188 Validation of an administrative algorithm to assess SLE disease severity. (April 2019)

• Record Type: Journal Article
• Authors: Speyer, Cameron B; Li, Daniel; Guan, Hongshu; Yoshida, Kazuki; Jorge, April; Feldman, Candace H; Costenbader, Karen H
• Is Part Of: Lupus science & medicine. Volume 6(2019)supplement 1
• Page Start: A142
• Page End: A143
• Publication Date: 2019-04
• Subjects: Systemic lupus erythematosus -- Periodicals; 616.772005
• DOI: 10.1136/lupus-2019-lsm.188
• Languages: English
• ISSNs: 2398-8851

Abstract

Abstract : Background: SLE severity is heterogeneous: some patients have mild disease with rashes and arthritis, while others have severe multi-organ system involvement. It is challenging to study SLE in administrative databases given this heterogeneity. Garris et al developed an administrative claims-based SLE severity algorithm derived from elements of the SLEDAI, SLAM and BILAG instruments (Garris, J Med Econ 2013). It employs ICD-9, CPT and NDC claims over a 1 year period and classifies patients as having mild, moderate or severe disease. We sought to validate this administrative algorithm in comparison to SLEDAI scores at clinical visits. Methods: We identified 100 SLE patients followed at the Brigham and Womens Hospital (BWH) Lupus Center (2008–2010) with SLEDAI-2K (Gladman, J Rheumatol 2002) data at each visit over a 1 year period per person. We also obtained ICD-9, CPT and NDC codes for the Garris algorithm items (e.g. codes for glucocorticoids, ICD-9 codes for pericarditis) for the same year per subject. We compared Garris SLE severity to the highest SLEDAI-2K in that year. We defined the SLEDAI-2K categories of mild <3, moderate 3–6, and severe >6 as in the literature (Polachek, Arthritis Care Res 2017). We compared classification in binary categories of mild vs. moderate/severe and mild/moderate vs. severe. For each, we calculated sensitivity, specificity, and C-statistics. Results: We analyzed 377 SLEDAI-2K assessments on 100 subjects (mean 3.77 [SD 2.63]) in the BWH Lupus Cohort. For the Garris vs. highest SLEDAI-2K model, 56 of 100 subjects were classified similarly by Garris and highest SLEDAI-2K (23/36 mild, 22/34 moderate, and 11/36 severe by SLEDAI-2K). The performance characteristics compared to the highest SLEDAI-2K of the year were: C-statistics were 0.755 for mild/moderate vs. severe SLE severity and 0.740 for mild vs. moderate/severe (table). Sensitivity of the Garris algorithm compared to the highest SLEDAI-2K were 63.9% for mild vs. moderate/severe and 94.3% for mild/moderate vs. severe. Specificity was 82.8% for mild vs. moderate/severe, but 36.7% for mild/moderate vs. severe. Conclusions: The Garris algorithm, developed for use in administrative datasets, has acceptable performance for classifying SLE severity when compared to the gold standard of highest SLEDAI-2K assessment in 1 year in a Lupus Center. It may be used to classify patients in administrative datasets according to their SLE severity over 1 year. Funding Source(s): Dr. Costenbaders research is supported by NIAMS R01 AR057327 and K24 AR066109.