Validity of a claim-based algorithm for classifying disease activity levels using Systemic Lupus Erythematosus Disease Activity Index 2000 in Korean patients with systemic lupus erythematosus

Abstract

Objective: To validate algorithms for classifying disease activity in patients with systemic lupus erythematosus (SLE) using Korean claims data. Methods: We used data from a prospective cohort of SLE patients enrolled at a single academic center between October 2014 and August 2020. Disease activity was assessed at each visit using the Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K), with the annual average score serving as the gold standard. Three claims-based algorithms incorporating diagnostic codes for comorbidities and medication use were evaluated: (1) a previously established model including SLE-related comorbidities, immunosuppressants, and oral glucocorticoids, (2) a modified version incorporating intravenous glucocorticoids, and (3) a version with adjusted glucocorticoid dosage criteria (5 mg) to better identify mild to moderate disease. The performance of each algorithm in classifying mild disease activity—defined as SLEDAI-2K <3—was assessed by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value, and the area under the curve. Results: A total of 151 patients were included. The mean age was 34.5±8.7 years, and 94.7% were female. The mean initial SLEDAI-2K score was 3.6±2.6. The PPV for identifying mild disease activity ranged from 75.9% to 77.2%, with Algorithm 3 demonstrating the highest PPV. However, incorporating intravenous glucocorticoids or adjusting dosage thresholds did not result in further improvement. Conclusion: A claims-based algorithm using diagnostic and medication codes demonstrated a PPV of 77.2% for classifying mild disease activity in SLE. This approach may offer a practical method for disease activity assessment in Korean claims-based research.