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Abstract Number: 1097

Spatial-Time Cluster Analysis of SLE Disease Activity

George Stojan1, Anton Kvit2, Frank Curriero2 and Michelle Petri3, 1Division of Rheumatology, Johns Hopkins University, Baltimore, MD, 2Bloomberg School of Public Health, Baltimore, MD, 3Johns Hopkins University School of Medicine, Baltimore, MD

Meeting: 2018 ACR/ARHP Annual Meeting

Keywords: Disease Activity, Lupus and epidemiologic methods

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Session Information

Date: Monday, October 22, 2018

Title: Systemic Lupus Erythematosus – Etiology and Pathogenesis Poster II

Session Type: ACR Poster Session B

Session Time: 9:00AM-11:00AM

Background/Purpose:

Cluster detection is an essential tool in the public health domain with the goal of detecting anomalous clusters of disease cases. We performed a spatial-time cluster analysis of the Hopkins Lupus cohort with the goal of identifying potential spatial-time clusters of SLE organ specific disease activity.

Methods:

1844 patients who fulfilled ACR or SLICC classification criteria for SLE and who had recorded home addresses were included in the analysis. Cluster detection analysis in both space and time of disease activity expressed as Physician Global Estimate (PGA) was performed. The area utilized in this analysis was a 350 kilometer radial buffer around the Hopkins Lupus Center, and included all of Maryland, Delaware, and District of Columbia, as well as parts of Pennsylvania, New Jersey, Virginia, and West Virginia. This area was considered due to the high and consistent density of study participants. The data ranged from 1987 to 2017, with the spring, summer, fall, and winter seasons serving as time units for the temporal based analyses.

Results: CNS, renal, and joint flares have both seasonal patterns as well as large-scale multi-year trends. CNS flares clustered between Annapolis, MD and Frederick, MD between 1987 and 2000, renal flares clustered in central Maryland and northern Virginia between 2002 and 2006, and a joint flares cluster included Delaware, Delaware Bay area, and Chesapeake Bay area between 2003 and 2014. Maps were generated highlighting the study area, flares, and identified clusters from all analyses.

Conclusion:

We describe the first space-time clusters of lupus organ-specific disease activity, strongly supporting the role of environmental factors as drivers of lupus activity.


Disclosure: G. Stojan, None; A. Kvit, None; F. Curriero, None; M. Petri, None.

To cite this abstract in AMA style:

Stojan G, Kvit A, Curriero F, Petri M. Spatial-Time Cluster Analysis of SLE Disease Activity [abstract]. Arthritis Rheumatol. 2018; 70 (suppl 9). https://acrabstracts.org/abstract/spatial-time-cluster-analysis-of-sle-disease-activity/. Accessed .
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