Patients who develop Alzheimer?s disease (AD) show performance declines in tests of episodic memory, executive functioning, and attention more than a decade before symptoms become apparent to their physician or family. The rate of this performance decline is the primary outcome measure in ongoing clinical trials evaluating interventions aimed at delaying AD onset. However, current clinical trials rely on measures from ?paper and pencil? tests of cognition that are manually-administered and scored, costly, inefficient, subject to examiner bias, and fail to comprehensively record and quantify test performance. Moreover, because of the limited number of licensed examiners, manual tests will be increasingly unable to meet the demand for cognitive assessments as the population ages. Although computerized tests help meet this demand by increasing the sensitivity, efficiency, comprehensiveness, and objectivity of cognitive testing, existing commercial test batteries lack the sensitivity, validity, and reliability of ?gold standard? manual assessments now used in clinical trials. In this ?fast-track? application, we propose to enhance the computerized tests of the California Cognitive Assessment Battery (CCAB), a set of empirically-validated, computerized versions of ?gold standard? manual tests. CCAB tests are more efficient, reliable, objective, and precise than their manual-test counterparts, while providing more detailed, comprehensive, and easily accessible archival records of longitudinal test performance. We will then test the enhanced CCAB?s sensitivity to longitudinal cognitive decline in older individuals, including those at increased risk of cognitive decline based on their APOE genotype. During Phase I, we will restructure the individual CCAB tests for self-administration on tablets and add automatic speech recognition to objectively score verbal responses and measure verbal-response latencies. We will also incorporate telemedical capabilities to enable examiners to interact with patients and administer tests at remote sites. During Phase II, we will develop a secure, encrypted database for hosting and analyzing anonymized data. We will compare performance on CCAB tests and equivalent manual tests, and develop regression functions for translating CCAB scores to equivalent manual test scores, and vice versa. Finally, we will evaluate the sensitivity of the CCAB tests to cognitive decline in 420 older paid volunteers, tested at six-month intervals over a two-year period. We will identify baseline performance measures, including practice effects (incidental improvements that occur when tests are repeated), that predict subsequent cognitive decline in individuals with and without genotype risk factors for AD. In addition, we will create CCAB licensing and data-management tools to provide researchers with free access to CCAB tests and anonymized data during the 4-year SBIR. Summary: Enhanced versions of the California Cognitive Assessment Battery (CCAB) will reduce the cost, expand the reach, and improve the sensitivity of tests of age- related cognitive decline in patients at risk for AD.
Alzheimer?s disease is a health care burden with enormous medical and personal cost that will affect an increasing number of Americans as the population ages. Cognitive testing plays a central role in identifying at-risk patients: declines in cognitive tests of memory and other mental functions can be detected long before the onset of dementia. Moreover, the success of clinical trials for new therapies designed to reverse Alzheimer?s pathology and slow cognitive decline depends on the sensitivity of the tests used to detect cognitive deterioration. The cognitive tests currently used are mostly ?paper-and-pencil? assessments that require manual administration. We propose to develop a set of innovative, computerized cognitive tests with greater sensitivity and reliability than manual tests, and demonstrate their increased sensitivity to cognitive decline by repeatedly testing a large group of older individuals, including some with increased genetic risk for Alzheimer?s disease.
