Prediction of disease relapses by multibiomarker disease activity and autoantibody status in patients with rheumatoid arthritis on tapering DMARD treatment

Predicting Flare in Patients With Rheumatoid Arthritis in Biologic Induced Remission, on Tapering, and on Stable Therapy

OBJECTIVE

The tapering of biologic disease-modifying antirheumatic drug (b-DMARD) therapy for patients with rheumatoid arthritis (RA) in stable remission is frequently undertaken, but specific guidance on how to successfully taper is lacking. The objective of this study is to identify predictors of flare in patients in stable b-DMARD-induced clinical remission, who did or did not follow structured b-DMARD tapering.

METHODS

Patients with RA receiving b-DMARD treatment who had achieved sustained remission according to a Disease Activity Score in 28 joints using the C-reactive protein level (DAS28-CRP) <2.6 for ≥6 months were offered tapering. Clinical, ultrasound (US) (total power Doppler [PD]/grayscale abnormalities), CD4+ T cell subsets, and patient-reported outcomes (PROs) were collected at inclusion. The primary endpoint was the occurrence of flare (loss of DAS28-CRP remission) over 12 months. Logistic regression analyses identified predictors of flare. Dichotomization into high/low-risk groups was based on 80% specificity using the area under the receiving operator curve (AUROC).

RESULTS

Of 63 patients choosing tapering, 23 (37%) flared compared with 12 of 60 (20%) on stable treatment (P = 0.043). All patients who flared regained remission upon reinstating treatment. In the tapering group, flare was associated with lower regulatory T cell (Treg) (P < 0.0001) and higher CRP levels (P < 0.0001), erythrocyte sedimentation rate (P < 0.035), and inflammation-related cells (IRCs) (P = 0.054); stepwise modeling selected Tregs (odds ratio [OR] = 0.350, P = 0.004), IRCs (OR = 1.871, P = 0.007), and CRP level (OR = 1.577, P = 0.004) with 81.7% accuracy and AUROC = 0.890. In the continued therapy group, modeling retained the tender joint count, total PD, and visual analog scale pain score, with 82.1% accuracy and AUROC = 0.899. Most patients in the study were considered low risk of flare (80 of 123 patients [65%]). Only 5 of 37 (13.5%) of the low-risk patients who tapered flared, which was notable compared with the continued therapy group (20% flare).

CONCLUSION

Flare on tapering b-DMARDs was predicted by lower Tregs and elevated inflammation biomarkers (IRCs/CRP level); flare on continued b-DMARDs was associated with raised pain parameters and US inflammation. Knowledge of these biomarkers should improve outcomes by targeted selection for tapering, and by increased monitoring of those on continued therapy predicted to flare.

Current status of immunological therapies for rheumatoid arthritis with a focus on antigen-specific therapeutic vaccines

Rheumatoid arthritis (RA) is recognized as an autoimmune joint disease driven by T cell responses to self (or modified self or microbial mimic) antigens that trigger and aggravate the inflammatory condition. Newer treatments of RA employ monoclonal antibodies or recombinant receptors against cytokines or immune cell receptors as well as small-molecule Janus kinase (JAK) inhibitors to systemically ablate the cytokine or cellular responses that fuel inflammation. Unlike these treatments, a therapeutic vaccine, such as CEL-4000, helps balance adaptive immune homeostasis by promoting antigen-specific regulatory rather than inflammatory responses, and hence modulates the immunopathological course of RA. In this review, we discuss the current and proposed therapeutic products for RA, with an emphasis on antigen-specific therapeutic vaccine approaches to the treatment of the disease. As an example, we describe published results of the beneficial effects of CEL-4000 vaccine on animal models of RA. We also make a recommendation for the design of appropriate clinical studies for these newest therapeutic approaches, using the CEL-4000 vaccine as an example. Unlike vaccines that create or boost a new immune response, the clinical success of an immunomodulatory therapeutic vaccine for RA lies in its ability to redirect autoreactive pro-inflammatory memory T cells towards rebalancing the "runaway" immune/inflammatory responses that characterize the disease. Human trials of such a therapy will require alternative approaches in clinical trial design and implementation for determining safety, toxicity, and efficacy. These approaches include adaptive design (such as the Bayesian optimal design (BOIN), currently employed in oncological clinical studies), and the use of disease-related biomarkers as indicators of treatment success.

Autoantibody-negative rheumatoid arthritis: still a challenge for the rheumatologist

Increased research over the past 30 years has greatly improved the understanding of the pathophysiological mechanisms and clinical aspects of autoantibody-positive rheumatoid arthritis, resulting in improved management and outcomes. In contrast, the subset of rheumatoid arthritis that does not have autoantibodies (such as rheumatoid factor and anti-citrullinated protein autoantibodies) remains less well defined in its pathogenic mechanisms. Autoantibody-negative rheumatoid arthritis continues to pose diagnostic challenges, might respond differently to therapies, and appears to be burdened with different comorbidities and outcomes. The clear separation of rheumatoid arthritis according to serotypes is still a subject of uncertainty and controversy, and studies specifically focused on comparing rheumatoid arthritis and rheumatoid arthritis-like arthritides that do not have autoantibodies remain scarce. The purpose of this Review is to summarise the peculiarities that make autoantibody-negative rheumatoid arthritis different from its autoantibody-positive counterpart, with the aim of generating debate and stimulating further research on this challenging condition.

Tailored therapeutic decision of rheumatoid arthritis using proteomic strategies: how to start and when to stop?

Unpredictable treatment responses have been an obstacle for the successful management of rheumatoid arthritis. Although numerous serum proteins have been proposed, there is a lack of integrative survey to compare their relevance in predicting treatment outcomes in rheumatoid arthritis. Also, little is known about their applications in various treatment stages, such as dose modification, drug switching or withdrawal. Here we present an in-depth exploration of the potential usefulness of serum proteins in clinical decision-making and unveil the spectrum of immunopathology underlying responders to different drugs. Patients with robust autoimmunity and inflammation are more responsive to biological treatments and prone to relapse during treatment de-escalation. Moreover, the concentration changes of serum proteins at the beginning of the treatments possibly assist early recognition of treatment responders. With a better understanding of the relationship between the serum proteome and treatment responses, personalized medicine in rheumatoid arthritis will be more achievable in the near future.

Physical Function of RA patients Tapering Treatment-A Post Hoc Analysis of the Randomized Controlled RETRO Trial

Several studies have shown that tapering or stopping disease-modifying anti-rheumatic drugs (DMARDs) in rheumatoid arthritis (RA) patients in sustained remission is feasible. However, tapering/stopping bears the risk of decline in physical function as some patients may relapse and face increased disease activity. Here, we analyzed the impact of tapering or stopping DMARD treatment on the physical function of RA patients. The study was a post hoc analysis of physical functional worsening for 282 patients with RA in sustained remission tapering and stopping DMARD treatment in the prospective randomized RETRO study. HAQ and DAS-28 scores were determined in baseline samples of patients continuing DMARD (arm 1), tapering their dose by 50% (arm 2), or stopping after tapering (arm 3). Patients were followed over 1 year, and HAQ and DAS-28 scores were evaluated every 3 months. The effect of treatment reduction strategy on functional worsening was assessed in a recurrent-event Cox regression model with a study-group (control, taper, and taper/stop) as the predictor. Two-hundred and eighty-two patients were analyzed. In 58 patients, functional worsening was observed. The incidences suggest a higher probability of functional worsening in patients tapering and/or stopping DMARDs, which is likely due to higher relapse rates in these individuals. At the end of the study, however, functional worsening was similar among the groups. Point estimates and survival curves show that the decline in functionality according to HAQ after tapering or discontinuation of DMARDs in RA patients with stable remission is associated with recurrence, but not with an overall functional decline.

Biomarkers for the diagnosis and treatment of rheumatoid arthritis - a systematic review

BACKGROUND

Rheumatoid arthritis (RA) is an autoimmune disease, symmetrically affecting the small joints. Biomarkers are tools that can be used in the diagnosis and monitoring of RA.

AIM

To systematically explore the role of the biomarkers: C-reactive protein (CRP), rheumatoid factor (RF), anti-cyclic citrullinated protein (Anti-CCP), 14-3-3η protein, and the multi-biomarker disease activity (MBDA) score for the diagnosis and treatment of RA.

METHODS

A systematic review of the English literature using four different databases was carried out.

RESULTS

CRP >7.1 mg/L predicted poor conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) outcome in RA. Anti-CCP, CRP ≥0.3 mg/dL, and RF predicted bone erosion and cartilage destruction. Combination of high 14-3-3η protein with RF and CRP improved the prediction of rapid erosion progression (REP). Anti-CCP was not associated with disease activity but was associated with increased radiographic damage (r = 0.46, p = 0.048). RF was not associated with joint damage but correlated with ultrasound-detected bone erosion. The 14-3-3η protein significantly correlated with inflammation, bone rremodeling, and osteoporosis in RA patients (p < 0.05). In addition, the 14-3-3η protein positively correlated with RA duration (p = 0.003), disease aactivity, and positive RF (p = 0.025) and it distinguished early from established RA. Early MBDA scores correlated with later response in disease activity after 6 and 12 weeks of treatment (p < 0.05). The MBDA score was able to differentiate between small differences in disease activity, predicted remission over 1-year pperiod, and was a strong predictor of radiographic progression of RA.

CONCLUSION

The investigated biomarkers are helpful tools in clinical practice for diagnosis, monitoring of treatment, and predicting prognosis in RA patients. However, further research is still required to investigate novel biomarkers for the pre-treatment selection of potentially responsive patients before starting therapy for a precision medicine in this area.

An AI-Powered Clinical Decision Support System to Predict Flares in Rheumatoid Arthritis: A Pilot Study

Treat-to-target (T2T) is a main therapeutic strategy in rheumatology; however, patients and rheumatologists currently have little support in making the best treatment decision. Clinical decision support systems (CDSSs) could offer this support. The aim of this study was to investigate the accuracy, effectiveness, usability, and acceptance of such a CDSS-Rheuma Care Manager (RCM)-including an artificial intelligence (AI)-powered flare risk prediction tool to support the management of rheumatoid arthritis (RA). Longitudinal clinical routine data of RA patients were used to develop and test the RCM. Based on ten real-world patient vignettes, five physicians were asked to assess patients' flare risk, provide a treatment decision, and assess their decision confidence without and with access to the RCM for predicting flare risk. RCM usability and acceptance were assessed using the system usability scale (SUS) and net promoter score (NPS). The flare prediction tool reached a sensitivity of 72%, a specificity of 76%, and an AUROC of 0.80. Perceived flare risk and treatment decisions varied largely between physicians. Having access to the flare risk prediction feature numerically increased decision confidence (3.5/5 to 3.7/5), reduced deviations between physicians and the prediction tool (20% to 12% for half dosage flare prediction), and resulted in more treatment reductions (42% to 50% vs. 20%). RCM usability (SUS) was rated as good (82/100) and was well accepted (mean NPS score 7/10). CDSS usage could support physicians by decreasing assessment deviations and increasing treatment decision confidence.

The pathogenesis of rheumatoid arthritis

Significant recent progress in understanding rheumatoid arthritis (RA) pathogenesis has led to improved treatment and quality of life. The introduction of targeted-biologic and -synthetic disease modifying anti-rheumatic drugs (DMARDs) has also transformed clinical outcomes. Despite this, RA remains a life-long disease without a cure. Unmet needs include partial response and non-response to treatment in many patients, failure to achieve immune homeostasis or drug free remission, and inability to repair damaged tissues. RA is now recognized as the end of a multi-year prodromal phase in which systemic immune dysregulation, likely beginning in mucosal surfaces, is followed by a symptomatic clinical phase. Inflammation and immune reactivity are primarily localized to the synovium leading to pain and articular damage, but is also associated with a broader series of comorbidities. Here, we review recently described immunologic mechanisms that drive breach of tolerance, chronic synovitis, and remission.

Synovial tissue macrophages in joint homeostasis, rheumatoid arthritis and disease remission

Synovial tissue macrophages (STMs) were principally recognized as having a pro-inflammatory role in rheumatoid arthritis (RA), serving as the main producers of pathogenic tumour necrosis factor (TNF). Recent advances in single-cell omics have facilitated the discovery of distinct STM populations, providing an atlas of discrete phenotypic clusters in the context of healthy and inflamed joints. Interrogation of the functions of distinct STM populations, via ex vivo and experimental mouse models, has re-defined our understanding of STM biology, opening up new opportunities to better understand the pathology of the arthritic joint. These works have identified STM subpopulations that form a protective lining barrier within the synovial membrane and actively participate in the remission of RA. We discuss how distinct functions of STM clusters shape the synovial tissue environment in health, during inflammation and in disease remission, as well as how an increased understanding of STM heterogeneity might aid the prediction of clinical outcomes and inform novel treatments for RA.

Current and Future Biomarkers in Multiple Sclerosis

Multiple sclerosis (MS) is a debilitating autoimmune disorder. Currently, there is a lack of effective treatment for the progressive form of MS, partly due to insensitive readout for neurodegeneration. The recent development of sensitive assays for neurofilament light chain (NfL) has made it a potential new biomarker in predicting MS disease activity and progression, providing an additional readout in clinical trials. However, NfL is elevated in other neurodegenerative disorders besides MS, and, furthermore, it is also confounded by age, body mass index (BMI), and blood volume. Additionally, there is considerable overlap in the range of serum NfL (sNfL) levels compared to healthy controls. These confounders demonstrate the limitations of using solely NfL as a marker to monitor disease activity in MS patients. Other blood and cerebrospinal fluid (CSF) biomarkers of axonal damage, neuronal damage, glial dysfunction, demyelination, and inflammation have been studied as actionable biomarkers for MS and have provided insight into the pathology underlying the disease process of MS. However, these other biomarkers may be plagued with similar issues as NfL. Using biomarkers of a bioinformatic approach that includes cellular studies, micro-RNAs (miRNAs), extracellular vesicles (EVs), metabolomics, metabolites and the microbiome may prove to be useful in developing a more comprehensive panel that addresses the limitations of using a single biomarker. Therefore, more research with recent technological and statistical approaches is needed to identify novel and useful diagnostic and prognostic biomarker tools in MS.

Defining the Optimal Strategies for Achieving Drug-Free Remission in Rheumatoid Arthritis: A Narrative Review

Background: It is now accepted that the optimum treatment goal for rheumatoid arthritis (RA) is sustained remission, as this has been shown to be associated with the best patient outcomes. There is little guidance on how to manage patients once remission is achieved; however, it is recommended that patients can taper therapy, with a view to discontinuing and achieving drug-free remission if treatment goals are maintained. This narrative review aims to present the current literature on drug-free remission in rheumatoid arthritis, with a view to identifying which strategies are best for disease-modifying anti-rheumatic drug (DMARD) tapering and to highlight areas of unmet clinical need. Methods: We performed a narrative review of the literature, which included research articles, meta-analyses and review papers. The key search terms included were rheumatoid arthritis, remission, drug-free remission, b-DMARDS/biologics, cs-DMARDS and tapering. The databases that were searched included PubMed and Google Scholar. For each article, the reference section of the paper was reviewed to find additional relevant articles. Results: It has been demonstrated that DFR is possible in a proportion of RA patients achieving clinically defined remission (both on cs and b-DMARDS). Immunological, imaging and clinical associations with/predictors of DFR have all been identified, including the presence of autoantibodies, absence of Power Doppler (PD) signal on ultrasound (US), lower disease activity according to composite scores of disease activity and lower patient-reported outcome scores (PROs) at treatment cessation. Conclusions: DFR in RA may be an achievable goal in certain patients. This carries importance in reducing medication-induced side-effects and potential toxicity, the burden of taking treatment if not required and cost effectiveness, specifically for biologic therapy. Prospective studies of objective biomarkers will help facilitate the prediction of successful treatment discontinuation.

Proteomic Approaches to Defining Remission and the Risk of Relapse in Rheumatoid Arthritis

Objectives

Patients with Rheumatoid Arthritis (RA) are increasingly achieving stable disease remission, yet the mechanisms that govern ongoing clinical disease and subsequent risk of future flare are not well understood. We sought to identify serum proteomic alterations that dictate clinically important features of stable RA, and couple broad-based proteomics with machine learning to predict future flare.

Methods

We studied baseline serum samples from a cohort of stable RA patients (RETRO, n = 130) in clinical remission (DAS28<2.6) and quantified 1307 serum proteins using the SOMAscan platform. Unsupervised hierarchical clustering and supervised classification were applied to identify proteomic-driven clusters and model biomarkers that were associated with future disease flare after 12 months of follow-up and RA medication withdrawal. Network analysis was used to define pathways that were enriched in proteomic datasets.

Results

We defined 4 proteomic clusters, with one cluster (Cluster 4) displaying a lower mean DAS28 score (p = 0.03), with DAS28 associating with humoral immune responses and complement activation. Clustering did not clearly predict future risk of flare, however an XGboost machine learning algorithm classified patients who relapsed with an AUC (area under the receiver operating characteristic curve) of 0.80 using only baseline serum proteomics.

Conclusions

The serum proteome provides a rich dataset to understand stable RA and its clinical heterogeneity. Combining proteomics and machine learning may enable prediction of future RA disease flare in patients with RA who aim to withdrawal therapy.

A novel multi-biomarker combination predicting relapse from long-term remission after discontinuation of biological drugs in rheumatoid arthritis

Biological disease modifying anti-rheumatic drugs (bDMARDs) show dramatic treatment efficacy in rheumatoid arthritis (RA). Long-term use of bDMARDs, however, has disadvantages such as high costs and infection risk. Therefore, a methodology is needed to predict any future RA relapse. Herein, we report a novel multi-biomarker combination which predicts relapse after bDMARDs-withdrawal in patients in remission. Forty patients with RA in remission for more than 12 months were enrolled. bDMARDs were withdrawn and they were followed monthly for the next 24 months. Fourteen patients (35%) of 40 in the cohort remained in remission at 24 months, whereas 26 (65%) relapsed at various time-points. Serum samples obtained longitudinally from patients in remission were assessed for the relapse-prediction biomarkers and index from 73 cytokines by the exploratory multivariate ROC analysis. The relapse-prediction index calculated from the 5 cytokines, IL-34, CCL1, IL-1β, IL-2 and IL-19, strongly discriminated between patients who relapsed and those who stayed in remission. These findings could contribute to clinical decision-making as to the timing of when to discontinue bDMARDs in RA treatment.

IgA anti-citrullinated protein antibodies (IgA ACPA) are associated with flares during DMARD tapering in rheumatoid arthritis

OBJECTIVES

A substantial proportion of rheumatoid arthritis (RA) patients flare upon withdrawal of disease modifying anti-rheumatic drugs (DMARDs), thus the definition of prognostic markers is crucial. Anti-citrullinated protein antibody (ACPA)-positivity has been identified as a risk factor for flare. However, only the role of IgG is established in this context, while the role of IgA ACPA is poorly defined. We thus aimed to investigate the role of IgA ACPA in flare of RA.

METHODS

Serum levels of IgA1 and IgA2 ACPA at baseline and after 12 months were measured in 108 patients from the randomized controlled RETRO study. RA patients in stable remission for at least 6 months at study recruitment were assigned to either one of the DMARD tapering arms or to continuation of DMARDs.

RESULTS

In patients remaining in remission but not in the ones who flared, IgA2 ACPA levels and proportion of IgA2 in ACPA (IgA2%ACPA) significantly declined (median of 17.5%; p< 0.0001). This seemed to be independent of the treatment choice, as there was no difference in IgA2 ACPA dynamics between the study arms. IgA2% ACPA was associated with disease activity (DAS28) at flare (r = 0.36; p= 0.046). IgA and IgG ACPA showed a tendency towards independent contribution to the risk of flare with the highest risk if a patient had both antibody classes.

CONCLUSION

In this study, IgA ACPA was identified as a risk factor for flare in combination with IgG ACPA. IgA2 ACPA levels were associated with flare severity and declined in patients in stable remission.

Tapering of disease-modifying antirheumatic drugs: an overview for daily practice

In this Review, we discuss the possibility of drug tapering in patients with rheumatoid arthritis in remission or low disease activity, for glucocorticoids and disease-modifying antirheumatic drugs. We review international guidelines and recommendations, as well as remaining uncertainties, and provide an overview of the current literature. Three strategies of tapering are discussed: (1) tapering by discontinuation of one of the drugs in combination therapy regimens, (2) tapering by reducing the dose of one of the drugs in combination therapy regimens, and (3) tapering by dose reduction of monotherapy with disease-modifying antirheumatic drugs. We discuss the outcomes and robustness of evidence of trials and observational cohorts, and we give a trajectory for further research and drug tapering in daily practice.

Biomarkers in Rheumatoid Arthritis

The utilization and identification of biomarkers in rheumatoid arthritis (RA) to facilitate timely diagnosis and the optimal management of the disease is an area of active investigation. This review focuses on biomarkers available for routine clinical use, details potential investigational biomarkers, and raises outstanding clinical questions.

Biomarkers of tolerance in immune-mediated inflammatory diseases: a new era in clinical management?

Modern therapeutic agents and treatment regimens have made sustained remission an attainable target for many patients across a spectrum of immune-mediated inflammatory diseases, albeit at the risk of adverse events and the expense of drug prescription and safety monitoring. Clinicians and patients are thus increasingly faced with a novel treatment dilemma: whether and how best to stop immunomodulatory treatment in patients who achieve remission. In this final paper in a Series on therapeutic tolerance induction, we summarise our current knowledge of biomarkers of immune homeostasis in immune-mediated inflammatory diseases and their application to the prediction and attainment of sustained drug-free remission. We summarise evidence from prospective studies of immunomodulatory drug cessation across a range of immune-mediated inflammatory diseases, including rheumatoid arthritis, juvenile idiopathic arthritis, and inflammatory bowel disease. We also consider current evidence for clinical, serological, proteomic, metabolomic, cellular, and microbiomic biomarkers of immune homeostasis. Finally, we discuss the steps necessary for clinical translation of these biomarkers, as well as the potential transformative effect of these biomarkers on management of patients with immune-mediated inflammatory diseases if clinical translation is successfully achieved.

Novel approaches to develop biomarkers predicting treatment responses to TNF-blockers

Introduction: Chronic inflammatory diseases (CIDs) cause significant morbidity and are a considerable burden for the patients in terms of pain, impaired function, and diminished quality of life. Important progress in CID treatment has been obtained with biological therapies, such as tumor-necrosis-factor blockers. However, more than a third of the patients fail to respond to these inhibitors and are exposed to the side effects of treatment, without the benefits. Therefore, there is a strong interest in developing tools to predict response of patients to biologics. Areas covered: The authors searched PubMed for recent studies on biomarkers for disease assessment and prediction of therapeutic responses, focusing on the effect of TNF blockers on immune responses in spondyloarthritis (SpA), and other CID, in particular rheumatoid arthritis and inflammatory bowel disease. Conclusions will be drawn about the possible development of predictive biomarkers for response to treatment. Expert opinion: No validated biomarker is currently available to predict treatment response in CID. New insight could be generated through the development of new bioinformatic modeling approaches to combine multidimensional biomarkers that explain the different genetic, immunological and environmental determinants of therapeutic responses.

Prediction of disease flare by biomarkers after discontinuing biologics in patients with rheumatoid arthritis achieving stringent remission

To elucidate the disease-flare process in rheumatoid arthritis (RA) after discontinuing biological disease-modifying antirheumatic drugs (bDMARDs), we first focused on RA-flare prediction after achieving stringent remission criteria. Patients with RA who maintained a simplified disease activity index ≤ 3.3 for ≥ 3 months during November 2014-January 2018 in our medical centre in Tokyo, Japan, were eligible. The primary endpoint was flare (disease activity score 28-erythrocyte sedimentation rate ≥ 3.2 with increase from baseline > 0.6) within 2 years after bDMARD discontinuation. Comprehensive clinical assessments, ultrasonographic evaluation of 40 joints, and blood sampling for 12 biomarkers were performed every 2-3 months for 2 years unless patients experienced flare. Flare-positive and flare-negative patients were compared using univariate and Kaplan-Meier analyses. Thirty-six patients (80.6% female, median disease duration, 5.2 years; median treatment period with discontinued bDMARD, 2 years; median remission duration, 18 months) were enrolled. Twenty patients (55.6%) experienced RA flare 43-651 (median, 115) days after the first skipped date of bDMARDs. Two patients who withdrew without disease flare were excluded from the comparison. Clinical and ultrasonographic evaluations did not show significant between-group differences; Kaplan-Meier analysis showed that higher baseline soluble tumour necrosis factor receptor 1 (sTNFR1) concentration impacted subsequent disease flare (p = 0.0041); higher baseline interleukin (IL)-2 concentration was exclusively beneficial to patients with lower sTNFR1 (p = 0.0058), resulting in remission maintenance in 83.3% of patients with lower sTNFR1 and higher IL-2. We demonstrated the usefulness of combined biomarker evaluation for predicting sustained remission after bDMARD discontinuation in RA.

Advanced machine learning for predicting individual risk of flares in rheumatoid arthritis patients tapering biologic drugs

BACKGROUND

Biological disease-modifying anti-rheumatic drugs (bDMARDs) can be tapered in some rheumatoid arthritis (RA) patients in sustained remission. The purpose of this study was to assess the feasibility of building a model to estimate the individual flare probability in RA patients tapering bDMARDs using machine learning methods.

METHODS

Longitudinal clinical data of RA patients on bDMARDs from a randomized controlled trial of treatment withdrawal (RETRO) were used to build a predictive model to estimate the probability of a flare. Four basic machine learning models were trained, and their predictions were additionally combined to train an ensemble learning method, a stacking meta-classifier model to predict the individual flare probability within 14 weeks after each visit. Prediction performance was estimated using nested cross-validation as the area under the receiver operating curve (AUROC). Predictor importance was estimated using the permutation importance approach.

RESULTS

Data of 135 visits from 41 patients were included. A model selection approach based on nested cross-validation was implemented to find the most suitable modeling formalism for the flare prediction task as well as the optimal model hyper-parameters. Moreover, an approach based on stacking different classifiers was successfully applied to create a powerful and flexible prediction model with the final measured AUROC of 0.81 (95%CI 0.73-0.89). The percent dose change of bDMARDs, clinical disease activity (DAS-28 ESR), disease duration, and inflammatory markers were the most important predictors of a flare.

CONCLUSION

Machine learning methods were deemed feasible to predict flares after tapering bDMARDs in RA patients in sustained remission.

PD-1 Expression on CD8+CD28- T cells within inflammatory synovium is associated with Relapse: A cohort of Rheumatoid Arthritis

Defect in T lymphocyte homeostasis could implicate initiation and development of rheumatoid arthritis (RA). Since PD-1 plays a key role in the regulation of T lymphocytes, its expression pattern in various CD8+ T cell subsets could be so effective in RA pathogenesis. Here, we investigated the expression of PD-1 and CXCR3 on CD8+CD28- T cells in association with the IFN-γ levels in patients with RA. A total of 42 RA patients, including 10 newly-diagnosed (ND) and 32 relapsed (RL) cases and also 20 healthy donors were enrolled. Phenotypic characterization of CD8+ T cells derived from peripheral blood (PB) and synovial fluid (SF) was performed by flow cytometry. The plasma and SF IFN-γ levels were also assessed by ELISA. The frequency of CD8+CD28- T cells showed no significant differences between patients and controls while its higher levels were observed in PB, versus SF of RL patients. Relapsed patients also showed higher CXCR3 and especially PD-1 expression on their CD8+CD28- T cells. The IFN-γ concentration was elevated in SF of ND patients while its plasma level was significantly lower in RL subgroup than controls. Although PD-1 could induce immune suppression in effector T cells, it is upregulated during inflammation and its overexpression on CD8+CD28- T cells within inflammatory synovium is associated with severity of disease in our cohort of RA patients.

Emerging Technologies and Platforms for the Immunodetection of Multiple Biochemical Markers in Osteoarthritis Research and Therapy

Biomarkers, especially biochemical markers, are important in osteoarthritis (OA) research, clinical trials, and drug development and have potential for more extensive use in therapeutic monitoring. However, they have not yet had any significant impact on disease diagnosis and follow-up in a clinical context. Nevertheless, the development of immunoassays for the detection and measurement of biochemical markers in OA research and therapy is an active area of research and development. The evaluation of biochemical markers representing low-grade inflammation or extracellular matrix turnover may permit OA prognosis and expedite the development of personalized treatment tailored to fit particular disease severities. However, currently detection methods have failed to overcome specific hurdles such as low biochemical marker concentrations, patient-specific variation, and limited utility of single biochemical markers for definitive characterization of disease status. These challenges require new and innovative approaches for development of detection and quantification systems that incorporate clinically relevant biochemical marker panels. Emerging platforms and technologies that are already on the way to implementation in routine diagnostics and monitoring of other diseases could potentially serve as good technological and strategic examples for better assessment of OA. State-of-the-art technologies such as advanced multiplex assays, enhanced immunoassays, and biosensors ensure simultaneous screening of a range of biochemical marker targets, the expansion of detection limits, low costs, and rapid analysis. This paper explores the implementation of such technologies in OA research and therapy. Application of novel immunoassay-based technologies may shed light on poorly understood mechanisms in disease pathogenesis and lead to the development of clinically relevant biochemical marker panels. More sensitive and specific biochemical marker immunodetection will complement imaging biomarkers and ensure evidence-based comparisons of intervention efficacy. We discuss the challenges hindering the development, testing, and implementation of new OA biochemical marker assays utilizing emerging multiplexing technologies and biosensors.

A multi-biomarker disease activity score can predict sustained remission in rheumatoid arthritis

Background

Reliable assessment of remission is important for the optimal management of rheumatoid arthritis (RA) patients. In this study, we used the multi-biomarker disease activity (MBDA) test to explore the role of biomarkers in predicting point remission and sustained remission.

Methods

RA patients on > 6 months stable therapy in stable low disease activity (DAS28-ESR ≤ 3.2) were assessed every 3 months for 1 year. Baseline, intermittent (IR) and sustained (SR) remission were defined by DAS28-ESR, DAS28-CRP, simple disease activity index (SDAI), clinical disease activity index (CDAI) and ACR/EULAR Boolean criteria. Patients not fulfilling any remission criteria at baseline were classified as ‘low disease activity state’ (LDAS). Patients not fulfilling any remission criteria over 1 year were classified as ‘persistent disease activity’ (PDA). MBDA score was measured at baseline/3/6 months. The baseline MBDA score, the 6-month time-integrated MBDA score and MBDA biomarkers were used for analyses. The area under the receiver operating characteristic curve (AUROC) assessed the ability of the MBDA score to discriminate between remission and non-remission. Biomarkers were analysed at baseline using the Mann-Whitney test and over time using the Jonckheere-Terpstra trend test.

Results

Of 148 patients, 27% were in the LDAS, 65% DAS28-ESR remission, 51% DAS28-CRP remission, 40% SDAI remission, 43% CDAI remission and 25% ACR/EULAR Boolean remission at baseline. Over 1 year, 9% of patients were classified as PDA. IR and SR were achieved in 42%/47% by DAS28-ESR, 46%/29% by DAS28-CRP, 45%/20% by SDAI, 44%/21% by CDAI and 35%/9% by ACR/EULAR Boolean criteria, respectively. By all remission criteria, baseline MBDA score discriminated baseline remission (AUROCs 0.68–0.75) and IR/SR (AUROCs 0.65–0.74). The 6-month time-integrated MBDA score discriminated IR/SR (AUROCs 0.65–0.79). Baseline MBDA score and concentrations of IL-6, leptin, SAA and CRP were significantly lower in all baseline remission criteria groups vs LDAS. They and the 6-month time-integrated values were lower among patients who achieved IR/SR vs PDA over 1 year.

Conclusions

This study demonstrated that the MBDA score and its biomarkers IL-6, leptin, SAA and CRP differentiated between small differences in disease activity (i.e. between low disease activity and remission states). They were also predictors of remission over 1 year.

Predictors of successful discontinuation of biologic and targeted synthetic DMARDs in patients with rheumatoid arthritis in remission or low disease activity: a systematic literature review

OBJECTIVE

To systematically review possible predictors of successful discontinuation of biologic or targeted synthetic DMARDs (b/tsDMARDs) in RA patients in remission or low disease activity.

METHODS

MEDLINE database and Cochrane Library were scanned for studies that discontinued b/tsDMARDs in remission/low disease activity and searched for predictors of successful discontinuation. Additionally, EULAR and ACR meeting abstracts were hand searched.

RESULTS

Thirty-four studies with a total of 5724 patients were included. Predictors of successful b/tsDMARD discontinuation were (number of studies): low disease activity (n = 13), better physical function (n = 6), low or absence of rheumatoid factor (n = 5) or ACPA (n = 3), low levels of CRP (n = 3) or ESR (n = 3), shorter disease duration (n = 3), low signals of disease activity by ultrasound (n = 3). Only one study with high risk of bias was identified on tsDMARD discontinuation.

CONCLUSION

Several predictors of successful bDMARD discontinuation were identified. Although studies are heterogeneous, these predictors may inform clinical decision making in patients who are considered for a potential bDMARD discontinuation.

Correlation of the Multi-Biomarker Disease Activity Score With Rheumatoid Arthritis Disease Activity Measures: A Systematic Review and Meta-Analysis

OBJECTIVE

There are conflicting reports on the validity of the multi-biomarker disease activity (MBDA) score for assessing rheumatoid arthritis (RA) disease activity. Our aim was to perform a systematic review of the MBDA and a meta-analysis of the correlation between the MBDA and other RA disease activity measures.

METHODS

A systematic review was performed by searching Medline, Embase, Scopus, Google Scholar, and the Cochrane Library from inception to March 7, 2017. Study details, MBDA performance, and study quality were assessed by independent reviewers. Correlations of the MBDA with composite RA disease activity measures were pooled using random-effects meta-analyses.

RESULTS

A total of 22 studies were identified in the systematic review, of which 8 (n = 3,242 assays) reported correlations of the MBDA with RA disease activity measures. Pooling results from these 8 studies in the meta-analysis, the MBDA demonstrated modest correlations with the Disease Activity Score in 28 joints using the C-reactive protein level (DAS28-CRP; r = 0.41, 95% confidence interval [95% CI] 0.36-0.46) and the Disease Activity Score using the erythrocyte sedimentation rate (DAS28-ESR; r = 0.48, 95% CI 0.38-0.58), with weaker correlations observed with the Simplified Disease Activity Index (SDAI; r = 0.35, 95% CI 0.26-0.43), Clinical Disease Activity Index (CDAI; r = 0.26, 95% CI 0.19-0.33), and Routine Assessment of Patient Index Data 3 (RAPID3; r = 0.23, 95% CI 0.19-0.27). Correlations between change in MBDA and change in disease activity measures ranged from r = 0.53 for the DAS28-ESR to r = 0.26 for the CDAI.

CONCLUSION

The MBDA demonstrates moderate convergent validity with the DAS28-CRP and the DAS28-ESR but weaker correlations with the SDAI, CDAI, and RAPID3. While it appears to complement existing RA disease activity measures, further assessment of the performance characteristics of the MBDA is warranted.

Development and formative evaluation of patient research partner involvement in a multi-disciplinary European translational research project

PLAIN ENGLISH SUMMARY

Patient and public involvement (PPI) improves the quality of health research and ensures that research is relevant to patients' needs. Though PPI is increasingly evident in clinical and health services research, there are few examples in the research literature of effective PPI in translational and laboratory-based research. In this paper, we describe the development and evaluation of PPI in a multi-centre European project (EuroTEAM - Towards Early biomarkers in Arthritis Management) that included both translational and laboratory-based and psychosocial research. We found that although most PPI in EuroTEAM was centred around the psychosocial research, there were examples of PPI in the laboratory studies. As the project evolved, researchers became better at accommodating PPI and identifying PPI opportunities. It was generally agreed that PPI had a positive impact on the project overall, particularly on public engagement with the research. We concluded that the inclusion of both psychosocial and laboratory-based research in the same project facilitated PPI across all aspects of the research. In future projects, we would try to specify individual PPI activities in more detail at the project-planning stage, and better accommodate patient partners who are not native speakers of English.

ABSTRACT

Background Patient and public involvement (PPI) enhances research quality and relevance and is central to contemporary health policy. The value of PPI has been recognised in rheumatology research, though there are limited examples of PPI in basic and translational science. The EU FP7 funded 'EuroTEAM' (Towards Early biomarkers in Arthritis Management) project was established to develop biomarker-based approaches to predict the future development of rheumatoid arthritis and incorporated psychosocial research to investigate the perceptions of 'at risk' individuals about predictive testing, and to develop informational resources about rheumatoid arthritis (RA) risk. Patient involvement was central to EuroTEAM from the inception of the project. The objective of this paper is to describe the development of PPI in EuroTEAM, formatively assess the impact of PPI from the perspectives of researchers and patient research partners (PRPs), reflect on successes and lessons learned, and formulate recommendations to guide future projects.Methods Two mixed-methods surveys (for PRPs and researchers) and a teleconference were undertaken to assess the impact of PPI on individual work packages and on EuroTEAM overall.Results There was consensus about the positive impact of PPI on the research and on the experiences of those involved. In particular, the positive impact of PPI on the personal development of researchers, and on effective public engagement with EuroTEAM research were highlighted. Researchers described adapting their practice in future projects to facilitate PPI. Spin-off projects and ongoing collaborations between PRPs and researchers reflected the value of PPI to participants. PPI was more frequently integrated in psychosocial research, though examples of PPI in laboratory/translational science were also described. PRPs asked for more opportunities to contribute meaningfully to basic scientific research and for more extensive feedback on their contributions.Conclusions The findings were used to formulate recommendations to guide effective involvement of patients in future similar projects, including identifying specific training requirements for PRPs and researchers, the identification of PRP focused tasks/deliverables at the project planning stage, and supporting access to involvement for all PRPs. Importantly, the distinctive multidisciplinary approach of EuroTEAM, incorporating both basic science and psychosocial research, facilitated patient involvement in the project overall.

Relapse in rheumatoid arthritis patients undergoing dose reduction and withdrawal of biologics: are predictable factors more relevant than predictive parameters? An observational prospective real-life study

OBJECTIVE

To determine predictive/predictable factors of relapse in rheumatoid arthritis (RA) patients undergoing biologic Disease-Modifying Anti-Rheumatic Drugs (bDMARDs) dose reduction/discontinuation.

PATIENTS AND METHODS

RA patients receiving the same bDMARD for more than 1 year, in Simplified Disease Activity Index (SDAI) remission, were selected in an observational monocentric real-life study. The 18-month follow-up included spacing (6 months) and withdrawal (12 months) periods of bDMARD. Clinical, biological and ultrasonographic (US) parameters were collected regularly. Relapse was defined by SDAI>11.

RESULTS

Fifty-three RA patients (mean age: 58 years; 72% women; median duration: 11 years) were enrolled. Forty-two received anti-cytokinic bDMARD targeting tumour necrosis factor (n=39) or interleukin-6R (n=3) and 11 were treated by abatacept. The number of relapses during the spacing and discontinuation periods were 19 and 20, respectively. After 18 months of follow-up, among the 53 patients, 12 maintained bDMARD-free remission, 39 had relapsed and 2 were lost of follow-up. Median time to relapse was 11.8 months. In multivariate analysis, baseline factors predictive of relapse were corticosteroid intake, female gender, longer disease duration and no methotrexate intake with bDMARD. Concerning the survival analysis, also taking into account the factors of predictability, the main risk factor of relapse after discontinuation was an increase of SDAI >0 during the spacing period (p=0.03). US findings were not contributive.

CONCLUSION

In the context of RA in remission under bDMARDs, variation of SDAI during the dose-reduction phase is more relevant than baseline parameters to predict success of drug withdrawal.

Effect of short-term methotrexate discontinuation on rheumatoid arthritis disease activity: post-hoc analysis of two randomized trials

To investigate the effects of short-term discontinuation of methotrexate (MTX) on disease activity in patients with rheumatoid arthritis (RA) taking a stable dose of MTX. A post-hoc analysis of two randomized controlled trials was used to investigate the effects of temporary MTX discontinuation (for 2 weeks or 4 weeks) on responses to seasonal influenza vaccination. The impact of MTX discontinuation on the RA disease activity score (DAS28) and RA flare rate during discontinuation and after reintroduction was examined. The DAS28 increased during the 4-week MTX discontinuation period, before returning to baseline after reintroduction. The overall flare-free survival period did not differ between the groups (log rank p = 0.142). However, during the 4-week MTX discontinuation period, more patients in the MTX-hold group than in the MTX-continue group experienced a flare (20.5% vs. 7.4%, respectively; p = 0.058). After resumption of MTX, the flare rate did not differ between groups. The flare rates in the MTX-continue group and the 2-week and 4-week MTX-hold groups were 5.8%, 10.8% and 20.5%, respectively (p < 0.01). The change in the DAS28 from baseline did not differ significantly between the MTX-continue and the 2-week MTX-discontinue groups. However, there was a significant difference between the 4-week MTX-hold group and the MTX-continue group (p = 0.005). Short-term discontinuation of MTX for up to 2 weeks is safe, whereas discontinuation for 4 weeks is associated with a transient increase in disease flares and activity in RA patients taking a stable MTX dose.Key Points• Methotrexate discontinuation for 2 weeks is safe.• Methotrexate discontinuation for 4 weeks transiently increases flare risk and disease activity.• Disease flare risk and disease activity return to baseline after restarting methotrexate treatment.

Circulating calprotectin (S100A8/A9) is higher in rheumatoid arthritis patients that relapse within 12 months of tapering anti-rheumatic drugs

Objective

To investigate whether calprotectin (S100A8/A9 or MRP8/14), an inflammatory complex released by monocytes, could indicate residual subclinical inflammation in rheumatoid arthritis (RA) patients who are in stable remission on disease-modifying anti-rheumatic drugs (DMARDs) and serve as a marker for disease flare after DMARD tapering.

Methods

We used data from two trials. Patients from the IMPROVED study had early (< 2 years) RA, and when they achieved disease activity score remission (DAS44 < 1.6), they stopped methotrexate to attempt drug-free remission. Patients from the RETRO study had established RA in stable remission (DAS28 < 2.6) and either tapered by 50% or stopped (biological or conventional) DMARDs. Circulating calprotectin at the tapering time point was determined by ELISA, and its predictive value for flare (loss of remission) within 12 months of DMARD tapering/stopping was determined.

Results

In both IMPROVED (n = 104) and RETRO (n = 57), patients that flared within 12 months had higher calprotectin at the moment of DMARD tapering/stopping. Twofold higher calprotectin at the moment of DMARD tapering/stopping was associated with an increased risk (odds ratio) of flare of 1.07 (95% CI 0.98–1.18, p = 0.14) in the IMPROVED and 3.62 (95% CI 1.76–7.46, p < 0.001) in the RETRO. Correcting for clinical predictors of flare (DAS at study inclusion, anti-CCP2 positivity, gender) did not change these estimates. The area under the receiver operating curve of calprotectin levels for predicting flare within 12 months was 0.63 (95% CIs 0.51–0.76) in the IMPROVED study and 0.80 (95% CIs 0.69 to 0.92) in the RETRO study.

Conclusion

Circulating calprotectin levels in RA patients in remission on DMARDs are higher in patients that will flare upon DMARD tapering/stopping. Since the differences between the cohorts precluded definitive conclusions, more research is needed to determine whether calprotectin has prognostic value in predicting flare after attempting drug tapering in RA.

Trial registration

IMPROVED, ISRCTN11916566. RETRO, 2009-015740-42.

Predicting drug-free remission in rheumatoid arthritis: A prospective interventional cohort study

BACKGROUND

Many patients with rheumatoid arthritis (RA) achieve disease remission with modern treatment strategies. However, having achieved this state, there are no tests that predict when withdrawal of therapy will result in drug-free remission rather than flare. We aimed to identify predictors of drug-free remission in RA.

METHODS

The Biomarkers of Remission in Rheumatoid Arthritis (BioRRA) Study was a unique, prospective, interventional cohort study of complete and abrupt cessation of conventional synthetic disease-modifying anti-rheumatic drugs (DMARDs). Patients with RA of at least 12 months duration and in clinical and ultrasound remission discontinued DMARDs and were monitored for six months. The primary outcome was time-to-flare, defined as disease activity score in 28 joints with C-reactive protein (DAS28-CRP) ≥ 2.4. Baseline clinical and ultrasound measures, circulating inflammatory biomarkers, and peripheral CD4+ T cell gene expression were assessed for their ability to predict time-to-flare and flare/remission status by Cox regression and receiver-operating characteristic (ROC) analysis respectively.

RESULTS

23/44 (52%) eligible patients experienced an arthritis flare after a median (IQR) of 48 (31.5-86.5) days following DMARD cessation. A composite score incorporating five baseline variables (three transcripts [FAM102B, ENSG00000228010, ENSG00000227070], one cytokine [interleukin-27], one clinical [Boolean remission]) differentiated future flare from drug-free remission with an area under the ROC curve of 0.96 (95% CI 0.91-1.00), sensitivity 0.91 (0.78-1.00) and specificity 0.95 (0.84-1.00).

CONCLUSION

We provide proof-of-concept evidence for predictors of drug-free remission in RA. If validated, these biomarkers could help to personalize immunosuppressant withdrawal: a therapy paradigm shift with ensuing patient and economic benefits.

Treatment Withdrawal Following Remission in Juvenile Idiopathic Arthritis: A Systematic Review of the Literature

BACKGROUND

Early diagnosis and treatment of juvenile idiopathic arthritis (JIA) with conventional and biologic disease-modifying anti-rheumatic drugs have vastly improved outcomes for children with these diseases. Currently, a large proportion of children with JIA are able to achieve clinical inactive disease and remission. With this success, important questions have arisen about when medications can be stopped and how to balance the risks and benefits of continuing medications versus the potential for flare after stopping.

AIM

The aim was to conduct a systematic review of the available literature to summarize current evidence about medication withdrawal for JIA in remission.

METHODS

We conducted a systematic literature search in PubMed and Embase from 1990 to 2019. References were first screened by title and then independently screened by title and abstract by two authors. A total of 77 original papers were selected for full-text review. Data were extracted from 30 papers on JIA and JIA-associated uveitis, and the quality of the evidence was evaluated using National Institutes of Health (NIH)/National Heart, Lung, and Blood Institute (NHLBI) tools. Studies on biochemical and radiologic biomarkers were also reviewed and summarized.

RESULTS

Most studies investigating treatment withdrawal in JIA have been observational and of poor or fair quality; interpretations of these studies have been limited by differences in study populations, disease and remission durations, the medications withdrawn, approaches to withdrawal, and definitions of disease outcomes. Overall the data suggest that flares are common after stopping JIA medications, particularly biologic medications. Clinical characteristics associated with increased risks of flare have not been consistently identified. Biochemical biomarkers and ultrasound findings have been shown to predict outcomes after stopping medications, but to date, no such predictor has been consistently validated across JIA populations. Studies have also not identified optimal strategies for withdrawing medication for well-controlled JIA. Promising withdrawal strategies include discontinuing methotrexate before biologic medications in children receiving combination therapy, dose reduction for children on biologics, and treat-to-target approaches to withdrawal. These and other strategies require further investigation in larger, high-quality studies.

CONCLUSIONS

The published literature on treatment withdrawal in JIA has varied in design and quality, yielding little conclusive evidence thus far on the management of JIA in remission. Given the importance of this question, international collaborative efforts are underway to study clinical and biologic predictors of successful medication withdrawal in JIA. These efforts may ultimately support the development of personalized approaches to withdrawing medication in children with JIA in remission.

Biologic discontinuation strategies and outcomes in patients with rheumatoid arthritis

Introduction: Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease, which affects joints as well as extra-articular tissues. In the last decades, increasing targeted therapeutic options dramatically improved RA management by doubling the rate of patients achieving clinical remission. Currently, there is a need for management strategies aimed at limiting treatment-related adverse events and costs in good responders.Areas covered: Data on de-escalation of biologic drugs (especially for anti-TNF agents) are mainly available from post-hoc analyses of randomized controlled trials and from registry-based observational studies. This narrative review illustrates the rationales for dose tapering and expands to provide an overview of the efficacy of the different available strategies for reducing the exposure to biologic drugs in patients achieving a sustained clinical response. Selected studies are discussed as illustrative examples.Expert opinion: Withdrawal of biologic therapy might be attempted in limited patients with very early RA; conversely, established RA is more suitably managed with a progressive decrease of drug regimen, by either dose reduction or injection/infusion spacing. Further studies investigating potential factors predicting post-tapering disease relapse are warranted, in order to better identify the best candidates for a decreased-dose approach.

The B side of rheumatoid arthritis pathogenesis

In the last years, a dramatic amount of research has been performedincreasing the knowledge about the biological mechanism underpinning Rheumatoid Arthritis (RA) inflammation, putting B lymphocytes in the center of RA pathogenesis. Nowadays, B cell phenotypes and autoantibodies positivity arose as important biomarkers in early and long-standing disease. Moreover, comparative analysis of peripheral blood and synovial tissue compartments enables the identification of novel physiopathological mechanisms promoting inflammation. In this narrative review we will discuss the biological relevance of B cell derived autoimmunity and in RA course, from disease onset to remission achievement.

[S2e guideline: treatment of rheumatoid arthritis with disease-modifying drugs]

BACKGROUND

Medication-based strategies to treat rheumatoid arthritis are crucial in terms of outcome. They aim at preventing joint destruction, loss of function and disability by early and consistent inhibition of inflammatory processes.

OBJECTIVE

Achieving consensus about evidence-based recommendations for the treatment of rheumatoid arthritis with disease-modifying anti-rheumatic drugs in Germany.

METHODS

Following a systematic literature research, a structured process among expert rheumatologists was used to reach consensus.

RESULTS

The results of the consensus process can be summed up in 6 overarching principles and 10 recommendations. There are several new issues compared to the version of 2012, such as differentiated adjustments to the therapeutic regime according to time point and extent of treatment response, the therapeutic goal of achieving remission as assessed by means of the simplified disease activity index (SDAI) as well as the potential use of targeted synthetic DMARDs (JAK inhibitors) and suggestions for a deescalating in case of achieving a sustained remission. Methotrexate still plays the central role at the beginning of the treatment and as a combination partner in the further treatment course. When treatment response to methotrexate is inadequate, either switching to or combining with another conventional synthetic DMARD is an option in the absence of unfavourable prognostic factors. Otherwise biologic or targeted synthetic DMARDs are recommended according to the algorithm. Rules for deescalating treatment with glucocorticoids and-where applicable-DMARDs give support for the management of patients who have reached a sustained remission.

DISCUSSION

The new guidelines set up recommendations for RA treatment in accordance with the treat-to-target principle. Modern disease-modifying drugs, now including also JAK inhibitors, are available in an algorithm.

Predictors and the optimal duration of sustained remission in rheumatoid arthritis

OBJECTIVE

To determine predictors and optimal duration of sustained remission (SR) in patients with rheumatoid arthritis (RA).

METHODS

A total of 428 consecutive patients with RA visiting our clinic routinely between 2012 and 2013 were evaluated. Seventy seven of these patients in DAS28 remission were enrolled and followed up for 62.2 ± 9.9 months. Patients in remission ≥ 6 months (SR) and shorter (non: N-SR) were compared in terms of demographic-clinical data and the psychosocial factors. At enrollment, 1st and 5th years, patients in DAS28, SDAI, and Boolean remission were determined.

RESULTS

Sixty three patients were in SR and 14 in N-SR. Lower baseline DAS28 and HAQ scores, anti-CCP were positive predictors of SR. Although the presence of anxiety, depression, fibromyalgia, and fatigue were lower in the SR group, there was no significance. Patients in DAS28 remission (100%) at baseline reduced to 64% at 1st and 42.6% at 5th years. Patients satisfying SDAI and Boolean remission at these three visits were 49%, 44%, and 32.4% vs 41%, 28%, and 20.6%, respectively. If the duration of remission is defined as 6 months, the remission rates of SDAI at inclusion and fifth years' visits were similar but Boolean remission rates differed significantly and if it is accepted as ≥ 12 months, both the SDAI and Boolean remission rates were not different.

CONCLUSION

Low DAS28 and HAQ scores at baseline, anti-CCP were positive predictors of SR. Instead of 6 months, remission duration for ≥ 12 months would probably help us to predict SR independently from the chosen criteria; Boolean or SDAI.

Predictors of biologic-free disease control in patients with rheumatoid arthritis after stopping tumor necrosis factor inhibitor treatment

Background

The aim of this study was to identify predictors of prolonged disease control after discontinuation of tumor necrosis factor inhibitor (TNFi) treatment in patients with rheumatoid arthritis (RA).

Methods

Post-hoc analysis of 439 RA patients (67.3% rheumatoid factor positive) with longstanding RA in remission or with stable low disease activity, randomized to stopping TNFi treatment in the multicenter POET trial. Prolonged acceptable disease control was defined as not restarting TNFi treatment within 12 months after stopping. Baseline demographic and disease-related variables were included in univariate and multivariate logistic regression analysis for identifying predictors of relapse.

Results

One year after baseline, 220 patients (50.1%) had not restarted TNFi treatment. Use of an anti-TNF monoclonal antibody (versus a receptor antagonist, OR = 2.41; 95% CI: 1.58–3.67), ≤10 yrs. disease duration (OR = 2.15; 95% CI: 1.42–3.26) and low or moderate multi-biomarker disease activity (MBDA) scores (OR = 2.00; 95% CI: 1.10–3.64) at baseline were independently predictive of successful TNFi discontinuation (area under the receiver operating characteristic curve = 0.66; 95% CI: 0.61–0.71). Results were similar when using no physician-reported flare as the criterion. TNFi-free survival was significantly different for patient groups based on the number of predictors present, ranging from 21.4% of patients with no predictor present to 66.7% of patients with all three predictors present.

Conclusion

Patients using an anti-TNF monoclonal antibody, with shorter disease duration and low or moderate baseline MBDA score are most likely to achieve prolonged disease control after TNFi discontinuation.

Trial registration

Netherlands Trial Register NTR3112, 21 October 2011.

Electronic supplementary material

The online version of this article (10.1186/s41927-019-0071-x) contains supplementary material, which is available to authorized users.

ACPA-negative RA consists of subgroups: patients with high likelihood of achieving sustained DMARD-free remission can be identified by serological markers at disease presentation

Background

Disease-modifying antirheumatic drug (DMARD)-free remission, the sustained absence of synovitis after DMARD cessation, is increasingly achievable, especially in autoantibody-negative rheumatoid arthritis (RA). However, underlying mechanisms are unknown and patient subgroups that achieve this outcome are insufficiently characterized. We evaluated whether serological biomarkers at disease onset, as measured within the multi-biomarker disease activity (MBDA) score, are differently expressed in RA patients who achieve sustained DMARD-free remission.

Methods

Two hundred ninety-nine RA patients were evaluated for achievement of sustained DMARD-free remission during a median follow-up of 4.3 years. Twelve biomarkers, as included in the MBDA score, were determined from the serum obtained at disease onset. Patients were categorized as having a low (< 30), moderate (30–44) or high (> 44) score. Analyses were stratified for anti-citrullinated protein antibodies (ACPA) based under the assumption that ACPA-positive and ACPA-negative RA are different disease entities.

Results

Twenty percent achieved sustained DMARD-free remission. Overall, high MBDA scores were associated with achieving DMARD-free remission (high vs. low HR 3.8, 95% CI 1.2–12.2). Among ACPA-negative RA patients, moderate or high scores associated strongly with DMARD-free remission (moderate vs. low HR 9.4, 95% CI 1.2–72.9; high vs. low HR 9.7, 95% CI 1.3–71.1). This association was independent of age and other clinical factors (high vs. low HR 8.2, 95% CI 1.1–61.8). For ACPA-negative RA patients, the biomarkers C-reactive protein, serum amyloid A and matrix metalloproteinase-3 were individually associated with sustained DMARD-free remission. Among ACPA-positive RA patients, scores were not associated with DMARD-free remission.

Conclusions

ACPA-negative RA patients who achieved sustained DMARD-free remission after treatment withdrawal were characterized by moderate to high MBDA scores at diagnosis. This is the first evidence that ACPA-negative RA can be subdivided in clinically relevant subsets at disease onset using a protein profile.

Electronic supplementary material

The online version of this article (10.1186/s13075-019-1902-2) contains supplementary material, which is available to authorized users.

Assessing prognosis and prediction of treatment response in early rheumatoid arthritis: systematic reviews

BACKGROUND

Rheumatoid arthritis (RA) is a chronic, debilitating disease associated with reduced quality of life and substantial costs. It is unclear which tests and assessment tools allow the best assessment of prognosis in people with early RA and whether or not variables predict the response of patients to different drug treatments.

OBJECTIVE

To systematically review evidence on the use of selected tests and assessment tools in patients with early RA (1) in the evaluation of a prognosis (review 1) and (2) as predictive markers of treatment response (review 2).

DATA SOURCES

Electronic databases (e.g. MEDLINE, EMBASE, The Cochrane Library, Web of Science Conference Proceedings; searched to September 2016), registers, key websites, hand-searching of reference lists of included studies and key systematic reviews and contact with experts.

STUDY SELECTION

Review 1 - primary studies on the development, external validation and impact of clinical prediction models for selected outcomes in adult early RA patients. Review 2 - primary studies on the interaction between selected baseline covariates and treatment (conventional and biological disease-modifying antirheumatic drugs) on salient outcomes in adult early RA patients.

RESULTS

Review 1 - 22 model development studies and one combined model development/external validation study reporting 39 clinical prediction models were included. Five external validation studies evaluating eight clinical prediction models for radiographic joint damage were also included. c-statistics from internal validation ranged from 0.63 to 0.87 for radiographic progression (different definitions, six studies) and 0.78 to 0.82 for the Health Assessment Questionnaire (HAQ). Predictive performance in external validations varied considerably. Three models [(1) Active controlled Study of Patients receiving Infliximab for the treatment of Rheumatoid arthritis of Early onset (ASPIRE) C-reactive protein (ASPIRE CRP), (2) ASPIRE erythrocyte sedimentation rate (ASPIRE ESR) and (3) Behandelings Strategie (BeSt)] were externally validated using the same outcome definition in more than one population. Results of the random-effects meta-analysis suggested substantial uncertainty in the expected predictive performance of models in a new sample of patients. Review 2 - 12 studies were identified. Covariates examined included anti-citrullinated protein/peptide anti-body (ACPA) status, smoking status, erosions, rheumatoid factor status, C-reactive protein level, erythrocyte sedimentation rate, swollen joint count (SJC), body mass index and vascularity of synovium on power Doppler ultrasound (PDUS). Outcomes examined included erosions/radiographic progression, disease activity, physical function and Disease Activity Score-28 remission. There was statistical evidence to suggest that ACPA status, SJC and PDUS status at baseline may be treatment effect modifiers, but not necessarily that they are prognostic of response for all treatments. Most of the results were subject to considerable uncertainty and were not statistically significant.

LIMITATIONS

The meta-analysis in review 1 was limited by the availability of only a small number of external validation studies. Studies rarely investigated the interaction between predictors and treatment.

SUGGESTED RESEARCH PRIORITIES

Collaborative research (including the use of individual participant data) is needed to further develop and externally validate the clinical prediction models. The clinical prediction models should be validated with respect to individual treatments. Future assessments of treatment by covariate interactions should follow good statistical practice.

CONCLUSIONS

Review 1 - uncertainty remains over the optimal prediction model(s) for use in clinical practice. Review 2 - in general, there was insufficient evidence that the effect of treatment depended on baseline characteristics.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016042402.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Guidelines for biomarkers in autoimmune rheumatic diseases - evidence based analysis

Autoimmune rheumatic diseases are characterised by an abnormal immune system response, complement activation, cytokines dysregulation and inflammation. In last years, despite many progresses in managing these patients, it has been shown that clinical remission is reached in less than 50% of patients and a personalised and tailored therapeutic approach is still lacking resulting in a significant gap between guidelines and real-world practice. In this context, the need for biomarkers facilitating early diagnosis and profiling those individuals at the highest risk for a poor outcome has become of crucial interest. A biomarker generally refers to a measured characteristic which may be used as an indicator of some biological state or condition. Three different types of medical biomarkers has been suggested: i. mechanistic markers; ii. clinical disease markers; iii. therapeutic markers. A combination of biomarkers from these different groups could be used for an ideal more accurate diagnosis and treatment. However, although a growing body of evidence is focused on improving biomarkers, a significant amount of this information is not integrated on standard clinical care. The overarching aim of this work was to clarify the meaning of specific biomarkers during autoimmune diseases; their possible role in confirming diagnosis, predicting outcome and suggesting specific treatments.

The Clinical Value of Autoantibodies in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a highly heterogeneous syndrome in terms of clinical presentation, progression, and response to therapy. In such a complicated context, the identification of disease-related biomarkers would be undoubtedly helpful in assisting tailored approaches for every patient. Despite remarkable efforts, however, progress in new biomarker development and validation is dramatically slow. At present, none of the candidate genetic, cellular, or molecular biomarker has yet surpassed the clinical value of RA-specific autoantibodies, including rheumatoid factor (RF) and anti-citrullinated protein autoantibodies (ACPA). Rather, recent years have witnessed significant advancements in our understanding of the multiple roles that RF and ACPA play in RA pathophysiology. This has helped clarifying the mechanistic basis of the clinical associations of autoantibodies in RA. In this short review, we will briefly summarize the effector functions of RF and ACPA, and analyse how autoantibodies may help subclassifying RA patients in terms of clinical presentation and response to therapy.

Cost-effective Tapering Algorithm in Patients with Rheumatoid Arthritis: Combination of Multibiomarker Disease Activity Score and Autoantibody Status

OBJECTIVE

To analyze the effect of a risk-stratified disease-modifying antirheumatic drug (DMARD)-tapering algorithm based on multibiomarker disease activity (MBDA) score and anticitrullinated protein antibodies (ACPA) on direct treatment costs for patients with rheumatoid arthritis (RA) in sustained remission.

METHODS

The study was a posthoc retrospective analysis of direct treatment costs for 146 patients with RA in sustained remission tapering and stopping DMARD treatment, in the prospective randomized RETRO study. MBDA scores and ACPA status were determined in baseline samples of patients continuing DMARD (arm 1), tapering their dose by 50% (arm 2), or stopping after tapering (arm 3). Patients were followed over 1 year, and direct treatment costs were evaluated every 3 months. MBDA and ACPA status were used as predictors creating a risk-stratified tapering algorithm based on relapse rates.

RESULTS

RA patients with a low MBDA score (< 30 units) and negative ACPA showed the lowest relapse risk (19%), while double-positive patients showed high relapse risk (61%). In ACPA-negative and MBDA-negative (< 30 units), and ACPA or MBDA single-positive (> 30 units) groups, DMARD tapering appears feasible. Considering only patients without flare, direct costs for synthetic and biologic DMARD in the ACPA/MBDA-negative and single positive groups (n = 41) would have been €372,245.16 for full-dose treatment over 1 year. Tapering and stopping DMARD in this low-risk relapse group allowed a reduction of €219,712.03 of DMARD costs. Average reduction of DMARD costs per patient was €5358.83.

CONCLUSION

Combining MBDA score and ACPA status at baseline may allow risk stratification for successful DMARD tapering and cost-effective use of biologic DMARD in patients in deep remission as defined by the 28-joint count Disease Activity Score using erythrocyte sedimentation rate.

RHEUMATOID ARTHRITIS: THE PROBLEMS OF REMISSION AND THERAPY RESISTANCE

Rheumatoid arthritis (RA) is an immunoinflammatory (autoimmune) rheumatic disease of unknown etiology, which is characterized by chronic erosive arthritis and systemic visceral organ damage that results in early disability and shorter patient survival. Despite RA treatment advances associated with the design of novel drugs and the improvement of treatment strategies to achieve remission in many patients, there are still many theoretical and clinical problems concerning both the definition of the concept of remission, its characteristics and types and approaches to the optimum policy of symptomatic and pathogenetic drug therapy at different stages of the disease, the use of which will be able to rapidly induce and maintain remission in the long-term. Further investigations are needed to study the nature of heterogeneity of pathogenetic mechanisms of RA and approaches to early diagnosis, to improve methods for monitoring disease activity and biomarkers for the efficiency of and resistance to therapy and, finally, to develop differentiation therapy, including those related to a search for new therapeutic targets.

Proteomics in Chronic Arthritis-Will We Finally Have Useful Biomarkers?

PURPOSE OF REVIEW

Current technical advances enable the assessment of the complex changes in body fluid proteomes and thus allow for the discovery of biomarker signatures rather than just following differences of a single marker. In this review, we aim to summarize current approaches to discover and evaluate multi-biomarker panels for improved monitoring of chronic arthritis disease activity.

RECENT FINDINGS

Mass spectrometry and affinity proteomic methodologies have been used to identify biomarker panels in synovial fluid, serum, plasma, or urine of pediatric and adult chronic arthritis patients. Notably, despite the numerous efforts to develop new and better biomarker panels, very few have undergone extensive analytical and clinical validation and been adopted into routine use for patient benefit. There remains a significant gap between discovery of chronic arthritis biomarker signatures and their validation for clinical use.

The potential impact of monitoring disease activity biomarkers on rheumatoid arthritis outcomes and costs

Rheumatoid arthritis (RA) management requires monitoring of disease activity to determine course of treatment. Global assessments are used in clinical practice to determine RA disease activity. Monitoring disease activity via biomarkers may also help providers optimize biologic and nonbiologic drug use while decreasing overall drug spend by delaying use of expensive biologic therapies. By testing multiple biologic domains at the same time, a multibiomarker disease activity test may have utility in RA patient management, through improved intra- and inter-rater reliability. This report provides a comprehensive review of studies of objective measures, single biomarkers and multibiomarker disease activity tests as disease activity measures to decrease uncertainty in treatment decisions, and of biomarkers’ potential impact on economic and clinical outcomes of treatment choices.

Multi-biomarker disease activity score as a predictor of disease relapse in patients with rheumatoid arthritis stopping TNF inhibitor treatment

Objective

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.

Methods

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.

Results

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).

Conclusion

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.

Mental health, fatigue and function are associated with increased risk of disease flare following TNF inhibitor tapering in patients with rheumatoid arthritis: an exploratory analysis of data from the Optimizing TNF Tapering in RA (OPTTIRA) trial

Background

Tapering of anti-tumour necrosis factor (TNF) therapy appears feasible, safe and effective in selected patients with rheumatoid arthritis (RA). Depression is highly prevalent in RA and may impact on flare incidence through various mechanisms. This study aims to investigate if psychological states predict flare in patients' dose tapering their anti-TNF therapy.

Methods

This study is a post-hoc analysis of the Optimizing TNF Tapering in RA trial, a multicentre, randomised, open-label study investigating anti-TNF tapering in RA patients with sustained low disease activity. Patient-reported outcomes (Health Assessment Questionnaire, EuroQol 5-dimension scale, Functional Assessment of Chronic Illness Therapy fatigue scale (FACIT-F), 36-Item Short Form Survey (SF-36)) were collected at baseline. The primary outcome was flare, defined as an increase in 28-joint count Disease Activity Score (DAS28) ≥0.6 and ≥1 swollen joint. Discrete-time survival models were used to identify patient-reported outcomes that predict flare.

Results

Ninety-seven patients were randomised to taper their anti-TNF dose by either 33% or 66%. Forty-one patients flared. Higher baseline DAS28 score was associated with flare (adjusted HR 1.96 (95% CI 1.18 to 3.24), p=0.01). Disability (SF-36 physical component score), fatigue (FACIT-F) and mental health (SF-36 mental health subscale (MH)) predicted flare in unadjusted models. In multivariate analyses, only SF-36 MH remained a statistically significant predictor of flare (adjusted HR per 10 units 0.74 (95% CI 0.60 to 0.93), p=0.01).

Conclusions

Baseline DAS28 and mental health status are independently associated with flare in patients who taper their anti-TNF therapy. Fatigue and function also associate with flare but the effect disappears when adjusting for confounders. Given these findings, mental health and functional status should be considered in anti-TNF tapering decisions in order to optimise the likelihood of success.

Trial registration numbers

EudraCT Number: 2010-020738-24; ISRCTN: 28955701; Post-results.