Crowson, CS

ABSTRACTThe risk of progression to end-stage kidney disease (ESKD) in patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) and glomerulonephritis (AAV-GN) remains high. At 5 years of follow-up, 14–25% of patients will evolve to ESKD, suggesting that kidney survival is not optimized in patients with AAV. The addition of plasma exchange (PLEX) to standard remission induction has been the standard of care, particularly in patients with severe renal disease. However, there is still some debate regarding which patients benefit from PLEX.A recently published meta-analysis concluded that the addition of PLEX to standard remission induction in AAV probably reduced the risk of ESKD at 12 months and that PLEX was associated with an estimated absolute risk reduction for ESKD at 12 months of 16.0% for those at high risk or with a serum creatinine >5.7 mg/dl (high certainty of important effects). These findings were interpreted as supportive of offering PLEX to patients with AAV and a high risk of progression to ESKD or requiring dialysis and are making their way into societies recommendations.However, the results of the analysis can be debated. We provide an overview on the meta-analysis as an attempt to guide the audience through how the data were generated, to comment on our interpretation of the results and to explain why we feel uncertainty remains. In addition, we would like to provide insights in two questions that we believe are very relevant to consider when addressing the role of PLEX: the role of kidney biopsy findings in the decision making of whom might benefit from PLEX and the impact of novel treatments (i.e. complement factor 5a inhibitors) in avoiding progression to ESKD at 12 months. The treatment of patients with severe AAV-GN is complex and further studies that include only patients at high risk of progression to ESKD are needed.

ObjectiveThe study objective was to identify differences in gene expression between treatment responders (TRs) and treatment non‐responders (TNRs) diagnosed with juvenile dermatomyositis (JDM).MethodsGene expression analyses were performed using whole blood messenger RNA sequencing in patients with JDM (n = 17) and healthy controls (HCs; n = 10). Four analyses were performed (A1‐4) comparing differential gene expression and pathways analysis exploiting the timing of sample acquisition and the treatments received to perform these comparative analyses. Analyses were done at diagnosis and follow‐up, which averaged 7 months later in the cohort.ResultsAt diagnosis, the expression of 10 genes differed between TRs and TNRs. Hallmark and canonical pathway analysis revealed 11 and 60 pathways enriched in TRs and 3 and 21 pathways enriched in TNRs, respectively. Pathway enrichment at diagnosis in TRs was strongest in pathways involved in metabolism, complement activation, and cell signaling as mediated by IL‐8, p38/microtubule associated protein kinases (MAPK)/extracellular signal‐regulated kinases (ERK), Phosphatidylinositol 3 Kinase Gamma (PI3Kγ), and the B cell receptor. Follow‐up hallmark and canonical pathway analysis showed that 2 and 14 pathways were enriched in TRs, whereas 24 and 123 pathways were enriched in treatment TNRs, respectively. Prior treatment with glucocorticoids significantly altered expression of 13 genes in the analysis of subjects at diagnosis with JDM as compared with HCs.ConclusionNumerous genes and pathways differ between TRs and TNRs at diagnosis and follow‐up. Prior treatment with glucocorticoids prior to specimen acquisition had a small effect on the performed analyses.

Objective To determine the association of allergic conditions with incident rheumatoid arthritis (RA), especially in relation to smoking history and anti-citrullinated peptide antibody (ACPA) status. Methods This case–control study included 3515 incident RA cases and 5429 matched controls from the Epidemiological Investigation of Rheumatoid Arthritis study 1995 to 2016, including questionnaire-based information on eight allergic conditions composed from a list of 59 unique allergies. We used logistic regression and adjusted ORs (aOR) to assess the association between allergic conditions and risk of RA, adjusting for age, sex, residential area, body mass index, education, and smoking, and stratified by smoking and ACPA. Results A history of any reported allergy was equally common in RA (n=1047, 30%) as among population controls (n=1540, 29%), aOR 1.04, 95% CI 0.95 to 1.15. Metal, respiratory, food, plant/pollen and chemical allergies were not associated with risk of RA. By contrast, statistically significant associations were observed for animal dander allergy (6% vs 5%, aOR 1.37, 95% CI 1.03 to 1.82), especially in ACPA-positive RA (aOR 1.46 95% CI 1.06 to 2.01) and for atopic dermatitis, in particular for older and ACPA-negative RA (aOR 2.33, 95% CI 1.37 to 3.96 at age 80). Never smokers with allergic rhinitis also had increased risk of developing RA (aOR 1.30, 95% CI 1.00 to 1.68). Conclusion Most common allergies do not increase risk of RA, nor do they protect against RA. However, some allergic conditions, notably animal dander allergy, atopic dermatitis and allergic rhinitis, were associated with an increased risk for RA.

Objective To characterize the incidence and prevalence of childhood‐onset systemic lupus erythematosus (SLE), and to estimate the proportion of patients who are diagnosed with SLE during childhood. Methods A cohort of patients with incident childhood‐onset SLE from 1976 to 2018 from an 8‐county region in the US were identified based on comprehensive medical record review. All patients met the European Alliance of Associations for Rheumatology (EULAR)/American College of Rheumatology (ACR) classification criteria for SLE or the ACR SLE classification criteria from 1997 at or before age 18 years. Incidence rates were estimated using Poisson methods. We estimated the childhood‐onset SLE point prevalence for January 1, 2015. Results were sex and age adjusted to the US 2000 population. Among all the SLE patients living in the 8‐county region on January 1, 2015, the proportion of patients diagnosed at ≤18 years was estimated. Results A total of 13 children were diagnosed with childhood‐onset SLE during the study period (using the EULAR/ACR definition; mean age at diagnosis 15.1 years, 85% female, 69% White). Childhood‐onset SLE overall adjusted incidence rate was 0.7 (95% confidence interval [95% CI] 0.2–1.1) per 100,000 children. The incidence rate in girls was 1.2 (95% CI 0.5–1.9) per 100,000 children, while in boys it was 0.2 (95% CI 0.0–0.5) per 100,000. The adjusted prevalence of childhood‐onset SLE was 1.1 (95% CI 0.0–3.1) per 100,000 children. The proportion of patients with SLE diagnosed as children was 9% (95% CI 6–13%). Conclusion In this population‐based study, both the incidence and prevalence rates of childhood‐onset SLE were ~1 per 100,000 children. One in 10 adults with SLE was diagnosed in childhood. More studies are needed to further characterize the epidemiology of childhood‐onset SLE in minorities.

ObjectiveTreat‐to‐target (T2T) and shared decision‐making are valued features of current guidelines for rheumatoid arthritis (RA) management. Although T2T has demonstrated value for improving RA outcomes, implementation remains inconsistent and lacks standardization and procedures for including patient input. We sought to better understand the impact of shared decisions on T2T and how treatment goal discussions between patients and providers impact RA treatment improvement and satisfaction.MethodsAn anonymous, web‐based questionnaire was presented to United States residents aged 18 years or older with a self‐reported diagnosis of RA by a medical professional with 28 questions regarding socio‐demographics, RA disease activity (DA), diagnosis, treatments, outcomes, and goals. Analyses included descriptive statistics with χ2 and rank sum tests for comparisons.ResultsThe questionnaire was completed by 907 people (mean age of 58 years; mean 11 years since diagnosis; 90% female). The majority (571; 63%) did not discuss RA treatment goals with providers. Patients engaging in treatment goal discussions with their providers were three times more likely to be satisfied with their treatment plans. Patients discussing treatment goals with their providers were more likely to have improved DA levels and 68% more likely to reach remission.ConclusionA majority of patients with RA report having no treatment goal discussion with their providers; however, these discussions are associated with greater DA improvement and treatment satisfaction. Further research should seek understanding of how shared treatment goal discussions relate to successful RA management and explore the development of practical tools to implement them in regular clinic practice as part of a T2T regimen.

Objective The link and interplay between different airway exposures and rheumatoid arthritis (RA) risk are unclear. This study was undertaken to determine whether respiratory disease is associated with development of RA, and specifically to examine this relationship by RA serostatus and smoking exposure. Methods Using data from the Epidemiological Investigation of Rheumatoid Arthritis study, this analysis included 1,631 incident RA cases and 3,283 matched controls recruited from 2006 to 2016. Linking these individuals to the National Patient Register provided information on past acute or chronic, upper or lower respiratory disease diagnoses. For each disease group, we estimated adjusted odds ratios (OR adj ) with 95% confidence intervals (95% CI) for RA, using logistic regression models adjusted for age, sex, residential area, body mass index, and education both overall and stratified by anti–citrullinated protein antibody (ACPA)/rheumatoid factor (RF) status and by smoking status. Results Respiratory disease diagnoses were associated with risk of RA, with an OR adj of 1.2 for acute upper respiratory disease (95% CI 0.8–1.7), 1.4 for chronic upper respiratory disease (95% CI 1.1–1.9), 2.4 for acute lower respiratory disease (95% CI 1.5–3.6), and 1.6 for chronic lower respiratory disease (95% CI 1.5–3.6). These associations were present irrespective of RF or ACPA status, though the association was somewhat stronger for ACPA/RF–positive than ACPA/RF–negative RA. The association between any respiratory disease and RA was stronger for nonsmokers (OR adj 2.1 [95% CI 1.5–2.9]) than for smokers (OR adj 1.2 [95% CI 0.9–1.5]). Conclusion Respiratory diseases increase the risk for both seropositive and seronegative RA, but only among nonsmokers. These findings raise the hypothesis that smoking and airway disease are associated with RA development through partly different mechanisms.

ObjectivePublished predictive models of disease outcomes in idiopathic inflammatory myopathies (IIMs) are sparse and of limited accuracy due to disease heterogeneity. Computational methods may address this heterogeneity by partitioning patients based on clinical and biological phenotype.MethodsTo identify new patient groups, we applied similarity network fusion (SNF) to clinical and biological data from 168 patients with myositis (64 adult polymyositis [PM], 65 adult dermatomyositis [DM], and 39 juvenile DM [JDM]) in the Rituximab in Myositis trial. We generated a sparse proof‐of‐concept bedside classifier using multinomial regression and identified characteristics that distinguished these groups. We conducted χ2 tests to link new patient groups with the myositis subtypes.ResultsSNF identified five patient groups in the discovery cohort that subdivided the myositis subtypes. The sparse multinomial regressor to predict patient group assignments (areas under the receiver operating characteristic curve = [0.78, 0.97]; areas under the precision‐recall curve = [0.55, 0.96]) found that autoantibody enrichment defined four of these groups: anti–Mi‐2, anti–signal recognition peptide (SRP), anti–nuclear matrix protein 2 (NXP2), and anti‐synthetase (Syn). Depletion of immunoglobulin M (IgM) defined the fifth group. Each group was associated with one subtype, with adult DM being associated with anti–Mi‐2 and anti‐Syn autoantibodies, JDM being associated with anti‐NXP2 autoantibodies, and adult PM being associated with IgM depletion and anti‐SRP autoantibodies. These associations enabled us to further resolve the current myositis subtypes.ConclusionUsing unsupervised machine learning, we identified clinically and biologically homogeneous groups of patients with IIMs, forming the basis of an integrated disease classification based on both clinical and biological phenotype, thus validating other approaches and what has been previously described.