Clinical and epidemiological research radiographic progression rate over 2 years was 0.0 (0.0–3.9); 26 patients were deﬁned as progressors. At baseline neither the MBDA score (OR=1.018, 95% CI 0.988 to 1.049, p=0.25) nor DAS28-CRP (OR=1.041, 95% CI 0.645 to 1.680, p=0.87) was a signiﬁcant predictor. Similar results were obtained using MBDA scores and DAS28-CRP at 6 months. After inclusion of other known predictors for poor long-term outcome (RF and baseline damage) in a multivariate logistic regression model, the baseline MBDA score was borderline signiﬁcant as an independent predictor for progression of joint damage (OR=1.033, 95% CI 0.995 to 1.072, p=0.09) next to RF (OR=1.768, 95% CI 0.396 to 7.885, p=0.46) and baseline joint damage (OR=4.213, 95% CI 0.878 to 20.211, p=0.07). When baseline DAS28-CRP was used in the model instead of the MBDA score, this result was less clear (OR=1.155, 95% CI 0.674 to 1.980, p=0.60) next to RF (OR=2.294, 95% CI 0.534 to 9.847, p=0.26) and baseline joint damage (OR=3.359, 95% CI 0.732 to 15.411, p=0.12). The 6-month MBDA scores or DAS28-CRP were not signiﬁcant predictors in multivariate analysis. DISCUSSION Tight control studies such as CAMERA, which include regu- lar assessments of disease activity and intensive treatment approaches, have demonstrated beneﬁcial effects on long-term patient outcomes for patients with RA.7 26 32 Although tight control strategies have been integrated into RA treatment guide- lines,3 4 they may not be easily implemented in clinical practice around the world. A comprehensive panel of relevant serum protein biomarkers containing biologically rich RA disease activity information has the potential to assess disease activ- ity in an objective manner and facilitate the use of tight control strategies. In the present study, 20 serum biomarkers of RA disease activity were evaluated and 12 were used to calculate the MBDA score, a biomarker-based measure of RA disease activ- ity. The individual biomarkers represent a broad range of bio- logical pathways associated with RA disease pathophysiology. Some biomarkers that were found to be individually associ- ated with disease activity in this study are not among the 12 biomarkers included in the MBDA score. This may be because they provide redundant information and are not independently predictive of disease activity in a multivariate model when other biomarkers are present. Conversely, some biomarkers that do not have signiﬁcant individual correlations with disease activity in the CAMERA study are included in the MBDA score algo- rithm. One reason for this is that a biomarker may provide use- ful information in combination with other biomarkers but not individually.33 This analysis involved only a small number of patients, which limited our ability to address some questions of interest (such as predictive value for radiographic progression) and necessitates further studies. However, the ﬁnal MBDA score was strongly associated with clinical disease activity despite the small sample size. κ Values also showed that there is fair agreement between disease activity levels according to both measures, although it is important to realise that there is no true gold standard for disease activity. It is expected that clinical assessment and dis- ease biomarkers will differ in some cases, since they measure different aspects of the disease. Further studies are required to determine how to interpret cases in which the biomarker-based and clinical measures of disease activity differ. Also, perform- ance estimates can be inﬂuenced by the characteristics of a given cohort and will vary between studies. 1696 annrheumdis-2011-200963.indd 5 In this analysis, neither the MBDA score nor other clinical variables were clearly predictive of radiographic progression. This could be because the study population had quite limited progression over the 2 years examined, because of the lim- ited sample size and because these disease activity measures were employed at only two time points. In another early RA population, the MBDA score was signiﬁcantly correlated to future joint damage.34 Additional studies will further clarify the predictive value of the MBDA score for future radiographic progression. To determine if MBDA scores in the CAMERA cohort at base- line and 6 months were affected by different RA management strategies, changes in MBDA scores were examined in patients receiving intensive and conventional therapy. MBDA scores improved in response to treatment with a 15-point decrease across all patients studied. The observed decrease in the MBDA score was greater in the intensive group than the conventional group. However, this study was not adequately powered to compare the effectiveness of the treatment strategies. Through monitoring RA disease activity and tailoring treatment strate- gies speciﬁcally to an individual patient’s needs, low disease activity and, in some cases, remission are attainable. While obtained from a small patient population, these results suggest that monitoring of disease activity with the MBDA score can identify changes in disease activity and response to treatment. To conﬁrm this, more measurements over time should be evalu- ated, and ultimately a trial evaluating the effect of a tight con- trol strategy using the MBDA score (as compared with a clinical DAS) could be performed. In conclusion, our results establish that the MBDA score measures clinical disease activity in RA patients and can detect changes in response to treatment. This clinical multi-biomarker test could be used (in conjunction with physical examination) to quantify overall disease activity in a patient management plan. Further studies are needed to deﬁne the optimal use of biomark- ers in the management of RA. Contributors MB, GC, JJ, JB, MC, JR, FL and PW contributed to conception and design of the study. MB, YS, DH and PW contributed to the analysis of data. MB, GC, JB, FL and PW contributed to the interpretation of data. LH and DS generated biomarker data. Article drafts were written by MB and GC and critically revised by all authors. The Þnal version of the manuscript was approved by all authors. Funding Crescendo Bioscience. Competing interests Cavet, Haney, Shen and Hesterberg are all employees of Crescendo Bioscience, the company performing the multi-biomarker score and all laboratory analyses. Centola received a consulting fee from Crescendo Bioscience for his contribution to this manuscript. Ethics approval Approval provided by the Medical Ethics Committee of UMC Utrecht, The Netherlands. Provenance and peer review Not commissioned; externally peer reviewed REFERENCES 1. Kvien TK. Epidemiology and burden of illness of rheumatoid arthritis. Pharmacoeconomics 2004;22:1Ð12. 2. Atar D, Birkeland KI, Uhlig T. ÔTreat to targetÕ: moving targets from hypertension, hyperlipidaemia and diabetes to rheumatoid arthritis. Ann Rheum Dis 2010;69:629Ð30. 3. Kiely PD, Brown AK, Edwards CJ, et al. Contemporary treatment principles for early rheumatoid arthritis: a consensus statement. Rheumatology (Oxford) 2009;48:765Ð72. 4. 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