The Data Management and Statistics Core provides the database and statistical support for research conducted in conjunction with the ADRC, including local projects and collaborative efforts with other ADCs and with national AD research initiatives. This includes database development and maintenance, data quality control and monitoring, study design and planning, and data analysis and interpretation. The Core will ensure adherence to the highest standards of database and statistical practice. Development of novel study designs to maximize the efficiency of early disease trials is a major research focus. A new focus of the Core is the training of biostatisticians with expertise in statistical methods that are necessary to solve analytic issues that arise in laboratory, clinical and epidemiologic studies of AD, and the training of physician- scientists with a mastery of epidemiologic and biostatistical principles of study design and clinical research. An additional new focus of the Core is development and deployment of novel software for integrating multimodal data and interpretations. This takes two forms: advanced longitudinal and multimodal database software, and software to support web-based collaboration amongst ADRC and collaborating researchers.
The specific aims of the Core are: (1) To provide computing and (a) database management and (b) statistical consultation and collaboration to the research projects, pilot projects and the cores of the ADRC;(2) To facilitate local research efforts, collaborations between and among ADCs, and with national AD research initiatives, including NACC. This includes preparing the Uniform Data Set (UDS) for transmission to NACC; (3) To develop, implement and share novel specialized software for multimodal database integration and query and provide training for users in the software and database;(4) To provide software support for the ADRC web page, including web-based collaboration amongst ADRC researchers;and to provide training for users in the software;(5) To train students in the Biostatistics and Epidemiology Departments at Harvard School of Public Health in statistical and epidemiologic methods that are required for AD studies. Also, to train junior clinical investigators in the principles and methods of clinjcal AD research;(6) To develop efficient clinical trial designs for the study of early stage patients, drawing upon analyses of existing cohorts with long follow-up, with validation in the NACC database;(7) To develop methods for analysis of observational data that properly account for selection bias due to nonrandom ascertainment and complex forms of truncation.

Public Health Relevance

}: The Data Management and Statistics Core is responsible for entering, managing, transferring, and analyzing all ADRC related data. The Core trains investigators to use its database software and web-based tools. It also provides training in statistical methods for the design and analysis of Alzheimer's studies.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Specialized Center (P50)
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Special Emphasis Panel (ZAG1-ZIJ-4)
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Massachusetts General Hospital
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Makaretz, Sara J; Quimby, Megan; Collins, Jessica et al. (2018) Flortaucipir tau PET imaging in semantic variant primary progressive aphasia. J Neurol Neurosurg Psychiatry 89:1024-1031
Gallagher, Damien; Kiss, Alex; Lanctot, Krista et al. (2018) Depression and Risk of Alzheimer Dementia: A Longitudinal Analysis to Determine Predictors of Increased Risk among Older Adults with Depression. Am J Geriatr Psychiatry 26:819-827
Davis, Jeremy J (2018) Performance validity in older adults: Observed versus predicted false positive rates in relation to number of tests administered. J Clin Exp Neuropsychol 40:1013-1021
Haaksma, Miriam L; Calderón-Larrañaga, Amaia; Olde Rikkert, Marcel G M et al. (2018) Cognitive and functional progression in Alzheimer disease: A prediction model of latent classes. Int J Geriatr Psychiatry 33:1057-1064
Wimalaratne, Sarala M; Juty, Nick; Kunze, John et al. (2018) Uniform resolution of compact identifiers for biomedical data. Sci Data 5:180029
Lin, Ming; Gong, Pinghua; Yang, Tao et al. (2018) Big Data Analytical Approaches to the NACC Dataset: Aiding Preclinical Trial Enrichment. Alzheimer Dis Assoc Disord 32:18-27
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
Woerman, Amanda L; Kazmi, Sabeen A; Patel, Smita et al. (2018) Familial Parkinson's point mutation abolishes multiple system atrophy prion replication. Proc Natl Acad Sci U S A 115:409-414
Woerman, Amanda L; Kazmi, Sabeen A; Patel, Smita et al. (2018) MSA prions exhibit remarkable stability and resistance to inactivation. Acta Neuropathol 135:49-63
Kirson, Noam Y; Scott Andrews, J; Desai, Urvi et al. (2018) Patient Characteristics and Outcomes Associated with Receiving an Earlier Versus Later Diagnosis of Probable Alzheimer's Disease. J Alzheimers Dis 61:295-307

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