There is a critical shortage of biostatisticians to work on clinical and translational research teams. This proposal aims to train predoctoral students to become biostatistical scientists that will provide leadership to multidisciplinary teams in academic settings that conduct research aimed at preventing and treating heart, lung, and blood disease. The training program is innovative, rigorous, and multidisciplinary. It builds on an already strong program that provides foundational courses in statistical theory and biostatistical applications and several existing collaborations to create a Heart, Lung, and Blood Disease Clinical Trials Area of Emphasis in our PhD program. This area of emphasis will include courses in cardiac physiology, public health aspects of cardiovascular disease, advanced clinical trial design, and a journal club/seminar series that focuses on the design, analysis, and reporting of clinical trials of interventions for the prevention and treatment of heart, lung, and blood disease Each trainee with have a senior biostatistical mentor, a junior biostatistical mentor who can serve as a role model, and a senior clinical mentor with expertise in heart, lung or blood disease. We also plan to promote interactions among our trainees and young clinical researchers. Trainees will develop methods and work on applications using data from clinical trials aimed at preventing and treating heart, lung, and blood disease. They will attend statistica and medical conferences with their mentors and, in order to gain an appreciation for field work and data collection, spend 2 weeks at a clinical site participating in an ongoing clinical trial. Trainees will be supported for 3 of their 5 years in our PhD program. Support for other years will come from a heart, lung, or blood disease research project. Salary, tuition, and limited travel support is requested for 2 new predoctoral trainees in each year of the grant. Substantial institutional support for this training program has been provided by the School of Public Health and the Division of Biostatistics. This reflects the institutional commitment to multidisciplinary research in general, and the recognition of the many challenges that exist to reduce the burden of heart, lung, and blood disease in the U.S. and worldwide. There is a critical shortage of biostatisticians to provide leadership to multidisciplinary teams conducting research aimed at preventing and treating heart, lung, and blood disease. This training program addresses this shortage by establishing an area of emphasis on heart, lung, and blood disease clinical trials in an already strong PhD program that provides foundational courses in statistical theory and biostatistical applications. This innovative training program includes course work on the underlying biology and epidemiology of these diseases and mentoring from a committed faculty of biostatisticians and senior clinicians.

Public Health Relevance

There is a critical shortage of biostatisticians to provide leadership to multidisciplinary teams conducting research aimed at preventing and treating heart, lung, and blood disease. This training program addresses this shortage by establishing an area of emphasis on heart, lung, and blood disease clinical trials in an already strong PhD program that provides foundational courses in statistical theory and biostatistical applications. This innovative training program includes course work on the underlying biology and epidemiology of these diseases and mentoring from a committed faculty of biostatisticians and senior clinicians.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Institutional National Research Service Award (T32)
Project #
5T32HL129956-05
Application #
9982373
Study Section
Special Emphasis Panel (ZHL1)
Program Officer
Einhorn, Paula T
Project Start
2016-08-01
Project End
2021-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
5
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
Ma, Xiaoye; Lian, Qinshu; Chu, Haitao et al. (2018) A Bayesian hierarchical model for network meta-analysis of multiple diagnostic tests. Biostatistics 19:87-102