Johns Hopkins University, Baltimore, Maryland.
Arthritis Rheumatol. 2020 Jul;72(7):1134-1142. doi: 10.1002/art.41217. Epub 2020 May 2.
To identify potential clusters of systemic lupus erythematosus (SLE) organ-specific flares and their relationship to fine particulate matter pollution (PM2.5), temperature, ozone concentration, resultant wind, relative humidity, and barometric pressure in the Hopkins Lupus Cohort, using spatiotemporal cluster analysis.
A total of 1,628 patients who fulfilled the Systemic Lupus International Collaborating Clinics classification criteria for SLE and who had a home address recorded were included in the analysis. Disease activity was assessed using the Lupus Activity Index. Assessment of rash, joint involvement, serositis, and neurologic, pulmonary, renal, and hematologic activity was quantified on a 0-3 visual analog scale (VAS). An organ-specific flare was defined as an increase in VAS of ≥1 point compared to the previous visit. Spatiotemporal clusters were detected using SaTScan software. Regression models were used for cluster adjustment and included individual, county-level, and environmental variables.
Significant clusters unadjusted for environmental variables were identified for joint flares (P < 0.05; n = 3), rash flares (P < 0.05; n = 4), hematologic flares (P < 0.05; n = 3), neurologic flares (P < 0.05; n = 2), renal flares (P < 0.001; n = 4), serositis (P < 0.001; n = 2), and pulmonary flares (P < 0.001; n = 2). The majority of the clusters identified changed in significance, temporal extent, or spatial extent after adjustment for environmental variables.
We describe the first spatiotemporal clusters of lupus organ-specific flares. Seasonal, as well as multi-year, cluster patterns were identified, differing in extent and location for the various organ-specific flare types. Further studies focusing on each individual organ-specific flare are needed to better understand the driving forces behind these observed changes.
利用时空聚类分析，在霍普金斯狼疮队列中识别系统性红斑狼疮（SLE）器官特异性发作的潜在聚集，并研究其与细颗粒物污染（PM2.5）、温度、臭氧浓度、主导风向、相对湿度和大气压的关系。
本研究共纳入 1628 名符合系统性红斑狼疮国际合作临床分类标准且有家庭住址记录的患者。使用狼疮活动指数评估疾病活动度。皮疹、关节受累、浆膜炎以及神经、肺、肾和血液学活动的评估均采用 0-3 视觉模拟量表（VAS）量化。器官特异性发作定义为与前一次就诊相比 VAS 增加≥1 分。使用 SaTScan 软件检测时空聚类。回归模型用于聚类调整，包括个体、县一级和环境变量。
在未调整环境变量的情况下，确定了关节发作（P<0.05；n=3）、皮疹发作（P<0.05；n=4）、血液学发作（P<0.05；n=3）、神经发作（P<0.05；n=2）、肾发作（P<0.001；n=4）、浆膜炎（P<0.001；n=2）和肺发作（P<0.001；n=2）的显著聚类。在调整环境变量后，大多数确定的聚类在显著性、时间范围或空间范围上发生了变化。
我们描述了狼疮器官特异性发作的首次时空聚类。确定了季节性和多年的聚类模式，不同器官特异性发作类型的范围和位置不同。需要进一步研究每个器官特异性发作，以更好地了解这些观察到的变化背后的驱动因素。
