The Biostatistics and Data Management Core (BDMC) can be conceptualized as the lynchpin for integration of the ADC Cores and is vital to the success of the UK-ADC. Its critical roles include managing a large centralized database, consulting with ADC-affiliated researchers, and working to develop and apply innovative statistical methodology for data analysis. Data management efforts focus on collecting and storing high quality data. This focus begins with the leadership and vision and attention to detail provided by the BDMC. This core has an enviable track record of timely and accurate reporting of a high volume of data to NACC. Further, weekly Core meetings are popular with UK-ADC investigators who find that the expert advice provided by our seasoned investigators improves their success in pilot studies, grant applications, and publications. This core also participates as a full partner to the research mission of the UK-ADC emphasizing transitions and translations. One such partnership with the Clinical and Neuropathology Cores relates to clinico-pathological models of mixed dementias. A key element of this BDMC is the well established track record of developing novel methodology to analyze data collected at the UK-ADC and from other cohorts with a focus on elderly subjects'transitions to MCI and eventually dementia. The BDMC also provides training for students enrolled in the graduate programs in Gerontology, Public Health, Epidemiology and Biostatistics, Psychology, and Statistics. In keeping with the mission of the UK-ADC, faculty in this core also contribute to the dementia research community at large through service on external advisory committees, study sections, manuscript reviews, and data safety monitoring boards. The BDMC will continue these critical responsibilities through the following specific aims. 1. Maintain a centralized database of the information collected by all ADC Cores and affiliated research projects in an integrated manner. 2. Provide expertise on experimental design and statistical analysis (and developing new analytical approaches). 3. Interact dynamically with other Cores to contribute to the clinical, neuropathological, and educational/outreach missions of the ADC.

Public Health Relevance

This core provides data management and analysis support that meets the highest standards of scientific conduct. The Core is also involved facilitating AD research through collaborations with investigators and development of new methods for analyzing data.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Center Core Grants (P30)
Project #
5P30AG028383-08
Application #
8491998
Study Section
Special Emphasis Panel (ZAG1-ZIJ-5)
Project Start
Project End
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
8
Fiscal Year
2013
Total Cost
$202,151
Indirect Cost
$66,022
Name
University of Kentucky
Department
Type
DUNS #
939017877
City
Lexington
State
KY
Country
United States
Zip Code
40506
Bardach, Shoshana H; Holmes, Sarah D; Jicha, Gregory A (2018) Motivators for Alzheimer's disease clinical trial participation. Aging Clin Exp Res 30:209-212
Bardach, Shoshana H; Schoenberg, Nancy E (2018) The Role of Primary Care Providers in Encouraging Older Patients to Change Their Lifestyle Behaviors. Clin Gerontol 41:326-334
Ramsey, Christine M; Gnjidic, Danijela; Agogo, George O et al. (2018) Longitudinal patterns of potentially inappropriate medication use following incident dementia diagnosis. Alzheimers Dement (N Y) 4:1-10
Hadjichrysanthou, Christoforos; McRae-McKee, Kevin; Evans, Stephanie et al. (2018) Potential Factors Associated with Cognitive Improvement of Individuals Diagnosed with Mild Cognitive Impairment or Dementia in Longitudinal Studies. J Alzheimers Dis 66:587-600
Hanfelt, John J; Peng, Limin; Goldstein, Felicia C et al. (2018) Latent classes of mild cognitive impairment are associated with clinical outcomes and neuropathology: Analysis of data from the National Alzheimer's Coordinating Center. Neurobiol Dis 117:62-71
Zhou, Zilu; Wang, Weixin; Wang, Li-San et al. (2018) Integrative DNA copy number detection and genotyping from sequencing and array-based platforms. Bioinformatics 34:2349-2355
Burke, Shanna L; Hu, Tianyan; Fava, Nicole M et al. (2018) Sex differences in the development of mild cognitive impairment and probable Alzheimer's disease as predicted by hippocampal volume or white matter hyperintensities. J Women Aging :1-25
Barber, Justin M; Bardach, Shoshana H; Jicha, Gregory A (2018) Alzheimer Disease Clinical Trial Recruitment: Does Participation in a Brief Cognitive Screen at a Community Health Fair Promote Research Engagement? Alzheimer Dis Assoc Disord 32:333-338
Wang, Qi; Guo, Lei; Thompson, Paul M et al. (2018) The Added Value of Diffusion-Weighted MRI-Derived Structural Connectome in Evaluating Mild Cognitive Impairment: A Multi-Cohort Validation1. J Alzheimers Dis 64:149-169
Wang, Tingyan; Qiu, Robin G; Yu, Ming (2018) Predictive Modeling of the Progression of Alzheimer's Disease with Recurrent Neural Networks. Sci Rep 8:9161

Showing the most recent 10 out of 471 publications