Development and External Validation of a Model Predicting New-Onset Chronic Uveitis at Different Disease Durations in Juvenile Idiopathic Arthritis

Trends in New Use of Disease-Modifying Antirheumatic Drugs for Juvenile Idiopathic Arthritis Among Commercially Insured Children in the United States from 2001 to 2022

OBJECTIVE

The objective of this study is to describe recent trends in disease-modifying antirheumatic drug (DMARD) use for children with juvenile idiopathic arthritis (JIA) in the United States.

METHODS

We used commercial claims data (2000-2022) to perform a serial cross-sectional utilization study of children aged 1 to 18 that were diagnosed with JIA. Initiations of conventional synthetic DMARDs (csDMARDs), biologic DMARDs (bDMARDs), or targeted synthetic DMARDs (tsDMARDs) were identified after a ≥12-month baseline and expressed as a percentage of all new DMARD initiations per year, by category, class, and individual agent. Trends were evaluated using linear regression. We also examined the first bDMARDs and tsDMARDs initiated after csDMARD monotherapy.

RESULTS

We identified 20,258 new DMARD use episodes among 13,696 individuals (median age 14 years, 67.5% female). csDMARDs, although most used overall, declined from 89.5% of new use episodes to 43.2% (2001-2022, P < 0.001 for trend). In contrast, bDMARD use increased (10.5-50.0%, P < 0.001). For tumor necrosis factor inhibitors (TNFi), etanercept peaked at 28.3% in 2006 and declined to 4.2% in 2022 (P = 0.002). Meanwhile, adalimumab use doubled (7.0-14.0%, 2007-2008) after JIA approval, increasing further following a less painful formulation release (20.5% in 2022, P < 0.001). However, overall TNFi use has declined with increasing use of other bDMARDs and tsDMARDs, particularly ustekinumab, secukinumab, and tofacitinib. By 2022, adalimumab was the most common b/tsDMARD initiated first after csDMARDs (77.8%).

CONCLUSION

Among commercially insured children with JIA in the United States, new b/tsDMARD use is rising and new csDMARD use is declining. For b/tsDMARDs, adalimumab is most used and is the predominant b/tsDMARD initiated first after csDMARDs. Patterns in DMARD use for JIA have evolved relative to multiple factors, including regulatory approvals and tolerability.

A practical approach to uveitis screening in children with juvenile idiopathic arthritis

BACKGROUND

Juvenile idiopathic arthritis (JIA)-associated uveitis typically presents as a silent chronic anterior uveitis and can lead to blindness. Adherence to current screening guidelines is hampered by complex protocols which rely on the knowledge of specific JIA characteristics. The Multinational Interdisciplinary Working Group for Uveitis in Childhood identified the need to simplify screening to enable local eye care professionals (ECPs), who carry the main burden, to screen children with JIA appropriately and with confidence.

METHODS

A consensus meeting took place in January 2023 in Barcelona, Spain, with an expert panel of 10 paediatric rheumatologists and 5 ophthalmologists with expertise in paediatric uveitis. A summary of the current evidence for JIA screening was presented. A nominal group technique was used to reach consensus.

RESULTS

The need for a practical but safe approach that allows early uveitis detection was identified by the panel. Three screening recommendations were proposed and approved by the voting members. They represent a standardised approach to JIA screening taking into account the patient's age at the onset of JIA to determine the screening interval until adulthood.

CONCLUSION

By removing the need for the knowledge of JIA categories, antinuclear antibody positivity or treatment status, the recommendations can be more easily implemented by local ECP, where limited information is available. It would improve the standard of care on the local level significantly. The proposed protocol is less tailored to the individual than the 'gold standard' ones it references and does not aim to substitute those where they are being used with confidence.

Integration of Genetic and Clinical Risk Factors for Risk Classification of Uveitis in Patients With Juvenile Idiopathic Arthritis

OBJECTIVE

Juvenile idiopathic arthritis (JIA)-associated uveitis (JIAU) is a serious JIA comorbidity that can result in vision impairment. This study aimed to identify genetic risk factors within the major histocompatibility complex for JIAU and evaluate their contribution for improving risk classification when combined with clinical risk factors.

METHODS

Data on single nucleotide polymorphisms, amino acids, and classical HLA alleles were available for 2,497 patients with JIA without uveitis and 579 patients with JIAU (female 2,060, male 1,015). Analysis was restricted to patients with inferred European ancestry. Forward conditional logistic regression identified genetic markers exceeding a Bonferroni-corrected significance (6 × 10-6). Multivariable logistic regression estimated the effects of clinical and genetic risk factors, and a likelihood ratio test calculated the improvement in model fit when adding genetic factors. Uveitis risk classification performance of a model integrating genetic and clinical risk factors was estimated using area under the receiver operator characteristic curve and compared with a model of clinical risk factors alone.

RESULTS

Three genetic risk factors were identified, mapping to HLA-DRB1, HLA-DPB1, and HLA-A. These markers were statistically independent from clinical risk factors and significantly improved the fit of a model when included with clinical risk factors (P = 3.3 × 10-23). The addition of genetic markers improved the classification of JIAU compared with a model of clinical risk factors alone (area under the curve 0.75 vs 0.71).

CONCLUSION

Integration of a genetic and clinical risk prediction model outperforms a model based solely on clinical risk factors. Future JIAU risk prediction models should include genetic risk factors.

Artificial Intelligence and Ophthalmic Clinical Registries

PURPOSE

The recent advances in artificial intelligence (AI) represent a promising solution to increasing clinical demand and ever limited health resources. Whilst powerful, AI models require vast amounts of representative training data to output meaningful predictions in the clinical environment. Clinical registries represent a promising source of large volume real-world data which could be used to train more accurate and widely applicable AI models. This review aims to provide an overview of the current applications of AI to ophthalmic clinical registry data.

DESIGN AND METHODS

A systematic search of EMBASE, Medline, PubMed, Scopus and Web of Science for primary research articles that applied AI to ophthalmic clinical registry data was conducted in July 2024.

RESULTS

Twenty-three primary research articles applying AI to ophthalmic clinic registries (n = 14) were found. Registries were primarily defined by the condition captured and the most common conditions where AI was applied were glaucoma (n = 3) and neovascular age-related macular degeneration (n = 3). Tabular clinical data was the most common form of input into AI algorithms and outputs were primarily classifiers (n = 8, 40%) and risk quantifier models (n = 7, 35%). The AI algorithms applied were almost exclusively supervised conventional machine learning models (n = 39, 85%) such as decision tree classifiers and logistic regression, with only 7 applications of deep learning or natural language processing algorithms. Significant heterogeneity was found with regards to model validation methodology and measures of performance.

CONCLUSIONS

Limited applications of deep learning algorithms to clinical registry data have been reported. The lack of standardized validation methodology and heterogeneity of performance outcome reporting suggests that the application of AI to clinical registries is still in its infancy constrained by the poor accessibility of registry data and reflecting the need for a standardization of methodology and greater involvement of domain experts in the future development of clinically deployable AI.

Diagnosis and Management of Non-Infectious Uveitis in Pediatric Patients

Uveitis in children accounts for 5-10% of all cases. The causes vary considerably. Classically, uveitis is distinguished according to its infectious or inflammatory origin and whether it is part of a systemic disease or represents an isolated ocular disease. It is important to highlight the specificity of certain etiologies among children such as juvenile idiopathic arthritis. The development of visual function can potentially be hindered by amblyopia (children aged < 7 years), in addition to the usual complications (synechiae, macular edema) seen in adult patients. Moreover, the presentation of uveitis in children is often "silent" with few warning signs and few functional complaints from young children, which frequently leads to a substantial diagnostic delay. The diagnostic approach is guided by the presentation of the uveitis, which can be characterized by its location, and corresponds to the initial and main site of intraocular inflammation; its presentation, whether acute or chronic, granulomatous or not; and the response to treatment. Pediatricians have an important role to play and must be aware of the various presentations and etiologies of uveitis in children. Juvenile idiopathic arthritis is the most common etiology of pediatric non-infectious uveitis, but other causes must be recognized. Promptly initiated treatment before complications arise requires early diagnosis, recognition, and treatment. Any dependence on prolonged local corticosteroid therapy justifies discussing the introduction of a corticosteroid-sparing treatment considering the risk to develop corticoid-induced glaucoma and cataracts. Systemic corticosteroid therapy can be required for urgent control of inflammation in the case of severe uveitis. Long-lasting immunosuppressive treatment and biotherapies are most often prescribed at the same time to reinforce treatment efficacy and to prevent relapse and corticosteroid dependency. We review the different causes of uveitis, excluding infection, and the diagnostic and therapeutic management aimed at limiting the risk of irreversible sequelae.

Methotrexate therapy associated with a reduced rate of new-onset uveitis in patients with biological-naïve juvenile idiopathic arthritis

OBJECTIVE

To study the effect of methotrexate (MTX) therapy on new-onset uveitis in patients with biological-naïve juvenile idiopathic arthritis (JIA).

METHODS

In this matched case-control study, we compared MTX exposure between cases with JIA-associated chronic uveitis (JIA-U) and patients with JIA and without JIA-U at the time of matching (controls). Data were collected from electronic health records of the University Medical Centre Utrecht, the Netherlands. Cases with JIA-U were matched 1:1 to JIA control patients based on JIA diagnosis date, age at JIA diagnosis, JIA subtype, antinuclear antibodies status and disease duration. The effect of MTX on JIA-U onset was analysed using a multivariable time-varying Cox regression analysis.

RESULTS

Ninety-two patients with JIA were included and characteristics were similar between cases with JIA-U (n=46) and controls (n=46). Both ever-use of MTX and exposure years were lower in cases with JIA-U than in controls. Cases with JIA-U significantly more often discontinued MTX treatment (p=0.03) and out of those who did, 50% afterwards developed uveitis within 1 year. On adjusted analysis, MTX was associated with a significantly reduced new-onset uveitis rate (HR: 0.35; 95% CI: 0.17 to 0.75). No different effect was observed between a low (<10 mg/m²/week) and standard MTX dose (≥10 mg/m²/week).

CONCLUSION

This study demonstrates an independent protective effect of MTX on new-onset uveitis in patients with biological-naïve JIA. Clinicians might consider early initiation of MTX in patients at high uveitis risk. We advocate more frequent ophthalmologic screening in the first 6-12 months after MTX discontinuation.