Rheumatoid Arthritis Medication Study Research Articles

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

ObjectivesIn 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 SettingA 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). ResultsThe 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. ConclusionWe 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.

The RESIST Study: Do TNF Inhibitors Protect Against Cognitive Decline in Rheumatoid Arthritis Patients With Mild Cognitive Impairment?

AbstractBackgroundRheumatoid arthritis (RA) is an autoimmune disease characterised by chronic inflammation in the joint synovium. Considering growing research interest into the role that systemic inflammation might play in the pathogenesis of Alzheimer’s disease (AD), studying cognitive decline in RA patients can provide important insights into the potential effects of inflammation on cognitive health. Furthermore, evidence suggests that biological drugs used to treat RA, specifically TNF inhibitors (TNFi), may protect against AD progression by reducing systemic inflammation. The rheumatoid arthritis medication and memory study (RESIST) is a multicentre longitudinal observational study which aims to compare rates of cognitive decline in adults with both RA and mild cognitive impairment who are on either a conventional synthetic disease modifying anti‐rheumatic drug (csDMARD) or a TNFi.Method251 participants were recruited (160 on csDMARDs, 91 on TNFis). Participants completed assessments at six‐month intervals for eighteen months. The primary outcome was performance on the Free and Cued Selective Reminding Test (FCSRT). It was hypothesised that the rate of decline in FCSRT score would be lower among participants taking TNFis.ResultBetween‐groups ANCOVA was conducted to compare mean FCSRT scores at 12/18 months, adjusting for baseline score, age, disease activity, pain, wellbeing, depressive symptoms and physical function. Results showed that neither group declined in FCSRT free recall score on average over the 18 month follow‐up period, and that there was no significant difference between groups at 12 (mean difference = 0.59, 95% CI = ‐1.54, 2.72) or 18 months (mean difference = 1.24, 95% CI = ‐0.99, 3.47).ConclusionThe absence of decline in FCSRT performance in either group was unexpected. These findings raise the possibility that both csDMARDs and TNFis may protect against cognitive decline However, a major limitation of the study was attrition due to the COVID‐19 pandemic, which may have influenced results – those who experienced a greater degree of cognitive decline may have been more likely to withdraw from the study. Additional planned analyses will examine the potential moderating effect of APOE genotype, and the relationship between peripheral serum C reactive protein, cytokine levels and cognitive outcomes.

Identification of Cell-Specific Differential DNA Methylation Associated With Methotrexate Treatment Response in Rheumatoid Arthritis.

We undertook this study to estimate changes in cell-specific DNA methylation (DNAm) associated with methotrexate (MTX) response using whole blood samples collected from rheumatoid arthritis (RA) patients before and after initiation of MTX treatment. Patients included in this study were from the Rheumatoid Arthritis Medication Study (n=66) and the University of California San Francisco Rheumatoid Arthritis study (n=11). All patients met the American College of Rheumatology RA classification criteria. Blood samples were collected at baseline and following treatment. Disease Activity Scores in 28 joints using the C-reactive protein level were collected at baseline and after 3-6 months of treatment with MTX. Methylation profiles were generated using the Illumina Infinium HumanMethylation450 and MethylationEPIC v1.0 BeadChip arrays using DNA from whole blood. MTX response was defined using the EULAR response criteria (responders showed good/moderate response; nonresponders showed no response). Differentially methylated positions were identified using the Limma software package and Tensor Composition Analysis, which is a method for identifying cell-specific differential DNAm at the CpG level from tissue-level ("bulk") data. Differentially methylated regions were identified using Comb-p software. We found evidence of differential global methylation between treatment response groups. Further, we found patterns of cell-specific differential global methylation associated with MTX response. After correction for multiple testing, 1 differentially methylated position was associated with differential DNAm between responders and nonresponders at baseline in CD4+ T cells, CD8+ T cells, and natural killer cells. Thirty-nine cell-specific differentially methylated regions associated with MTX treatment response were identified. There were no significant findings in analyses of whole blood samples. We identified cell-specific changes in DNAm that were associated with MTX treatment response in RA patients. Future studies of DNAm and MTX treatment response should include measurements of DNAm from sorted cells.

P046 A multinomial approach to prediction of methotrexate treatment response and discontinuation due to adverse events in rheumatoid arthritis

Abstract Background/Aims As recommended by the NICE guidelines, methotrexate (MTX) is typically prescribed as the first line therapy for patients with rheumatoid arthritis (RA). However, around 40% of patients do not respond to MTX at 6 months and around 80% experience adverse events (AEs). Our previous systematic review identified that clinical prediction models of MTX outcomes suffered from methodological limitations, including a lack of validation, suboptimal handling of missing data, and no consideration of competing risks, such as patients discontinuing due to adverse events (AEs). These shortcomings resulted in high risk of bias and should be addressed to aid the implementation of outcome prediction in clinical practice. Therefore, this study aimed to (i) develop a multinomial prediction model for estimating an individual’s risks of not achieving low disease activity (LDA) and discontinuing due to AEs at 6 months after starting MTX, using information observable at the starting point of treatment, (ii) update prognosis at 3 months, and (iii) internally validate these models to assess performance. Methods Data came from the national multi-centre (n = 38) Rheumatoid Arthritis Medication Study (RAMS), which recruited patients with a diagnosis of RA or undifferentiated polyarthritis starting MTX for the first time. We conducted a Patient and Public Involvement focus group with past and current MTX users, which informed our outcome choice of LDA (DAS28 ≤3.2). A multinomial logistic regression (MLR) was used to develop a prediction model that estimated the probabilities of three outcomes: 1) not in LDA, 2) achieved LDA, and 3) discontinued due to AEs. The updated model at 3 months was conditional on patients not having achieved LDA. Missing data was handled using multiple imputation and models were internally validated through bootstrapping. Calibration, discrimination, and variance explained was assessed to quantify model performance. Results A total of 1632 patients were included in the analysis. At 6 months, 756 (46%) patients achieved LDA, 730 (45%) were not in LDA, and 146 (9%) discontinued due to AEs. The updated model at 3 months included 1179 (72%) patients as they had not achieved LDA. For the LDA outcome pair, the c-statistic was 0.73 (0.70, 0.75), while it was 0.54 (0.49, 0.59) for the AEs outcome. The calibration slope was 0.99 (0.85, 1.12) and 0.74 (0.23, 1.23), respectively. Predictive performance at 3 months was similar to baseline. Conclusion Our MLR models handled outcomes of disease activity and AEs simultaneously. We were able to predict outcomes of LDA more accurately than AEs and performance was better in terms of calibration, which is crucial for the clinical utility of a prediction model. This modelling approach could provide more clinically useful and realistic predictions of MTX outcomes, as competing risks such as AEs have previously been ignored. Disclosure C.K. Gehringer: None. G.P. Martin: None. K.L. Hyrich: Honoraria; Abbvie. Grants/research support; BMS and Pfizer. S.M.M. Verstappen: None. J.C. Sergeant: None.

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

ObjectivesTo estimate prevalence rates and identify baseline predictors of adverse events (AEs) over the first year of treatment in patients with RA starting MTX.MethodsData 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 ≤2 years, who were commencing MTX for the first time. AEs were recorded by interviewing patients at 6- and 12-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.ResultsA 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 haematological 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 and alcohol consumption were associated with less reporting of haematological AEs.ConclusionsAEs were common among patients over the first year of MTX, although most were not serious. Knowledge of the rates and factors associated with AE 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.

TNF inhibitors for the prevention of Alzheimer’s disease: Preliminary findings from the rheumatoid arthritis medication and memory study (RESIST)

AbstractBackgroundA raised level of serum TNFα observed in patients with Alzheimer’s disease has been associated with an increased rate of neurodegeneration and risk of conversion from mild cognitive impairment (MCI) to AD dementia. This led to the hypothesis that reduction in peripheral TNFα via TNF inhibitors (TNFi) may reduce the rate of neurodegeneration and may protect against development of AD.MethodThe rheumatoid arthritis medication and memory study (RESIST) is an 18‐month observational study which aims to compare the rate of cognitive decline between TNFi and conventional synthetic disease modifying anti‐rheumatic drugs (csDMARDs) in patients with both rheumatoid arthritis (RA) and MCI. Participants ≥ 55 years of age were recruited from rheumatology clinics in both Northern Ireland and Southampton and were cognitively assessed using the Free and Cued Selective Reminding Test (FCSRT) and Montreal Cognitive Assessment (MoCA). At the time of analysis n=130 participants had completed a 6‐month assessment and n=69 had completed a 12‐month assessment. ANCOVA analysis was conducted to calculate the difference in mean (and 95% CI) FCSRT and MoCA scores at both 6‐ and 12‐month timepoints between TNFi and csDMARD treatment groups, adjusting for baseline cognitive scores. Further adjustments were made for age, gender, RA disease activity and other confounding variables.ResultThere was no evidence of a difference between TNFi and csDMARD treatment in cognitive outcomes measured by FCSRT (6‐month cohort (mean difference 0.58, 95% CI ‐ 1.40, 2.56, p = 0.565); 12‐month cohort (mean difference ‐1.09, 95% CI ‐3.57, 1.38, p = 0.381)) or MoCA (6‐month cohort (mean difference ‐1.09, 95% CI ‐3.57, 1.38, p = 0.381); 12‐month cohort (mean difference ‐0.04, 95% CI ‐1.06, 0.98, p = 0.940)) after adjustment for baseline cognitive scores nor was there a difference in cognitive outcomes between treatment groups after adjustment for additional confounders.ConclusionThis preliminary analysis found little evidence of a relationship between TNFi and better cognitive performance however analysis was limited by lack of power and short follow‐up periods. This analysis will be repeated once RESIST has ended to determine if there is any statistically significant cognitive benefit of TNFi treatment after 18‐months.

O06 Baseline predictors of methotrexate-related adverse events in methotrexate-naïve patients with RA

Abstract Background/Aims Methotrexate (MTX) is the most common treatment for rheumatoid arthritis (RA). The prevalence of adverse events (AEs) associated with MTX treatment for RA have been studied extensively, but there are limited data on the predictors of these AEs. This study aims to summarise the prevalence rates of MTX AEs, including gastrointestinal (GI), neurological, mucocutaneous, and elevated alanine transaminase (ALT) enzyme, and to identify baseline demographic and clinical predictors of these AEs. Methods The Rheumatoid Arthritis Medication Study (RAMS) is a UK multi-centre prospective cohort study of patients with RA starting MTX for the first time. Relevant demographic, medication, clinical and disease related data were collected at baseline. AEs were reported at six and twelve months follow-ups. The prevalence rates of AEs were calculated based on the proportions of patients who reported having had an AE within one year of follow-up. The associations between candidate baseline predictors and AEs were assessed using multivariable logistic regression. Results A total of 2,089 patients were included with a mean age of 58.4 (standard deviation: 13.5) years, 1390 (66.5%) were women. 1,814 and 1,579 patients completed the 6 and 12 months follow-up visits, respectively. The prevalence rates of the AEs within one year of follow-up were: GI = 777 (40.6%), mucocutaneous = 441 (23.1%), neurological = 487 (25.5%), elevated ALT (> upper limit of normal [ULN]) = 286 (15.5%). Younger age and being a woman were associated with increased risk of GI AEs, (age: OR 0.97 per year increase in age, 95% CI 0.98, 1.00; male sex: OR 0.58 vs female, 95% CI 0.46, 0.74) (Table 1). Higher baseline Health Assessment Questionnaire (HAQ) score was an independent predictor of GI, mucocutaneous, and neurological AEs. Furthermore, having ALT >1xULN at baseline or history of diabetes was associated with increased risk of subsequent ALT elevation during the study follow-up. Conclusion In patients with RA starting MTX, GI AEs were the most commonly reported AEs during the first year of follow-up. The identified predictors of AEs may facilitate discussions between clinicians and patients prior to commencing MTX, and may lead to increased adherence and consequently improved effectiveness. Disclosure A.A. Sherbini: None. J.M. Gwinnutt: Grants/research support; BMS. K.L. Hyrich: Member of speakers’ bureau; Abbvie. Grants/research support; Pfizer, UCB, BMS. S.M.M. Verstappen: Consultancies; Celltrion. Member of speakers’ bureau; Pfizer. Grants/research support; BMS.

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.

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

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

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

ObjectivesTo describe the illness perceptions of patients with RA over the first year of MTX treatment, and the association between illness perceptions and outcomes.MethodsData 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.ResultsThree 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.ConclusionNegative 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.

P17 Prediction of response of methotrexate in patients with rheumatoid arthritis using serum lipidomics

Abstract Background For patients with rheumatoid arthritis (RA), introduction of early, effective therapy has consistently been shown to improve long-term outcomes. Low-dose methotrexate (MTX) is commonly prescribed as first-line treatment for RA. However, MTX is not effective for a large minority of patients and there is currently no way to determine ahead of therapy which patients are most likely to benefit. Metabolomics and lipidomics are emerging approaches for studying patient stratification in RA and have the potential to identify disease processes that underpin treatment outcomes. Here we apply state-of-the-art machine learning algorithms to predict MTX treatment response, by testing serum lipid levels measured at two time-points (pre-treatment and following 4 weeks on drug) to predict MTX response by 6 months. Methods This study included patients from the Rheumatoid Arthritis Medication Study (RAMS), a UK multi-centre one-year prospective observational study investigating predictors of response to MTX in patients with RA. Since 2008, patients who are about to start MTX for the first time are asked to provide demographic and clinical data, as well as blood samples to permit DNA, RNA and serum-based biomarker studies. Patients about to commence MTX treatment were followed longitudinally and those categorised as good or non-responders following 6 months on-drug using EULAR response criteria were analysed. Serum lipid levels were measured at pre-treatment and following 4 weeks on drug using ultra-performance liquid chromatography tailored for complex lipid analysis, coupled to mass spectrometry. State-of-the-art supervised machine learning methods were then applied to predict EULAR response at 6 months. Models including lipid levels were compared to models including clinical covariates (including: MTX start dose, steroid use at inclusion, BMI, number of swollen joints, number of tender joints, CRP levels, patients’ assessment of their overall wellbeing, gender, age-at-inclusion, age-at-onset, disease duration, HAQ score and pre-treatment smoking habits). Results Following quality control, 3,366 features (1,060 in negatively-charged mode and 2,306 in positive mode) were available for analysis at pre-treatment and 4 weeks from 100 RA patients categorised as good (GR, n = 50) or poor (NR, n = 50) responders to MTX following 6 months on drug. The best model performance for the classifier including clinical covariates was observed using L1/L2-regularised logistic regression (ROC AUC 0.68 ± 0.02). However, the clinical covariate model outperformed the classifier including lipid levels when either pre- or on-treatment time-points were investigated (ROC AUC 0.61 ± 0.02). Conclusion These data do not support the utility of early treatment lipidomic monitoring in routine clinical practice in patients started on MTX for their RA. Disclosures M. Maciejewski: Shareholder/stock ownership; owns stock or stock options in Pfizer. C. Sands None. N. Nair None. S. Ling None. S. Verstappen None. K. Hyrich None. A. Barton None. D. Ziemek Shareholder/stock ownership; owns stock or stock options in Pfizer. M. Lewis None. D. Plant None.

EP14 Association between initial csDMARD strategy and disease activity at 6 months in patients with new onset rheumatoid arthritis

Abstract Background Until 2018, NICE guidance recommended the use of a combination of disease-modifying anti-rheumatic drugs (DMARDs), including methotrexate (MTX), in the initial management of people with rheumatoid arthritis (RA). In 2018 the guideline was updated to recommend monotherapy with MTX due to uncertainties in the evidence for combination therapy. However, it remains a requirement for progression onto any biologic that the patient should have persistent high disease activity and/or have intolerance to, a minimum of two DMARDs. The aim of this study was to understand the association between initial treatment strategy and EULAR response at 6 months. Methods This analysis included patients recruited to the longitudinal observational Rheumatoid Arthritis Medication Study (RAMS) in the UK who were DMARD naïve and had symptoms for less than 1 year. Patients were defined as either starting MTX monotherapy or MTX in combination with another DMARD (6 weeks either side of MTX start date) and categorised into EULAR non responders or moderate/ good responders after 6 months. A logistic regression model was applied to test the association between initial treatment strategy and EULAR response at 6 months, adjusting for confounders. Results A total of 948 participants were included in the analysis. MTX monotherapy was prescribed in 72% (n = 678) of patients and combination therapy was prescribed in 28% (n = 270) of patients, the majority of whom received MTX plus hydroxychloroquine (HCQ) (n = 236, 87%). There was no significant difference between the MTX monotherapy and combination therapy groups in EULAR response at 6-months (adjusted odds ratio [aOR] 0.77, 95% CI 0.53 to 1.14). Conclusion In this large UK observational study investigating the effect of treatment strategy within the first 6 weeks of presentation and treatment response at 6 months, there was no significant difference between combination DMARD therapy and MTX monotherapy on EULAR response. Most patients received MTX in combination with HCQ, for which little evidence exists. Disclosures S. Wood None. K. Hyrich Consultancies; ABBVIE. Grants/research support; BMS, PFIZER, UCB. S. Verstappen None. D. Steinke None.

Predictors of presenteeism, absenteeism and job loss in patients commencing methotrexate or biologic therapy for rheumatoid arthritis.

ObjectivesWork is an important health outcome. This study aimed to identify predictors of work loss, absenteeism and presenteeism over 1 year in RA patients commencing treatment with MTX or biologics.MethodsPatients aged 18–65 years in full/part-time employment from two UK prospective cohorts were included: MTX-starters = Rheumatoid Arthritis Medication Study; and biologic-starters = Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate. Presenteeism and absenteeism were assessed using the RA-specific Work Productivity Survey at baseline, and 6 and 12 months. Potential predictors including baseline age, gender, clinical measures (e.g. disability, pain, fatigue), psychological distress, occupation and EULAR response from baseline to 6 months were investigated.ResultsA total of 51/463 MTX-starters and 30/260 biologic-starters left work over 12 months. Higher baseline psychological distress in MTX-starters [odds ratio (OR) 1.1 (95% CI: 1.0, 1.1)] and higher disability in biologic-starters [OR 3.5 (95% CI: 1.4, 8.6)] predicted work loss. Some 16.1% of patients reported sick-leave, which was predicted by disability [OR (95% CI): MTX-starters: 1.5 (0.9, 2.3); biologic-starters: 2.4 (1.1, 5.2)]. Median presenteeism scores were very low (minimal interference) in both cohorts. Higher fatigue for MTX starters [incidence rate ratio 1.2 (95% CI: 1.0, 1.4)] and higher disability in biologic-starters (incidence rate ratio 1.4 (95% CI: 1.1, 1.7)] predicted presenteeism. Good EULAR response was associated with lower absenteeism and presenteeism in both cohorts.ConclusionPatients with RA still face significant limitations regarding their ability to work. Disability and EULAR response were the main predictors of work outcomes, emphasizing the need to control the disease and the importance of function in enabling work participation.

Long-term outcomes of patients who rate symptoms of rheumatoid arthritis as 'satisfactory'.

ObjectivesTo describe outcomes of patients with early RA in a patient acceptable symptom state (PASS) at treatment initiation and to identify clusters of symptoms associated with poor outcomes.MethodsData came from the Rheumatoid Arthritis Medication Study, a UK multicentre cohort study of RA patients starting MTX. The HAQ, DAS28 and other patient-reported outcome measures (PROMs) were collected at baseline, and at 6 and 12 months. Patients answering yes to the question ‘Is your current condition satisfactory, when you take your general functioning and your current pain into consideration?’ were defined as PASS; patients answering no were defined as N-PASS. Symptom clusters in the baseline PASS group were identified using K-medians cluster analysis. Outcomes of baseline PASS vs N-PASS patients and each cluster are compared using random effects models.ResultsOf 1127 patients, 572 (50.8%) reported being in PASS at baseline. Over one year, baseline PASS patients had lower DAS28 (mean difference = −0.71, 95% CI −0.83, −0.59) and HAQ scores (mean difference = −0.48, 95% CI −0.56, −0.41) compared with N-PASS patients. Within the baseline PASS group, we identified six symptom clusters. Clusters characterized by high disease activity and high PROMs, or moderate disease activity and high PROMs, had the worst outcomes compared with the other clusters.ConclusionDespite reporting their condition as ‘satisfactory’, early RA patients with high PROM scores are less likely to respond to therapy. This group may require increased vigilance to optimize outcomes.

Differential DNA methylation correlates with response to methotrexate in rheumatoid arthritis.

ObjectivesIdentifying blood-based biomarkers that predict treatment response in RA is a clinical priority. We investigated differential DNA methylation as a candidate biomarker of response for the first-line drug used in RA, MTX.MethodsDNA methylation was measured in DNA samples from individuals recruited to the Rheumatoid Arthritis Medication Study. Differentially methylated positions were compared between whole blood samples collected at baseline and at 4 weeks from patients who, by 6 months, had a good (n = 34) or poor response (n = 34) to MTX using linear modelling, adjusting for gender, age, cell composition, baseline 28-joint disease activity score (DAS28) and smoking status. Analyses also compared methylation with changes in DAS28 and changes in swollen joint count and tender joint count, and changes in CRP over the initial 6 months after MTX commencement. Differentially methylated positions showing significant differences with any response parameter were tested using pyrosequencing in an independent group of 100 patients from the Rheumatoid Arthritis Medication Study.ResultsIn the discovery group, two CpG sites showed methylation changes at 4 weeks associated with clinical EULAR response by 6 months. Significant changes in methylation for three differentially methylated positions associated with change in tender joint counts, three with change in swollen joint count and a further four with change in CRP. Of the 12 CpGs, four showed replicated association in an independent dataset of samples from the Rheumatoid Arthritis Medication Study.ConclusionThese data represent an advance on current practice by contributing to a personalized medicine strategy allowing an escalation or change in therapy as early as 4 weeks.

The predictors of and reasons for non-adherence in an observational cohort of patients with rheumatoid arthritis commencing methotrexate.

In order to develop interventions to optimize MTX use for the treatment of RA we evaluated the rate of, reasons for and predictors of MTX non-adherence during the first 6 months of therapy. The Rheumatoid Arthritis Medication Study (RAMS) is a prospective multicentre cohort study of incident MTX users in the UK. Prior to MTX commencement demographic, clinical and psychological data were collected. A weekly patient-completed diary recorded MTX dose, possible side effects and adherence over 26 weeks. The number of non-adherent weeks was calculated. Potential baseline predictors of ever non-adherence (⩾1 week non-adherent) during the first 6 months of MTX therapy were identified using logistic regression analyses. 606 patients with RA were included; 69% female, mean (s.d.) age 60 (13) years and DAS28 score 4.2 (1.2). Over the first 6 months following MTX initiation, 158 (26%) patients were ever non-adherent (71% intentional, 19% non-intentional, 10% unexplained) and mean (s.d.) number of non-adherent weeks was 2.5 (2.1). Multivariable predictors of ever non-adherence included DAS28 [odds ratios (OR) 1.1, 95% CI 1.0, 1.4], fatigue (OR 1.1, 95% CI 1.0, 1.2 per cm), ⩾2 comorbidities vs no comorbidities (OR 1.9, 95% CI 1.1, 3.5) and high medication concerns despite perceived need (OR 1.1, 95% CI 1.0, 1.1 per unit decrease in need/concern differential). This is the largest study evaluating early intentional and non-intentional non-adherence to MTX, which has identified that patient beliefs and multi-morbidity strongly link with non-adherence. These findings can direct the design of and provide potential targets for interventions to improve patient adherence.

Profiling of Gene Expression Biomarkers as a Classifier of Methotrexate Nonresponse in Patients With Rheumatoid Arthritis.

ObjectiveApproximately 30–40% of rheumatoid arthritis (RA) patients who are initially started on low‐dose methotrexate (MTX) will not benefit from the treatment. To date, no reliable biomarkers of MTX inefficacy in RA have been identified. The aim of this study was to analyze whole blood samples from RA patients at 2 time points (pretreatment and 4 weeks following initiation of MTX), to identify gene expression biomarkers of the MTX response.MethodsRA patients who were about to commence treatment with MTX were selected from the Rheumatoid Arthritis Medication Study. Using European League Against Rheumatism (EULAR) response criteria, 42 patients were categorized as good responders and 43 as nonresponders at 6 months following the initation of MTX treatment. Data on whole blood transcript expression were generated, and supervised machine learning methods were used to predict a EULAR nonresponse. Models in which transcript levels were included were compared to models in which clinical covariates alone (e.g., baseline disease activity, sex) were included. Gene network and ontology analysis was also performed.ResultsBased on the ratio of transcript values (i.e., the difference in log2‐transformed expression values between 4 weeks of treatment and pretreatment), a highly predictive classifier of MTX nonresponse was developed using L2‐regularized logistic regression (mean ± SEM area under the receiver operating characteristic [ROC] curve [AUC] 0.78 ± 0.11). This classifier was superior to models that included clinical covariates (ROC AUC 0.63 ± 0.06). Pathway analysis of gene networks revealed significant overrepresentation of type I interferon signaling pathway genes in nonresponders at pretreatment (P = 2.8 × 10−25) and at 4 weeks after treatment initiation (P = 4.9 × 10−28).ConclusionTesting for changes in gene expression between pretreatment and 4 weeks post–treatment initiation may provide an early classifier of the MTX treatment response in RA patients who are unlikely to benefit from MTX over 6 months. Such patients should, therefore, have their treatment escalated more rapidly, which would thus potentially impact treatment pathways. These findings emphasize the importance of a role for early treatment biomarker monitoring in RA patients started on MTX.

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

BackgroundMethotrexate (MTX) remains the disease-modifying anti-rheumatic drug of first choice in rheumatoid arthritis (RA) but response varies. Predicting non-response to MTX could enable earlier access to alternative or additional medications and control of disease progression. We aimed to identify baseline predictors of non-response to MTX and combine these into a prediction algorithm.MethodsThis study included patients recruited to the Rheumatoid Arthritis Medication Study (RAMS), a UK multi-centre prospective observational study of patients with RA or undifferentiated polyarthritis, commencing MTX for the first time. Non-response to MTX at 6 months was defined as “no response” using the European League Against Rheumatism (EULAR) response criteria, discontinuation of MTX due to inefficacy or starting biologic therapy. The association of baseline demographic, clinical and psychosocial predictors with non-response was assessed using logistic regression. Predictive performance was assessed using the area under the receiver operating characteristic curve (AUC) and calibration plots.ResultsOf 1050 patients, 449 (43%) were classified as non-responders. Independent multivariable predictors of MTX non-response (OR (95% CI)) were rheumatoid factor (RF) negativity (0.62 (0.45, 0.86) for RF positivity versus negativity), higher Health Assessment Questionnaire score (1.64 (1.25, 2.15)), higher tender joint count (1.06 (1.02, 1.10)), lower Disease Activity score in 28 joints (0.29 (0.23, 0.39)) and higher Hospital Anxiety and Depression Scale anxiety score (1.07 (1.03, 1.12)). The optimism-corrected AUC was 0.74.ConclusionsThis is the first model for MTX non-response to be developed in a large contemporary study of patients commencing MTX in which demographic, clinical and psychosocial predictors were considered. Patient anxiety was a predictor of non-response and could be addressed at treatment commencement.

089 The association between poor prognostic factors at methotrexate initiation and disease activity and disability over one year: results from the Rheumatoid Arthritis Medication Study

089 The association between poor prognostic factors at methotrexate initiation and disease activity and disability over one year: results from the Rheumatoid Arthritis Medication Study

SAT0095 Control of Disease Activity is Associated with Improvement in Physical Activity in Patients with Rheumatoid Arthritis

BackgroundIt is well-known that patients with rheumatoid/undifferentiated arthritis (RA/UA) experience reduced functioning in daily tasks. Less is known about changes in physical activity over time and the association with disease...