University of Nebraska Medical Center

Dr. Baojiang Chen, PhD, Research on Biostatistical Methodological Development and Applications

source: nihseniorhealth.gov

Spotlight on Research at COPH – Dr. Chen’s current research focuses on both methodological development and statistical applications to research, such as in Alzheimer’s disease (AD) studies and cancer studies.

Dr. Chen has been working on statistical methods and analyses for Alzheimer’s disease (AD) in the National Alzheimer’s Coordinating Center (NACC). Approximately 5 million people in the United States and more than 37 million people worldwide are affected by AD. With AD, a person’s memory and ability to learn and carry out daily activities such as talking and eating are gradually destroyed. As the disease progresses, individuals may also experience changes in personality and behavior. Unfortunately, there is no cure for AD, and there is no way to predict how fast the disease will progress. However, early AD diagnosis and treatment can slow the progression of symptoms. Therefore, it is desirable to identify risk factors that affect the progression of the disease. The NACC maintains a Uniform Data Set of standardized clinical and neuropathological research data collected from each of 29 National Institute on Aging-funded AD centers. This database is a valuable resource for both exploratory and explanatory AD research. It is challenging to analyze this data set because people with AD are often lost to follow-up over time due to a decline in health or death. Dr. Chen has developed innovative statistical methods to correct the estimate biases caused by non-randomly missing data and thereby provide valid inference.

Dr. Chen’s research also contributes to public health by examining characteristics of subgroups at greatest risk of progression to dementia. It is believed that disease-modifying therapies may have greater efficacy in subjects who have not yet developed AD and therefore have not experienced neuronal loss. Identifying risk factors for conversion to AD will help target interventions prior to the onset of symptoms to subjects who are at increased risk of progression. Risk factor identification may also assist in streamlining the drug development process, by targeting interventions to high risk subjects.

Baojiang Chen, PhD, is an assistant professor in the UNMC COPH Department of Biostatistics.

Leave a comment