中文

Faculty

Xun Tang

Xun Tang

Xun Tang

  • Associate Professor
  • tangxun@bjmu.edu.cn
  • Xueyuan Road 38, Haidian District, Beijing, China
  • Peking University
Personal profile

Dr. Xun TANG is an Associate Professor of Epidemiology at the School of Public Health, Peking University (PKU). He earned his PhD degree in epidemiology at PKU (2008) and his Master of Health Science (MHS) degree in clinical research at Duke University (2013). His doctoral dissertation, "Family-based Study on Genetic Epidemiology of Ischemic Stroke in Chinese", won the Nomination Award of the 2010 National Excellent Doctoral Dissertation of China. Funded by the Fogarty International Center at the U.S. National Institutes of Health (NIH) Millennium Promise Awards, Dr. TANG received training in the Clinical Research Training Program at Duke during 2011-2013. Upon his return to PKU in 2013, his research interests centered on understanding the determinants of, and risk factors for, non-communicable diseases (NCDs) at the population level. His current research focuses on the prevention and prediction of cardiometabolic diseases through lifestyle and genetic factors, employing a range of epidemiological designs - observational, experimental, and theoretical - with an emphasis on incorporating mathematical methods and computational techniques in public health modelling; some papers were published in the leading peer-reviewed medical and scientific journals, such as the JAMA, Lancet Respiratory Medicine, Lancet Regional Health - Western Pacific, BMC Medicine (https://orcid.org/0000-0002-6990-0168). Dr. TANG was awarded the Second Prize of Chinese Preventive Medicine Association Science and Technology Award (2023), the Second Prize of China Huaxia Medical Science and Technology Award (2022) and the First Prize of Beijing Prevent Medical Association Science and Technology Award (2022), as a co-investigator. Dr. TANG served as the Fellow of several professional societies, such as the Evidence-Based Medicine subcommittee of the Chinese Medical Doctor Association and the NCDs Prevention and Control subcommittee of the Chinese Preventive Medicine Association. He is on the editorial board of Clinical Trials (Chinese Edition), the official journal of the Society for Clinical Trials (SCT).


Main research directions

Non-communicable Diseases (NCDs) Epidemiology, Mathematical Modelling in Theoretical Epidemiology


Representative scientific research projects

1. Principal Investigator, Dynamic Risk-based Early wArning and Monitoring system with a Wearable Electrocardiogram pAtch for cardioVascular prEvention tRial (DREAMWEAVER). Funded by the National Natural Science Foundation of China (Grant Number: 82373662) (2024/01-2027/12).

2. Principal Investigator, Cardiovascular Risk assessment and dynamIc monitoring based prevention Trial for prImary Care quALity evaLuation in Yinzhou (CRITICALLY): a stepped-wedge study. Funded by the National Natural Science Foundation of China (Grant Number: 81973132) (2020/01-2023/12).

3. Co-Investigator, Key technology of integrated online intelligent prediction and early warning for major non-communicable diseases. Funded by the National Key Research and Development Program of China (Grant Number: 2020YFC2003503) (2020/07-2023/07). (Principal Investigator: Prof. Pei Gao)

4. Co-Investigator, Cardiovascular Risk Equations for Diabetes patiEnts from New Zealand and Chinese Electronic health records (CREDENCE) study. Funded by the National Natural Science Foundation of China (Grant Number: 81961128006) (2019/07-2021/06). (Principal Investigator: Prof. Pei Gao)

5. Principal Investigator, Integrative pathway analysis and multi-locus genetic risk scores for the risk assessment of ischemic stroke in Chinese. Funded by the National Natural Science Foundation of China (Grant Number: 81573226) (2016/01-2019/12).

6. Co-Investigator, Research on risk-based health management by dynamic monitoring of the population: a case study in cardiovascular disease. Funded by the National Natural Science Foundation of China (Grant Number: 91846112) (2019/01-2019/12).  (Principal Investigator: Prof. Pei Gao)

7. Co-Investigator, Cardiovascular risk prediction for the Chinese population using big data: from discovery to application. Funded by the National Natural Science Foundation of China (Grant Number: 91546120) (2016/01-2018/12). (Principal Investigator: Prof. Pei Gao)

8. Principal Investigator, Integrative pathway analysis and family-based linkage and association studies of ischemic stroke susceptibility in Chinese. Funded by the Beijing Natural Science Foundation (Grant Number: 7162107) (2016/01-2018/12).

9. Co-Investigator, Family-based cerebral and cardiovascular diseases cohort in Northern Chinese population. Funded by the National Natural Science Foundation of China (Grant Number: 81230066) (2013/01-2017/12).  (Principal Investigator: Prof. Yonghua Hu)

10. Principal Investigator, Combined design of family-based and case-control study on stroke genetics in Chinese population. Funded by the National Natural Science Foundation of China (Grant Number: 81102177) (2012/01-2014/12).


10 representative papers

1. Li C, Liu X, Shen P, Sun Y, Zhou T, Chen W, Chen Q, Lin H, Tang X*, Gao P*. Improving cardiovascular risk prediction through machine learning modelling of irregularly repeated electronic health records. European Heart Journal - Digital Health. 2024;5(1): 30-40. [with Editorial: 2024;5(1): 6-8] (* co-corresponding authors)

2. Chen Q#, Liu Q#, Gong C#, Yin W, Mu D, Li Y, Ding S, Liu Y, Yang H, Zhou S, Chen S, Tao Z, Zhang Y*, Tang X*. Strategies to inTerrupt RAbies Transmission for the Elimination Goal by 2030 In China (STRATEGIC): a modelling study. BMC Medicine. 2023; 21:100. (* co-corresponding authors)

3. Liang J, Li Q, Fu Z, Liu X, Shen P, Sun Y, Zhang J, Lu P, Lin H, Tang X*, Gao P*. Validation and comparison of cardiovascular risk prediction equations in Chinese patients with type 2 diabetes. European Journal of Preventive Cardiology. 2023;30(12): 1293-1303. [with Editorial: 2023;30(12): 1291-1292] (* co-corresponding authors)

4. Li W, Chen J, He X, Wang J, Wei C, Tang X*, Gao P*. Stock volatility and hospital admissions for cardiovascular disease: results from the National Insurance Claims for Epidemiological Research (NICER) study. Lancet Regional Health - Western Pacific. 2023; 31:100595. (* co-corresponding authors)

5. Liu X, Shen P, Zhang D, Sun Y, Chen Y, Liang J, Wu J, Zhang J, Lu P, Lin H, Tang X*, Gao P*. Evaluation of Atherosclerotic Cardiovascular Risk Prediction Models in China: Results from the CHERRY Study. JACC: Asia. 2022; 2(1):33-43. [with Editorial: 2022; 2(1):44-45] (* co-corresponding authors)

6. Liu X#, Li Q#, Chen W, Shen P, Sun Y, Chen Q, Wu J, Zhang J, Lu P, Lin H, Tang X*, Gao P*. A dynamic risk-based early warning monitoring system for population-based management of cardiovascular disease. Fundamental Research. 2021; 1(5):534-542. (* co-corresponding authors)

7. Tang X #, Lu K#, Liu X, Jin D, Jiang W, Wang J, Zhong Y, Wei C, Wang Y*, Gao P*, Du J*. Incidence and Survival of Aortic Dissection in Urban China: Results from the National Insurance Claims for Epidemiological Research (NICER) Study. Lancet Regional Health - Western Pacific. 2021; 17:100280. [issue cover with Editorial: 2021; 17:100308] (# equal contributions)

8. Tang X, Zhang D, He L, Wu N, Si Y, Cao Y, Huang S, Li N, Li J, Dou H, Gao P*, Hu Y*. Performance of atherosclerotic cardiovascular risk prediction models in a rural Northern Chinese population: Results from the Fangshan Cohort Study. American Heart Journal. 2019; 211:34-44.

9. Lin H#, Tang X#, Shen P, Zhang D, Wu J, Zhang J, Lu P, Si Y, Gao P*. Using big data to improve cardiovascular care and outcomes in China: a protocol for the CHinese Electronic health Records Research in Yinzhou (CHERRY) study. BMJ Open. 2018; 8: e019698. (# equal contributions)

10. Wang L#, Gao P#, Zhang M, Huang Z, Zhang D, Deng Q, Li Y, Zhao Z, Qin X, Jin D, Zhou M, Tang X, Hu Y*, Wang L*. Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013. JAMA. 2017; 317(24):2515-2523. [with Comment & Response: 2017;318(16):1612-1613]