Despite numerous biological advances in the study of Alzheimer's disease (AD), we remain unable to reliably estimate the length of time from disease onset to the point when patients can no longer perform basic activities of daily living, require nursing home care, or die. In addition, the inherent inter-patient variability in the course of the disease makes it difficult to evaluate the results of therapeutic interventions such as drug trials. The goal of this renewal application is to maintain our efforts to develop models to predict the rate of progression and the time to reach specific outcomes in AD. Our previous studies suggested that extrapyramidal signs (EPS), myoclonus and psychotic features might be useful predictors. Over the past 4 years, we assembled a cohort of patients in the early stages of AD at 3 independent centers, initiated semiannual followup, and improved methods to assess predictive signs, potential covariates, and outcomes. Our analyses of baseline data and preliminary longitudinal analyses have validated many of our original hypotheses, allowing us to begin to develop predictive correlations between clinical signs and disease outcomes as well as algorithms for presenting this information to the clinician in a meaningful manner. Analyses have also suggested other clinical signs that may also have predictive utility. We propose to continue to follow our cohort of patients for an additional 5 years in order to better address outcomes that occur in advanced AD such as institutionalization and death. We will continue to apply our newly developed instrumentation, including measures of cognition, function, dependence, and living status, as well as measures of medical and neurological status in order to quantify the rate of disease progression and detect important disease outcomes. We will supplement our current evaluations with new measures of quality of life and cognitive function in advanced AD. We will determine the incidence of predictors and estimate their impact on subsequent disease progression. Postmortem data will be used to validate clinical diagnoses. We will investigate the Lewy body variant (LBV) of AD, which has been reported in patients who develop EPS and is associated with psychosis or a related behavioral abnormality; and determine whether LBV differs from typical AD in terms initial manifestations, progression and mortality rate. Our ultimate goal is to develop predictor models for the rate of progression of AD and for specific disease outcomes which will be suitable for application by professionals in the management of AD.
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