Standard-Protocol-Guideline
Interpretation for the group standards in data management for large population-based cohorts
Yu Canqing, Liu Yaning, Lyu Jun, Bian Zheng, Tan Yunlong, Guo Yu, Tang Haijing, Yang Xu, Li Liming
Published 2019-01-10
Cite as Chin J Epidemiol, 2019, 40(1): 17-19. DOI: 10.3760/cma.j.issn.0254-6450.2019.01.005
Abstract
Precision medicine became the key strategy in development priority of science and technology in China. The large population-based cohorts become valuable resources in preventing and treating major diseases in the population, which can contribute scientific evidence for personalized treatment and precise prevention. The fundamental question of the achievements above, therefore, is how to construct a large population-based cohort in a standardized way. The Chinese Preventive Medicine Association co-ordinated experienced researchers from Peking University and other well-known institutes to write up two group standards Technical specification of data processing for large population-based cohort study (T/CPMA 001-2018) and Technical specification of data security for large population-based cohort study (T/CPMA 002-2018), on data management. The standards are drafted with principles of emphasizing their scientific, normative, feasible, and generalizable nature. In these two standards, the key principles are proposed, and technical specifications are recommended in data standardization, cleansing, quality control, data integration, data privacy protection, and database security and stability management in large cohort studies. The standards aim to guide the large population-based cohorts that have been or intended to be established in China, including national cohorts, regional population cohorts, and special population cohorts, hence, to improve domestic scientific research level and the international influence, and to support decision-making and practice of disease prevention and control.
Key words:
Cohort study; Data processing; Data security; Technical specification; Group standard
Contributor Information
Yu Canqing
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Liu Yaning
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Lyu Jun
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
Bian Zheng
Chinese Academy of Medical Sciences, Beijing 100730, China
Tan Yunlong
Chinese Academy of Medical Sciences, Beijing 100730, China
Guo Yu
Chinese Academy of Medical Sciences, Beijing 100730, China
Tang Haijing
School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081
Yang Xu
School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081
Li Liming
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China