calculated based on distributions in a reference population. Descriptive statistics described relationships between age, FMI Z-score, and the original MBDA and adjusted MBDA (aMBDA). Swollen joint counts (SJC) and the clinical disease activity index (CDAI) were assessed over MBDA categories.ResultsThere were 104 participants (50% female) with mean (SD) age of 56.1 (12.5) and body mass index (BMI) of 28.8 (6.9). Older age was associated with higher MBDA scores in men. The aMBDA was not associated with age. The original MBDA score was associated with FMI Z-score among women (Rho = 0.42, p = 0.002) but not men. The aMBDA was not associated with FMI Z-score in either women or men. The aMBDA score was lower than the original MBDA in the highest quartile of FMI in women and was higher in the lowest FMI quartiles in women and men. CDAI, SJC, and radiographic scores were similar across activity categories for the original MBDA score and aMBDA.ConclusionsThe aMBDA demonstrated reduced associations with adiposity, particularly among women. The aMBDA may be less likely to overestimate disease activity in women with greater adiposity and to underestimate disease activity in men and women with lesser adiposity.Key Points• Leptin adjustment of the MBDA score reduces the influence of adiposity, particularly among women.• Leptin adjustment results in significantly higher estimated disease activity in thin men and women.• The adjusted and unadjusted score correlate similarly with clinical disease activity measures.

By analysing archived baseline samples from the SWEFOT study, we found that MBDA predicted radiographic progression at 1 year in early patients with RA and that MBDA was a stronger predictor of radiographic progression than conventional measures of disease activity at baseline, such as Disease Activity Score in 28 Joints, C-reactive protein or erythrocyte sedimentation rate.