254 Identification of damage clusters in systemic lupus erythematosus. (April 2019) - Ahn, Ga Young; Lee, Jiyoung; Won, Soyoung; Ha, Eunji; Kim, Hyoungyoung; Kim, Ji Soong; Kang, Juyeon; Nam, Bora; Bang, So-Young; Shim, Seung Cheol; Lee, Hye-Soon; Kim, Kwangwoo; et al.
Abstract : Background: Damage in SLE is an irreversible change of organ system results from SLE involvement or adverse effects of medications. Recently, the awareness and evidence of subphenotypes in SLE has been increased. In this study, thus we are to identify damage clusters and compare organ damage involvement, demographic and clinical manifestations, mortality and weighted genetic risk score (GRS) between clusters. Methods: The study was conducted from Hanyang Bae lupus Cohort. Patients whose disease duration is less than 5 years were excluded to minimize potential confounding effects of disease duration. Patients were grouped into 3 clusters based on SLICC Damage Index (SDI) at last follow-up visit using K-mean cluster analysis. Comparison of characteristics between clusters were performed using ANOVA and Chi-square test. Results: A total number of 1130 patients were analyzed. Both the last follow-up visit, musculoskeletal damage was the most frequent damage domain followed by ocular, renal and neuropsychiatric damage. Three separate damage clusters were identified. Cluster 1 included 824 (72.9%) of patients. None of patients in cluster 1 was accompanied by ocular, neuropsychiatric, renal damage and premature gonadal failure. Patients in cluster 1 had significantly less pulmonary damage than cluster 3, significantly less diabetes mellitus than cluster 2, and significantly less musculoskeletal damage than two the other clusters. Cluster 2 (n=195, 17.3%) was represented by prevalent ocular (58.0%) and renal (55.4%) damage. Patients in cluster 2 had significantly more ocular, renal damage than two the other clusters. All the patients of cluster 3 (n=111, 9.8%) was accompanied by neuropsychiatric damage (100%). Patients in cluster 3 had significantly more musculoskeletal (35.1%) damage than two the other clusters. Age of SLE diagnosis and autoantibody positivity were similar among 3 clusters. Adjusted mean SLEDAI (AMS) was highest in cluster 2 (Mean ±SD, 6.7±4.8), and mortality was highest in cluster 3. Weighted GRS showed no significant difference between clusters. Conclusions: We classified patients by patterns of damage involvement (damage cluster) within a SLE cohort. Renal and neuropsychiatric damage were the two distinct domain of damage that classified patients into 3 clinically meaningful clusters. Patients in cluster 2 (prevalent renal and glucocorticoid associated damage) had the highest AMS. The highest mortality was recognized in cluster with prevalent neuropsychiatric damage. Therefore, we should be attentive to prevent renal and neuropsychiatric damage to improve the survival. Funding Source(s): Comparison of demographic and clinical characteristics between damage clusters