With the advent of international precision medicine initiatives, it is important to evaluate existing large-scale studies to inform future investigation. This study sought to review, describe, and evaluate all large-scale cardiovascular disease (CVD) studies completed in China. We undertook a review of all large-scale CVD studies completed in China to describe and evaluate their design, implementation, and dissemination in published medical reports. Seventeen studies met the inclusion criteria. There were substantial variations in study design, geographic location, and data collection. Most studies lacked standard study names, did not publish their methods, and provided no publicly available data. Few studies included underdeveloped regions or minority groups. Most published articles contained only descriptions of the average population at risk of CVD, and no study predicted individual CVD risk or identified people at high risk. Future CVD studies in China may need to incorporate stronger systematic data collection methods, increased data transparency, clearer documentation, and standard study names to most gain from China's burgeoning field of CVD research.

Highlights

• In seeking large epidemiologic studies of CVD and its risk factors in China, 17 large-scale studies with populations of approximately 100,000 or more were identified. Substantial variation existed in study design, geographic location, follow-up length, funding sources, and data collection methods.
• A majority of the studies lacked standard study names and did not publish method papers, and most provided no publicly available data or public data acquisition procedures, which hindered the systematic identification, collection, and evaluation of accurate information regarding study design and methodology.
• Few studies enrolled participants from underdeveloped regions, migrant workers, young people, or minority groups.
• Most of the published articles contained only descriptions of the average population at risk of CVD, and no study predicted individual CVD risk or identified people at high risk.
• Stronger systematic data collection methods, increased data transparency, clearer documentation, and standard study names might be incorporated in order to gain the most from the devoted effort from both researchers and participants.