Initial glucocorticoid bridging in rheumatoid arthritis: does it affect glucocorticoid use over time?

OBJECTIVES: To compare the use of glucocorticoids (GC) over time in patients with rheumatoid arthritis (RA) who were or were not treated initially with GC bridging therapy. METHODS: Data from the BeSt, CareRA and COBRA trials were combined in an individual patient data (IPD) meta-analysis. We compared GC use between bridgers and non-bridgers at 12, 18 and 24 months from baseline with mixed-effects regression analysis. Secondary outcomes were mean cumulative GC dose until 24 months after baseline with and without the bridging period, Disease Activity Score based on 28 joints (DAS28) over time and number of disease-modifying antirheumatic drug (DMARD) changes. RESULTS: 252/625 patients (40%) were randomised to GC bridging (bridgers). Excluding the period of bridging, later GC use was low in both groups and cumulative doses were similar. Mean DAS28 was similar between the groups, but bridgers improved more rapidly (p<0.001) in the first 6 months and the bridgers required significantly fewer changes in DMARDs (incidence rate ratio 0.59 (95% CI 0.38 to 0.94)). GC use was higher in the bridgers at t=12 months (OR 3.27 (95% CI 1.06 to 10.08)) and the bridging schedules resulted in a difference in cumulative GC dose of 2406 mg (95% CI 1403 to 3408) over 24 months. CONCLUSION: In randomised trials comparing GC bridging and no GC bridging, bridgers had a more rapid clinical improvement, fewer DMARD changes and similar late use of GC compared with non-bridgers. GC bridging per protocol resulted, as could be expected, in a higher cumulative GC dose over 2 years.

The susceptibility of attaining and maintaining DMARD-free remission in different (rheumatoid) arthritis phenotypes.

OBJECTIVES: To compare (sustained) DMARD-free remission rates((S)DFR), defined as respectively ≥6 months and >1 year, after 2 and 5 years between three clinical arthritis phenotypes; undifferentiated arthritis(UA), autoantibody-negative(RA-) and positive rheumatoid arthritis(RA+). METHODS: All UA(n = 130), RA-(n = 176) and RA + (n = 331) patients from the tREACH trial, a stratified single-blinded trial with a treat-to-target approach, were used. (S)DFR comparisons between phenotypes after 2 and 5 years were performed with Logistic regression. Medication use and early and late flares(DAS ≥ 2.4), respectively defined as < 12 and >12 months after reaching DFR, were also compared. Cox proportional hazard models were used to evaluate potential predictors for (S)DFR. RESULTS: Within 2 and 5 years less DFR was seen in RA + (17.2-25.7%), followed by RA-(28.4-42.1%) and UA patients(43.1-58.5%). This also applied for SDFR within 2 and 5 years (respectively 7.6% and 21.4%; 20.5% and 38.1%; and 35.4% and 55.4%). A flare during tapering was seen in 22.7% of patients. Of the patients in DFR 7.5% had an early flare and 3.4% a late flare. Also more treatment intensifications occurred in RA+ compared with RA- and UA. We found that higher baseline DAS, ACPA positivity, BMI and smoking were negatively associated with (S)DFR, while clinical phenotype(reference RA+), short symptom duration(<6 months) and remission within 6 months were positively associated. CONCLUSIONS: (Long-term) clinical outcomes differ between undifferentiated arthritis, autoantibody-negative and positive rheumatoid arthritis(RA). These data reconfirm that RA can be subdivided into aforementioned clinical phenotypes and that treatment might be stratified upon these phenotypes, although validation is needed. TRIAL REGISTRATION: ISRCTN, https://www.isrctn.com/, ISRCTN26791028.

The impact of different (rheumatoid) arthritis phenotypes on patients' lives.

OBJECTIVES: To compare patient-reported outcome (PRO) domains between three arthritis phenotypes [undifferentiated arthritis (UA), autoantibody-negative RA (RA-) and autoantibody-positive RA (RA+)] at diagnosis, after 2 years and over time. METHODS: All UA (n = 130), RA- (n = 176) and RA+ (n = 331) patients from the tREACH trial, a stratified single-blinded trial with a treat-to-target approach, were used. PRO comparisons between phenotypes at baseline and after 2 years were performed with analysis of variance, while a linear mixed model compared them over time. Effect sizes were weighted against the minimal clinically important differences (MCIDs) for each PRO. RESULTS: RA- patients had a higher disease burden compared with RA+ and UA. At baseline and after 2 years, RA- patients had more functional impairment and a poorer Physical Component Summary (PCS) compared with the other phenotypes, while they only scored worse for general health and morning stiffness duration at baseline. The MCIDs were exceeded at baseline, except for functional ability between RA+ and UA, while after 2 years only the MCID of the PCS was exceeded by RA- compared with UA and RA. After 2 years the PROs of all phenotypes improved, but PROs measuring functioning were still worse compared with the general population, even when patients had low disease activity. CONCLUSION: RA- patients had the highest disease burden of all phenotypes. Although most patients have low disease activity after treatment, all clinical phenotypes still have a similar significant impact on patients' lives, which is mainly physical. Therefore it is important to assess and address PROs in daily practice because of persistent disease burden despite low disease activity. TRIAL REGISTRATION: ISRCTN26791028.

Tapering towards DMARD-free remission in established rheumatoid arthritis: 2-year results of the TARA trial.

OBJECTIVES: To evaluate the 2-year clinical effectiveness of two gradual tapering strategies. The first strategy consisted of tapering the conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) first (i.e., methotrexate in ~90%), followed by the tumour necrosis factor inhibitor (TNF-inhibitor), the second strategy consisted of tapering the TNF-inhibitor first, followed by the csDMARD. METHODS: This multicentre single-blinded randomised controlled trial included patients with rheumatoid arthritis (RA) with well-controlled disease for ≥3 consecutive months, defined as a Disease Activity Score (DAS) measured in 44 joints ≤2.4 and a swollen joint count ≤1, which was achieved with a csDMARD and a TNF-inhibitor. Eligible patients were randomised into gradual tapering the csDMARD followed by the TNF-inhibitor, or vice versa. The primary outcome was the number of disease flares. Secondary outcomes were DMARD-free remission (DFR), DAS, functional ability (Health Assessment Questionnaire Disability Index (HAQ-DI)) and radiographic progression. RESULTS: 189 patients were randomly assigned to tapering their csDMARD (n=94) or TNF-inhibitor (n=95) first. The cumulative flare rate after 24 months was, respectively, 61% (95% CI 50% to 71%) and 62% (95% CI 52% to 72%). The patients who tapered their csDMARD first were more often able to go through the entire tapering protocol and reached DFR more often than the group that tapered the TNF-inhibitor first (32% vs 20% (p=0.12) and 21% vs 10% (p=0.07), respectively). Mean DAS and HAQ-DI over time, and radiographic progression did not differ between groups (p=0.45, p=0.17, p=0.8, respectively). CONCLUSION: The order of tapering did not affect flare rates, DAS or HAQ-DI. DFR was achievable in 15% of patients with established RA, slightly more frequent in patients that first tapered csDMARDs. Because of similar effects from a clinical viewpoint, financial arguments may influence the decision to taper TNF-inhibitors first.

Two-year cost effectiveness between two gradual tapering strategies in rheumatoid arthritis: cost-utility analysis of the TARA trial.

OBJECTIVE: The aim of the current study was to evaluate the 2-year cost-utility ratio between tapering conventional synthetic disease-modifying antirheumatic drugs (csDMARD) first followed by the tumour necrosis factor (TNF)-inhibitor, or vice versa, in patients with rheumatoid arthritis (RA). METHODS: Two-year data of the Tapering strategies in Rheumatoid Arthritis trial were used. Patients with RA, who used both a csDMARD and a TNF-inhibitor and had a well-controlled disease (disease activity score ≤2.4 and swollen joint count≤1) for at least 3 months, were randomised into gradual tapering the csDMARD first followed by the TNF-inhibitor, or vice versa. Quality-adjusted life years (QALYs) were derived from the European Quality of life questionnaire with 5 dimensions. Healthcare and productivity costs were calculated with data from patient records and questionnaires. The incremental cost-effectiveness ratio and the incremental net monetary benefit were used to assess cost effectiveness between both tapering strategies. RESULTS: 94 patients started tapering their TNF-inhibitor first, while the other 95 tapered their csDMARD first. QALYs (SD) were, respectively, 1.64 (0.22) and 1.65 (0.22). Medication costs were significantly lower in the patients who tapered the TNF-inhibitor first, while indirect cost were higher due to more productivity loss (p=0.10). Therefore, total costs (SD) were €38 833 (€39 616) for tapering csDMARDs first, and €39 442 (€47 271) for tapering the TNF-inhibitor (p=0.88). For willingness-to-pay (WTP) levels <€83 800 tapering, the csDMARD first has the highest probability of being cost effective, while for WTP levels >€83 800 tapering the TNF-inhibitor first has the highest probability. CONCLUSION: Our economic evaluation shows that costs are similar for both tapering strategies. Regardless of the WTP, tapering either the TNF-inhibitor or the csDMARD first is equally cost effective. TRIAL REGISTRATION NUMBER: NTR2754.

Gradual tapering TNF inhibitors versus conventional synthetic DMARDs after achieving controlled disease in patients with rheumatoid arthritis: first-year results of the randomised controlled TARA study.

OBJECTIVES: The aim of this study is to evaluate the effectiveness of two tapering strategies after achieving controlled disease in patients with rheumatoid arthritis (RA), during 1 year of follow-up. METHODS: In this multicentre single-blinded (research nurses) randomised controlled trial, patients with RA were included who achieved controlled disease, defined as a Disease Activity Score (DAS) ≤ 2.4 and a Swollen Joint Count (SJC) ≤ 1, treated with both a conventional synthetic disease-modifying antirheumatic drugs (csDMARD) and a TNF inhibitor. Eligible patients were randomised into gradual tapering csDMARDs or TNF inhibitors. Medication was tapered if the RA was still under control, by cutting the dosage into half, a quarter and thereafter it was stopped. Primary outcome was proportion of patients with a disease flare, defined as DAS > 2.4 and/or SJC > 1. Secondary outcomes were DAS, European Quality of Life-5 Dimensions (EQ5D) and functional ability (Health Assessment Questionnaire Disability Index [HAQ-DI]) after 1 year and over time. RESULTS: A total of 189 patients were randomly assigned to tapering csDMARDs (n = 94) or tapering anti-TNF (n = 95). The cumulative flare rates in the csDMARD and anti-TNF tapering group were, respectively, 33 % (95% CI,24% to 43 %) and 43 % (95% CI, 33% to 53 % (p = 0.17). Mean DAS, HAQ-DI and EQ-5D did not differ between tapering groups after 1 year and over time. CONCLUSION: Up to 9 months, flare rates of tapering csDMARDs or TNF inhibitors were similar. After 1 year, a non-significant difference was found of 10 % favouring csDMARD tapering. Tapering TNF inhibitors was, therefore, not superior to tapering csDMARDs. From a societal perspective, it would be sensible to taper the TNF inhibitor first, because of possible cost reductions and less long-term side effects. TRIAL REGISTRATION NUMBER: NTR2754.

Response to glucocorticoids at 2 weeks predicts the effectiveness of DMARD induction therapy at 3 months: post hoc analyses from the tREACH study.

OBJECTIVE: To investigate if a glucocorticoid (GC) response at 2 weeks, defined by EULAR response criteria, can predict active disease (Disease Activity Score (DAS)>2.4) at 3 months. METHODS: For this study, data of the Treatment in the Rotterdam Early Arthritis Cohort study (tREACH), an ongoing clinical trial that evaluates different induction therapies in early rheumatoid arthritis, were used. We selected patients who had a high probability of progressing to persistent arthritis (>70% based on the prediction model of Visser). All patients within the high-probability stratum, who had a baseline DAS>2.2 and a DAS assessment at 2 weeks after randomisation, were included (n=120). Besides GC response at 2 weeks, we investigated which other factors were associated with active disease (DAS>2.4) after 3 months of disease-modifying antirheumatic drug (DMARD) treatment. All variables with a p≤0.25 were assessed in our logistic regression model with backward selection. Variables were eliminated until all remaining variables had a significant association (p<0.05). RESULTS: Patients who did not respond to GC bridging therapy at 2 weeks had an overall OR of having active disease at 3 months of 10.29 (95% CI 3.34 to 31.64; p<0.001) in comparison with responders. The corrected OR was 14.00 (95% CI 3.31 to 59.21; p<0.001). Our final model predicting response at 3 months included the following variables: gender, GC response, induction therapy arms and baseline DAS, which had an explained variance of 39%. CONCLUSIONS: GC response at 2 weeks is a useful tool for recognising those patients who will probably have active disease (DAS>2.4) after 3 months of DMARD treatment.

Meta-Analyses on the Effects of Disease-Modifying Antirheumatic Drugs on the Most Relevant Patient-Reported Outcome Domains in Rheumatoid Arthritis.

OBJECTIVE: Whereas in the treatment of rheumatoid arthritis much evidence exists on the effects of current pharmacologic treatment on clinical outcomes, little is known about the effects on patient-reported outcomes. This systematic review aims to evaluate the effects of disease-modifying antirheumatic drugs (DMARDs) on the patient-relevant domains of pain, fatigue, activity limitation, overall emotional and physical health impact, and work/school/housework ability and productivity. METHODS: A literature search was conducted to identify randomized controlled trials wherein registered DMARDs were compared with placebo or methotrexate and reported the effects on patient-reported outcomes included in the International Consortium of Health Outcomes Measurement standard set for inflammatory arthritis. Random effects meta-analyses using the standardized mean differences of change scores as the effect measure were performed for the domains of pain, fatigue, and activity limitation, comparing DMARDs with placebo and methotrexate. The other 2 domains were presented narratively. RESULTS: Across the 5 domains, 69 records belonging to 52 studies were identified. All meta-analyses showed a decrease of burden when DMARDs were compared with placebo (standardized mean differences [95% confidence interval] in pain -0.80 [-0.99, -0.61], fatigue -0.48 [-0.64, -0.32], and activity limitation -0.56 [- 0.63, -0.49]) and when compared with methotrexate (-0.55 [-0.70, -0.41), -0.44 [-0.55, -0.33], and - 0.37 [-0.44, -0.30], respectively). CONCLUSION: DMARDs decrease the burden in all the domains that are relevant to patients. Effect sizes may be influenced by DMARD type. Therefore, in the decision for rheumatoid arthritis treatment, patient-reported outcomes should be taken into account.

Possibilities for personalised medicine in rheumatoid arthritis: hype or hope.

Knowledge of pathophysiology of rheumatoid arthritis (RA) has improved over the past decades, which resulted in new treatment options and strategies that led to better clinical outcomes. At the same time, we have come to understand that RA is a heterogeneous disease on a clinical as well as a pathophysiological level. Despite this heterogeneity, current management recommendations still adopt a 'one-size-fits-all' treatment approach, where ideally individualised treatment, or personalised medicine, is preferred. The first step towards personalised medicine in RA would be to designate different treatment strategies to distinct clinical or molecular phenotypes of patients. This viewpoint discusses current evidence and elaborates on future possibilities for personalised medicine in RA.