大型人群队列研究数据管理团体标准解读

Interpretation for the group standards in data management for large population-based cohorts

精准医学已成为我国科学技术优先发展的重点战略,大型人群队列的建设是人群疾病防治的重要资源,其研究结果为个体化治疗和精准预防提供科学证据。因此,如何规范化的建设大型人群队列是上述工作的基础。中华预防医学会组织北京大学等单位撰写《大型人群队列研究数据处理技术规范(T/CPMA001-2018)》和《大型人群队列研究数据安全技术规范(T/CPMA002-2018)》两项团体标准。标准以"科学性、规范性、可行性、可推广性"为原则,提出了大型人群队列研究在数据标准化技术、数据清理及质控技术、数据整合技术、数据隐私保护技术和数据库安全稳定性管理技术的原则和具体要求,以指导和规范我国已建立或拟开展的大型人群队列、区域性人群队列以及特殊人群队列,促进国内科研水平的提升,增加国际影响力,最大程度的支持疾病防控的决策与实践。

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.