The SMART Safety: An empirical dataset for evidence synthesis of adverse events
Shiqi Fan,
Tianqi Yu,
Xi Yang,
Rui Zhang,
Luis Furuya-Kanamori,
Chang Xu
Affiliations
Shiqi Fan
MOE Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Anhui, China; Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Anhui, China; Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Anhui, China
Tianqi Yu
Université Paris Cité, Research Center of Epidemiology and Statistics (CRESS-U1153), INSERM, Paris, France
Xi Yang
MOE Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Anhui, China; Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Anhui, China; Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Anhui, China
Rui Zhang
MOE Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Anhui, China; Anhui Provincial Key Laboratory of Population Health and Aristogenics, Anhui Medical University, Anhui, China; Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Anhui, China
Luis Furuya-Kanamori
UQ Centre for Clinical Research, Faculty of Medicine, University of Queensland, Brisbane, Australia
Chang Xu
MOE Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Anhui, China; Corresponding author at: Ministry of Education Key Laboratory for Population Health Across-life Cycle, Anhui Medical University, Anhui, China.
Evidence synthesis serves an important role to promote informed decision-making in healthcare practice. A key issue of evidence synthesis is the approach to deal with rare adverse events and the methods to address bias of harm effects. Empirical data is essential to help methodologists and statisticians to solve the issues in evidence synthesis of adverse events. For this reason, we have established SMART Safety dataset, the largest empirical dataset of meta-analyses of adverse events. The dataset contains 151 systematic reviews with 629 meta-analyses on safety outcomes, which covers more than 2,300 randomized controlled trials and 362 harm outcomes, with 10,069 rows and 45 columns of trial level information. All information was double- or even quadra-checked and further verified by referring the original source (e.g., the full-text of the included randomized trials) to ensure high validity of the data.
