Diagnostic performance of classification criteria for systemic lupus erythematosus: A validation study from Singapore.

Introduction: Classification criteria for systemic lupus erythematosus (SLE) include American College of Rheumatology (ACR) 1997, Systemic Lupus Erythematosus International Collaborating Clinics (SLICC) 2012 and European Alliance of Associations for Rheumatology (EULAR)/ACR 2019 criteria. Their performance in an Asian childhood-onset SLE (cSLE) population remains unclear as the clinical manifestations differ. We aim to evaluate the diagnostic performance in a cSLE cohort in Singapore. Method: Cases were physician-diagnosed cSLE, while controls were children with mixed and undifferentiated connective tissue disease that posed an initial diagnostic challenge. Data were retrospec-tively reviewed to establish the 3 criteria fulfilled at diagnosis and over time. Results: The study population included 120 cSLE cases and 36 controls. At diagnosis, 102 (85%) patients fulfilled all criteria. SLICC-2012 had the highest sensitivity (97.5%, 95% confidence interval [CI] 92.3-99.5), while ACR-1997 had the highest specificity (91.7%, 95% CI 77.5-98.3). All criteria had diagnostic accuracies at more than 85%. Over time, 113 (94%) fulfilled all criteria. SLICC-2012 remained the criteria with the highest sensitivity (99.2%, 95% CI 95.4-99.9), while ACR-1997 had the highest specificity (75.0%, 95% CI 57.8-87.9). Only SLICC-2012 and ACR-1997 had more than 85% diagnostic accuracy over time. Using a cutoff score of ≥13 for EULAR/ACR-2019 criteria resulted in improved diagnostic performance. Conclusion: SLICC-2012 criteria had the highest sensitivity early in the disease course in this first study evaluating the SLE classification criteria performance in a Southeast Asian cSLE cohort, while the ACR-1997 criteria had the highest specificity. Using a cutoff score of ≥13 for EULAR/ACR-2019 improved the diagnostic performance.

Genetic interrogation for sequence and copy number variants in systemic lupus erythematosus.

Early-onset systemic lupus erythematosus presents with a more severe disease and is associated with a greater genetic burden, especially in patients from Black, Asian or Hispanic ancestries. Next-generation sequencing techniques, notably whole exome sequencing, have been extensively used in genomic interrogation studies to identify causal disease variants that are increasingly implicated in the development of autoimmunity. This Review discusses the known casual variants of polygenic and monogenic systemic lupus erythematosus and its implications under certain genetic disparities while suggesting an age-based sequencing strategy to aid in clinical diagnostics and patient management for improved patient care.

Anti-tumor necrosis factor (aTNF) weaning strategy in juvenile idiopathic arthritis (JIA): does duration matter?

BACKGROUND: To compare outcomes of a short and long weaning strategy of anti-tumor necrosis factor (aTNF) in our prospective juvenile idiopathic arthritis (JIA) cohort. RESEARCH DESIGN AND METHODS: JIA patients on subcutaneous adalimumab with at least 6 months of follow-up were recruited (May 2010-Jan 2022). Once clinical remission on medication (CRM) was achieved, adalimumab was weaned according to two protocols-short (every 4-weekly for 6 months and stopped) and long (extending dosing interval by 2 weeks for three cycles until 12-weekly intervals and thereafter stopped) protocols. Outcomes assessed were flare rates, time to flare, and predictors. RESULTS: Of 110 JIA patients, 77 (83% male, 78% Chinese; 82% enthesitis-related arthritis) underwent aTNF weaning with 53% on short and 47% on long weaning protocol. The total flare rate during and after stopping aTNF was not different between the two groups. The time to flare after stopping aTNF was not different (p = 0.639). Positive anti-nuclear antibody increased flare risk during weaning in long weaning group (OR 7.0, 95%CI: 1.2-40.8). Positive HLA-B27 (OR 6.5, 95%CI: 1.1-30.4) increased flare risks after stopping aTNF. CONCLUSION: Duration of weaning aTNF may not minimize flare rate or delay time to flare after stopping treatment in JIA patients. Recapture rates for inactive disease at 6 months remained high for patients who flared after weaning or discontinuing medication.

Artificial intelligence and high-dimensional technologies in the theragnosis of systemic lupus erythematosus.

Systemic lupus erythematosus is a complex, systemic autoimmune disease characterised by immune dysregulation. Pathogenesis is multifactorial, contributing to clinical heterogeneity and posing challenges for diagnosis and treatment. Although strides in treatment options have been made in the past 15 years, with the US Food and Drug Administration approval of belimumab in 2011, there are still many patients who have inadequate responses to therapy. A better understanding of underlying disease mechanisms with a holistic and multiparametric approach is required to improve clinical assessment and treatment. This Review discusses the evolution of genomics, epigenomics, transcriptomics, and proteomics in the study of systemic lupus erythematosus and ways to amalgamate these silos of data with a systems-based approach while also discussing ways to strengthen the overall process. These mechanistic insights will facilitate the discovery of functionally relevant biomarkers to guide rational therapeutic selection to improve patient outcomes.

Latent Class Analysis Identifies Distinct Phenotypes of Systemic Lupus Erythematosus Predictive of Flares after mRNA COVID-19 Vaccination: Results from the Coronavirus National Vaccine Registry for ImmuNe Diseases SINGapore (CONVIN-SING).

We recently reported that messenger ribonucleic acid (mRNA) coronavirus disease 2019 (COVID-19) vaccination was associated with flares in 9% of patients with systemic lupus erythematosus (SLE). Herein, we focused our analysis on patients from a multi-ethnic Southeast Asian lupus cohort with the intention of identifying distinct phenotypes associated with increased flares after mRNA COVID-19 vaccination. METHODS: Six hundred and thirty-three SLE patients from eight public healthcare institutions were divided into test and validation cohorts based on healthcare clusters. Latent class analysis was performed based on age, ethnicity, gender, vaccine type, past COVID-19 infection, interruption of immunomodulatory/immunosuppressive treatment for vaccination, disease activity and background immunomodulatory/immunosuppressive treatment as input variables. Data from both cohorts were then combined for mixed effect Cox regression to determine which phenotypic cluster had a higher risk for time to first SLE flare, adjusted for the number of vaccine doses. RESULTS: Two clusters were identified in the test (C1 vs. C2), validation (C1' vs. C2') and combined (C1″ vs. C2″) cohorts, with corresponding clusters sharing similar characteristics. Of 633 SLE patients, 88.6% were female and there was multi-ethnic representation with 74.9% Chinese, 14.2% Malay and 4.6% Indian. The second cluster (C2, C2' and C2″) was smaller compared to the first. SLE patients in the second cluster (C2 and C2') were more likely to be male, non-Chinese and younger, with higher baseline disease activity. The second cluster (C2″) had more incident flares (hazard ratio = 1.4, 95% confidence interval 1.1-1.9, p = 0.014) after vaccination. A higher proportion of patients in C2″ had immunomodulatory/immunosuppressive treatment interruption for vaccination as compared to patients in C1″ (6.6% vs. 0.2%) (p < 0.001). CONCLUSION: We identified two distinct phenotypic clusters of SLE with different patterns of flares following mRNA COVID-19 vaccination. Caution has to be exercised in monitoring for post-vaccination flares in patients with risk factors for flares such as non-Chinese ethnicity, young age, male gender and suboptimal disease control at the time of vaccination.