Disease activity trajectories in early rheumatoid arthritis following intensive DMARD therapy over 3 years: association with persistence to therapy

Comorbidity clusters in patients with rheumatoid arthritis identify a patient phenotype with a favourable prognosis

OBJECTIVES

We aimed to cluster patients with rheumatoid arthritis (RA) based on comorbidities and then examine the association between these clusters and RA disease activity and mortality.

METHODS

In this population-based study, residents of an eight-county region with prevalent RA on 1 January 2015 were identified. Patients were followed for vital status until death, last contact or 31 December 2021. Diagnostic codes for 5 years before the prevalence date were used to define 55 comorbidities. Latent class analysis was used to cluster patients based on comorbidity patterns. Standardised mortality ratios were used to assess mortality.

RESULTS

A total of 1643 patients with prevalent RA (72% female; 94% white; median age 64 years, median RA duration 7 years) were studied. Four clusters were identified. Cluster 1 (n=686) included patients with few comorbidities, and cluster 4 (n=134) included older patients with 10 or more comorbidities. Cluster 2 (n=200) included patients with five or more comorbidities and high prevalences of depression and obesity, while cluster 3 (n=623) included the remainder. RA disease activity and survival differed across the clusters, with cluster 1 demonstrating more remission and mortality comparable to the general population.

CONCLUSIONS

More than 40% of patients with prevalent RA did not experience worse mortality than their peers without RA. The cluster with the worst prognosis (<10% of patients with prevalent RA) was older, had more comorbidities and had less disease-modifying antirheumatic drug and biological use compared with the other clusters. Comorbidity patterns may hold the key to moving beyond a one-size-fits-all perspective of RA prognosis.

Advances in non-biological drugs for the treatment of rheumatoid arthritis

INTRODUCTION

Rheumatoid arthritis (RA) is a complex autoimmune disease that affects millions of people worldwide, with a systemic impact. This review explores the role of non-biological conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) in its management.

AREAS COVERED

We discuss the effectiveness and safety of key csDMARDs such as Nonsteroidal anti-inflammatory drugs, corticosteroids, Hydroxychloroquine, Sulfasalazine, Methotrexate, and Leflunomide in relieving symptoms and slowing the progression of the disease. We also highlight the importance of combination therapy using csDMARDs, supported by clinical studies demonstrating the benefits of various csDMARD combinations. Early intervention with these drugs is emphasized to prevent joint damage, improve clinical symptoms, and enhance patient outcomes.

EXPERT OPINION

Overall, csDMARDs have proven pivotal in managing RA, providing cost-effective and versatile treatment options. We acknowledge the advantages of biologics but highlight the associated challenges, making the choice between non-biological and biological drugs a personalized decision. This comprehensive overview aims to provide a deeper understanding of RA treatment strategies, contributing to improving the quality of life for patients with this chronic condition.

Heterogeneity of treatment responses in rheumatoid arthritis using group based trajectory models: secondary analysis of clinical trial data

BACKGROUND

Traditionally rheumatoid arthritis (RA) trials classify patients as responders and non-responders; they ignore the potential range of treatment responses. Group Based Trajectory Models (GBTMs) provide a more refined approach. They identify patient subgroups with similar outcome trajectories. We used GBTMs to classify patients into subgroups of varying responses and explore factors associated with different responses to intensive treatment in a secondary analysis of intensive treatment in the TITRATE clinical trial.

METHODS

The TITRATE trial enrolled 335 patients with RA: 168 patients were randomised to receive intensive management, which comprised monthly assessments including measures of the disease activity score for 28 joints (DAS28), treatment escalation when patients were not responding sufficiently and psychosocial support; 163 of these patients completed the trial. We applied GBTMs to monthly DAS28 scores over one year to these patients who had received intensive management. The control group had standard care and were assessed every 6 months; they had too few DAS28 scores for applying GBTMs.

RESULTS

GBTMs identified three distinct trajectories in the patients receiving intensive management: good (n = 40), moderate (n = 76) and poor (n = 47) responders. Baseline body mass index (BMI), disability, fatigue and depression levels were significantly different between trajectory groups. Few (10%) good responders were obese, compared to 38% of moderate, and 43% of poor responders (P = 0.002). Few (8%) good responders had depression, compared to 14% moderate responders, and 38% poor responders (P < 0.001). The key difference in treatments was using high-cost biologics, used in only 5% of good responders but 30% of moderate and 51% of poor responders (P < 0.001). Most good responders had endpoint remissions and low disability, pain, and fatigue scores; few poor responders achieved any favourable outcomes.

CONCLUSION

GBTMs identified three trajectories of disease activity progression in patients receiving intensive management for moderately active RA. Baseline variables like obesity and depression predicted different treatment responses. Few good responders needed biologic drugs; they responded to conventional DMARDs alone. GBTMs have the potential to facilitate precision medicine enabling patient-oriented treatment strategies based on key characteristics.

REGISTRATION

TITRATE Trial ISRCTN 70160382.

Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis

Background

The purpose of this study was to stratify patients with rheumatoid arthritis (RA) according to the trend of disease activity by trajectory-based clustering and to identify contributing factors for treatment response to biologic and targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs) according to trajectory groups.

Methods

We analyzed the data from a nationwide RA cohort from the Korean College of Rheumatology Biologics and Targeted Therapy registry. Patients treated with second-line biologic and targeted synthetic DMARDs were included. Trajectory modeling for clustering was used to group the disease activity trend. The contributing factors using the machine learning model of SHAP (SHapley Additive exPlanations) values for each trajectory were investigated.

Results

The trends in the disease activity of 688 RA patients were clustered into 4 groups: rapid decrease and stable disease activity (group 1, n = 319), rapid decrease followed by an increase (group 2, n = 36), slow and continued decrease (group 3, n = 290), and no decrease in disease activity (group 4, n = 43). SHAP plots indicated that the most important features of group 2 compared to group 1 were the baseline erythrocyte sedimentation rate (ESR), prednisolone dose, and disease activity score with 28-joint assessment (DAS28) (SHAP value 0.308, 0.157, and 0.103, respectively). The most important features of group 3 compared to group 1 were the baseline ESR, DAS28, and estimated glomerular filtration rate (eGFR) (SHAP value 0.175, 0.164, 0.042, respectively). The most important features of group 4 compared to group 1 were the baseline DAS28, ESR, and blood urea nitrogen (BUN) (SHAP value 0.387, 0.153, 0.144, respectively).

Conclusions

The trajectory-based approach was useful for clustering the treatment response of biologic and targeted synthetic DMARDs in patients with RA. In addition, baseline DAS28, ESR, prednisolone dose, eGFR, and BUN were important contributing factors for 4-year trajectories.

Association of the Healthcare Effectiveness Data and Information Set (HEDIS) Follow-Up Care Measures and Medication Adherence Among Medicaid Insured Children with ADHD

OBJECTIVES

To assess the association of HEDIS C&M phase follow-up measure with ADHD medication adherence.

METHODS

A retrospective study was conducted using Medicaid data (2014-2016) of children initiated with ADHD medication. Patients were categorized as meeting the C&M follow-up measure or not according to the HEDIS specifications. Medication adherence was measured using both Proportion of Days Covered (PDC) & Group-Based Trajectory Modeling (GBTM). The association of medication adherence with HEDIS measure was assessed using Chi-square test.

RESULTS

Nearly all (97%) children with PDC≥0.7 and 72% of patients following the late decliner adherence trajectory met the HEDIS C&M follow-up criteria. In contrast, none of the children with PDC<0.7 and only two following rapid and slow decliner trajectories met the criteria.

CONCLUSION

ADHD medication adherence, regardless of how it was measured, clearly differentiated children with and without C&M phase follow-up, which essentially questions the implication of HEDIS C&M phase follow-up care measure.

Trajectories of Adherence to Biologic Disease-Modifying Anti-Rheumatic Drugs in Tuscan Administrative Databases: The Pathfinder Study

Scanty information on clustering longitudinal real-world data is available in the medical literature about the adherence implementation phase in rheumatoid arthritis (RA). To identify and characterize trajectories by analyzing the implementation phase of adherence to biologic Disease-Modifying Anti-Rheumatic Drugs (DMARDs), we conducted a retrospective cohort drug-utilization study using Tuscan administrative databases. RA patients were identified by a validated algorithm, including the first biologic DMARD supply from 2010 to 2015, RA specialist visit in the year before or after the first supply date and RA diagnosis in the five years before or in the year after the first supply date. We observed users for three years or until death, neoplasia, or pregnancy. We evaluated adherence quarterly through the Medication Possession Ratio. Firstly, we identified adherence trajectories and described the baseline characteristics; then, we focused on the trajectory most populated to distinguish the related sub-trajectories. We identified 952 first ever-biologic DMARD users in RA (712 females, mean age 52.7 years old, standard deviation 18.8). The biologic DMARD mostly supplied was etanercept (387 users) followed by adalimumab (233). Among 935 users with at least 3 adherence values, we identified 49 fully-adherent users, 829 continuous users, and 57 early-discontinuing users. Significant differences were observed among the index drugs. After focusing on the continuous users, three sub-trajectories were identified: continuous-steady users (556), continuous-alternate users (207), and continuous-declining users (66). No relevant differences emerged at the baseline. The majority of first ever-biologic DMARD users showed a continuous adherence behavior in RA. The role of adherence potential predictors and the association with effectiveness and safety outcomes should be explored by further studies.

Evaluating the Use of Hydroxychloroquine in Treating Patients With Rheumatoid Arthritis

Rheumatoid Arthritis (RA) is one of the most common autoimmune diseases present today. Although treatment options may differ among clinicians, a commonly prescribed treatment is hydroxychloroquine (HCQ), alone or in combination with other medications. HCQ has been studied for its immunomodulatory effects as well as its role in treating adverse conditions associated with RA. This systematic review examined the use of HCQ therapy in RA patients. A systematic search for relevant literature through PubMed, National Institute of Informatics, Japan (CiNii), and Science Direct databases were carried out in August 2021. Literature directly related to HCQ therapy for RA patients, RA-associated chronic kidney disease, and cardiovascular disease (including lipid profile) was considered relevant. HCQ associated retinopathic adverse effects were also selected for this review. Thirty-eight articles were found to be relevant, passed quality assessment, and were included in this review. Nine articles discussed HCQ therapy in comparison with other therapies (mainly methotrexate and sulfasalazine), but were contradictory in their outcomes, as were the seven papers that reviewed kidney function in RA patients with and without HCQ. Five articles credited better cardiovascular outcomes to RA patients taking HCQ. Sixteen articles studied the relationship between HCQ and retinal toxicity, providing insights into the risks associated with HCQ therapy. HCQ therapy was found not only to be beneficial in slowing the disease progression in RA patients but enhanced the effects of methotrexate in treating RA as well. Data strongly associates HCQ therapy with the mitigation of RA-related cardiovascular and kidney conditions. However, if HCQ is prescribed, it is imperative to be aware of the possible (although rare) retinopathic adverse effects associated with this therapy.

Central Aspects of Pain in Rheumatoid Arthritis (CAP-RA): protocol for a prospective observational study

BACKGROUND

Pain and fatigue are persistent problems in people with rheumatoid arthritis. Central sensitisation (CS) may contribute to pain and fatigue, even when treatment has controlled inflammatory disease. This study aims to validate a self-report 8-item questionnaire, the Central Aspects of Pain in Rheumatoid Arthritis (CAP-RA) questionnaire, developed to measure central pain mechanisms in RA, and to predict patient outcomes and response to treatment. A secondary objective is to explore mechanisms linking CS, pain and fatigue in people with RA.

METHODS/DESIGN

This is a prospective observational cohort study recruiting 250 adults with active RA in secondary care. The CAP-RA questionnaire, demographic data, medical history, and patient reported outcome measures (PROMs) of traits associated with central sensitization will be collected using validated questionnaires. Quantitative sensory testing modalities of pressure pain detection thresholds, temporal summation and conditioned pain modulation will be indices of central sensitization, and blood markers, swollen joints and ultrasound scans will be indices of inflammation. Primary data collection will be at baseline and 12 weeks. The test-retest reliability of CAP-RA questionnaire will be determined 1 week after the baseline visit. Pain and fatigue data will be collected weekly via text messages for 12 weeks. CAP-RA psychometric properties, and predictive validity for outcomes at 3 months will be evaluated.

DISCUSSION

This study will validate a simple self-report questionnaire against psychophysical indices of central sensitization and patient reported outcome measures of traits associated with CS in a population of individuals with active RA. The application of this instrument in the clinical environment could provide a mechanism-based stratification tool to facilitate the provision of targeted therapy to individuals with pain and fatigue in RA, alongside treatments that target joint inflammation.

TRIAL REGISTRATION

Clinicaltrials.gov NCT04515589 . Date of registration 17 August 2020.

Identification of Distinct Disease Activity Trajectories in Methotrexate-Naive Patients With Rheumatoid Arthritis Receiving Tofacitinib Over Twenty-Four Months

Objective

Tofacitinib is an oral JAK inhibitor for the treatment of rheumatoid arthritis (RA). To better understand tofacitinib treatment responses, we used group‐based trajectory modeling to investigate distinct disease activity trajectories and associated baseline variables in patients with active RA.

Methods

This post hoc analysis used data from a phase III study of methotrexate‐naive patients receiving tofacitinib 5 mg twice daily. Changes in the 4‐variable Disease Activity Score in 28 joints, using the erythrocyte sedimentation rate (DAS28‐ESR) from baseline to month 24 were used in group‐based trajectory modeling to identify distinct disease activity trajectories. Patient and disease characteristics, changes in radiographic progression and patient‐reported outcomes, and safety up to month 24 were compared among trajectory groups.

Results

From 346 methotrexate‐naive patients, 5 disease trajectory groups, defined by DAS28‐ESR scores, were identified, which progressed from high disease activity (HDA) to remission (group 1, n = 28), to low disease activity (LDA) rapidly (group 2, n = 107), to moderate disease activity (group 3, n = 98), to LDA gradually (group 4, n = 46), or remained in HDA (group 5, n = 67), at month 24. At baseline, groups 1 and 2 generally had lower disease activity and more favorable patient‐reported outcomes, compared with other groups. Improvements in radiographic progression and patient‐reported outcomes over 24 months were generally consistent with DAS28‐ESR–predicted disease activity trajectories. Adverse event rates were generally comparable across groups.

Conclusion

Distinct phenotypic subgroups identified heterogeneity in patients with RA normally analyzed as a single population. Trajectory modeling may enable separation of clinically meaningful subsets of patients with RA, and may help optimize treatment outcomes.

Comparative Adherence Trajectories of Oral Fingolimod and Injectable Disease Modifying Agents in Multiple Sclerosis

BACKGROUND

Oral fingolimod is convenient to use than injectable disease modifying agents (DMAs) in patients with multiple sclerosis (MS). However, the existing literature regarding the comparative adherence trajectories between oral fingolimod and injectable DMAs is limited.

OBJECTIVE

To compare the adherence trajectories between oral DMA, fingolimod, and injectable DMAs in patients with MS.

METHODS

A retrospective longitudinal study was conducted using adults (≥18 years) with MS (ICD-9-CM: 340 and a DMA prescription) from the IBM MarketScan Commercial Claims and Encounters Database between 2010 and 2012. Patients were grouped into oral fingolimod or injectable DMA users based on the index DMA among patients with MS. The annual DMA adherence trajectories, based on the proportion of days covered (PDC), were examined using group-based trajectory modeling (GBTM) during the one-year follow-up period after treatment initiation. Multivariable multinomial logistic regression using stabilized inverse probability treatment weights (IPTW) was performed to assess the association between the DMA route of administration (Oral vs Injectable) and the adherence trajectory groups. The balance of covariates between oral and injectable DMAs before and after IPTW was checked against a standardized difference threshold of 0.25.

RESULTS

The study cohort consisted of 1,700 MS patients who were initiated with oral (15.8%) or injectable (84.2%) DMAs between 2010 and 2012. The adherence rates (PDC≥0.8) in oral fingolimod and injectable DMA users were found to be 64.7% and 50.8%, respectively. The GBTM grouped individuals in the study cohort into three adherence trajectories - rapid discontinuers (23.5%), complete adherers (49.9%), and slow decliners (26.6%). The multinomial logistic regression model with stabilized IPTW revealed that oral fingolimod users had higher odds to be a complete adherer (adjusted odds ratio [AOR]: 2.78, 95% CI: 1.85-4.16) or a slow discontinuer (AOR: 2.62, 95% CI: 1.70-4.05) than injectable DMA users.

CONCLUSIONS

Oral DMA fingolimod was associated with better adherence than injectable DMAs across group-based trajectories. Further research is warranted to evaluate the adherence trajectories with newer oral DMAs introduced in the last decade for MS.

Disease activity trajectories in rheumatoid arthritis: a tool for prediction of outcome

Objective: Predicting treatment response and disease progression in rheumatoid arthritis (RA) remains an elusive endeavour. Identifying subgroups of patients with similar progression is essential for understanding what hinders improvement. However, this cannot be achieved with response criteria based on current versus previous Disease Activity Scores, as they lack the time component. We propose a longitudinal approach that identifies subgroups of patients while capturing their evolution across several clinical outcomes simultaneously (multi-trajectories). Method: For exploration, the RA cohort BARFOT (n = 2829) was used to identify 24 month post-diagnosis simultaneous trajectories of 28-joint Disease Activity Score and its components. Measurements were available at inclusion (0), 3, 6, 12, 24, and 60 months. Multi-trajectories were found with latent class growth modelling. For validation, the TIRA-2 cohort (n = 504) was used. Radiographic changes, assessed by the modified Sharp van der Heijde score, were correlated with trajectory membership. Results: Three multi-trajectories were identified, with 39.6% of the patients in the lowest and 18.9% in the highest (worst) trajectory. Patients in the worst trajectory had on average eight tender and six swollen joints after 24 months. Radiographic changes at 24 and 60 months were significantly increased from the lowest to the highest trajectory. Conclusion: Multi-trajectories constitute a powerful tool for identifying subgroups of RA patients and could be used in future studies searching for predictive biomarkers for disease progression. The evolution and shape of the trajectories in TIRA-2 were very similar to those in BARFOT, even though TIRA-2 is a newer cohort.

Sociodemographic factors as determinants of disease, disability and quality of life trajectories in early rheumatoid arthritis: A multi-ethnic inception cohort study

OBJECTIVE

This study aims to describe the association between sociodemographic factors and trajectories of disease, disability and health-related quality of life (HRQoL) in early rheumatoid arthritis (ERA).

METHODS

Data were collected prospectively over 3 years in the Singapore Early Arthritis Cohort study. Trajectories were modeled using multi-trajectory group-based trajectory modeling (GBTM) and determinants of trajectory membership were identified using multinomial logistic regression.

RESULTS

Two hundred and thirteen patients were included: 58.2% Chinese, 16.4% Malay, 21.6% Indian, mean (SD) age 51.3 (12.6) years and symptom duration 21.8 (15.3) weeks. In the multi-trajectory analysis, three groups of disease trajectories and corresponding disability and HRQoL trajectories were identified: group 1 (moderate disease rapid response, 49.9%), group 2 (high disease rapid response, 31.1%) and group 3 (high disease slow response, 19.1%). Malay patients had higher relative risk ratio (RRR) of being in trajectory groups 2 and 3 compared to group 1 (RRR = 2.30, 95% CI 1.05-3.98 and RRR = 4.02, 95% CI 1.45-6.43, respectively) while patients with tertiary education had lower relative risk (RRR = 0.56, 95% CI 0.45-0.89 and RRR = 0.33, (95% CI 0.14-0.83, respectively). In the analysis of individual outcomes, ethnicity, education level and body mass index were determinants of the heterogeneous disease activity trajectories. Gender and education level were determinants of the disability trajectories. Only gender was a determinant of the HRQoL trajectories. Further, 96.2% of the patients were treated with conventional synthetic disease-modifying antirheumatic drugs.

CONCLUSION

Disparities in sociodemographic factors should be taken into consideration in formulating treatment strategies in ERA.