Stricter treat-to-target in RA does not result in less radiographic progression: a longitudinal analysis in RA BIODAM

OBJECTIVES

To investigate whether meticulously following a treat-to-target (T2T)-strategy in daily clinical practice will lead to less radiographic progression in patients with active RA who start (new) DMARD-therapy.

METHODS

Patients with RA from 10 countries starting/changing conventional synthetic or biologic DMARDs because of active RA, and in whom treatment intensification according to the T2T principle was pursued, were assessed for disease activity every 3 months for 2 years (RA-BIODAM cohort). The primary outcome was the change in Sharp-van der Heijde (SvdH) score, assessed every 6 months. Per 3-month interval DAS44-T2T could be followed zero, one or two times (in a total of two visits). The relation between T2T intensity and change in SvdH-score was modelled by generalized estimating equations.

RESULTS

In total, 511 patients were included [mean (s.d.) age: 56 (13) years; 76% female]. Mean 2-year SvdH progression was 2.2 (4.1) units (median: 1 unit). A stricter application of T2T in a 3-month interval did not reduce progression in the same 6-month interval [parameter estimates (for yes vs no): +0.15 units (95% CI: -0.04, 0.33) for 2 vs 0 visits; and +0.08 units (-0.06; 0.22) for 1 vs 0 visits] nor did it reduce progression in the subsequent 6-month interval.

CONCLUSIONS

In this daily practice cohort, following T2T principles more meticulously did not result in less radiographic progression than a somewhat more lenient attitude towards T2T. One possible interpretation of these results is that the intention to apply T2T already suffices and that a more stringent approach does not further improve outcome.

POS1259 AXIAL SPONDYLOARTHRITIS, AGE AND MALE GENDER IMPACT COVID VACCINATION AEs MORE THAN RHEUMATOID ARTHRITIS

Background

Rheumatologists recommend vaccination in rheumatoid arthritis (RA) and axial spondyloarthritis (axSpA) patients, but there are few studies on the occurrence of adverse events (AEs), particularly worsening disease related activity and unrelated immune reactions in these groups.

Objectives

To evaluate the uptake of COVID vaccination in RA and axSpA patients, compare the frequency of AEs, and identify risk factors associated with vaccine AEs in two prospective cohorts comprised of these patients.

Methods

The IMPACT study is a monthly survey of two prospective cohorts of established RA and axSpA patients in northern Alberta, Canada from November 2020-2021 who answered at least one or more Redcap surveys through de-identified email link surveying demographics, disease characteristics, COVID symptoms, treatment of RA and axSpA, health care utilization, vaccination status, vaccine AEs and use of cannabis. Univariate analyses evaluated independent variables associated with the dependent variables of (1) any AE, (2) any severe AE, (3) any arthritis flare, and (4) any severe arthritis flare, followed by multivariate analyses of these four dependant variables using all clinically relevant variables from the univariate analysis.

Results

773/2167 patients (RA 574, axSpA 197) responded to at least one survey. 32/663 (5%) were single vaccinated, 631 (95%) double vaccinated and 230 (54%) triple vaccinated with 80% receiving Pfizer, 24% Moderna, 28% AstraZeneca and 30% “other”. 456 (69%) reported at least one AE (Figure 1) with 21 (3%) patients seeing a physician for their AE. Increased age was associated with all AEs. RA patients had lower reported AEs versus axSpA patients for all AE definitions except for severe arthritis flares. Generally, males reported worse AEs (Table 1). “Any arthritis flare” was lower in patients reporting cannabis use.

Table 1.

Summary of Multivariate Level Mixed-Effect Logistic Regression Models Evaluating the IMPACT of RA and axSpA Disease Characteristics on Vaccine AEs

VariableAny Adverse EventOR (95 % CI) p valueSevere Adverse Event* OR 95 % CI) p valueAny Arthritis Flare or Joint Ache Adverse Event OR (95 % CI) p valueAny Severe Arthritis Flare or Joint Ache* OR (95 % CI) p valueGenderMale1.47 (0.89 – 2.43)p=0.132.10 (1.30-3.41)p=0.0032.05 (1.20 – 3.50) p=0.013.97 (1.84 – 8.57)p=0.0004FemaleAge1.06 (1.04 – 1.08)p<0.011.05 (1.03 – 1.06)p<0.011.03 (1.01 – 1.04)p=0.0031.03 (1.01 – 1.06)p=0.004Rheumatic Disease TypeRA0.42 (0.23 – 0.76)p=0.050.55 (0.31 – 0.98)p=0.040.52 (0.28 – 0.98)p=0.040.78 (0.34 – 1.78)p=0.55axSpASteroidsYes0.85 (0.40 – 1.83) P=0.680.66 (0.32 – 1.35) p=0.250.84 (0.36 – 1.95) p=0.690.38 (0.15 – 0.97)p=0.04NoNSAIDSYes1.11 (0.81 – 1.52) p=0.511.03 (0.75 – 1.41)p=0.861.05 (0.74 – 1.48)p=0.801.17 (0.73 – 1.89)p=0.52NoCurrent Disease Activity0.95 (0.88 – 1.03) p=0.230.90 (0.83 – 0.97)p=0.190.92 (0.85 – 1.00)p=0.060.82 (0.74 – 0.92)p=0.001HAQ1.08 (0.73 – 1.61) p=0.700.77 (0.52 – 1.14)p=0.010.74 (0.48 – 1.13)p=0.170.65 (0.38 – 1.11)p=0.12Nicotine productsYes1.33 (0.75 – 2.37) p=0.341.42 (0.80 – 2.52)p=0.241.15 (0.60 – 2.01)p=0.760.97 (0.43 – 2.17)p=0.94NoCannabis productsYes0.78 (0.49 – 1.25) p=0.300.87 (0.55 – 1.38)p=0.550.51 (0.31 – 0.83)p=0.070.66 (0.35 – 1.26)p=0.21NoDMARDsYes1.98 (1.28 – 3.06)p=0.0021.52 (1.01 – 2.28)p=0.051.43 (0.91 – 2.23) p=0.121.86 (1.03 – 3.36)p=0.04NoBiologic DMARDYes0.72 (0.42 – 1.25) p=0.240.79 (0.45 – 1.41) p=0.431.20 (0.66 – 2.18 p=0.541.39 (0.63 – 3.08)p=0.42No

*Severe = Any of the following: ranked moderate to severe and/or lasting more than 7 days and/or saw physician

Conclusion

RA and axSpA patients showed high uptake of COVID vaccination with largely minor AEs. Older age and male gender were associated with more general and arthritis specific AEs. The association of any AE and/or arthritis-specific AEs in SpA versus RA patients is a novel finding which may correlate with the male predominance of SpA. The association of cannabis with fewer arthritis AEs may reflect the nociceptive properties of cannabis.

Acknowledgements

Epidemiology Coordinating and Research (EPICORE) Centre provided support for the REDCAP survey and biostatistical analyses.

Disclosure of Interests

Stephanie Keeling Speakers bureau: Pfizer, Abbvie, GSK, UCB, Consultant of: Abbvie, GSK, UCB, AstraZeneca, Sandoz, Pfizer, Grant/research support from: Abbvie, Sandoz, Merck, UCB, Bo Pan: None declared, Edna Hutchings Shareholder of: BMS, Stephanie Wichuk: None declared, Mohammed Osman Speakers bureau: Boehringer Ingelheim, Takeda Pharmaceuticals, Grant/research support from: Boehringer Ingelheim and CSL-Behring, Ameeta Singh: None declared, Ashlesha Sonpar Speakers bureau: Novartis, Ilan Swartz: None declared, Walter P Maksymowych Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, UCB, Consultant of: Abbvie, Boehringer Ingelheim, Celegene, Eli-Lilly, Galapagos, Novartis, Pfizer, UCB, Grant/research support from: Abbvie, Novartis, Pfizer, UCB

POS1258 LESS THAN EXPECTED IMPACT OF RHEUMATOID ARTHRITIS AND AXIAL SPONDYLOARTHRITIS DISEASE ON COVID SEVERITY

Background

Throughout the pandemic, there has been ongoing concern that people with autoimmune diseases such as rheumatoid arthritis (RA) and axial spondyloarthritis (axSpA) will have more severe COVID-19 disease due to immune dysfunction associated with autoimmune diseases and their treatment.

Objectives

We aimed to compare the severity of COVID-19 in patients with RA versus axSpA and characterize the predictors of COVID-19 severity during the pre-Omicron pandemic phases.

Methods

The IMPACT (IMPact of inflammatory Arthritis on COVID Outcomes STudy) study is a monthly survey of two established northern Alberta, Canada prospective cohorts of RA and axSpA patients from November 2020-2021 who answered Redcap surveys through de-identified email link surveying patient demographics, disease characteristics, COVID-19 symptoms, treatment of RA and axSpA, health care utilization, vaccination status and vaccine adverse events. Descriptive and univariate analyses (dependent variable = severe COVID-19) were performed followed by multivariate analyses of all significant and clinically relevant independent variables from the univariate analysis. Infection severity was defined as any patient with COVID-19 symptoms who visited a doctor, ER or required hospital admission.

Results

773 of 2167 (36%) patients (RA n=574, axSpA n=197) registered in both cohorts answered at least one baseline survey, 28 (4%) reporting positive COVID-19 tests (24 positive once). Of 442 reporting COVID-19 symptoms during the survey, 11 (3%) were admitted for a mean of 4 days, 2 requiring ICU or blood clot treatment and 1 requiring advanced therapy. 116 (26%) visited a physician for Covid symptoms. Univariate analysis showed that the use of steroids, NSAIDs and increased disease activity were associated with having less severe infection but these associations were not significant in the multivariate analysis (Table 1). There were no significant impacts of RA vs axSpA, age, gender, treatment, disease activity, or smoking.

Table 1.

Multivariate Level Mixed-Effect Logistic Regression Model: IMPACT of RA and axSpA Disease Characteristics on COVID Infection Severity Defined as Patients with COVID Symptoms Requiring Visit to Doctor, Emergency Room and/or Hospital Admission.

VariableCoefficient (S.E)Odds Ratio (95 % Confidence Interval)P-valueGenderMale0.17 (0.34)1.18 (0.61 – 2.31)0.6193FemaleReferenceAge-0.01 (0.01)0.99 (0.97 – 1.01)0.2543Rheumatic Disease TypeRA0.18 (0.40)1.20 (0.58 – 2.48)0.6213SpAReferenceSteroidsYes-0.40 (0.56)0.67 (0.23 – 2.01)0.4757NoReferenceNSAIDSYes-0.20 (0.26)0.82 (0.49 – 1.37)0.4508NoReferenceCurrent Disease Activity-0.04 (0.06)0.96 (0.85 – 1.09)0.5275HAQ-0.03 (0.29)0.97 (0.55 – 1.70)0.9041Nicotine productsYes-0.67 (0.37)0.51 (0.25 – 1.06)0.0714NoReferenceCannabis productsYes-0.45 (0.31)0.64 (0.35 – 1.18)0.1510NoReferenceDMARDsYes0.26 (0.30)1.30 (0.72 – 2.35)0.3860NoReferenceBiologic DMARDYes-0.46 (0.43)0.63 (0.27 – 1.46)0.2813NoReference

Conclusion

Possible disease related risk factors for increased COVID-19 severity in RA and axSpA patients preceding the onset of the Omicron variant including use of steroids or DMARDs were not associated with severe infection. These findings are consistent with other international studies whereby other non-rheumatic disease comorbidities played a greater role in infection severity.

Acknowledgements

Epidemiology Coordinating and Research (EPICORE) Centre provided support for the REDCAP survey and biostatistical anayses.

Disclosure of Interests

Stephanie Keeling Speakers bureau: Abbvie, GSK, Pfizer, UCB, Consultant of: Abbvie, GSK, Pfizer, Sandoz, UCB, Eli-Lilly, Galapagos, Novartis, Grant/research support from: Abbvie, UCB, Sandoz, Pfizer, Merck, Bo Pan: None declared, Edna Hutchings Shareholder of: BMS, Stephanie Wichuk: None declared, Mohammed Osman Speakers bureau: Boehringer Ingelheim, Takeda Pharmaceuticals, Grant/research support from: Yes, Boehringer Ingelheim and CSL-Behring, Ameeta Singh: None declared, Ashlesha Sonpar Speakers bureau: Novartis, Ilan Swartz: None declared, Walter P Maksymowych Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, UCB

, Consultant of: Abbvie, Boehringer Ingelheim, Celegene, Eli-Lilly, Galapagos, Novartis, Pfizer, UCB, Grant/research support from: Abbvie, Novartis, Pfizer, UCB

POS0111 MORE METICULOUSLY FOLLOWING TREAT-TO-TARGET IN RA DOES NOT LEAD TO LESS RADIOGRAPHIC PROGRESSION: A LONGITUDINAL ANALYSIS IN BIODAM

Background

A Treat-to-Target approach (T2T) is broadly considered to lead to better clinical outcomes and recommended in patients with RA. However, very few studies have analyzed the effect of T2T on radiographic progression, and any such studies have provided inconsistent results.

Objectives

To investigate whether meticulously following a treat-to-target (T2T)-strategy in daily clinical practice leads to lower radiographic progression in RA.

Methods

Patients from the multicenter RA-BIODAM cohort with ≥2 consecutive visits with radiographs available were included. In RA-BIODAM patients were enrolled as they were initiating a new csDMARD/bDMARD treatment were followed-up with the intention to benchmark and intensify treatment. The primary outcome of this analysis was the change in Sharp-van der Heijde score (SvdH, 0-448), assessed every 6 months, using average scores from 2 readers (scores with known chronological order). Following a DAS44-T2T remission strategy, which was defined at each 3-month visit, was the main variable of interest. Patients were categorized based on the proportion of visits in which T2T was followed according to our definition: very low (≤40% of the visits, low (>40%, <62.5%), high (≥62.5%, ≤75%) and very high (>75%). Radiographic progression at 2 years was visualized across groups by cumulative probability plots. Per 3-month interval T2T could be followed zero, one or two times (in a total of 2 visits). Associations between the number of visits with T2T in an interval and radiographic progression, both in the same and in the subsequent 6-month interval, were analysed by generalised estimating equations, adjusted for age, gender, disease duration and country.

Results

In total, 511 patients were included (mean (SD) age: 56 (13) years; 76% female). After 2 years, patients showed on average 2.2 (4.1) units progression (median:1 unit). Mean (SD) 2-year progression was not significantly different across categories of T2T: very low: 2.1 (2.7)-units; low: 2.8 (6.0); high: 2.4 (4.5), very high: 1.6 (2.2) (Figure 1). Meticulously following-up T2T in a 3-month interval neither reduced progression in the same 6-month interval (parameter estimates (for yes vs no): +0.15 units (95%CI: -0.04 to 0.33) for 2 vs 0 visits; and +0.08 units (-0.06;0.22) for 1 vs 0 visits) nor did it reduce progression in the subsequent 6-month interval (Table 1).

Table 1.

Effect of following DAS44-remission-T2T strategy on 6-month radiographic progression over 2 years

Change in radiographic damage(regression coefficient (95% CI))N=506T2T during 3 months on radiographic progression in the same 6-month period 2 visits vs 0 followed0.15 (-0.04; 0.33) 1 visit vs 0 followed0.08 (-0.06; 0.22)T2T during 3 months on radiographic progression in the subsequent 6-month period 2 visits vs 0 followed-0.09 (-0.28; 0.10) 1 visit vs 0 followed-0.10 (-0.24; 0.05)Figure 1.

Cumulative probability plot with 2-year radiographic progression according to the proportion of 3-monthly visits with T2T followed

Conclusion

In this daily practice cohort, more meticulously following T2T principles did not result in more reduction of radiographic progression than a somewhat more liberal attitude toward T2T. One possible interpretation of these results is that the intention to apply T2T already suffices and that a more stringent approach does not further improve outcome.

Acknowledgements

BIODAM was financially supported by an unrestricted grant from AbbVie

Disclosure of Interests

Sofia Ramiro Speakers bureau: Eli Lilly, MSD, Novartis, UCB, Consultant of: AbbVie, Eli Lilly, MSD, Novartis, Pfizer, UCB, Sanofi, Grant/research support from: AbbVie, Galapagos, Novartis, Pfizer, UCB, Robert B.M. Landewé Speakers bureau: AbbVie, BMS, Gilead, Galapagos, GSK,Janssen, Lilly, Novartis, Pfizer, UCB, Consultant of: AbbVie, BMS, Gilead, Galapagos, GSK,Janssen, Lilly, Novartis, Pfizer, UCB

Dr Landewé owns Rheumatology Consultancy BV, Désirée van der Heijde Consultant of: AbbVie, Bayer, BMS, Cyxone, Eisai, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Lilly, Novartis, Pfizer, UCB Pharma. Director of Imaging Rheumatology bv., Alexandre Sepriano Speakers bureau: Novartis, Consultant of: UCB, Oliver FitzGerald Speakers bureau: Biogen, Novartis, AbbVie, BMS, Pfizer, Grant/research support from: BMS, Novartis, UCB, Pfizer, Lilly, Janssen, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Celgene, Eli-Lilly, Galapagos, Gilead, Janssen, Merck, Novartis, Orion, Pfizer, Roche and UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Grant/research support from: Abbvie, Amgen, BMS, Merck, Celgene and Novartis, Joanne Homik: None declared, Ori Elkayam Speakers bureau: Pfizer, Lilly, Novartis, Abbvie, BI, Janssen, Consultant of: Pfizer, Lilly, Novartis, Abbvie, BI, Janssen, Grant/research support from: Pfizer, Abbvie, Janssen, Carter Thorne Consultant of: Abbvie, Organon, Pfizer, Sandoz, Maggie Larché Speakers bureau: AbbVie, Actelion, Amgen, BMS, Boehringer-Ingelheim, Fresenius-Kabi, Gilead, Janssen, Mallinckrodt, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, Sobi, UCB, Grant/research support from: Abbvie, BMS, Gianfranco Ferraccioli Speakers bureau: SOBI, Consultant of: Abbivie, Marina Backhaus: None declared, Gilles Boire Speakers bureau: Abbvie Canada, BMS Canada, Lilly Canada, Janssen Canada, Merck Canada, Pfizer Canada, Viatris, Consultant of: Abbvie Canada, Amgen Canada, BMS Canada, Celgene, GileadSciences, Janssen Canada, Lilly Canada, Merck Canada, Mylan Canada, Novartis Canada, Pfizer Canada, Roche Canada, Samsung Bioepis, Sanofi Canada, Teva, Grant/research support from: Lilly Canada, BMS Canada, Pfizer, Sandoz Canada, UCB Canada, Merck Canada, Novartis Canada, Roche Canada, Bernard Combe Speakers bureau: Abbvie, BMS,Celltrion,Galapgos-Gilead, Janssen, Lilly, MERCK, Pfizer,Roche-Chugai, Consultant of: Abbvie, Celltrion,Galapgos-Gilead, Janssen, Lilly, MERCK, Roche-Chugai, Grant/research support from: Pfizer, Roche-chugai, Thierry Schaeverbeke: None declared, Alain Saraux Speakers bureau: Abbvie, Lilly, Nordic, Novartis, Pfizer, Roche-Chugai, Sanofi, UCB, Consultant of: Abbvie, Lilly, Nordic, Novartis, Pfizer, Roche-Chugai, UCB, Grant/research support from: Novartis, Fresenius, Lilly, Maxime Dougados Consultant of: Pfizer, AbbVie, UCB, Merck, Lilly, Novartis, BMS, Galapagos, Biogen, Roche, Grant/research support from: Pfizer, AbbVie, UCB, Merck, Lilly, Novartis, BMS, Galapagos, Biogen, Roche, Maurizio Rossini Speakers bureau: Amgen, Abbvie, BMS, Eli-Lilly, Galapagos,MSD, Novartis, Pfizer, Sandoz, Theramex, UCB, Marcello Govoni Speakers bureau: Abbvie, Pfizer, Galapagos, BMS, Eli-Lilly, Paid instructor for: Pfizer, Consultant of: Abbvie, BMS, Novartis, Astrazeneca, Pfizer, Luigi Sinigaglia: None declared, Alain Cantagrel Speakers bureau: Abbvie, Amgen, Biogen, BMS, Janssen, Lilly France, Médac, MSD France, Nordic-Pharma, Novartis, Pfizer, Sanofi Aventis, UCB, Consultant of: BMS, Janssen, Lilly France, MSD France, Sandoz, Grant/research support from: MSD France, Novartis, Pfizer, Cornelia Allaart: None declared, Cheryl Barnabe Speakers bureau: Sanofi Genzyme, Pfizer, Fresenius Kabi, Janssen, Consultant of: Gilead, Celltrion Healthcare, Clifton Bingham Consultant of: AbbVie, BMS, Eli Lilly, Janssen, Moderna, Pfizer, Sanofi, Grant/research support from: BMS, Dirkjan van Schaardenburg: None declared, Hilde Berner Hammer Speakers bureau: AbbVie, Novartis, Lilly, Rana Dadashova: None declared, Edna Hutchings: None declared, Joel Paschke: None declared, Walter P Maksymowych Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, UCB, Consultant of: Abbvie, Boehringer Ingelheim, Celgene, Eli-Lilly, Galapagos, Novartis, Pfizer, UCB, Grant/research support from: Abbvie, Novartis, Pfizer

Outcomes and Findings of the International Rheumatoid Arthritis (RA) BIODAM Cohort for Validation of Soluble Biomarkers in RA

OBJECTIVE

The Outcome Measures in Rheumatology Soluble Biomarker Working Group initiated an international, multicenter, prospective study, the Rheumatoid Arthritis (RA) BIODAM cohort, to generate resources for the clinical validation of candidate biomarkers predictive of radiographic progression. This first report describes the cohort, clinical outcomes, and radiographic findings.

METHODS

Patients with RA from 38 sites in 10 countries starting or changing conventional synthetic disease-modifying antirheumatic drugs and/or starting tumor necrosis factor inhibitors were followed for 2 years. Participating physicians were required to adhere to a treat-to-target strategy. Biosamples (serum, urine) were acquired every 3 months, radiography of hands and feet every 6 months, and ultrasound of hands and feet every 3 months in a subset. Primary endpoint was radiographic progression by the Sharp/van der Heijde score.

RESULTS

A total of 571 patients were recruited and 439 (76.9%) completed 2-year followup. At baseline, the majority was female (76%), mean age 55.7 years, and mean disease duration 6.5 years. Patients had a mean of 8.4 swollen and 13.6 tender joints, 44-joint count Disease Activity Score (DAS44) 3.8, 77.7% rheumatoid factor-positive or anticitrullinated protein antibody-positive. Percentage of patients in DAS and American College of Rheumatology remission at 2 years was 52.2% and 27.1%, respectively. Percentage of patients with radiographic progression (> 0.5) at 1 and 2 years was 38.2% and 59.9%, respectively.

CONCLUSION

The RA BIODAM prospective study succeeded in generating an extensive list of clinical, imaging (2343 radiographs), and biosample (4638 sera) resources that will be made available to expedite the identification and validation of biomarkers for radiographic damage endpoints. (Clinicaltrials.gov: NCT01476956, clinicaltrials.gov/ct2/show/NCT01476956).

THU0105 ISOTOPE-LABELING-LC-MS-BASED METABOLIC PROFILING OF MULTIPLE SERUM SAMPLE SETS FOR THE DISCOVERY OF HIGH-CONFIDENCE RHEUMATOID ARTHRITIS BIOMARKERS

Background:

Early diagnosis of rheumatoid arthritis (RA) is hampered by suboptimal accuracy of currently available serological biomarkers. Metabolomics may reveal promising biomarker candidates associated with the biomolecular processes of RA. In this work, we applied a high-performance chemical isotope labeling (CIL) LC-MS technique for in-depth profiling of the amine/phenol-submetabolome in serum samples. To avoid false positives and obtain high-confidence biomarker candidates, we analyzed three independent sets of serum samples collected from RA patients and healthy controls to examine the common effects.

Objectives:

We aimed to identify a metabolite signature with consistently high accuracy for RA.

Methods:

Serum samples were taken from 3 RA cohorts, which comprised 50, 49, and 131 RA patients, respectively. Within each cohort, there were sex/age-matched healthy controls: 50 in Cohort 1, 50 in Cohort 2, and 100 in Cohort 3. Among these 446 subjects, 75% were females and the average age was 52.5 years. Amine/phenol-containing metabolites were labeled by12C-dansyl chloride to improve the LC-MS detection. For each cohort, a pooled sample was prepared and labeled by13C-dansyl group to serve as the reference sample for relative quantification. Then the individual samples and the pooled sample were mixed 1:1. Finally, an LC-QTOF-MS platform analyzed the mixtures and output the intensity ratios of12C/13C peak pairs.

Results:

1,149 amine/phenol-containing metabolites were commonly detected across the three sample sets. Among them, 134 were positively identified by our dansyl-labeling standard library, and 141 were matched to predicted retention times and mass values of dansyl-labeled human metabolites. Visualized by the partial least squares discriminant analysis (PLS-DA), the overall amine/phenol-submetabolome demonstrated clear and consistent differences between healthy controls and the RA groups, with cross-validation Q2 = 0.765, 0.745, 0.793, respectively. The selection of significant metabolites was conducted according to the fold change and false-discovery-rate-adjusted Welch’s t-test. Cohort 1 demonstrated 85 metabolites having higher concentrations in the RA samples than the controls, and 89 metabolites with lowered concentrations. The numbers of increased/decreased metabolites in Cohort 2 and 3 were 87/26 and 90/53, respectively. Importantly, there were 59 significantly discriminatory metabolites commonly found in the three data sets (49 increased and 9 decreased). We picked the top three with the highest univariate classification performance to form a biomarker panel. We implemented the linear support vector machine (SVM) to build the classifier and the receiver operating characteristic (ROC) analysis to measure the performance. The area-under-the-curve (AUC) values (95% confidence interval) were 1.000 (1.000-1.000), 0.992 (0.967-1.000) and 0.902 (0.858-0.945) for the three cohorts, respectively. The results revealed the importance of examining multiple sample sets and even in the worst case (Cohort 3), our biomarker candidates could differentiate RA at 82.5% sensitivity and 82.5% specificity. Particularly, in Cohort 3, there were 30 RA patients negative for anti-cyclic citrullinated peptide and rheumatoid factor, and our metabolite panel demonstrated consistently high performance for differentiating these specific subjects from healthy controls.

Conclusion:

Metabolites showing significant and consistent changes associated with RA have been identified with high discriminative power.

Disclosure of Interests:

Wei Han: None declared, Xiaohang Wang: None declared, Liang Li: None declared, Stephanie Wichuk: None declared, Edna Hutchings: None declared, Rana Dadashova: None declared, Joel Paschke: None declared, Walter P Maksymowych Grant/research support from: Received research and/or educational grants from Abbvie, Novartis, Pfizer, UCB, Consultant of: WPM is Chief Medical Officer of CARE Arthritis Limited, has received consultant/participated in advisory boards for Abbvie, Boehringer, Celgene, Eli-Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, UCB, Speakers bureau: Received speaker fees from Abbvie, Janssen, Novartis, Pfizer, UCB.

Is treat-to-target really working in rheumatoid arthritis? a longitudinal analysis of a cohort of patients treated in daily practice (RA BIODAM)

OBJECTIVES

To investigate whether following a treat-to-target (T2T)-strategy in daily clinical practice leads to more patients with rheumatoid arthritis (RA) meeting the remission target.

METHODS

RA patients from 10 countries starting/changing conventional synthetic or biological disease-modifying anti-rheumatic drugs were assessed for disease activity every 3 months for 2 years (RA BIODAM (BIOmarkers of joint DAMage) cohort). Per visit was decided whether a patient was treated according to a T2T-strategy with 44-joint disease activity score (DAS44) remission (DAS44 <1.6) as the target. Sustained T2T was defined as T2T followed in ≥2 consecutive visits. The main outcome was the achievement of DAS44 remission at the subsequent 3-month visit. Other outcomes were remission according to 28-joint disease activity score-erythrocyte sedimentation rate (DAS28-ESR), Clinical Disease Activity Index (CDAI), Simplified Disease Activity Index (SDAI) and American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) Boolean definitions. The association between T2T and remission was tested in generalised estimating equations models.

RESULTS

In total 4356 visits of 571 patients (mean (SD) age: 56 (13) years, 78% female) were included. Appropriate application of T2T was found in 59% of the visits. T2T (vs no T2T) did not yield a higher likelihood of DAS44 remission 3 months later (OR (95% CI): 1.03 (0.92 to 1.16)), but sustained T2T resulted in an increased likelihood of achieving DAS44 remission (OR: 1.19 (1.03 to 1.39)). Similar results were seen with DAS28-ESR remission. For more stringent definitions (CDAI, SDAI and ACR/EULAR Boolean remission), T2T was consistently positively associated with remission (OR range: 1.16 to 1.29), and sustained T2T had a more pronounced effect on remission (OR range: 1.49 to 1.52).

CONCLUSION

In daily clinical practice, the correct application of a T2T-strategy (especially sustained T2T) in patients with RA leads to higher rates of remission.

Adherence to Treat-to-target Management in Rheumatoid Arthritis and Associated Factors: Data from the International RA BIODAM Cohort

Objective.

Compelling evidence supports a treat-to-target (T2T) strategy for optimal outcomes in rheumatoid arthritis (RA). There is limited knowledge regarding the factors that impede implementation of T2T, particularly in a setting where adherence to T2T is protocol-specified. We aimed to assess clinical factors that associate with failure to adhere to T2T.

Methods.

Patients with RA from 10 countries who were starting or changing conventional synthetic disease-modifying antirheumatic drugs and/or starting tumor necrosis factor inhibitors were followed for 2 years. Participating physicians were required per protocol to adhere to the T2T strategy. Factors influencing adherence to T2T low disease activity (T2T-LDA; 44-joint count Disease Activity Score ≤ 2.4) were analyzed in 2 types of binomial generalized estimating equations models: (1) including only baseline features (baseline model); and (2) modeling variables that inherently vary over time as such (longitudinal model).

Results.

A total of 571 patients were recruited and 439 (76.9%) completed 2-year followup. Failure of adherence to T2T-LDA was noted in 1765 visits (40.5%). In the baseline multivariable model, a high number of comorbidities (OR 1.10, 95% CI 1.02–1.19), smoking (OR 1.32, 95% CI 1.08–1.63) and high number of tender joints (OR 1.03, 95% CI 1.02–1.04) were independently associated with failure to implement T2T, while anticitrullinated protein antibody/rheumatoid factor positivity (OR 0.63, 95% CI 0.50–0.80) was a significant facilitator of T2T. Results were similar in the longitudinal model.

Conclusion.

Lack of adherence to T2T in the RA BIODAM cohort was evident in a substantial proportion despite being a protocol requirement, and this could be predicted by clinical features. [Rheumatoid Arthritis (RA) BIODAM cohort; ClinicalTrials.gov: NCT01476956].

Comparative pharmacokinetics and pharmacodynamics of two marketed bid formulations of diltiazem in healthy volunteers

Cardizem SR and Bi-Tildiem were both approved in their respective countries on the basis of clinical trials demonstrating efficacy and safety in the treatment of angina pectoris. In this cross-over randomized study, we assessed whether these two sustained-release formulations of diltiazem have equivalent pharmacokinetic and pharmacodynamic profiles. Twenty-four young healthy male volunteers were hooked to Holters and ambulatory blood pressure monitors for 24 h to establish baseline systolic blood pressure (SBP), diastolic blood pressure (DBP), sinus rate and PR intervals. They then received a single dose of 120 mg of diltiazem from one formulation. The pharmacodynamic measurements were recorded for a further 24 h and blood samples were collected over 36 h for evaluation of diltiazem in plasma by a high-performance liquid chromatogrpahic (HPLC) method. The procedures were repeated with the alternate formulation after a 7 d wash-out. Pharmacokinetics showed statistically significant (p < 0.01) differences in AUC0-12 with means (+/- SD) of 519.2(+/- 172.8) and 429.6(+/- 147.2) ng h ml-1, AUC0-36 of 835.6(+/- 281.6) and 730.9 (+/- 271.5) ng h ml-1 and Cmax of 89.1(+/- 30.3) and 61.1(+/- 21.2) ng ml-1 for Cardizem SR and Bi-Tildiem, respectively. The only pharmacodynamic parameter showing a statistically significant difference in change from baseline between the two formulations was DBP with mean (+/- SD) change in AUC0-12 of -13.6(+/- 20.8) and +8.4(+/- 31.7) mm Hg h (p = 0.0135) and in AUC0-24 of -33.0(+/- 43.7) and -0.3(+/- 59.2) mm Hg h (p = 0.0463) for Cardizem SR and Bi-Tildiem, respectively. These findings suggest that assessment of efficacy of sustained-release formulations of diltiazem by bioequivalence could be misleading. They also confirm that a single dose of diltiazem does not elicit a significant pharmacodynamic response in healthy volunteers. Equivalence for such formulations should therefore be demonstrated by pharmacodynamic evaluation or clinical studies in a patient population.

The autonomous viking

The two Viking spacecraft launched to Mars in 1975 were designed for 90 days of intense observations followed by an extended mission phase to end in 1978. Because the spacecraft were still operating so well in 1978, three more mission phases were added and the project was not officially terminated until 1980. During these last three mission phases delays in controlling the orbiters from the earth increased. The spacecraft were kept functional and the length of the Viking mission was extended because the ground crew, over a period of 2 years, gradually made the orbiters autonomous.