Crowson, Cynthia S.

Objective To evaluate the efficacy of cytokine‐directed therapies in VEXAS (vacuoles, E1 enzyme, X‐linked, autoinflammatory somatic) syndrome using previously proposed treatment response criteria. Methods All patients with genetically confirmed VEXAS syndrome who received targeted therapies with JAK inhibitors (JAKi), tumor necrosis factor α inhibitors (TNFαi), or interleukin‐1 (IL‐1) or IL‐6 inhibitors were identified. Clinical and biochemical data were recorded for patients at time of targeted therapy initiation, and at 3‐, 6‐, and 12‐month follow‐up time points. Treatment response was labeled as complete response (CR; normalization of C‐reactive protein [CRP], prednisone <10 mg/day, and resolution of disease activity), partial response (PR; >50% improvement in CRP, >50% prednisone dose reduction, improvement or resolution of disease features), treatment failure (TF; worsening CRP, increasing prednisone, worsening of disease features), or no response (not meeting criteria for CR, PR, or TF). Results Overall, 52 patients received an IL‐1i, IL‐6i, or JAKi therapy. At six‐month follow‐up, 3 of 19 IL‐6i patients experienced CR, 4 of 19 experienced PR, and 7 of 19 experienced TF. 2 of 17 patients receiving JAKi experienced CR, 3 of 17 experienced PR, and 6 of 17 experienced TF. No patients receiving IL‐1i or TNFαi experienced CR, and only 1 of 5 IL‐1i patients experienced PR. Among those still receiving biologic therapy at 12 months, only 1 of 11 receiving IL‐6i and 0 of 7 receiving JAKi experienced CR. Conclusion IL‐6i and JAKi therapies demonstrated limited, unsustained efficacy for management of VEXAS syndrome. IL‐1i and TNFαi therapies were not efficacious. Useful application of previously reported treatment response criteria was demonstrated, but future incorporation of hematologic parameters may be beneficial.

ABSTRACT Background Mobility functional status is inconsistently recorded in electronic health records. Recent advances in Large Language Models (LLMs) enable automated extraction of functional information from unstructured clinical notes. Leveraging a validated functional LLM with high performance in mobility extraction, we aimed to study the association between LLM‐derived mobility functional status and clinical outcomes, including emergency department (ED) visits, hospitalizations, and mortality. Methods Individuals aged 60 years and older enrolled in the Mayo Clinic Study of Aging, with documented clinical notes in 2022 were included. Individuals without any identifiable functional information were excluded. The LLM‐derived mobility functional status categorized mobility as impaired or unimpaired, across the five mobility domains as classified by International Classification of Functioning, Disability, and Health. Clinical outcomes in 2023 were extracted from the Rochester Epidemiology Project database. Logistic regression models assessed associations between mobility impairment and outcomes, adjusted for age, sex, Elixhauser comorbidity index, and education. Results Three thousand three hundred thirty‐seven individuals were screened, of whom three hundred forty‐three had no functional information. Two thousand nine hundred ninety‐four individuals were analyzed. 79.4% had at least one mobility impairment. Higher mobility impairment is associated with older age and greater Elixhauser comorbidity. Individuals with 3 or more impairments had an increased adjusted odds of ED visits (Adjusted Odds Ratio (aOR): 2.18 (1.64, 2.90)) and hospitalizations (aOR: 2.35 (1.51, 3.65)) compared to unimpaired individuals ( p < 0.001), while mortality did not demonstrate a significant association with mobility impairment. Conclusion LLM‐derived mobility functional status assessment was associated with ED visits and hospitalization, but not with all‐cause mortality after adjustment. Prospective validation and evaluation of incremental discrimination, calibration, and clinical utility are needed before clinical implementation.

Objective The aim of this study was to compare infection‐related hospitalization risk among patients with nonrenal systemic lupus erythematosus initiating commonly used immunosuppressants. Methods We emulated a target trial using Optum Labs Data Warehouse claims to compare the risk of infection‐related hospitalization among patients initiating azathioprine, belimumab, methotrexate, or mycophenolic acid analogues (MPAAs) between March 2011 and September 2023. We excluded patients with prior lupus nephritis, solid‐organ or bone marrow transplantation, or rituximab/cyclophosphamide exposure. The primary outcome was time to first infection‐related hospitalization using intention‐to‐treat (ITT) and per‐protocol (PP) analyses. We applied inverse probability of treatment weighting to account for baseline covariates and fitted marginal structural Cox models incorporating time‐varying monthly glucocorticoid dose during follow‐up. Results Among 6,168 patients, 24‐month cumulative incidence of infection‐related hospitalization was 10% (95% confidence interval [CI] 8–12) for azathioprine, 8% (95% CI 5–10) for belimumab, 10% (95% CI 8–11) for methotrexate, and 13% (95% CI 10–15) for MPAAs. In ITT analyses, MPAAs had higher risk than belimumab (hazard ratio [HR] 1.55, 95% CI 1.07–2.25) and methotrexate (HR 1.32, 95% CI 1.04–1.68). In PP analyses, azathioprine (HR 2.04, 95% CI 1.01–4.16) and MPAAs (HR 2.27, 95% CI 1.11–4.62) had higher risk compared with belimumab. After accounting for time‐varying monthly glucocorticoid dose, between‐treatment differences were no longer significant. Conclusion Initial differences in the infection‐related hospitalization risk were attenuated after accounting for time‐varying glucocorticoid exposure. These findings highlight glucocorticoid exposure as an important factor associated with serious infection risk while recognizing that postbaseline glucocorticoid use may reflect both evolving disease activity and a pathway through which therapies influence infection risk. image

Objective Epidemiologic estimates for age of systemic lupus erythematosus (SLE) diagnosis are limited, particularly for men and racial and ethnic subpopulations in the United States. Leveraging the Centers for Disease Control and Prevention (CDC) National Lupus Registry network of population‐based SLE registries, meta‐analyses were performed estimating age‐specific incidence of SLE by sex, race, and ethnicity. Methods The CDC network of SLE registries includes five state‐based registries, plus a sixth Indian Health Service registry. Incidence periods spanned calendar years 2002‐2018. Registries provided age‐specific incidence of SLE, fulfilling the American College of Rheumatology (ACR) SLE classification criteria, per 100,000 person‐years, stratified by sex, race, and ethnicity for the meta‐analyses. Results Incidence rates among women were highest for those aged 30‐39 (12.7, 95%CI: 9.5‐16.8), while rates among men were highest for those aged 60‐69 (2.1, 95%CI: 1.3‐3.4). Black women aged 20‐39 had the highest SLE incidence rates (23.6, 95%CI: 20.7‐26.8). Among women diagnosed with SLE before age 20, incidence was highest among Asian (6.5, 95%CI: 2.8‐15.2) individuals. Among women diagnosed with SLE after age 60, incidence was highest among American Indian/Alaska Native (9.4, 95%CI: 3.4‐15.4) individuals. Weighted percentages show 10.0% of those with SLE were diagnosed before age 20, while 15.1% were diagnosed after age 60. The largest proportion of individuals with SLE, 22.1%, were diagnosed between 30‐39 years. Conclusions This study provides comprehensive sex‐ and race‐specific estimates of age at SLE diagnosis. The substantial later in life SLE incidence among men and disease burden in pediatric and older populations should raise awareness in considering SLE in the differential diagnosis in previously underrecognized groups.

Abstract Objective This study evaluated sequential multi-site fine-tuning of large language models (LLMs), simulating incremental deployment across institutions for extracting mobility functional status from unstructured clinical notes. Materials and Methods We assembled a corpus of 600 clinical notes from 3 institutions, yielding 3810 annotated note sections (1200 training; 2610 testing). Building upon our previously established LLM mobility extraction pipeline, which utilized optimized prompt engineering, we applied parameter-efficient low-rank adaptation (LoRA) fine-tuning. We evaluated sequential multi-site fine-tuning, where the model is trained locally and only the updated LoRA weights are transferred to the next site. We compared this against joint fine-tuning, which requires pooling all multi-site patient data centrally before training. Performance was measured by micro F1-scores for 2 distinct subtasks: mobility extraction and impairment classification. Results Sequential multi-site fine-tuning yielded comparable results to centralized joint fine-tuning for mobility extraction (F1, 0.861 vs 0.894) and impairment classification (F1, 0.912 vs 0.900). Both sequential and joint fine-tuning outperformed an untuned 70B model. Additionally, single-site LoRA models showed robust cross-site generalization. Discussion Sequential multi-site fine-tuning offers a resource-friendly approach to adapt LLMs to clinical environments. By retaining previously acquired knowledge without severe interference, this strategy allows for local fine-tuning at each institution without the need to pool or share sensitive patient data required for joint fine-tuning. Conclusion Sequential multi-site fine-tuning provides a viable solution for the scalable, incremental deployment of LLMs across institutions, showing promising generalizability for clinical information extraction from electronic health record narratives.

Objective We aim to identify risk factors to enable stratification of patients' susceptibility to inflammatory arthritis immune‐related adverse events (IA‐irAEs). This retrospective study mainly examines whether preexisting osteoarthritis (OA) increases the likelihood of de novo IA‐irAEs. Methods The prevalence of OA among immune checkpoint inhibitor (ICI)–treated patients who developed IA‐irAE, those who developed other types of irAEs but not IA (non‐IA irAEs), and those who did not develop any irAEs (non‐irAEs) were compared. Electronic medical records were reviewed to extract demographic, clinical, and laboratory data. Group comparisons and logistic regression analyses were performed. Results A total of 181 de novo IA‐irAE patients, 140 non‐IA irAE patients, and 170 non‐irAE patients were included. The prevalence of OA was significantly higher in the IA‐irAE group (69%) than in the non‐IA irAE group (48%) and the non‐irAE group (48%) (both P < 0.001). The IA‐irAE group demonstrated a higher frequency of multisite OA, with more predominant hand involvement (62%) than the non‐IA irAE with OA group (13%) and the non‐irAE with OA group (13%) (both P < 0.001). A family history of autoimmune disease (AID) (odds ratio [OR] 2.03, 95% confidence interval [CI] 1.02–4.05), preexisting OA (OR 2.88, 95% CI 1.85–4.52), and melanoma (OR 2.63, 95% CI 1.56–4.47) were identified as risk factors for the development of IA‐irAE. Conclusion OA was more prevalent among ICI‐treated patients developing IA‐irAE than those who were not. Hand OA was the most common OA pattern in IA‐irAE patients. Preexisting OA, melanoma, and a family history of AID were associated with IA‐irAE.

Abstract Rationale Interstitial lung disease (ILD) affects ∼50% of patients with systemic sclerosis (SSc) and is a leading cause of mortality. Visual assessment of ILD extent and morphologies, including ground-glass opacities (GGO) and reticular densities (RD), suffers from poor interobserver agreement, limiting prognostic consistency. CALIPER Quantitative CT (QCT) provides reproducible volumetric measures of parenchymal and vascular features. This study evaluated baseline QCT-derived lung features for association with transplant/mortality risk in SSc-ILD. Methods A retrospective cohort of SSc patients (≥18 years) seen at an academic center from 2007-2018 was identified using ICD codes, with ACR/EULAR 2013 SSc criteria confirmed by chart review. Inclusion required ILD on high-resolution CT (HRCT) ±2 years of SSc diagnosis, and PFTs ±6 months of HRCT. CALIPER quantified volumes of normal lung, GGO, RD, hyperlucency, honeycombing (HC), and pulmonary vascular-related structures (PVRS), which are expressed as percentages of total lung volume. Right heart catheterization confirmed pulmonary hypertension (PH) defined by 2022 ESC/ERS criteria (Eur Heart J, 2022). Cox hazards models assessed associations with combined mortality/transplant outcome, a priori adjusted for age, sex, diffuse SSc subtype, ILD duration, and PH (Column B), and further adjusted for baseline percent predicted FVC (ppFVC) and ppDLCO (Column C)(Table 1). Results Of 132 SSc-ILD patients, median SSc and ILD disease durations at HRCT were 1.4 (0.6, 2.4) and 0.0 (0.0, 0.5) years. Median feature percentages: total ILD 13.0% (IQR: 6.4, 21.0), GGO 10.2% (4.6, 16.9), RD 1.9% (0.8, 3.7), HC 0.03% (0.00, 0.09), PVRS 3.2% (2.3, 4.1). Median ppFVC was 81.1% (69.4, 92.6), and ppDLCO 60.0% (46.0, 75.7); 21 patients had PH. There were 2 transplants and 45 deaths. Every 5% increase in baseline total ILD and GGO associated with 22% (HR 1.22; 95% CI 1.12-1.33) and 24% (1.24; 1.12-1.36) higher risk of transplant/mortality on unadjusted models (Column A), respectively, remaining significant after a priori (CB) and full adjustment (CC)(Table 1). Every 1% increase in RD and PVRS conferred 19% (1.19; 1.08-1.31) and 33% (1.33; 1.08-1.63) higher risk of transplant/mortality in unadjusted models (CA); RD retained significance after a priori adjustment (1.17; 1.03-1.33), while PVRS trended non-significant in adjusted models. Conclusions In early SSc-ILD, QCT-derived GGO, RD, and PVRS provide robust prognostic value for mortality/transplant risk assessment, with small increases in baseline severity—at or below visual detection thresholds—associating with clinically meaningful risk increases. These findings support integrating baseline QCT biomarkers into risk stratification beyond clinical and PFT measures. This abstract is funded by: Rheumatology Research Foundation

The underlying immunopathogenesis of inflammatory arthritis (IA) immune-related adverse event (irAE) remains obscure. Unlike rheumatoid arthritis (RA), where autoantibodies and B cell dysfunction are central features, the contribution of humoral immunity to IA-irAE is unclear. Here, we performed immunophenotyping of peripheral blood from patients with IA-irAE and compared them with patients with seronegative RA, immune checkpoint inhibition–treated patients without irAE, and healthy controls. IA-irAE was marked with increased cytotoxic gene expression and metabolic activation in T cells and reduced CXCR3 and CCR6 expression in CD4 + T cells. Contrary to seronegative RA, patients with IA-irAE displayed no substantial elevation in autoantibody levels or atypical CD11c + CD21 − B cells. IA-irAE was further characterized by elevated levels of interleukin-6 (IL-6), IL-12, and type I interferon, which correlated with the T cell activation phenotypes. Together, our findings define IA-irAE as a disease with certain immunological features distinctive from RA, representing a potentially T cell–driven, autoantibody-independent autoimmunity. These results offer insights into immune tolerance breakdown and therapeutic targeting in irAEs.