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Abstract
Background Previous US study presented a claims-based algorithm, consisted with comorbidities and medication information, to classify systemic lupus erythematosus (SLE) severity as mild, moderate or severe. We aimed to validate algorithms to measure SLE activity in Korean claims data.
Methods We identified SLE patients in a single academic hospital between October 2014 and August 2020. To measure SLE disease activity, we set five algorithms using diagnostic codes for comorbidities and medications: (1) previously suggested algorithm consisted of SLE-related comorbidities, immunosuppressant including rituximab, cyclophosphamide, etc., and oral glucocorticoid, (2) modified (1) by adding intravenous glucocorticoid, (3) modified (1) by adjusting glucocorticoid criteria with 55mg to differentiate between moderate and severe SLE, (4) modified (1) by adjusting glucocorticoid criteria with 5mg to differentiate between mild and moderate SLE, (5) combined algorithm (3) with (4), We assessed SLE Disease Activity Index-2000 (SLEDAI-2K) score at each visit over a year per person, and calculated average SLEDAI-2K for 1 year as gold standard. After categorizing moderate to severe ≥ 3 of SLEDAI-2K, sensitivity, specificity, positive predictive values (PPV), and negative predictive values for the algorithms to detect patients with moderate to severe SLE were estimated.
Results We included 151 patients with SLE. Their mean age was 34.5 ± 8.8, and 94.7% were female, presenting initial SLEDAI-2K score of 3.8 ± 3.2. For classifying moderate to severe SLE, the PPV of claims-based algorithm ranged from 75.86 to 77.19%. The algorithms (4) and (5) improved PPV up to 77.19%. However, the algorithms modifying glucocorticoid dose to differentiate between moderate and severe SLE or considering any prescriptions of intravenous glucocorticoid did not increase the PPV.
Conclusions The algorithm using diagnostic codes for comorbidities and medications demonstrated PPV of 77.19% to detect moderate to severe SLE. It may be a useful for classifying SLE severity in Korean claims database studies.
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