Towards a minimal core dataset for systemic lupus erythematosus studies

构建系统性红斑狼疮研究的最小核心数据集

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Abstract

OBJECTIVE: SLE is a complex, heterogenous autoimmune disease. SLE researchers do not always collect the same data, making comparative studies difficult. We aimed to ascertain what variables SLE clinical researchers commonly collect for SLE research. Our ultimate goal is to generate a minimal core dataset for future SLE studies. METHODS: In 2020, we designed and distributed a questionnaire to members of the Systemic Lupus Erythematosus International Collaborating Clinics (SLICC) as well as additional active research centres in China. Our survey included 26 questions about the types of data that are routinely collected for research. Variables collected by ≥75% of participating respondents were used as a threshold for inclusion. RESULTS: 18 of 36 invited respondents replied (8 from USA/Canada, 5 from China and 5 from Europe). Many key variables in the domains of sociodemographics, SLE specific, comorbidities, baseline haematology/biochemistry/immunology and treatment data were collected by ≥75% respondents including the 1997 American College of Rheumatology (ACR) Classification Criteria (83%), SLE Disease Activity Index-2000 (82%), current treatment (100%), drug name, dose, frequency and start date (75-100%) and complement C3/4 (94%). A range of other items was collected by 50-<75% of respondents including SLICC 2012 Criteria (67%), SLICC/ACR Damage Index (68%) and Short Form Health Survey-36 (53%). Less than 50% of respondents collect certain items including European Alliance of Associations for Rheumatology/ACR 2019 criteria (33%), British Isles Lupus Assessment Group scores (12%) and pneumococcal vaccine status (39%). CONCLUSIONS: The frequency with which an initial set of variables is collected in SLE cohorts globally was identified and can form the basis from which to develop a core minimum dataset for SLE. Further refinement and common definitions will be needed to finalise a minimal core dataset suitable for widespread use.

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