Comparison of an administrative algorithm for SLE disease severity to clinical SLE Disease Activity Index scores

Abstract

Systemic lupus erythematosus (SLE) severity, reflecting both disease intensity and duration, is heterogeneous making it challenging to study in administrative databases where severity may confound or mediate associations with outcomes. Garris et al. developed an administrative claims-based algorithm employing claims over a 1-year period to classify SLE severity as mild, moderate or severe. We sought to compare this administrative algorithm to a measure of SLE activity, the SLE Disease Activity Index-2000 (SLEDAI-2K) score at clinical visits. We identified 100 SLE patients followed in the Brigham and Women’s Hospital (BWH) Lupus Center (in 2008–2010) with SLEDAI-2K scores at each visit over a 1-year period per person. We obtained data for the Garris algorithm for the same year per subject. We compared Garris SLE severity to the highest SLEDAI-2K in that year, with SLEDAI-2K categories of mild < 3, moderate 3–6, and severe > 6. We compared classification using weighted kappa statistics, and positive and negative predictive values (PPV, NPV). We also assessed the binary comparison of mild vs. moderate/severe. We calculated sensitivity, specificity, and McNemar’s test. We analyzed 377 SLEDAI-2K assessments (mean 3.8 [SD 2.6] per subject/year). For classifying moderate/severe vs. mild SLE severity, the sensitivity was 85.7%, specificity 67.6%, PPV 81.8% and NPV 73.5%. The Garris algorithm for classifying SLE severity in administrative datasets had moderate agreement for classification of mild vs. moderate/severe SLE activity assessed by SLEDAI-2K assessments in an academic lupus center. It may be a useful tool for classifying SLE severity in administrative database studies.