{
  "abstract": "Objectives The 2023 EULAR recommendations for the management of SLE endorse stratifying disease activity into mild, moderate, and severe categories to guide treat-to-target (T2T) strategies. Both SLEDAI and BILAG are suggested for this purpose, but their limitations may affect treatment guidance. We aimed to compare disease activity classification based on SLEDAI-2K and BILAG-2004.Methods This post-hoc analysis included the aggregated placebo arms from phase 2 and 3 anifrolumab trials (MUSE, TULIP-1, TULIP-2) in moderate-to-severe SLE. Physicians’ assessments (clinical and laboratory data, BILAG-2004, CLASI-A, SLEDAI-2K, and Physician Global Assessment [PhGA]) and patient-reported outcomes (PROs: LupusQoL, EQ-5D, FACIT-F, and Patient Global Assessment [PtGA]) were analyzed at week 12. The SLE-DAS was retrospectively scored. Disease activity was categorized as mild, moderate, or severe according to SLEDAI-2K (<=6, 7–12, >12) and BILAG-2004 (<=1B/C, >=2B, >=1A domains). Agreement between classifications was assessed with Cohen’s Kappa. Proportions of patients per category were compared using McNemar’s test. Differences in lupus features, disease activity, and PROs between patients classified only by SLEDAI-2K, only by BILAG-2004, or by both indices were evaluated with Kruskal-Wallis, Chi-squared, or Fisher’s exact tests.Results At week 12, disease activity classification differed substantially between indices ( figure 1). By SLEDAI-2K, 36.1% of patients were mild, 49.1% moderate, and 14.8% severe, whereas BILAG-2004 classified 56.2%, 22.4%, and 21.5%, respectively. The proportion of patients across mild and moderate categories differed significantly between tools (p<0.0001), as did the severe category (p < 0.01). Overall agreement was only fair (K=0.255, p<0.0001). Patients uniquely classified by each tool showed significant differences in disease activity (SLE-DAS and PhGA) and in several lupus features and PROs.Abstract PT7:02 Figure 1Percentages of patients in each category of disease activity according to SLEDAI-2K and BILAG-2004Conclusions SLEDAI-2K and BILAG-2004 yield markedly different disease activity classifications, potentially leading to divergent treatment decisions when applying the 2023 EULAR T2T framework. A more accurate and granular scoring system—capturing the full spectrum of disease severity while remaining feasible in clinical practice—is needed to optimize T2T strategies in SLE.Acknowledgments This publication is based on research using data from data contributors AstraZeneca that has been made available through Vivli,Inc. Vivli has not contributed to or approved, and is not in any way responsible for, the contents of this publication.",
  "authors": [
    {
      "affiliations": [
        "Faculty of Health Sciences, University of Beira Interior, Covilhã, Portugal"
      ],
      "name": "Diogo Jesus"
    },
    {
      "affiliations": [
        "School of Technology and Management, Polytechnic Institute of Viseu, Viseu, Portugal",
        "Centre for Mathematics, University of Coimbra, Coimbra, Portugal"
      ],
      "name": "Carla Henriques"
    },
    {
      "affiliations": [
        "School of Technology and Management, Polytechnic Institute of Viseu, Viseu, Portugal",
        "Research Centre in Digital Services (CISeD), Viseu, Portugal"
      ],
      "name": "Ana Matos"
    },
    {
      "affiliations": [
        "Rheumatology Unit, Department of Medicine, University of Padova, Padova, Italy"
      ],
      "name": "Andrea Doria"
    },
    {
      "affiliations": [
        "Faculty of Health Sciences, University of Beira Interior, Covilhã, Portugal",
        "HUC Lupus Clinic, Rheumatology Department, Hospitais da Universidade de Coimbra, ULS Coimbra, Coimbra, Portugal",
        "Faculty of Medicine, University of Coimbra, Coimbra, Portugal"
      ],
      "name": "Luís Inês"
    }
  ],
  "title": "PT7:02 Discordance between SLEDAI-2K and BILAG-2004 disease activity classification leads to divergent treatment decisions under EULAR 2023 recommendations: a post-hoc analysis of anifrolumab trials",
  "uid": "08141598-041f-5de1-ae1c-2a50931eaa65"
}