Timing matters: real-world effectiveness of early combination of biologic and conventional synthetic disease-modifying antirheumatic drugs for treating newly diagnosed polyarticular course juvenile idiopathic arthritis

Adverse events of biological agents in pediatric rheumatologic diseases

OBJECTIVES

To evaluate adverse events (AEs) in pediatric patients with rheumatologic diseases being treated with approved or off-label biologic agents (BAs).

METHODS

This observational, retrospective, multicenter study was conducted from 2010 to 2022 in patients under 18 years of age with rheumatic diseases who were receiving interleukin-1 antibodies (Anti-IL1), interleukin-6 antibodies (Anti-IL6), and tumor necrosis factor alpha inhibitors (anti-TNF). Efficacy, AEs, and timing of AEs were collected from electronic medical records.

RESULTS

Three hundred and fifteen BAs were prescribed to 237 patients. Fifty AEs occurred in 44 patients (18.6%). Anti-TNF exposure was present in 8 (72.2%) of 11 patients with latent tuberculosis (TB) and in all 7 patients with herpes infections. Four of 6 patients (66.7%) with recurrent upper respiratory tract infections and 7 of 8 patients (87.5%) with local skin reactions were on Anti-IL1. The cutoff value for latent TB development was determined as 23.5 months by ROC analysis (AUC: 0.684 ± 0.072, p = 0.038, 95% CI: 0.54-0.82). In patients who used BA for 23.5 months or more, the risk of latent TB was 5.94-fold (p = 0.024, 95% CI: 1.26-27.97). Drug rash with eosinophilia and systemic symptoms (DRESS) occurred in 2 patients on anakinra, and anaphylaxis occurred in 1 patient on anti-IL6. There were no cases of malignancy or death in any patient.

CONCLUSION

The physician should be vigilant for latent TB in patients exposed to BA for more than 2 years. While local skin reactions are more prevalent in patients receiving anti-IL1, severe skin reactions such as DRESS may also occur.

Bayesian causal inference for observational studies with missingness in covariates and outcomes

Missing data are a pervasive issue in observational studies using electronic health records or patient registries. It presents unique challenges for statistical inference, especially causal inference. Inappropriately handling missing data in causal inference could potentially bias causal estimation. Besides missing data problems, observational health data structures typically have mixed-type variables - continuous and categorical covariates - whose joint distribution is often too complex to be modeled by simple parametric models. The existence of missing values in covariates and outcomes makes the causal inference even more challenging, while most standard causal inference approaches assume fully observed data or start their works after imputing missing values in a separate preprocessing stage. To address these problems, we introduce a Bayesian nonparametric causal model to estimate causal effects with missing data. The proposed approach can simultaneously impute missing values, account for multiple outcomes, and estimate causal effects under the potential outcomes framework. We provide three simulation studies to show the performance of our proposed method under complicated data settings whose features are similar to our case studies. For example, Simulation Study 3 assumes the case where missing values exist in both outcomes and covariates. Two case studies were conducted applying our method to evaluate the comparative effectiveness of treatments for chronic disease management in juvenile idiopathic arthritis and cystic fibrosis.

Trajectories of disease activity in patients with JIA in the Childhood Arthritis and Rheumatology Research Alliance Registry

OBJECTIVE

To describe 2-year trajectories of the clinical Juvenile Arthritis Disease Activity Score, 10 joints (cJADAS10) and associated baseline characteristics in patients with JIA.

METHODS

JIA patients in the Childhood Arthritis and Rheumatology Research Alliance Registry enrolled within 3 months of diagnosis from 15 June 2015 to 6 December 2017 with at least two cJADAS10 scores and 24 months of follow-up were included. Latent growth curve models of cJADAS10 were analysed; a combination of Bayesian information criterion, posterior probabilities and clinical judgement was used to select model of best fit.

RESULTS

Five trajectories were identified among the 746 included patients: High, Rapidly Decreasing (HRD) (n = 199, 26.7%); High, Slowly Decreasing (HSD) (n = 154, 20.6%); High, Increasing (HI) (n = 39, 5.2%); Moderate, Persistent (MP) (n = 218, 29.2%); and Moderate, Decreasing (MD) (n = 136, 18.2%). Most patients spent a significant portion of time at moderate to high disease activity levels. At baseline, HSD patients were more likely to be older, have a lower physician global assessment, normal inflammatory markers, longer time to first biologic, and have taken systemic steroids compared with HRD. Those with a HI trajectory were more likely to be ANA negative, have a longer time to first biologic, and less likely to be taking a conventional synthetic DMARD compared with HRD. MP patients were more likely to be older with lower household income, longer time to diagnosis, and markers of higher disease activity than those with a MD trajectory.

CONCLUSIONS

Five trajectories of JIA disease activity, and associated baseline variables, were identified.

Pharmacological treatment patterns in patients with juvenile idiopathic arthritis in the Netherlands: a real-world data analysis

OBJECTIVE

To investigate medication prescription patterns among children with JIA, including duration, sequence and reasons for medication discontinuation.

METHODS

This study is a single-centre, retrospective analysis of prospective data from the electronic medical records of JIA patients receiving systemic therapy aged 0-18 years between 1 April 2011 and 31 March 2019. Patient characteristics (age, gender, JIA subtype) and medication prescriptions were extracted and analysed using descriptive statistics, Sankey diagrams and Kaplan-Meier survival methods.

RESULTS

Over a median of 4.2 years follow-up, the 20 different medicines analysed were prescribed as monotherapy (n = 15) or combination therapy (n = 48 unique combinations) among 236 patients. In non-systemic JIA, synthetic DMARDs were prescribed to almost all patients (99.5%), and always included MTX. In contrast, 43.9% of non-systemic JIA patients received a biologic DMARD (mostly adalimumab or etanercept), ranging from 30.9% for oligoarticular persistent ANA-positive JIA, to 90.9% for polyarticular RF-positive JIA. Among systemic JIA, 91.7% received a biologic DMARD (always including anakinra). When analysing medication prescriptions according to their class, 32.6% involved combination therapy. In 56.8% of patients, subsequent treatment lines were initiated after unsuccessful first-line treatment, resulting in 68 unique sequences. Remission was the most common reason for DMARD discontinuation (44.7%), followed by adverse events (28.9%) and ineffectiveness (22.1%).

CONCLUSION

This paper reveals the complexity of pharmacological treatment in JIA, as indicated by: the variety of mono- and combination therapies prescribed, substantial variation in medication prescriptions between subtypes, most patients receiving two or more treatment lines, and the large number of unique treatment sequences.

Real-world data reveals the complexity of disease modifying anti-rheumatic drug treatment patterns in juvenile idiopathic arthritis: an observational study

OBJECTIVE

Pharmacological treatment is a cornerstone of care for children with juvenile idiopathic arthritis (JIA). The objective of this study is to evaluate prescription patterns of conventional and biologic disease modifying anti-rheumatic drugs (c-DMARDs and b-DMARDs) for patients with JIA.

METHODS

We conducted a retrospective cohort study of children diagnosed with JIA at a rheumatology pediatric clinic. Eligibility criteria were defined as children and youth newly diagnosed with enthesis-related arthritis, polyarticular, or oligoarticular JIA between 2011 and 2019, with at least one year of observation. Data on c-DMARDs and b-DMARDs prescriptions were obtained from electronic medical charts. We used descriptive statistics, Kaplan-Meier survival methods, and Sankey diagrams to describe treatment prescription patterns.

RESULTS

A total of 325 patients with JIA were included, with a median observation time of 3.7 years. The most frequently prescribed c-DMARD and b-DMARD were methotrexate and etanercept, respectively. Within the first year of rheumatology care, 62% and 21% of patients had a c-DMARD and a b-DMARD prescribed, respectively. These proportions varied greatly by JIA subtype. Among the 147 (147/325, 45%) patients that had at least one b-DMARD prescribed, 24% were prescribed a second, and 7% a third-line of b-DMARD. A total of 112 unique treatment sequences were observed, with c-DMARD monotherapy followed by the addition of either a b-DMARD (56%) or another c-DMARD (30%) being the two most prevalent patterns in this cohort.

CONCLUSION

We observed a variety of treatment trajectories, with many patients experiencing multiple treatment lines, illustrating the complexity of the overall JIA treatment path.

Disparities in Pediatric Rheumatic Diseases

Health and health care disparities in pediatric rheumatology are prevalent among socially disadvantaged and marginalized populations based on race/ethnicity, socioeconomic position, and geographic region. These groups are more likely to experience greater disease severity, morbidity, mortality, decreased quality of life, and poor mental health outcomes, which are in part due to persistent structural and institutional barriers, including decreased access to quality health care. Most of the research on health and health care disparities in pediatric rheumatology focuses on juvenile idiopathic arthritis and childhood-onset systemic lupus erythematosus; there are significant gaps in the literature assessing disparities associated with other pediatric rheumatic diseases. Understanding the underlying causes of health care disparities will ultimately inform the development and implementation of innovative policies and interventions on a federal, local, and individual level.

Improved Disease Course Associated With Early Initiation of Biologics in Polyarticular Juvenile Idiopathic Arthritis: Trajectory Analysis of a Childhood Arthritis and Rheumatology Research Alliance Consensus Treatment Plans Study

OBJECTIVE

To investigate the effects of early introduction of biologic disease-modifying antirheumatic drugs (bDMARDs) on the disease course in untreated polyarticular juvenile idiopathic arthritis (JIA).

METHODS

We analyzed data on patients with polyarticular JIA participating in the Start Time Optimization of Biologics in Polyarticular JIA (STOP-JIA) study (n = 400) and a comparator cohort (n = 248) from the Childhood Arthritis and Rheumatology Research Alliance Registry. Latent class trajectory modeling (LCTM) was applied to identify subgroups of patients with distinct disease courses based on disease activity (clinical Juvenile Arthritis Disease Activity Score in 10 joints) over 12 months from baseline.

RESULTS

In the STOP-JIA study, 198 subjects (49.5%) received bDMARDs within 3 months of baseline assessment. LCTM analyses generated 3 latent classes representing 3 distinct disease trajectories, characterized by slow, moderate, or rapid disease activity improvement over time. Subjects in the rapid improvement trajectory attained inactive disease within 6 months from baseline. Odds of being in the rapid improvement trajectory versus the slow improvement trajectory were 3.6 times as high (95% confidence interval 1.32-10.0; P = 0.013) for those treated with bDMARDs ≤3 months from baseline compared with subjects who started bDMARDs >3 months after baseline, after adjusting for demographic characteristics, clinical attributes, and baseline disease activity. Shorter disease duration at first rheumatology visit approached statistical significance as a predictor of favorable trajectory without bDMARD treatment.

CONCLUSION

Starting bDMARDs within 3 months of baseline assessment is associated with more rapid achievement of inactive disease in subjects with untreated polyarticular JIA. These results demonstrate the utility of trajectory analysis of disease course as a method for determining treatment efficacy.

Update on the treatment of nonsystemic juvenile idiopathic arthritis including treatment-to-target: is (drug-free) inactive disease already possible?

PURPOSE OF REVIEW

This review concerns the outcome for nonsystemic juvenile idiopathic arthritis (JIA) with emphasis on treatment-to-target (T2T) and treatment strategies aiming at inactive disease by giving an overview of recent articles.

RECENT FINDINGS

More efficacious therapies and treatment strategies/T2T with inactive disease as target, have improved the outcome for JIA significantly. Recent studies regarding treatment strategies have shown 47-68% inactive disease after 1 year. Moreover, probability of attaining inactive disease at least once in the first year seems even higher in recent cohort-studies, reaching 80%, although these studies included relatively high numbers of oligoarticular JIA patients. However, 26-76% of patients flare upon therapy withdrawal and prediction of flares is still difficult.

SUMMARY

Remission can be achieved and sustained in (some) JIA patients, regardless of initial treatment. Cornerstone principles in the management of nonsystemic JIA treatment are early start of DMARD therapy, striving for inactive disease and T2T by close and repeated monitoring of disease activity. T2T and tight control appear to be more important than a specific drug in JIA. Next to inactive disease, it is important that patients/parents are involved in personal targets, like reduction of pain and fatigue. Future studies should focus on predictors (based on imaging-methods or biomarkers) for sustained drug-free remission and flare.

Prescribing Patterns and Impact of Factors Associated with Time to Initial Biologic Therapy among Children with Non-systemic Juvenile Idiopathic Arthritis

OBJECTIVE

The aim of this study was to examine patterns of initial prescriptions, investigate time to initiation of biologic disease-modifying anti-rheumatic drugs (bDMARDs), and evaluate the impact of clinical and other baseline factors associated with the time to first bDMARD in treating children with newly diagnosed non-systemic juvenile idiopathic arthritis (JIA).

METHODS

Using longitudinal patient-level data extracted from electronic medical records (EMR) in a large Midwestern pediatric hospital from 2009 to 2018, the initial prescriptions and prescribing patterns of bDMARDs, conventional synthetic disease-modifying anti-rheumatic drugs (csDMARDs), non-steroidal anti-inflammatory drugs (NSAIDs) and glucocorticoids within 3 months of JIA diagnosis were examined. Kaplan-Meier analyses were performed to assess time to initiation of bDMARDs. Cox proportional hazard models were used to identify factors associated with time to first bDMARD.

RESULTS

Of 821 children, the proportion of patients with initial csDMARDs increased from 45.3% in 2009 to 60.3% in 2018. Around 57.5% of polyarthritis rheumatoid factor-positive (Poly RF+) patients and 43.2% of polyarthritis rheumatoid factor-negative (Poly RF-) patients received a bDMARD therapy within 3 months of diagnosis, 14.4% as monotherapy and 28.3% in combination with a csDMARD. Among patients who received combination therapy, combination of methotrexate with adalimumab increased from 16.7% in 2009 to 40% in 2018. The proportion of patients treated with adalimumab gradually increased and passed etanercept in 2016. The predictors of earlier initiation of biologic therapy were JIA category enthesitis-related arthritis (ERA) [hazard ratio (HR) vs persistent oligoarthritis 4.82; p < 0.0001], psoriatic arthritis (PsA) (HR 2.46; p = 0.0002), or Poly RF- (HR 2.43; p = 0.0002); the number of joints with limited range of motion (HR 1.02; p = 0.0222), and erythrocyte sedimentation rate (ESR, HR 1.01; p = 0.0033).

CONCLUSIONS

There was a substantial increase in the proportion of patients receiving the combination of methotrexate and adalimumab among patients receiving combination therapy. Adalimumab overtook etanercept as the most frequently prescribed bDMARD. Multiple factors affect the time to biologic initiation, including the number of joints with limited range of motion, ESR, and JIA category.

A scoping review of studies using observational data to optimise dynamic treatment regimens

BACKGROUND

Dynamic treatment regimens (DTRs) formalise the multi-stage and dynamic decision problems that clinicians often face when treating chronic or progressive medical conditions. Compared to randomised controlled trials, using observational data to optimise DTRs may allow a wider range of treatments to be evaluated at a lower cost. This review aimed to provide an overview of how DTRs are optimised with observational data in practice.

METHODS

Using the PubMed database, a scoping review of studies in which DTRs were optimised using observational data was performed in October 2020. Data extracted from eligible articles included target medical condition, source and type of data, statistical methods, and translational relevance of the included studies.

RESULTS

From 209 PubMed abstracts, 37 full-text articles were identified, and a further 26 were screened from the reference lists, totalling 63 articles for inclusion in a narrative data synthesis. Observational DTR models are a recent development and their application has been concentrated in a few medical areas, primarily HIV/AIDS (27, 43%), followed by cancer (8, 13%), and diabetes (6, 10%). There was substantial variation in the scope, intent, complexity, and quality between the included studies. Statistical methods that were used included inverse-probability weighting (26, 41%), the parametric G-formula (16, 25%), Q-learning (10, 16%), G-estimation (4, 6%), targeted maximum likelihood/minimum loss-based estimation (4, 6%), regret regression (3, 5%), and other less common approaches (10, 16%). Notably, studies that were primarily intended to address real-world clinical questions (18, 29%) tended to use inverse-probability weighting and the parametric G-formula, relatively well-established methods, along with a large amount of data. Studies focused on methodological developments (45, 71%) tended to be more complicated and included a demonstrative real-world application only.

CONCLUSIONS

As chronic and progressive conditions become more common, the need will grow for personalised treatments and methods to estimate the effects of DTRs. Observational DTR studies will be necessary, but so far their use to inform clinical practice has been limited. Focusing on simple DTRs, collecting large and rich clinical datasets, and fostering tight partnerships between content experts and data analysts may result in more clinically relevant observational DTR studies.

Costs of medication use among patients with juvenile idiopathic arthritis in the Dutch healthcare system

Background: This study aims to quantify medication costs in juvenile idiopathic arthritis (JIA), based on subtype.Research design and methods: This study is a single-center, retrospective analysis of prospective data from electronic medical records of JIA patients, aged 0-18 years between 1 April 2011 and 31 March 2019. Patient characteristics (age, gender, subtype) and medication use were extracted. Medication use and costs were reported as: 1) mean total annual costs; 2) between-patient heterogeneity in these costs; 3) duration of medication use; and, 4) costs over the treatment course.Results: The analysis included 691 patients. Mean total medication costs were €2,103/patient/year, including €1,930/patient/year (91.8%) spent on biologicals. Costs varied considerably between subtypes, with polyarticular rheumatoid-factor positive and systemic JIA patients having the highest mean costs (€5,020/patient/year and €4,790/patient/year, respectively). Mean annual medication costs over the patient's treatment course ranged from <€1,000/year (71.1% of patients) to >€11,000/year (2.5% of patients). Etanercept and adalimumab were the most commonly used biologicals. Cost fluctuations over the treatment course were primarily attributable to biological use.Conclusions: Polyarticular rheumatoid-factor positive and systemic JIA patients had the highest mean total annual medication costs, primarily attributable to biologicals. Costs varied considerably between subtypes, individuals, and over the treatment course.