DISCOVERY - Statistics and Analysis Core

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ABSTRACT (STATISTICS CORE) The Statistical Core, led by Drs. Gottesman and Wruck, will provide key analytic plans and completion of key analyses, power and sample size calculations, and design of the cognitive evaluation and cognitive outcome assessment. This core will support the DISCOVERY Network application and associated cores in the design of the study and also for the detailed cognitive measurement that is a key component of the overall study design, as well as in the ultimate evaluation and communication of the final study results. This Core will facilitate the study aims, and for its cognitive assessments and classification, it will use methods previously used in the Atherosclerosis Risk in Communities (ARIC) study, where the Core PIs Drs. Gottesman and Wruck have previously collaborated, and which are relevant to disparity populations in the assessment of long-term cognitive trajectories and outcomes. In addition to standard methods to consider, time-to-dementia and longitudinal cognitive trajectory analyses, this Core will propose novel methods for predictive modeling, including the use of machine learning and deep learning techniques. The DISCOVERY Statistics Core will: 1) develop and implement a feasible neurocognitive battery at the DISCOVERY Network clinical sites, with repeated measurements over at least a 2-year follow-up period; 2) conduct adjudication of cognitive events, including MCI and dementia, using the neurocognitive battery described in Aim 1, and to perform validation of dementia classification using the shorter battery in those participants undergoing both the shorter and more comprehensive battery; 3) contribute statistical expertise to the design and operation of the DISCOVERY project. This will include power calculations and sampling plans to ensure optimal representation of disparity populations and stroke subtypes for the overall cohort and for sub-studies, semi-annual quality control checks of study data, a quality assurance plan for the neurocognitive battery, and statistical input on OSMB reports; 4) develop an analytic strategy and perform statistical analyses for the specific aims and sub-aims of the DISCOVERY project. Statistics core investigators will provide methodological expertise in analysis of time-to-event endpoints (dementia, MCI); cognitive change analyses; domain-specific performance and change analyses; and novel machine learning approaches to predictive modeling of PSCID, incorporating neuroimaging, biomarker, “omics” and cognitive longitudinal measurements. Through this Core, state-of-the-art cognitive measurement methods and statistical analysis methodologies will allow unbiased consideration of cognitive outcomes in this proposed cohort of stroke patients.