Predictors of British Isles Lupus Assessment Group-based outcomes in patients with systemic lupus erythematosus: Analysis from the Systemic Lupus International Collaborating Clinics Inception Cohort

• Published in: Lupus 2023-08, Vol.32 (9), p.1043-1055
• Main Authors: David, Trixy, Su, Li, Cheng, Yafeng, Gordon, Caroline, Parker, Benjamin, Isenberg, David, Reynolds, John A, Bruce, Ian N
• Format: Article
• Language: English
• Subjects: Atrophy; Clinical trials; Lupus; Prediction models; Steroids; Systemic lupus erythematosus
• ISSN: 0961-2033; 1477-0962
• DOI: 10.1177/09612033231183273

Background We aimed to identify factors associated with a significant reduction in SLE disease activity over 12 months assessed by the BILAG Index. Methods In an international SLE cohort, we studied patients from their ‘inception enrolment’ visit. We also defined an ‘active disease’ cohort of patients who had active disease similar to that needed for enrolment into clinical trials. Outcomes at 12 months were; Major Clinical Response (MCR: reduction to classic BILAG C in all domains, steroid dose of ≤7.5 mg and SLEDAI ≤ 4) and ‘Improvement’ (reduction to ≤1B score in previously active organs; no new BILAG A/B; stable or reduced steroid dose; no increase in SLEDAI). Univariate and multivariate logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) and cross-validation in randomly split samples were used to build prediction models. Results ‘Inception enrolment’ (n = 1492) and ‘active disease’ (n = 924) patients were studied. Models for MCR performed well (ROC AUC = .777 and .732 in the inception enrolment and active disease cohorts, respectively). Models for Improvement performed poorly (ROC AUC = .574 in the active disease cohort). MCR in both cohorts was associated with anti-malarial use and inversely associated with active disease at baseline (BILAG or SLEDAI) scores, BILAG haematological A/B scores, higher steroid dose and immunosuppressive use. Conclusion Baseline predictors of response in SLE can help identify patients in clinic who are less likely to respond to standard therapy. They are also important as stratification factors when designing clinical trials in order to better standardize overall usual care response rates.