Therapy with JAK inhibitors or bDMARDs and the risk of cardiovascular events in the Dutch rheumatoid arthritis population.

OBJECTIVE: Caution has been advocated recently when using Janus kinase inhibitors (JAKi) in rheumatoid arthritis (RA) patients with an unfavorable cardiovascular risk profile. We aimed to compare the incidences in cardiovascular events between JAKi or bDMARDs in a large population of RA patients. METHODS: RA patients starting a new bDMARD or JAKi between August 1st 2018 and January 31st 2022 have been selected from IQVIA's Dutch Real-World Data Longitudinal Prescription database, covering about 63% of outpatient prescriptions in the Netherlands. Study outcome was a cardiovascular event, defined as the start of platelet aggregation inhibitors during study period. The incidence densities of cardiovascular events were compared between JAKi and bDMARDs using multilevel Poisson regression, adjusted for exposition time and confounders. RESULTS: 15 191 unique patients were included, with 28 481 patient-years on treatment with either JAKi (2,373) or bDMARDs (26 108). Most patients were female (72%) and median age was 62 years. We found 36 cardiovascular events (1.52 events/100 patient years) during therapy with JAKi and 383 events (1.47 events/100 patient years) during therapy with bDMARDs, respectively, resulting in an adjusted incidence rate ratio (IRR) of 0.99 for JAKi compared with bDMARDs (95% confidence interval (CI), 0.70-1.41). Sub-analyses in patients >65 years, by sex, or separately for tofacitinib and baricitinib, yielded similar results. CONCLUSION: In a large Dutch general RA population, the risk of cardiovascular events seems not different between JAKi users and those using bDMARDs, although a small increase in higher risk patients cannot be excluded.

[Methotrexate to prevent progression to rheumatoid arthritis?] / Methotrexaat om reumatoïde artritis te voorkomen?

The TREAT EARLIER was aimed at testing whether methotrexate could prevent the evolution from clinically suspect arthralgia to Rheumatoid Arthritis. Although the primary outcome was negative, symptoms did improve during and after use of methotrexate. Here we discuss how to interpret these findings, and place the study in the existing evidence.

The added value of predictive biomarkers in treat-to-target strategies for rheumatoid arthritis patients: a conceptual modelling study.

OBJECTIVES: To quantify the additional value of a hypothetical biomarker predicting response to treatment for RA regarding efficacy and costs by using a modelling design. METHODS: A Markov model was built comparing a usual care T2T strategy with a biomarker-steered strategy for RA patients starting biologic therapy. Outcome measures include time spent in remission or low disease activity (LDA) and costs. Four additional scenario analyses were performed by varying biomarker or clinical care characteristics: (i) costs of the biomarker; (ii) sensitivity and specificity of the biomarker; (iii) proportion of eligible patients tapering; and (iv) medication costs. RESULTS: In the base model, patients spent 2.9 months extra in LDA or remission in the biomarker strategy compared with usual care T2T over 48 months. Total costs were €43 301 and €42 568 for, respectively, the usual care and biomarker strategy, and treatment costs accounted for 91% of total costs in both scenarios. Cost savings were driven due to patients in the biomarker strategy experiencing remission or LDA earlier, and starting tapering sooner. Cost-effectiveness was not so much driven by costs or test characteristics of the biomarker (scenario 1/2), but rather by the level of early and proactive tapering and drug costs (scenarios 3/4). CONCLUSIONS: The use of a biomarker for prediction of response to b/tsDMARD treatment in RA can be of added value to current treat-to-target clinical care. However, gains in efficacy are modest and cost gains are depending on a combination of early proactive tapering and high medication costs.

Drug levels, anti-drug antibodies and B-cell counts were not predictive of response in rheumatoid arthritis patients on (ultra-)low-dose rituximab.

OBJECTIVES: The REDO trial (REtreatment with Rituximab in RhEumatoid arthritis: Disease Outcome after Dose Optimisation) showed that ultra-low-dose rituximab (500 mg or 200 mg) was similarly effective to a 1000 mg dosage in the majority of RA patients. This pre-planned secondary analysis investigated (1) associations between rituximab dosage, drug levels, anti-drug antibodies (ADAs) and B-cell counts and (2) the predictive value of pharmacokinetic and pharmacodynamic parameters, and of patient, disease and treatment characteristics in relation to response to ultra-low-dose rituximab. METHODS: For 140 RA patients from the REDO trial, differences in drug levels, ADAs and B-cell counts were examined at baseline, and at 3 and 6 months after dosing. Treatment response was defined as absence of flare and no extra rituximab or >1 glucocorticoid injection received during follow-up. The association between potential predictors and response was investigated using logistic regression analyses. RESULTS: Lower doses of rituximab resulted in lower drug levels but did not significantly affect ADA levels or B-cell counts, and 3 (10.7%), 12 (20.7%) and 7 (13.0%) patients failed to meet the response criteria in, respectively, the 1000 mg, 500 mg and 200 mg dosage groups. Drug levels, ADAs, B-cell counts, and patient, disease and treatment characteristics were not predictive for response to ultra-low-dose rituximab. CONCLUSION: The results of this study further support the hypothesis that continued treatment with 500 or 200 mg rituximab is similarly effective to a 1000 mg dosage in RA patients doing well on rituximab. These results, combined with lack of finding a clinical dose-response relationship in the original REDO study, suggest that 200 mg rituximab is not yet the lowest effective rituximab retreatment dose in RA.

Prediction of response to anti-TNF treatment using laboratory biomarkers in patients with rheumatoid arthritis: a systematic review.

OBJECTIVES: In this systematic review, we aim to identify laboratory biomarkers that predict response to tumour necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA). METHODS: EMBASE, PubMed and Cochrane Library (CENTRAL) were searched for studies that presented predictive accuracy measures of laboratory biomarkers, or in which these were calculable. Likelihood ratios were calculated in order to determine whether a test result relevantly changed the probability of response. Likelihood ratios between 2-10 and 0.5-0.1 were considered weak predictors, respectively, and ratios above 10 or below 0.1 were considered strong predictors of response. Primary focus was on biomarkers studied ≥3 times. RESULTS: From 41 included studies, data on 99 different biomarkers were extracted. Five biomarkers were studied ≥3 times, being (1) anti-cyclic citrullinated peptide (CCP), (2) rheumatoid factor, (3) -308 polymorphism in the TNF-α gene, (4) SE copies in the HLA-DRB1 gene and (5) FcGR2A polymorphism. No studies showed a strong predictive association and only one study on anti-CCP showed a weak positive association. CONCLUSIONS: No biomarkers were found that consistently showed a (strong) predictive effect for response to TNFi in patients with RA. Given the disappointing yield of previous predictive biomarker research, future studies should focus on exploring, combining and validating the most promising laboratory biomarkers identified in this review, and searching for new predictors. Besides this, they should focus on contexts where prediction-aided decision-making can have a large impact (even with limited predictive value of markers/models). PROSPERO REGISTRATION NUMBER: CRD42021278987.

Using adalimumab serum concentration to choose a subsequent biological DMARD in rheumatoid arthritis patients failing adalimumab treatment (ADDORA-switch): study protocol for a fully blinded randomised superiority test-treatment trial.

BACKGROUND: A substantial proportion of rheumatoid arthritis (RA) patients discontinues treatment with tumour necrosis factor inhibitors (TNFi) due to inefficacy or intolerance. After the failure of treatment with a TNFi, treatment can be switched to another TNFi or a bDMARD with a different mode of action (non-TNFi). Measurement of serum drug concentrations and/or anti-drug antibodies (therapeutic drug monitoring (TDM)) may help to inform the choice for the next step. However, the clinical utility of TDM to guide switching has not been investigated in a randomised test-treatment study. METHODS: ADDORA-switch is a 24-week, multi-centre, triple-blinded, superiority test-treatment randomised controlled trial. A total of 84 RA patients failing adalimumab treatment (treatment failure defined as DAS28-CRP > 2.9) will be randomised in a 1:1 ratio to a switching strategy to either TNFi or non-TNFi based on adalimumab serum trough level (intervention group) or random allocation (control group). The primary outcome is the between-group difference in mean time-weighted DAS28 over 24 weeks. DISCUSSION: The trial design differs in many aspects from previously published and ongoing TDM studies and is considered the first blinded test-treatment trial using TDM in RA. Several choices in the design of this trial are described, and overarching principles regarding test-treatment trials and clinical utility of TDM are discussed in further detail. TRIAL REGISTRATION: Dutch Trial Register NL8210 . Registered on 3 December 2019 (CMO NL69841.091.19).

Clinical utility of therapeutic drug monitoring in biological disease modifying anti-rheumatic drug treatment of rheumatic disorders: a systematic narrative review.

INTRODUCTION: Biological Disease Modifying Anti-Rheumatic Drugs (bDMARDs) have improved the treatment outcomes of inflammatory rheumatic diseases including Rheumatoid Arthritis and spondyloarthropathies. Inter-individual variation exists in (maintenance of) response to bDMARDs. Therapeutic Drug Monitoring (TDM) of bDMARDs could potentially help in optimizing treatment for the individual patient. Areas covered: Evidence of clinical utility of TDM in bDMARD treatment is reviewed. Different clinical scenarios will be discussed, including: prediction of response after start of treatment, prediction of response to a next bDMARD in case of treatment failure of the first, prediction of successful dose reduction or discontinuation in case of low disease activity, prediction of response to dose-escalation in case of active disease and prediction of response to bDMARD in case of flare in disease activity. Expert opinion: The limited available evidence does often not report important outcomes for diagnostic studies, such as sensitivity and specificity. In most clinical relevant scenarios, predictive value of serum (anti-) drug levels is absent, therefore the use of TDM of bDMARDs cannot be advocated. Well-designed prospective studies should be done to further investigate the promising scenarios to determine the place of TDM in clinical practice.