Prediction of primary non-response to methotrexate therapy using demographic, clinical and psychosocial variables: results from the UK Rheumatoid Arthritis Medication Study (RAMS)

Longitudinal effects of affective distress on disease outcomes in rheumatoid arthritis: a meta-analysis and systematic review

Patients with rheumatoid arthritis have higher rates of mental health conditions compared to the general population. It is believed that affective distress and rheumatoid arthritis have a bi-directional relationship. This review will examine the associations between affective distress and rheumatoid arthritis outcomes over time. Several disease outcomes are included covering disease activity, function, and disability to provide a broad picture of the various ways patients are impacted. A quality assessment was also conducted. There were 71 studies included in the review. Three measures (disease activity, disability, and mortality) had enough data to complete meta-analyses of odds ratios or hazard ratios. The outcomes included were disease activity, tender joint count, swollen joints, pain, physician global assessment, patient global assessment, physical disability, acute phase reactants, stiffness, fatigue, work disability, and mortality. Numerous measures were included for most of the outcomes due to the variability across studies of measures used. Patients with affective distress had lower rates of remission according to the DAS-28, greater disability, and higher mortality. All of the outcomes covered had studies with mixed results, but swollen joint count, tender joint count, patient global assessment, and physician global assessment had the strongest evidence that they were associated with mental health longitudinally. The relationships between affective distress and disease outcomes are complex and vary depending on the measures. Overall, the effects fade over time. It is important for clinicians to be aware of the differing manifestations of the relationship between affective distress and rheumatoid arthritis outcomes.

The fibroid phenotype of biological naïve patients with rheumatoid arthritis are less likely to respond to anti-IL-6R treatment

Type III collagen gene expression is upregulated in the synovium of patients with rheumatoid arthritis (RA) presenting the fibroid phenotype. The soluble type III collagen formation biomarker, PRO-C3, is known to measure fibrogenesis in fibrotic diseases. In this exploratory study, we aimed to investigate the association between fibrogenesis (PRO-C3) and the disease- and treatment response in patients with RA. We measured PRO-C3 in subsets of two clinical trials assessing the effect of the anti-interleukin-6 (IL-6) receptor treatment tocilizumab (TCZ) as monotherapy or polytherapy with methotrexate. PRO-C3 levels had weak or very weak correlations with the clinical parameters (Spearman's). However, when the patients were divided into Disease Activity Score-28 groups characterized by the erythrocyte sedimentation rate (DAS28-ESR), there was a statistical difference between the PRO-C3 levels of the different groups (p < 0.05). To determine the response in relation to PRO-C3, a cut-off based on PRO-C3 levels and patients in remission (DAS28-ESR ≤ 2.6) was identified. This showed that a reduction in PRO-C3 after treatment initiation was associated with decreased DAS28-ESR and a higher response rate in patients with low PRO-C3 levels than in those with high PRO-C3 levels. This indicates that a fibrotic component affects the responsiveness of patients.

Proteomics analyses of human plasma reveal triosephosphate isomerase as a potential blood marker of methotrexate resistance in rheumatoid arthritis

OBJECTIVE

The objective of this study was to assess differentially expressed blood proteins between patients with active RA and patients in remission after MTX treatment, with the aim of identifying a biomarker of MTX resistance (MTXR).

METHODS

Two populations of RA patients treated with a stable dose of s.c. MTX for at least 3 months were constituted according to the DAS28: remission (DAS28 < 2.6; n = 24) and active disease (DAS28 > 3.2; n = 32). The two groups of RA patients were homogeneous regarding their epidemiological characteristics, except for the duration of treatment, which was longer in the remission group. After collection of a blood sample, plasma protein digestion was performed, followed by untargeted proteomics analysis. Then, a targeted analysis was performed to confirm the results of the untargeted approach.

RESULTS

Untargeted proteomics analysis revealed eight plasma proteins that were differentially expressed between the two groups of patients. Among them, triosephosphate isomerase (TPI-1) and glucose-6-phosphate isomerase (GPI), which are main actors in glycolysis, were found down-regulated in the active group. This result was confirmed for TPI-1 in the targeted proteomics analysis.

CONCLUSION

A first step was achieved in the search for biomarkers of MTXR, with the identification of two actors in glycolysis (TPI-1 and GPI). The next step will be to confirm these results in a larger cohort, including samples from treatment-naive patients, to assess the predictive potential of these protein markers.

Associations of gender with sexual functioning, loneliness, depression, fatigue and physical function amongst patients suffering from rheumatoid arthritis with a particular focus on methotrexate usage

There is a lack of knowledge regarding methotrexate (MTX) usage in patients with rheumatoid arthritis (RA) and its possible links with gender, disease characterization and sexual functioning, loneliness, fatigue and depression. We, therefore, investigated the associations of gender with physical function, fatigue, depression, loneliness and sexual functioning with a particular focus on MTX usage. A cross-sectional study design was used. Inclusion criteria were RA diagnosis, age above 18 years and available data on MTX treatment 1 year after diagnosis. Data consisted of responses from validated questionnaires regarding physical function, fatigue, depression, loneliness and sexual functioning combined with evaluations from medical records. Data were analysed with linear regression models comparing numerical outcome measures between male and female patients and between MTX users and MTX non-users. Amongst 286 patients with RA (69 men and 217 women), 67.8% were MTX users 1 year after diagnosis. Comparing women and men, both overall and within subgroups of MTX usage, we found significantly more adverse outcomes for women than men in physical functioning at diagnosis and in sexual function, depression, fatigue and physical functioning at enrolment in the study. Gender differences were also present when comparing MTX users with MTX non-users divided by gender. There were only significant differences in the HAQ and loneliness scores when comparing MTX users with MTX non-users. Women with RA had more negative outcomes measured by the selected PROMs compared to men with RA, both overall and in subgroups of users and non-users of MTX. These findings call for sharpened attention to the importance of gender in the treatment and care of patients with RA, as well as in future clinical research.

The impact of folate pathway variants on the outcome of methotrexate therapy in rheumatoid arthritis patients

BACKGROUND

There are currently no validated criteria that entirely explain or predict response to methotrexate (MTX) treatment in rheumatoid arthritis (RA). We tried to identify the connection between three variants (RFC1 G80A (rs1051266), TYMS 2R/3R (rs34743033), and ATIC C347G (rs2372536)) in the folate pathway of MTX metabolism and the response to MTX monotherapy in a cohort of RA cases.

METHODS

A prospective study on 100 RA patients on MTX monotherapy was performed. Disease activity was measured at the start of treatment and 6 months after treatment with MTX. The patients were then split into two groups: those who responded to the treatment and those who did not. The molecular genetic study for the RFC1 (G80A) variant was employed via the PCR-restriction fragment length polymorphism (PCR-RFLP) technique, the ATIC (C347G) variant was performed using TaqMan allelic discrimination real-time PCR, and the tandem repeat sequences of TYMS (2R/3R) were amplified by conventional PCR and detected by agarose gel electrophoresis.

RESULTS

The genotype distribution of RFC-1 (G80A) showed significant variations among non-responders and responders in the recessive genetic model. A significant difference was found in TYMS (2R/3R) in the dominant and heterozygous genetic models. However, ATIC (C347G) genotype frequency did not exhibit substantial link with drug response in all genetic models. Furthermore, the genotype and allele rates of the analyzed variants did not show any significant association with adverse events in all genetic models.

CONCLUSION

The 80AA genotype of RFC-1 G80A and the 2R/3R or 3R/3R genotypes of TYMS 2R/3R are more vulnerable to the good consequences of MTX therapy. Key Points • Current recommendations support the gold standard role of MTX as a first-line monotherapy for RA patients. However, up to 40% of RA patients do not respond or exhibit partial response to MTX. • Persistent disease activity due to treatment unresponsiveness will affect the long-term outcomes in RA patients. • We aimed, through molecular genetic study, to identify the connection between three variants in the folate pathway of MTX metabolism and the response to methotrexate monotherapy in a cohort of RA patients.

Developing and externally validating multinomial prediction models for methotrexate treatment outcomes in patients with rheumatoid arthritis: results from an international collaboration

OBJECTIVES

In rheumatology, there is a clinical need to identify patients at high risk (>50%) of not responding to the first-line therapy methotrexate (MTX) due to lack of disease control or discontinuation due to adverse events (AEs). Despite this need, previous prediction models in this context are at high risk of bias and ignore AEs. Our objectives were to (i) develop a multinomial model for outcomes of low disease activity and discontinuing due to AEs 6 months after starting MTX, (ii) update prognosis 3-month following treatment initiation, and (iii) externally validate these models.

STUDY DESIGN AND SETTING

A multinomial model for low disease activity (submodel 1) and discontinuing due to AEs (submodel 2) was developed using data from the UK Rheumatoid Arthritis Medication Study, updated using landmarking analysis, internally validated using bootstrapping, and externally validated in the Norwegian Disease-Modifying Antirheumatic Drug register. Performance was assessed using calibration (calibration-slope and calibration-in-the-large), and discrimination (concordance-statistic and polytomous discriminatory index).

RESULTS

The internally validated model showed good calibration in the development setting with a calibration-slope of 1.01 (0.87, 1.14) (submodel 1) and 0.83 (0.30, 1.34) (submodel 2), and moderate discrimination with a c-statistic of 0.72 (0.69, 0.74) and 0.53 (0.48, 0.59), respectively. Predictive performance decreased after external validation (calibration-slope 0.78 (0.64, 0.93) (submodel 1) and 0.86 (0.34, 1.38) (submodel 2)), which may be due to differences in disease-specific characteristics and outcome prevalence.

CONCLUSION

We addressed previously identified methodological limitations of prediction models for outcomes of MTX therapy. The multinomial approach predicted outcomes of disease activity more accurately than AEs, which should be addressed in future work to aid implementation into clinical practice.

Identification of gene expression biomarkers to predict clinical response to methotrexate in patients with rheumatoid arthritis

OBJECTIVES

To identify biomarkers at the gene expression level to predict response to methotrexate (MTX) in patients with rheumatoid arthritis (RA).

METHODS

MTX-naïve patients with RA were started on MTX and followed up over three months. The disease activity score 28 (DAS28) was used to classify patients into responders and non-responders. Genome-wide gene expression analysis was performed in CD4 + and CD14 + mononuclear cells sampled from whole blood at baseline to identify differentially expressed genes in responders versus non-responders. Gene selection methods and prediction modelling obtained the most relevant differentially expressed genes. A logistic regression prediction model was subsequently constructed and validated via bootstrapping. The area under the receiver operating characteristic (AUC) curve was calculated to judge model quality.

RESULTS

Seventy-nine patients with RA (53.4 ± 13.9 years, 74.7% females) were enrolled, and 70 finished the study with a documented treatment EULAR response (77.1% responders). Forty-six differentially expressed genes were found. The most promising genes were KRTAP4-11, LOC101927584, and PECAM1 in CD4 + cells and PSMD5 and ID1 in CD14 + cells. The final prediction model using these genes reached an AUC of 90%; the validation set's AUC was 82%.

CONCLUSIONS

Our prediction model constructed via genome-wide gene expression analysis in CD4 + and CD14 + mononuclear cells yielded excellent predictions. Our findings necessitate confirmation in other cohorts of MTX-naïve RA patients. Especially if used in conjunction with previously identified clinical and laboratory (bio)markers, our results could help predict response to MTX in RA to guide treatment decisions. Key Points • Patients with rheumatoid arthritis may or may not respond to treatment with methotrexate, which is the recommended first-line drug in guidelines around the world. • In non-responders, valuable time is lost until second-line treatments are started. • This study aimed at predicting response to methotrexate by identifying differentially expressed genes from peripheral blood samples. • The final prediction model yielded excellent prognostic values, but validation in other cohorts is necessary to corroborate these findings.

The effect of smoking on response to methotrexate in rheumatoid arthritis patients: A systematic review and meta-analysis

OBJECTIVES

In the current study, we aimed to investigate the effect of smoking on inadequate response to methotrexate (MTX-IR) in rheumatoid arthritis (RA) patients.

METHODS

We searched PubMed, Embase, and Web of Science until 6 June 2022. Observational or interventional studies investigating MTX-IR in RA patients based on smoking status were included. Two independent reviewers assessed the risk of bias and the certainty of the evidence using the Risk of Bias in Nonrandomized Studies-of Interventions and Grades of Recommendation, Assessment, Development, and Evaluation tools, respectively.

RESULTS

We included 23 studies in the systematic review and 13 in the meta-analysis. Of the 13 included studies, 6 had a moderate risk, 3 had a serious risk, and 4 had a critical risk of bias. The overall random-effect meta-analysis suggested that smokers were 58% more likely to be MTX-IR when compared with nonsmokers [odds ratio (OR) 1.58, 95% confidence interval 1.21-2.06; P = .001; I2 = 69.3%]. The common-effect meta-analysis of the adjusted ORs demonstrated an overall OR of 2.69 (1.88-3.83; P < .001; I2 = 27.1%).

CONCLUSIONS

The current study showed that smoking is a significant predictor of MTX-IR, especially in disease-modifying antirheumatic drug-naïve early RA patients, as most of the included studies in the meta-analysis consisted of this population.

Methotrexate Polyglutamates Exposure - Response Modeling in a Large Cohort of Rheumatoid Arthritis Patients Starting Methotrexate

Methotrexate polyglutamates (MTX-PG) concentrations in red blood cells (RBCs) have been suggested as a biomarker of response in patients with rheumatoid arthritis (RA) receiving low-dose MTX therapy. We investigated the association and interpatient variability between RBC-MTX-PG3-5 -exposure and response in patients with RA starting MTX. Data of three prospective cohorts were available. The relationship between exposure and Disease Activity Score in 28 joints (DAS28) was analyzed using a population pharmacokinetic-pharmacodynamic model. Relevant covariates were tested using full covariate modeling and backward elimination. From 395 patients, 3,401 MTX-PG concentrations and 1,337 DAS28 measurements were available between 0 and 300 days after MTX treatment onset. The developed model adequately described the time course of MTX-PG3-5 and DAS28. The median MTX-PG3-5 level at month 1 was 30.9 nmol/L (interquartile range (IQR): 23.6-43.7; n = 41) and at month 3: 69.3 nmol/L (IQR: 17.9-41.2; n = 351). Clearance of MTX-PG3-5 from RBCs was 28% lower (95% confidence interval (CI): 23.6-32.8%) in a woman and 10% lower (95% CI: 7.7-12.4%) in a 65-year-old compared with a 35-year-old patient. MTX-PG3-5 concentrations associated with DAS28: half-maximal effective concentration (EC50 ) was 9.14 nmol/L (95% CI: 4.2 nmol/L-14.1 nmol/L). EF at 80% (EC80 ) above 47 nmol/L was regarded as the optimal response. Independent of the MTX-PG 3-5 - response association, co-administration of disease-modifying antirheumatic drugs and corticosteroids improved response (additive effect on maximum effect (Emax )), whereas smoking, high body mass index and low albumin decreased Emax . In patients with RA starting MTX, RBC-MTX-PG3-5 was associated with clinical response. A dose increase is suggested when MTX-PG3-5 at month 1 is below 9.15 nmol/L, continued with the same dose when the concentration is above 47 nmol/L, and consider other treatment options above 78 nmol/L from 3 months onwards.

Detecting and exploiting the circadian clock in rheumatoid arthritis

Over the past four decades, research on 24-h rhythms has yielded numerous remarkable findings, revealing their genetic, molecular, and physiological significance for immunity and various diseases. Thus, circadian rhythms are of fundamental importance to mammals, as their disruption and misalignment have been associated with many diseases and the abnormal functioning of many physiological processes. In this article, we provide a brief overview of the molecular regulation of 24-h rhythms, their importance for immunity, the deleterious effects of misalignment, the link between such pathological rhythms and rheumatoid arthritis (RA), and the potential exploitation of chronobiological rhythms for the chronotherapy of inflammatory autoimmune diseases, using RA as an example.

3,3-dimethyl-1-butanol and its metabolite 3,3-dimethylbutyrate ameliorate collagen-induced arthritis independent of choline trimethylamine lyase activity

Previous studies have identified significant alterations in intestinal carnitine metabolism in mice with collagen-induced arthritis (CIA), potentially linking bacterial dysbiosis with autoimmunity. Bacterial trimethylamine (TMA) lyases metabolize dietary carnitine to TMA, which is oxidized in the liver to trimethylamine-N-oxide (TMAO). TMAO is associated with inflammatory diseases, such as atherosclerosis, whose immunologic processes mirror that of rheumatoid arthritis (RA). Therefore, we investigated the possibility of ameliorating CIA by inhibiting TMA lyase activity using 3,3-dimethyl-1-butanol (DMB) or fluoromethylcholine (FMC). During CIA, mice were treated with 1% vol/vol DMB, 100mg/kg FMC, or vehicle. DMB-treated mice demonstrated significant (>50%) reduction in arthritis severity compared to FMC and vehicle-treated mice. However, in contrast to FMC, DMB treatment did not reduce cecal TMA nor circulating TMAO concentrations. Using gas chromatography, we confirmed the effect of DMB is independent of TMA lyase inhibition. Further, we identified a novel host-derived metabolite of DMB, 3,3-dimethyl-1-butyric acid (DMBut), which also significantly reduced disease and proinflammatory cytokines in CIA mice. Altogether, our study suggests that DMB the immunomodulatory activity of DMB and/or its metabolites are protective in CIA. Elucidating its target and mechanism of action may provide new directions for RA therapeutic development.

Inappropriate treatment response to DMARDs: A pathway to difficult-to-treat rheumatoid arthritis

In recent years, difficult-to-treat rheumatoid arthritis (D2T RA) has attracted significant attention from rheumatologists due to its poor treatment response and the persistent symptoms or signs experienced by patients. The therapeutic demands of patients with D2T RA are not properly met due to unclear pathogenic causes and a lack of high-quality data for current treatment options, creating considerable management difficulties with this patient population. This review describes the clinical challenges associated with disease-modifying antirheumatic drugs (DMARDs) and explores contributing factors associated with inappropriate response to DMARDs that may lead to D2T RA and related immunological dysregulation. It is now understood that D2T RA is a highly heterogeneous pathological status that involves multiple factors. These factors include but are not limited to genetics, environment, immunogenicity, comorbidities, adverse drug reactions, inappropriate drug application, poor adherence, and socioeconomic status. Besides, these factors may manifest in the selection and utilization of specific DMARDs, either individually or in combination, thereby contributing to inadequate treatment response. Finding these variables may offer hints for enhancing DMARD therapy plans and bettering the condition of D2T RA patients.

Age, Sex, Metabolic and Pharmacologic Factors May Predict Nonresponse Status to Rheumatoid Arthritis Therapies

BACKGROUND/AIM

A real challenge for patients with rheumatoid arthritis (RA) and rheumatologists is primary nonresponse status (PNRS) or secondary nonresponse status (SNRS) to various therapies. Despite their detrimental influence on patient life quality, PNRS and SNRS have no accurate definition and no early predictive criteria for their development exist. Patients with RA under 40 years of age are rare, hence PNRS and SNRS data for this age group are scarce. This study examined the PNRS and SNRS according to sex, age, BMI, therapy type, and duration.

PATIENTS AND METHODS

Retrospectively, 115 patients with RA having PNRS and/or SNRS were stratified by age (22-39, 40-59, and 60-81). The association between body mass index (BMI), proinflammatory cytokines inhibitors, JAK inhibitors, and TNF-alpha inhibitors, sex, age, and PNRS and SNRS was examined.

RESULTS

All three proinflammatory cytokine inhibitors (rituximab, tocilizumab, and abatacept) were associated with PNRS and SNRS in women with a high BMI aged 40-59 years. Abatacept-related PNRS and SNRS was significant in women with normal BMI aged 60-81 years. Adalimumab, infliximab, and golimumab affected SNRS differently in women with normal BMI aged 22-39 years and women with high BMI aged 60-81 years. Etanercept and infliximab were associated with SNRS status in men with high-BMI aged 40-59 years.

CONCLUSION

PNRS and SNRS development in patients with RA is significantly influenced by age, sex, and BMI, but most importantly is closely and differentially related to therapy type and duration.

Factors influencing prescribing the first add-on disease-modifying antirheumatic drugs in patients initiating methotrexate for rheumatoid arthritis

Background

Advances in Disease-Modifying Antirheumatic Drugs (DMARDs) have expanded the treatment landscape for Rheumatoid Arthritis (RA). Guidelines recommend adding either conventional synthetic (cs), biologic (b), or targeted synthetic (ts) DMARDs to methotrexate (MTX) for managing RA. Limited evidence exists regarding the factors that contribute to adding a DMARD agent to the MTX regimen. This study examined the factors associated with adding the first DMARD in RA patients initiating MTX.

Methods

This retrospective cohort study utilized the MarketScan data (2012-2014) involving adults (aged ≥18) with RA initiating an MTX (index date) between Jul 1, 2012 and Dec 30, 2013, and with continuous enrollment for the 6-month pre-index period. The combination therapy users received the first treatment addition of DMARD starting from day 30 after the index MTX over one year period. The study focused on the addition of csDMARDs, Tumor Necrosis Factor Inhibitors (TNFi) bDMARDs, non-TNFi bDMARDs, or tsDMARDs. Baseline covariates were measured in the 6-month pre-index and grouped into predisposing, enabling, and need factors, as per the Andersen Behavior Model. Multivariable logistic regression examined the factors associated with the addition of TNFi compared to adding a csDMARD. An additional regression model evaluated the factors associated with adding any biologic (combining TNFi and non-TNFi biologics).

Results

Among 8350 RA patients starting MTX, 31.92% (n = 2665) initiated any DMARD within the 1-year post-index period. Among RA patients initiating a DMARD prescription after starting MTX, 945 (11.32%) received combination therapy with treatment addition of a DMARD to MTX regimen; majority added TNFi (550, 58%), followed by csDMARD (352, 37%); non-TNF biologic (40, 4%), or tsDMARD (3, 0.3%). The tsDMARD group was limited and was not included for further analysis. The multivariable model found Preferred Provider Organization insurance coverage (odds ratio [OR], 1.43; 95% confidence interval (CI), 1.06-1.93), chronic pulmonary disease (OR, 1.98; 95% CI, 1.14-3.44), liver disease (OR, 5.24; 95% CI, 1.77-15.49), and Elixhauser score (OR, 0.91; 95% CI, 0.86-0.97) were significantly associated with the addition of TNF-α inhibitors. The separate multivariable model additionally found that patients from metropolitan areas (OR, 1.50; 95% CI, 1.04-2.16) were positively associated with adding any biological agent.

Conclusions

TNFi are often added to MTX for managing RA. Enabling and need factors contribute to the prescribing of a TNFi add-on therapy in RA. Future research should examine the impact of these combination therapies on RA management.

DNA Methylation Signatures of Response to Conventional Synthetic and Biologic Disease-Modifying Antirheumatic Drugs (DMARDs) in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a complex condition that displays heterogeneity in disease severity and response to standard treatments between patients. Failure rates for conventional, target synthetic, and biologic disease-modifying rheumatic drugs (DMARDs) are significant. Although there are models for predicting patient response, they have limited accuracy, require replication/validation, or for samples to be obtained through a synovial biopsy. Thus, currently, there are no prediction methods approved for routine clinical use. Previous research has shown that genetics and environmental factors alone cannot explain the differences in response between patients. Recent studies have demonstrated that deoxyribonucleic acid (DNA) methylation plays an important role in the pathogenesis and disease progression of RA. Importantly, specific DNA methylation profiles associated with response to conventional, target synthetic, and biologic DMARDs have been found in the blood of RA patients and could potentially function as predictive biomarkers. This review will summarize and evaluate the evidence for DNA methylation signatures in treatment response mainly in blood but also learn from the progress made in the diseased tissue in cancer in comparison to RA and autoimmune diseases. We will discuss the benefits and challenges of using DNA methylation signatures as predictive markers and the potential for future progress in this area.

Machine learning identifies a profile of inadequate responder to methotrexate in rheumatoid arthritis

OBJECTIVES

Around 30% of patients with RA have an inadequate response to MTX. We aimed to use routine clinical and biological data to build machine learning models predicting EULAR inadequate response to MTX and to identify simple predictive biomarkers.

METHODS

Models were trained on RA patients fulfilling the 2010 ACR/EULAR criteria from the ESPOIR and Leiden EAC cohorts to predict the EULAR response at 9 months (± 6 months). Several models were compared on the training set using the AUROC. The best model was evaluated on an external validation cohort (tREACH). The model's predictions were explained using Shapley values to extract a biomarker of inadequate response.

RESULTS

We included 493 therapeutic sequences from ESPOIR, 239 from EAC and 138 from tREACH. The model selected DAS28, Lymphocytes, Creatininemia, Leucocytes, AST, ALT, swollen joint count and corticosteroid co-treatment as predictors. The model reached an AUROC of 0.72 [95% CI (0.63, 0.80)] on the external validation set, where 70% of patients were responders to MTX. Patients predicted as inadequate responders had only 38% [95% CI (20%, 58%)] chance to respond and using the algorithm to decide to initiate MTX would decrease inadequate-response rate from 30% to 23% [95% CI: (17%, 29%)]. A biomarker was identified in patients with moderate or high activity (DAS28 > 3.2): patients with a lymphocyte count superior to 2000 cells/mm3 are significantly less likely to respond.

CONCLUSION

Our study highlights the usefulness of machine learning in unveiling subgroups of inadequate responders to MTX to guide new therapeutic strategies. Further work is needed to validate this approach.

Rhodiola rosea L. Extract, a Known Adaptogen, Evaluated in Experimental Arthritis

Rhodiola rosea L. extract (RSE) is mostly known for its adaptogen properties, but not for its antiarthritic activities, therefore monotherapy and combination with low-dose methotrexate (MTX) was studied. The collagen-induced arthritis (CIA) model was used to measure the functional score, and the change in hind paw volume (HPV). Both parameters had significant antiarthritic effects. Based on these preliminary results, an adjuvant arthritis (AA) model was further applied to assess another parameters. The experiment included these animal groups: healthy controls, untreated AA, AA administered with RSE (150 mg/kg b.w. daily, p.o.), AA administered by MTX (0.3 mg/kg b.w. twice a week, p.o.), and AA treated with the combination of RSE+MTX. The combination of RSE+MTX significantly reduced the HPV and increased the body weight. The combination significantly decreased HPV when compared to MTX monotherapy. The plasmatic levels of inflammatory markers (IL-6, IL-17A, MMP-9 and CRP) were significantly decreased by MTX+RSE treatment. The RSE monotherapy didn't influence any of the inflammatory parameters studied. In CIA, the RSE monotherapy significantly decreased the arthritic parameters studied. In summary, the combination of RSE and sub-therapeutic MTX was significantly effective in AA by improving inflammatory and arthritic parameters.

Therapeutic drug monitoring of disease-modifying antirheumatic drugs in circulating leukocytes in immune-mediated inflammatory diseases

The treatment of immune-mediated inflammatory diseases (IMIDs) is one of the main challenges of modern medicine. Although a number of disease-modifying antirheumatic drugs (DMARDs) are available, there is wide variability in clinical response to treatment among individuals. Therapeutic drug monitoring (TDM) has been proposed to optimize treatment; however, some patients still experience unsatisfactory outcomes, although the blood concentrations of drugs in these patients remain in the therapeutic range. One possible reason for this is that the conventional samples (e.g., whole blood or plasma) used in TDM may not accurately reflect drug concentrations or concentrations of their metabolites at the target site. Hence, more refined TDM approaches to guide clinical decisions related to dose optimization are necessary. Circulating leukocytes or white blood cells have a critical role in driving the inflammatory process. They are recruited to the site of injury, infection and inflammation, and the main target of small molecule DMARDs is within immune cells. Given this, assaying drug concentrations in leukocytes has been proposed to be of possible relevance to the interpretation of outcomes. This review focuses on the clinical implications and challenges of drug monitoring of DMARDs in peripheral blood leukocytes from therapeutic or toxicological perspectives in IMIDs.

IFABP2 as a new prognostic biomarker for secondary non-response in rheumatoid arthritis

BACKGROUND

Increased intestinal permeability promotes the translocation of bacterial products from the local microbiome to the circulation, inducing inflammation and increasing clinical activity in rheumatoid arthritis (RA). This study evaluates whether intestinal fatty acid binding protein 2 (IFABP2) serum levels are prognostic biomarkers of non-response to conventional synthetic disease-modifying antirheumatic drug therapy (csDMARDs) in RA.

METHODS

The therapeutic schemes administered to 60 women with RA for at least 18 months were assessed retrospectively, and the treatment response was classified according to the change in DAS28-ESR over time. Serum levels of IFABP2 and TNF-α were determined by ELISA. Receiver operating characteristics (ROC) curve analysis and logistic regression models were used to assess the predictive value and the association of IFABP2 with the non-responder phenotype in RA patients.

RESULTS

Eleven women had a responder phenotype, 23 had a primary non-responder phenotype, and 26 had a secondary non-responder phenotype. Secondary non-responders showed higher DAS28-ESR (P = 0.009) and higher IFABP2 serum levels compared to the responder group (P = 0.023) and the primary non-responder group (P = 0.018). IFABP2 serum levels were positively correlated with chloroquine dose (r = 0.581, P = 0.007) and negatively correlated with total cholesterol (r = -0.456, P = 0.019) in secondary non-responders. The area under the curve (AUC) value of IFABP2 for predicting secondary non-response was 0.736, and IFABP2 serum levels > 9.311 ng/mL were associated with secondary non-response to csDMARDs (OR = 6.00, P = 0.003).

CONCLUSION

IFABP2 serum levels are potentially a new biomarker predictive of secondary non-response to csDMARDs in RA, although our findings should be validated externally and in a larger cohort.

Genome-wide Association Study of Methotrexate-Induced Liver Injury in Rheumatoid Arthritis Patients

Hepatotoxicity is a serious adverse drug reaction related to methotrexate (MTX). However, the cause of drug-induced liver injury (DILI) is still unclear and unpredictable. Genetic risk factors may predispose for MTX-DILI. Therefore, we conducted a nested case-control genome-wide association study to explore genetic risk factors associated with MTX-DILI. Seven international groups contributed blood samples and data of patients with rheumatoid arthritis who used MTX. MTX-DILI was defined as an alanine aminotransferase (ALT) level of at least three times the upper limit of normal (ULN), to increase contrast controls ALT levels did not raise above two times the ULN. Per study site, control subjects and patients with MTX-DILI (ratio 3:1) were matched for age, gender, and duration of MTX use. Patients were genotyped using Illumina GSA MD-24v1-0 and data were imputed using the 1000 Genomes reference panel. Single-nucleotide polymorphisms (SNPs) were analyzed using an additive genetic model, corrected for sex, country, and age. A P-value of ≤ 5 × 10^-8 was considered significant, whereas a  P-value of ≤ 5 × 10^-6 was considered suggestive. A total of 108 MTX-DILI cases and 311 controls were included for association analysis. None of the SNPs were significantly associated with MTX-DILI. However, we found seven suggestive genetic variants associated with MTX-DILI (P-values 7.43 × 10^-8 to 4.86 × 10^-6 ). Of those, five SNPs were in the intronic protein-coding regions of FTCDNL1, BCOR, FGF14, RBMS3, and PFDN4/DOK5. Investigation of candidates SPATA9 (rs72783407), PLCG2 (rs60427389), RAVER2 (rs72675408), JAK1 (rs72675451), PTPN2 (rs2476601), MTHFR C677T (rs1801133), and into the HLA region did not show significant findings. No genetic variants associated with MTX-DILI were found, whereas suggestive SNPs need further investigation.

Rheumatoid arthritis: advances in treatment strategies

Rheumatoid arthritis (RA) is characterised by severe joint and bone damage due to heightened autoimmune response at the articular sites. Worldwide annual incidence and prevalence rate of RA is 3 cases per 10,000 population and 1%, respectively. Several genetic and environmental (microbiota, smoking, infectious agents) factors contribute to its pathogenesis. Although convention treatment strategies, predominantly Disease Modifying Anti Rheumatic Drugs (DMARDs) and Glucocorticoids (GC), are unchanged as the primary line of treatment; novel strategies consisting of biological DMARDs, are being developed and explored. Personalized approaches using biologicals targetspecific pathways associated with disease progression. However, considering the economic burden and side-effects associated with these, there is an unmet need on strategies for early stratification of the inadequate responders with cDMARDs. As RA is a complex disease with a variable remission rate, it is important not only to evaluate the current status of drugs in clinical practice but also those with the potential of personalised therapeutics. Here, we provide comprehensive data on the treatment strategies in RA, including studies exploring various combination strategies in clinical trials. Our systematic analysis of current literature found that conventional DMARDs along with glucocorticoid may be best suited for early RA cases and a combination of conventional and targeted DMARDs could be effective for treating seronegative patients with moderate to high RA activity. Clinical trials with insufficient responders to Methotrexate suggest that adding biologicals may help in such cases. However, certain adverse events associated with the current therapy advocate exploring novel therapeutic approaches such as gene therapy, mesenchymal stem cell therapy in future.

The prevalence of rheumatoid arthritis in Western Australia

BACKGROUND

Rheumatoid arthritis (RA) is the most common form of autoimmune arthritis, but the prevalence in Australia is unknown. We estimated RA period prevalence and identified factors associated with frequent RA hospitalisations, using linked administrative health and state-specific Australian Pharmaceutical Benefits Scheme (PBS) datasets in Western Australia (WA) from 1995 to 2014.

METHODS

This was a longitudinal population-based cohort study using two independent datasets to identify prevalent RA patients. RA prevalence was calculated per 1000 hospital separations and biological therapy users. RA patients were identified in the WA linked health dataset using ICD codes 714.0-714.9 and M05.00-M06.99. Dispensing data on biological therapy for RA were obtained from PBS records and converted to defined daily doses /1000 population/day. Multivariable logistic regression was used to analyse factors associated with frequent RA hospitalisations (> 2/year), controlling for sex, age, and geographic locations. Potential interactions were assessed using logistic regression in a stepwise approach.

RESULTS

A total of 17,125 RA patients had 50,353 hospital separations between 1995 and 2014, averaging three hospitalisations per patient over 20 years. The RA period prevalence was 3.4 per 1000 separations (0.34%; 95% CI 0.33-0.34), while the RA period prevalence based on biological therapy use was 0.36% (95% CI 0.35-0.37). The corrected RA prevalence based on biological therapy usage was 0.36% (95% CI 0.35-0.37) for the 2005-2009 and increased to 0.72% (95% CI 0.70-0.74) in 2010-2014 period. Associated factors for frequent RA hospitalisations were being female [1.21 (95% CI 1.15-1.26)], aged 60-69 years [4.45 (95% CI 3.74-5.30)], living in rural areas [1.12 (95% CI 1.02-1.24)]. The odd ratio of interaction between these associated factors was 1.34 (95% CI 1.16-1.55).

CONCLUSION

The minimal prevalence of RA in Western Australia is 0.34-0.36%, which falls within the literature range. Older female RA patients in rural were more likely to be hospitalised, suggesting unmet primary care for needs.

Pre-defined gene co-expression modules in rheumatoid arthritis transition towards molecular health following anti-TNF therapy

BACKGROUND

No reliable biomarkers to predict response to TNF inhibitors (TNFi) in RA patients currently exist. The aims of this study were to replicate changes in gene co-expression modules that were previously reported in response to TNFi therapy in RA; to test if changes in module expression are specific to TNFi therapy; and to determine whether module expression transitions towards a disease-free state in responding patients.

METHOD

Published transcriptomic data from the whole blood of disease-free controls (n = 10) and RA patients, treated with the TNFi adalimumab (n = 70) or methotrexate (n = 85), were studied. Treatment response was assessed using the EULAR response criteria following 3 or 6 months of treatment. Change in transcript expression between pre- and post-treatment was recorded for previously defined modules. Linear mixed models tested whether modular expression after treatment transitioned towards a disease-free state.

RESULTS

For 25 of the 27 modules, change in expression between pre- and post-treatment in the adalimumab cohort replicated published findings. Of these 25 modules, six transitioned towards a disease-free state by 3 months (P < 0.05), irrespective of clinical response. One module (M3.2), related to inflammation and TNF biology, significantly correlated with response to adalimumab. Similar patterns of modular expression, with reduced magnitude, were observed in the methotrexate cohort.

CONCLUSION

This study provides independent validation of changes in module expression in response to therapy in RA. However, these effects are not specific to TNFi. Further studies are required to determine whether specific modules could assist molecular classification of therapeutic response.

Baseline bony erosions and time-averaged DAS28 predict discontinuation of TNF inhibitors in rheumatoid arthritis

The present study evaluated the predictive role of baseline radiographic change and disease activity on drug retention and clinical response in patients with rheumatoid arthritis (RA) treated with tumor necrosis factor inhibitor (TNFi). Korean Observational Study Network for Arthritis (KORONA) registry was evaluated to identify RA patients treated with a TNFi. Disease activity score-28 (DAS28) was evaluated at baseline and 1 year after TNFi initiation or at termination of TNFi due to inefficacy (within 1 year). The retention rate of TNFi was compared in patients with and without bony erosions. The hazard ratio (HR) for drug retention was evaluated by Cox regression analysis, as was the odds ratio (OR) for achieving remission (DAS28 < 2.6). This study included 109 RA patients, including 97 (89%) women and 30 (27.5%) with erosions, who were treated with a TNFi. Higher baseline DAS28 was negatively associated with achievement of remission (OR = 0.56, 95% CI 0.35-0.88). The TNFi retention rate was significantly lower in RA patients with than in those without erosions (p = 0.04). Factors significantly associated with drug discontinuation included the presence of erosions (HR = 2.45, 95% CI 1.08-5.51) and higher time-averaged DAS28 (HR = 2.17, 95% CI 1.47-3.20), whereas concomitant methotrexate was associated with lack of drug discontinuation (HR = 0.40, 95% CI 0.17-0.95). The presence of erosions and high time-averaged disease activity could predict poor retention of TNFi by RA patients. Higher baseline DAS28 was associated with a reduced clinical response in patients with RA.Trial registration Clinical Research Information Service of South Korea https://cris.nih.go.kr : KCT0000086, registered May 26, 2009.

Immune hallmarks of rheumatoid arthritis management: A brief review

The purpose of this review was to examine current evidence on immunomodulation mediated by conventional drugs and the use of novel biological agents for the treatment of rheumatoid arthritis (RA). Currently, treatment is focused on maximizing quality of life through sustained clinical remission and/or attenuating disease activity. To do so, disease-modifying antirheumatic drugs, especially methotrexate, are used alone or in combination with other drugs, including leflunomide, biological disease-modifying antirheumatic drugs (bDMARDs) and targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs). The most recent strategies modulate the immune response of the individual RA patient using tsDMARDs such as JAK inhibitors and bDMARDs such as ig-CTLA-4, anti- IL6R, anti-TNF-α and anti-CD20. To better understand current immunopharmacological interventions, we also looked at documented mechanisms of RA-mediated immunomodulation, highlighting perspectives potentially boosting RA treatment.

Clinical predictors of response to methotrexate in patients with rheumatoid arthritis: a machine learning approach using clinical trial data

BACKGROUND

Methotrexate is the preferred initial disease-modifying antirheumatic drug (DMARD) for rheumatoid arthritis (RA). However, clinically useful tools for individualized prediction of response to methotrexate treatment in patients with RA are lacking. We aimed to identify clinical predictors of response to methotrexate in patients with rheumatoid arthritis (RA) using machine learning methods.

METHODS

Randomized clinical trials (RCT) of patients with RA who were DMARD-naïve and randomized to placebo plus methotrexate were identified and accessed through the Clinical Study Data Request Consortium and Vivli Center for Global Clinical Research Data. Studies with available Disease Activity Score with 28-joint count and erythrocyte sedimentation rate (DAS28-ESR) at baseline and 12 and 24 weeks were included. Latent class modeling of methotrexate response was performed. The least absolute shrinkage and selection operator (LASSO) and random forests methods were used to identify predictors of response.

RESULTS

A total of 775 patients from 4 RCTs were included (mean age 50 years, 80% female). Two distinct classes of patients were identified based on DAS28-ESR change over 24 weeks: "good responders" and "poor responders." Baseline DAS28-ESR, anti-citrullinated protein antibody (ACPA), and Health Assessment Questionnaire (HAQ) score were the top predictors of good response using LASSO (area under the curve [AUC] 0.79) and random forests (AUC 0.68) in the external validation set. DAS28-ESR ≤ 7.4, ACPA positive, and HAQ ≤ 2 provided the highest likelihood of response. Among patients with 12-week DAS28-ESR > 3.2, ≥ 1 point improvement in DAS28-ESR baseline-to-12-week was predictive of achieving DAS28-ESR ≤ 3.2 at 24 weeks.

CONCLUSIONS

We have developed and externally validated a prediction model for response to methotrexate within 24 weeks in DMARD-naïve patients with RA, providing variably weighted clinical features and defined cutoffs for clinical decision-making.

Patient-reported outcomes of upadacitinib versus abatacept in patients with rheumatoid arthritis and an inadequate response to biologic disease-modifying antirheumatic drugs: 12- and 24-week results of a phase 3 trial

Background

In previous clinical trials, patients with active rheumatoid arthritis (RA) treated with upadacitinib (UPA) have improved patient-reported outcomes (PROs). This post hoc analysis of SELECT-CHOICE, a phase 3 clinical trial, evaluated the impact of UPA vs abatacept (ABA) with background conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) on PROs in patients with RA with inadequate response or intolerance to biologic disease-modifying antirheumatic drugs (bDMARD-IR).

Methods

Patients in SELECT-CHOICE received UPA (oral 15 mg/day) or ABA (intravenous). PROs evaluated included Patient Global Assessment of Disease Activity (PtGA) by visual analog scale (VAS), patient’s assessment of pain by VAS, Health Assessment Questionnaire Disability Index (HAQ-DI), morning stiffness duration and severity, 36-Item Short Form Health Survey (SF-36), Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F), Work Productivity and Activity Impairment (WPAI), and EQ-5D 5-Level (EQ-5D-5L) index score. Least squares mean (LSM) changes from baseline to weeks 12 and 24 were based on an analysis of covariance model. Proportions of patients reporting improvements ≥ minimal clinically important differences (MCID) were compared using chi-square tests.

Results

Data from 612 patients were analyzed (UPA, n=303; ABA, n=309). Mean age was 56 years and mean disease duration was 12 years. One-third received ≥2 prior bDMARDs and 72% received concomitant methotrexate at baseline. At week 12, UPA- vs ABA-treated patients had significantly greater improvements in PtGA, pain, HAQ-DI, morning stiffness severity, EQ-5D-5L, 2/4 WPAI domains, and 3/8 SF-36 domains and Physical Component Summary (PCS) scores (P<0.05); significant differences persisted at week 24 for HAQ-DI, morning stiffness severity, SF-36 PCS and bodily pain domain, and WPAI activity impairment domain. At week 12, significantly more UPA- vs ABA-treated patients reported improvements ≥MCID in HAQ-DI (74% vs 64%) and SF-36 PCS (79% vs 66%) and 4/8 domain scores (P<0.05).

Conclusions

At week 12, UPA vs ABA treatment elicited greater improvements in key domains of physical functioning, pain, and general health and earlier improvements in HAQ-DI. Overall, more UPA- vs ABA-treated patients achieved ≥MCID in most PROs at all timepoints; however, not all differences were statistically significant. These data, however, highlight the faster response to UPA treatment.

Trial registration

NCT03086343, March 22, 2017.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-022-02813-x.

IL-10 Induced by mTNF Crosslinking-Mediated Reverse Signaling in a Whole Blood Assay Is Predictive of Response to TNFi Therapy in Rheumatoid Arthritis

(1) Background: To date, the response of patients with rheumatoid arthritis (RA) to the various biologic DMARD available cannot be predicted due to a lack of reliable biomarkers. Based on our preliminary work on tmTNF reverse signaling, we developed a whole-blood assay measuring tmTNF crosslinking-induced IL-10 production to predict the response to TNF inhibitor (TNFi) therapy. (2) Methods: This prospective study included patients with active RA. Depending on the clinical judgment of the attending rheumatologist, either therapy with a TNF or JAK inhibitor was initiated. Clinical parameters and blood samples were obtained at baseline and after 8 weeks of therapy. The blood samples were collected using a newly developed whole-blood assay based on the principle of tmTNF reverse signalling. Subsequently, IL-10 was measured via enzyme-linked immunosorbent assay (ELISA) technique. (3) Results: 63 patients with RA were enrolled. In fifteen patients, TNFi therapy was initiated, while eight patients started a JAKi treatment. The cross-sectional analysis of all patients showed a positive correlation between tmTNF crosslinking-induced IL-10 and parameters of disease activity (CRP [r = 0.4091, p = 0.0009], DAS28 [r = 0.3303, p = 0.0082]) at baseline. In the TNFi treatment study, IL-10 was found to be significantly higher in EULAR responders than in non-responders (p = 0.0033). After initiation of JAKi treatment, in contrast, IL-10 induction was not linked to response. Longitudinal analysis of the TNFi-treated patients revealed IL-10 to decrease in responders (p = 0.04), but not in non-responders after 8 weeks of therapy. Of importance, the IL-10 production at baseline correlated inversely with TNFi response determined by ΔDAS28 in patients with TNFi treatment (r = −0.5299, p = 0.0422) while no such link was observed under JAKi therapy (p = 0.22). Receiver operation characteristics (ROC) analysis demonstrated a high performance of tmTNF/crosslinking-induced IL-10 in predicting a TNFi therapy response according to the EULAR criteria (AUC = 0.9286, 95% Confidence interval 0.7825–1.000, p = 0.0055). (4) Conclusions: In this pilot investigation, we demonstrated the feasibility of a whole-blood assay measuring tmTNF-induced IL-10 to predict clinical response to TNF inhibitor treatment. This approach might support rheumatologists in their decision for an individually tailored RA therapy.

Toward Individualized Prediction of Response to Methotrexate in Early Rheumatoid Arthritis: A Pharmacogenomics-Driven Machine Learning Approach

OBJECTIVE

To test the ability of machine learning (ML) approaches with clinical and genomic biomarkers to predict methotrexate treatment response in patients with early rheumatoid arthritis (RA).

METHODS

Demographic, clinical, and genomic data from 643 patients of European ancestry with early RA (mean age 54 years; 70% female) subdivided into a training (n = 336) and validation cohort (n = 307) were used. The genomic data comprised 160 single-nucleotide polymorphisms (SNPs) previously associated with RA or methotrexate metabolism. Response to methotrexate monotherapy was defined as good or moderate by the European Alliance of Associations for Rheumatology (EULAR) response criteria at the 3-month follow-up. Supervised ML methods were trained with 5 repeats and 10-fold cross-validation using the training cohort. Prediction performance was validated in the independent validation cohort.

RESULTS

Supervised ML methods combining age, sex, smoking, rheumatoid factor, baseline Disease Activity Score in 28 joints (DAS28) scores and 160 SNPs predicted EULAR response at 3 months with the area under the receiver operating curve of 0.84 (P = 0.05) in the training cohort and achieved a prediction accuracy of 76% (P = 0.05) in the validation cohort (sensitivity 72%, specificity 77%). Intergenic SNPs rs12446816, rs13385025, rs113798271, and ATIC (rs2372536) had variable importance above 60.0 and along with baseline DAS28 scores were among the top predictors of methotrexate response.

CONCLUSION

Pharmacogenomic biomarkers combined with baseline DAS28 scores can be useful in predicting response to methotrexate in patients with early RA. Applying ML to predict treatment response holds promise for guiding effective RA treatment choices, including timely escalation of RA therapies.

Risk of Severe Infection among Rheumatoid Arthritis Patients on Biological DMARDs: A Population-Based Cohort Study

Biological disease-modifying anti-rheumatic drugs (bDMARDs) are widely used for the management of rheumatoid arthritis, although their benefits are counterweight by an increased risk of infections. In the present study, we used administrative data to compare the risk of severe infections among different classes of bDMARDs. A retrospective cohort study was conducted using Administrative Health Databases of the Piedmont Region, Italy. Relevant data were obtained from: (1) the inhabitants registry, (2) hospital discharge records, and (3) the co-payment exemption registry and (4) drug claims registry. Fine and Gray competing risk models were fitted to evaluate the association between the use of different types of bDMARDs and occurrence of severe infection accounting for treatment interruption as competing risk. A total of 1780 new users of bDMARDs were identified. Among them, 50 hospitalizations for infection occurred during the study period. The use of Tocilizumab was associated with an increased risk of infection, compared to tumor necrosis factor (TNF) inhibitor drugs (sub-distribution hazard ratios-sHR: 2.510; 95% CI: 1.279–4.926), whereas no difference in the risk of severe infection was found for abatacept (sHR: 0.584; 95% CI: 0.234–1.457). bDMARDs treatment is generally safe in clinical practice with slight but important differences among classes. The increased risk of infection associated with tocilizumab use should be taken into account when balancing the risk and benefits of starting a treatment with this drug.

Worse outcomes linked to ethnicity for early inflammatory arthritis in England and Wales: a national cohort study

OBJECTIVE

To assess variability in care quality and treatment outcomes across ethnicities in early inflammatory arthritis (EIA).

METHODS

We conducted an observational cohort study in England and Wales from May 2018 to March 2020, including patients with a suspected/confirmed EIA diagnosis. Care quality was assessed against six metrics defined by national guidelines. Clinical outcomes were measured using DAS28. Outcomes between ethnic groups ('White', 'Black', 'Asian', 'Mixed', 'Other') were compared, and adjusted for confounders.

RESULTS

A total of 35 807 eligible patients were analysed. Of those, 30 643 (85.6%) were White and 5164 (14.6%) were from ethnic minorities: 1035 (2.8%) Black; 2617 (7.3%) Asian; 238 (0.6%) Mixed; 1274 (3.5%) Other. In total, 12 955 patients had confirmed EIA, of whom 11 315 were White and 1640 were from ethnic minorities: 314 (2.4%) Black; 927 (7.1%) Asian; 70 (0.5%) Mixed; 329 (2.5%) Other. A total of 14 803 patients were assessed by rheumatology within three weeks, and 5642 started treatment within six weeks of referral. There were no significant differences by ethnicity. Ethnic minority patients had lower odds of disease remission at three months [adjusted odds ratio 0.79 (95% CI: 0.65, 0.96)] relative to White patients. Ethnic minorities were significantly less likely to receive initial treatment withMTX[0.68 (0.52, 0.90)] or with glucocorticoids [0.63 (0.49, 0.80)].

CONCLUSION

We demonstrate that some ethnic minorities are less likely to achieve disease remission in three months following EIA diagnosis. This is not explained by delays in referral or time to treatment. Our data highlight the need for investigation into the possible drivers of these inequitable outcomes and reappraisal of EIA management pathways.

Rates and predictors of methotrexate-related adverse events in patients with early rheumatoid arthritis: results from a nationwide UK study

OBJECTIVES

To estimate prevalence rates and identify baseline predictors of adverse events (AEs) over the first year of treatment in patients with rheumatoid arthritis (RA) starting methotrexate (MTX).

METHODS

Data came from the UK Rheumatoid Arthritis Medication Study (RAMS), a prospective cohort of patients with RA starting MTX. This analysis included patients aged ≥ 18 years with physician diagnosed RA and symptom duration ≤ two years, who were commencing MTX for the first time. AEs were recorded by interviewing patients at six- and twelve-month follow-up visits. The period prevalence rates of AEs are reported for 0-6 months, 6-12 months, and 0-12 months of follow-up. The associations between baseline characteristics and AEs were assessed using multivariable logistic regression.

RESULTS

A total of 1069 patients were included in the analysis. Overall, 77.5% experienced at least one AE. The most commonly reported AEs were: gastrointestinal (42.0%), neurological (28.6%), mucocutaneous (26.0%), pulmonary (20.9%), elevated alanine transaminase (18.0%) and haematologic AEs (5.6%).Factors associated with increased odds of AEs were: women vs men (gastrointestinal, mucocutaneous, neurological), and alcohol consumption (nausea, alopecia, mucocutaneous). Older age, higher estimated Glomerular Filtration Rate (eGFR), and alcohol consumption were associated with less reporting of haematologic AEs.

CONCLUSIONS

AEs were common among patients over the first year of MTX, although most were not serious. Knowledge of the rates and factors associated with AEs occurrence are valuable when communicating risks prior to commencing MTX. This can help patients make informed decisions whether to start MTX, potentially increasing adherence to treatment.

Pharmacomicrobiology of Methotrexate in Rheumatoid Arthritis: Gut Microbiome as Predictor of Therapeutic Response

Rheumatoid arthritis (RA) is a disabling autoimmune disease with invasive arthritis as the main manifestation and synovitis as the basic pathological change, which can cause progressive destruction of articular cartilage and bone, ultimately leading to joint deformity and loss of function. Since its introduction in the 1980s and its widespread use in the treatment of RA, low-dose methotrexate (MTX) therapy has dramatically changed the course and outcome of RA treatment. The clinical use of this drug will be more rational with a better understanding of the pharmacology, anti-inflammatory mechanisms of action and adverse reaction about it. At present, the current clinical status of newly diagnosed RA is that MTX is initiated first regardless of the patients’ suitability. But up to 50% of patients could not reach adequate clinical efficacy or have severe adverse events. Prior to drug initiation, a prognostic tool for treatment response is lacking, which is thought to be the most important cause of the situation. A growing body of studies have shown that differences in microbial metagenomes (including bacterial strains, genes, enzymes, proteins and/or metabolites) in the gastrointestinal tract of RA patients may at least partially determine their bioavailability and/or subsequent response to MTX. Based on this, some researchers established a random forest model to predict whether different RA patients (with different gut microbiome) would respond to MTX. Of course, MTX, in turn, alters the gut microbiome in a dose-dependent manner. The interaction between drugs and microorganisms is called pharmacomicrobiology. Then, the concept of precision medicine has been raised. In this view, we summarize the characteristics and anti-inflammatory mechanisms of MTX and highlight the interaction between gut microbiome and MTX aiming to find the optimal treatment for patients according to individual differences and discuss the application and prospect of precision medicine.

Functional coding haplotypes and machine-learning feature elimination identifies predictors of Methotrexate Response in Rheumatoid Arthritis patients

BACKGROUND

Major challenges in large scale genetic association studies include not only the identification of causative single nucleotide polymorphisms (SNPs), but also accounting for SNP-SNP interactions. This study thus proposes a novel feature engineering approach integrating potentially functional coding haplotypes (pfcHap) with machine-learning (ML) feature selection to identify biologically meaningful, possibly causative genetic factors, that take into consideration potential SNP-SNP interactions within the pfcHap, to best predict for methotrexate (MTX) response in rheumatoid arthritis (RA) patients.

METHODS

Exome sequencing from 349 RA patients were analysed, of which they were split into training and unseen test set. Inferred pfcHaps were combined with 30 non-genetic features to undergo ML recursive feature elimination with cross-validation using the training set. Predictive capacity and robustness of the selected features were assessed using six popular machine learning models through a train set cross-validation and evaluated in an unseen test set.

FINDINGS

Significantly, 100 features (95 pfcHaps, 5 non-genetic factors) were identified to have good predictive performance (AUC: 0.776-0.828; Sensitivity: 0.656-0.813; Specificity: 0.684-0.868) across all six ML models in an unseen test dataset for the prediction of MTX response in RA patients.

INTERPRETATION

Majority of the predictive pfcHap SNPs were predicted to be potentially functional and some of the genes in which the pfcHap resides in were identified to be associated with previously reported MTX/RA pathways.

FUNDING

Singapore Ministry of Health's National Medical Research Council (NMRC) [NMRC/CBRG/0095/2015; CG12Aug17; CGAug16M012; NMRC/CG/017/2013]; National Cancer Center Research Fund and block funding Duke-NUS Medical School.; Singapore Ministry of Education Academic Research Fund Tier 2 grant MOE2019-T2-1-138.

Putative Association between Low Baseline Gene Expression in the Peripheral Blood and Clinical Remission in Rheumatoid Arthritis Patients Treated with Tofacitinib

We investigated the importance of the baseline expression of genes involved in energy generation, as prognostic biomarkers of the treatment response to tofacitinib in patients with rheumatoid arthritis (RA). Peripheral blood samples were obtained from 28 patients with RA who received 3 months of tofacitinib therapy from 26 healthy controls. Clinical response was evaluated based on the disease activity score, the erythrocyte sedimentation rate (DAS28-ESR), and the serum levels of ACPA, RF, CRP, and ESR. Clinical remission was assessed based on DAS28 score <2.6. Protein concentrations were measured using ELISA. Total RNA isolated from whole blood was used for gene expression analysis using quantitative RT-PCR. All patients were diagnosed with Steinbrocker’s radiographic stage II-III at baseline, and most showed erosive arthritis with ACPA and RF positivity. Tofacitinib treatment significantly decreased the disease activity. Upon study completion, seven patients showed remission. Before and after TOFA therapy, a significantly higher expression of succinate dehydrogenase and pyruvate kinase genes was observed in all the examined patients compared to healthy subjects. However, the pre-therapy expression of these genes and corresponding proteins was significantly (p ≤ 0.05) lower in patients who showed remission than in other patients with RA. Moreover, we observed that, during follow-up, patients who developed remission showed an increasing trend in the expression of the examined genes, whereas the others showed some decreases in gene expression, although this was not statistically significant. We concluded that, compared with RA patients maintaining persistent moderate or high disease activity, those with clinical remission following tofacitinib treatment showed a significantly lower baseline expression of genes involved in energy generation.

Certolizumab Can Also Be Effective in Monotherapy for the Treatment of Rheumatoid Arthritis Patients

OBJECTIVE

Although it is known that methotrexate (MTX) increases the effectiveness of biological drugs (mainly anti-TNFs) in patients with rheumatoid arthritis (RA), in real life, it is known that many patients using anti-TNFs are on monotherapy due to many causes. This article compares the effectiveness of certolizumab as monotherapy as combined with MTX or leflunomide (LFN) in RA patients with failure to conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) in a real-world setting.

METHODS

A retrospective observational cohort study was conducted at a specialized centre for RA management in Colombia. Patients treated with certolizumab as monotherapy or in combination with MTX, LFN, or MTX+LFN, between 2011 and 2020 with a minimum 3-month follow-up were included. Demographics and RA clinical characteristics were recorded; effectiveness was assessed as the improvement in Disease Activity Score (DAS28) getting remission or low disease activity at 3, 6, and 12 months of treatment.

RESULTS

A total of 181 patients were included, 24 received certolizumab as monotherapy, 62 certolizumab plus MTX, 47 certolizumab plus LFN and 48 certolizumab plus MTX+LFN. At 3 months of follow-up, 80% of the patients showed decreased disease activity, with no significant differences between groups; at 12 months of treatment, response in certolizumab monotherapy group was 94.4% compared to 81.8% in combination with MTX, 80.5% in combination with LFN and 51.4% in combination with MTX+LFN. Response at 3 months (OR 4.04; 95% CI 1.28-12.69) and positive anti-CCP (OR 3.83; 95% CI 1.11-13.21) were associated with 12-month response.

CONCLUSION

Certolizumab seems to be effective as monotherapy in the treatment of RA patients with failure to csDMARDs.

Do people with rheumatoid arthritis maintain their physical activity level at treatment onset over the first year of methotrexate therapy?

OBJECTIVES

To describe how many people with RA reduce their baseline physical activity level over the first year of MTX treatment, and which factors predict this.

METHODS

Data came from the Rheumatoid Arthritis Medication Study (RAMS), a prospective cohort of people with early RA starting MTX. Participants reported demographics and completed questionnaires at baseline, and 6 and 12 months, including reporting the number of days per week they performed ≥20 min of physical activity, coded as none, low (1-3 days) or high (4-7 days). The physical activity levels of participants over 12 months are described. Predictors of stopping physical activity were assessed using multivariable logistic regression.

RESULTS

In total, 1468 participants were included [median (interquartile range) age 60 (50, 69) years; 957 (65.2%) women]. At baseline, the physical activity levels of the people with RA were: none = 408 (27.8%), low = 518 (35.3%) and high = 542 (36.9%). Eighty percent of participants maintained some physical activity or began physical activity between assessments (baseline to 6 months = 79.3%, 6 months to 12 months = 80.7%). In total, 24.1% of participants reduced physical activity and 11.3% of participants stopped performing physical activity between baseline and 6 months (6 months to 12 months: 22.6% and 10.2%, respectively). Baseline smoking, higher disability and greater socioeconomic deprivation were associated with stopping physical activity.

CONCLUSION

Many people with early RA were not performing physical activity when starting MTX, or stopped performing physical activity over the first year of treatment. These people may require interventions to stay active. These interventions need to be mindful of socioeconomic barriers to physical activity participation.

Evaluation of a medication optimization intervention and predictors of medication adherence, patient satisfaction and medication adverse events in patients with rheumatoid arthritis

BACKGROUND

Because effective treatment for rheumatoid arthritis (RA) is dependent on medication use, medication optimization is critically important. Medication adherence, patient satisfaction with care and medication adverse events are core concepts of medication optimization that are either a significant problem and/or understudied in patients with RA.

OBJECTIVE

To (1) evaluate treatment effects from a medication optimization intervention; (2) assess treatment differences and changes over time in medication adherence, patient satisfaction, and medication adverse events; and (3) to determine whether age, gender, provider trust, and disease activity affect these outcomes.

METHODS

We conducted a prospective, longitudinal intervention study (N = 143 RA patients) using repeated measures models.

RESULTS

We did not identify significant intervention effects. For both the medication adherence and patient satisfaction models, the significant predictors in the model included age, gender and trust in provider. Older age, female gender (relative to male), and greater trust in the provider were associated with increased medication adherence scores and patient satisfaction. For the adverse events model, the only significant predictor in the model was gender. Compared with males, females were more likely to report experiencing adverse events. Time was significantly associated with decreased experiences of adverse events.

CONCLUSION

This study has identified important predictors of medication adherence, patient satisfaction and medication adverse events in a sample of patients with RA which can facilitate targeted approaches to improve adherence in those high-risk groups.

Association of altered folylpolyglutamate synthetase pre-mRNA splicing with methotrexate unresponsiveness in early rheumatoid arthritis

Objectives

An efficient pharmacological response to MTX treatment in RA patients relies on the retention and accumulation of intracellular MTX-polyglutamates catalysed by the enzyme folylpolyglutamate synthetase (FPGS). We recently identified a partial retention of FPGS intron 8 (8PR) as a prominent splice variant conferring FPGS dysfunction and decreased MTX polyglutamylation in acute lymphoblastic leukaemia. Here, we explored the association between FPGS 8PR levels and lack of MTX responsiveness in RA patients.

Methods

Thirty-six patients undergoing MTX treatment were enrolled from the Combinatie behandeling Reumatoide Artritis (COBRA)-light trial. RNA was isolated from blood samples at baseline, 13 weeks and 26 weeks of therapy, from patients in either COBRA-light (n = 21) or COBRA (n = 15) treatment arms. RT-qPCR analysis was used to assess RNA levels of FPGS 8PR over wild-type FPGS (8WT).

Results

In the COBRA-light treatment arm, higher baseline ratios of 8PR/8WT were significantly associated with higher 44-joint disease activity score (DAS44) at 13 and 26 weeks. Higher baseline ratios of 8PR/8WT also trended towards not obtaining low disease activity (DAS <1.6) and becoming a EULAR non-responder at 13 and 26 weeks. In the COBRA-treatment arm, a significant association was observed between high baseline 8PR/8WT ratios and higher DAS44 score at 26 weeks. Higher 8PR/8WT ratios were associated with non-response at week 26 based on both low disease activity and EULAR criteria.

Conclusion

This study is the first to associate alterations in FPGS pre-mRNA splicing levels with reduced responsiveness to MTX treatment in RA patients.

Trial registration

ISRCTN55552928.

Changes in the illness perceptions of patients with rheumatoid arthritis over the first year of methotrexate therapy

Objectives

To describe the illness perceptions of patients with RA over the first year of MTX treatment, and the association between illness perceptions and outcomes.

Methods

Data came from the Rheumatoid Arthritis Medication Study (RAMS), a UK multicentre cohort study of RA patients starting MTX for the first time. Patients were assessed at baseline, and at 6 and 12 months. Patients completed the Brief Illness Perception Questionnaire (B-IPQ) at each assessment, as well as other patient-reported outcomes (PROs). The inflammation score (2-component DAS28) was calculated. Subgroups of patients with similar trajectories across the eight (B-IPQ) items were identified using a latent class growth model. Predictors of group membership were identified using multinomial logistic regression. Associations between subgroups and PROs over follow-up were assessed using linear mixed models.

Results

Three subgroups were identified in the analysis population (N = 1087): Positive illness perceptions (N = 322), Negative illness perceptions (N = 534) and Improvers (N = 231) who switched from negative to positive illness perceptions over follow-up. Baseline disability was associated with group membership [Positive vs Negative: relative risk ratio (RRR) 0.37, 95% CI: 0.25, 0.54; Improvers vs Negative: RRR 0.60, 95% CI: 0.43, 0.83], as were other PROs (pain, fatigue, anxiety, depression). The Negative group had worse disability, pain and fatigue over follow-up compared with the other groups, controlling for inflammation.

Conclusion

Negative illness perceptions are associated with poor PROs over time. The Improvers subgroup illustrated that illness perceptions can change in RA. Illness perceptions represent a potential therapeutic target that should be assessed using randomized trials.

Smoking and Methotrexate Inefficacy in Rheumatoid Arthritis: What About Underlying Molecular Mechanisms?

The study by Safy-Khan, et al in the current issue of The Journal of Rheumatology ¹ reports that in a methotrexate (MTX)-based treatment regimen for patients with early arthritis, current smoking was significantly associated with a smaller reduction of Disease Activity Score in 28 joints (DAS28) over time compared to noncurrent smoking. This negative effect of current smoking on DAS28 was dose-dependent: patients who smoked 10-19 cigarettes per day did worse than patients who smoked 1-9 cigarettes per day.

The synergistic efficacy of hydroxychloroquine with methotrexate is accompanied by increased erythrocyte mean corpuscular volume

OBJECTIVES

To determine whether concomitant hydroxychloroquine modulates the increase in erythrocyte mean corpuscular volume (MCV) caused by methotrexate therapy, and whether this is associated with improved clinical response in rheumatoid arthritis (RA).

METHODS

A retrospective observational analysis was conducted on two independent hospital datasets of biologic-naïve, early-RA patients who started oral methotrexate. Baseline characteristics, DAS28-ESR and monthly MCV after starting methotrexate were obtained. Conventional and machine-learning statistical approaches were applied to the discovery cohort (Cohort-1, 655 patients) and results validated using Cohort 2 (225 patients).

RESULTS

Hydroxychloroquine therapy with methotrexate was associated with a two-fold increase in the likelihood of response defined in this study as clinical remission or low disease activity at 6 months (p < 0.001). The improved clinical outcome of combination hydroxychloroquine and methotrexate therapy was associated with an accelerated rise in MCV from 2 months after commencing therapy. The increase in MCV at three months was equivalent to the contemporaneous reduction in the disease activity score (DAS28-ESR) in predicting clinical response at 6 months. Using latent class mixed modelling, five trajectories of MCV change over six months from baseline were identified. The odds ratio of response to treatment was 16.2 (95% CI 5.7 to 46.4, <ip > <0.001) in those receiving combination therapy classified within the MCV elevation >5fL class, which contained the most patients, compared to methotrexate alone.

CONCLUSION

Our data provides mechanistic insight into the synergistic clinical benefit of concomitant hydroxychloroquine with methotrexate, boosting the rise in MCV which could serve as a companion biomarker of treatment response.

Current smoking predicts inadequate response to methotrexate monotherapy in rheumatoid arthritis patients naïve to DMARDs: Results from a retrospective cohort study

ABSTRACT

Identifying predictors of inadequate response to methotrexate (MTX) in rheumatoid arthritis (RA) is key to move from a "trial and error" to a "personalized medicine" treatment approach where patients less likely to adequately respond to MTX monotherapy could start combination therapy at an earlier stage. This study aimed to identify potential predictors of inadequate response to MTX in RA patients naïve to disease modifying anti-rheumatic drugs.Data from a real-life cohort of newly diagnosed RA patients starting MTX (baseline, T0) as first-line therapy were analyzed. Outcomes, assessed after 6 months (T1), were defined as failure to achieve a disease activity score 28 (DAS28) low disease activity (LDA) or a good/moderate response to MTX, according to the European League Against Rheumatism (EULAR) response criteria. Logistic regression was used to assess the associations between baseline variables and the study outcomes.Overall, 294 patients (60.5% females, median age 54.5 years) with a median disease duration of 7.9 months were recruited. At T1, 47.3% of subjects failed to achieve LDA, and 29.3% did not have any EULAR-response. In multivariate analysis, significant associations were observed between no LDA and current smoking (adjusted odds ratio [adjOR] 1.79, P = .037), female gender (adjOR 1.68, P = .048), and higher DAS28 (adjOR 1.31, P = .013); and between no EULAR-response and current smoking (adjOR: 2.04, P = .019), age (adjOR: 0.72 per 10-years increases, P = .001), and higher erythrocyte sedimentation rate (adjOR: 0.49; P = .020). By contrast, there were no associations between past smoker status and study outcomes.In summary, in our real-life cohort of disease modifying anti-rheumatic drug naïve RA patients, current smoking habit independently predicts inadequate response to MTX. This, together with other independent predictors of response to treatment identified in our study, might assist with personalized monitoring in RA patients. Further studies are required to investigate whether smoking quitting strategies enhance the therapeutic response to MTX.

Translating research into clinical practice: quality improvement to halve non-adherence to methotrexate

Objective

MTX remains the cornerstone for therapy for RA, yet research shows that non-adherence is significant and correlates with response to therapy. This study aimed to halve self-reported non-adherence to MTX at the Kellgren Centre for Rheumatology.

Methods

An anonymous self-report adherence questionnaire was developed and data collected for 3 months prior to the introduction of interventions, and then regularly for the subsequent 2.5 years. A series of interventions were implemented, including motivational interviewing training, consistent information about MTX and development of a summary bookmark. Information on clinic times was collected for consultations with and without motivational interviewing. Surveys were conducted to ascertain consistency of messages about MTX. A biochemical assay was used to test MTX serum levels in patients at two time points: before and 2.8 years following introduction of the changes. Remission rates at 6 and 12 months post-MTX initiation were retrieved from patient notes and cost savings estimated by comparing actual numbers of new biologic starters compared with expected numbers based on the numbers of consultants employed at the two time points.

Results

Between June and August 2016, self-reported non-adherence to MTX was 24.7%. Following introduction of the interventions, self-reported non-adherence rates reduced to an average of 7.4% between April 2018 and August 2019. Clinic times were not significantly increased when motivational interviewing was employed. Consistency of messages by staff across three key areas (benefits of MTX, alcohol guidance and importance of adherence) improved from 64% in September 2016 to 94% in January 2018. Biochemical non-adherence reduced from 56% (September 2016) to 17% (June 2019), whilst remission rates 6 months post-initiation of MTX improved from 13% in 2014/15 to 37% in 2017/18, resulting is estimated cost savings of £30 000 per year.

Conclusion

Non-adherence to MTX can be improved using simple measures including focussing on the adherence and the benefits of treatment, and providing consistent information across departments.

Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics

Methotrexate (MTX) is a common first-line treatment for new-onset rheumatoid arthritis (RA). However, MTX is ineffective for 30–40% of patients and there is no way to know which patients might benefit. Here, we built statistical models based on serum lipid levels measured at two time-points (pre-treatment and following 4 weeks on-drug) to investigate if MTX response (by 6 months) could be predicted. Patients about to commence MTX treatment for the first time were selected from the Rheumatoid Arthritis Medication Study (RAMS). Patients were categorised as good or non-responders following 6 months on-drug using EULAR response criteria. Serum lipids were measured using ultra‐performance liquid chromatography–mass spectrometry and supervised machine learning methods (including regularized regression, support vector machine and random forest) were used to predict EULAR response. Models including lipid levels were compared to models including clinical covariates alone. The best performing classifier including lipid levels (assessed at 4 weeks) was constructed using regularized regression (ROC AUC 0.61 ± 0.02). However, the clinical covariate based model outperformed the classifier including lipid levels when either pre- or on-treatment time-points were investigated (ROC AUC 0.68 ± 0.02). Pre- or early-treatment serum lipid profiles are unlikely to inform classification of MTX response by 6 months with performance adequate for use in RA clinical management.

Polymorphism of genes involved in methotrexate pathway: Predictors of response to methotrexate therapy in Indian rheumatoid arthritis patients

INTRODUCTION

The adenosine pathway is one of the ways through which methotrexate (MTX) ameliorates inflammation. We therefore explored an association of polymorphism of genes involved in adenosine and MTX metabolic pathways with response to MTX.

METHODS

Association of polymorphism in 7 genes (rs2236225 [MTHFD1 1958G>A], rs17602729 [AMPD1 G>A], rs1127354 [ITPA C>A], rs1431131 [TGFBR2 A>T], rs2372536 [ATIC C>G], rs11188513 [ENTPD1 C>T] and rs5751876 [ADORA2A T>C]) with efficacy of MTX was studied in Indian rheumatoid arthritis (RA) patients. The patients, classified by European League Against Rheumatology (EULAR)/American College of Rheumatology (ACR) 2010 criteria, were DMARD (disease-modifying antirheumatic drug)-naïve, with Disease Activity Score (DAS28) >3.2. After 4 months of MTX monotherapy, patients were classified as responders (R) or non-responders (NR) based on EULAR response criteria. Genotyping was done by TaqMan 5' nuclease assay and association of gene polymorphisms with response to MTX was determined by Chi-squared test.

RESULTS

Two hundred and twenty-six patients (86% female, median age 40 [interquartile range, IQR = 17.25] years), with disease duration of 24 (IQR = 38.25) months and DAS28-C-reactive protein score of 4.61 (IQR = 1.34) were enrolled. After therapy, 186 patients were classified as R and 40 as NR. GG genotype of ATIC (P = .01, odds ratio [OR] 2.56, 95% CI, 1.04-6.30) and CC genotype of ITPA (P = .009, OR 1.34, 95% CI 1.02-1.76) genes were found to be associated with the response. On binary logistic regression analysis, GG genotype of ATIC and CC of ITPA genes were independent predictors of the response.

CONCLUSION

Polymorphisms of ATIC and ITPA genes alone or with clinical variables were associated with response to MTX therapy in Indian RA patients.

Real-World Evidence: Bridging Gaps in Evidence to Guide Payer Decisions

Randomized controlled trials (RCTs) are preferred by payers for health technology assessments and coverage decisions. However, the inclusion of a highly selective patient population and the rigorously controlled conditions in RCTs may not be reflective of real-world clinical practice. Real-world evidence (RWE) obtained from an analysis of real-world data (RWD) from observational studies can bridge gaps in evidence not addressed by RCTs and is thus valuable to public and private payers for decision-making. Through a broad literature search to obtain insights into payers' experience, we found that payers have concerns about real-world studies with respect to data quality, poor internal validity, potential bias, and lack of meaningful endpoints. However, they valued RWE to fill evidence gaps not addressed by RCTs, such as high-quality, real-world, long-term effectiveness and safety data; head-to-head drug comparisons; cost analyses for tiering formulary placement; medication use and adherence patterns; identification of relevant responder and non-responder patient subpopulations; and patient-reported outcomes (PROs). RWE can be used to assess clinically meaningful endpoints and gauge the impact of interventions on the quality of healthcare. Here, we review how payers use or can use RWD on the comparative effectiveness and safety of treatments, PROs, medication adherence and persistence, prescribing patterns, healthcare resource utilization, and patient characteristics and/or biomarkers associated with treatment response when making health technology assessments and payer coverage decisions across therapeutic areas.

Good response to methotrexate is associated with a decrease in the gene expression of ABCG2, a drug transporter, in patients with rheumatoid arthritis

OBJECTIVES

Methotrexate (MTX) is used as an anchor drug in the treatment of rheumatoid arthritis (RA), although more than a half of the patients with RA require additional treatments. We designed a prospective study involving two medical centers in Japan to examine the association between the expression of MTX-related genes including a drug transporter ATP-binding cassette sub-family G member 2 (ABCG2) gene and the clinical response to MTX in MTX-naive patients with RA.

METHODS

The primary endpoint of this study was good response based on the European League Against Rheumatism (EULAR) response criteria by Disease Activity Score using 28-joint count (DAS28). We evaluated the association between the baseline expression of six genes involved in the intracellular pharmacokinetics of MTX, including ABCG2, as well as their temporal changes, and the clinical response at week 12 from the initiation of MTX.

RESULTS

Based on the clinical response at 12 weeks after the initiation of MTX, 24 patients were classified into good responders (n = 9) and non-good responders (n = 15; 10 moderate responders and 5 non-responders) groups. A univariate logistic regression analysis of the baseline gene expression levels to predict the EULAR good response at week 12 showed a significant association with ABCG2 expression alone. Furthermore, the rate of baseline expression of ABCG2 mRNA above the cut-off value determined using a receiver operating characteristic curve was higher in good responders than in non-good responders (p = .012). Moreover, ABCG2 expression decreased in almost all good responders, but not in non-good responders, after MTX treatment for 12 weeks (median -76% vs. +41% from baseline, respectively; p = .011). The ABCG2 expression level did not correlate with DAS28 at baseline or week 12.

CONCLUSIONS

Our study revealed that good response to MTX is associated with a decrease in the expression of ABCG2 in patients with RA.