title: Early detection of Alzheimer disease: methods, markers, and misgivings.
abstract: There is at present no reliable predictive test for most forms of Alzheimer disease (AD). Although some information about future risk for disease is available in theory through ApoE genotyping, it is of limited accuracy and utility. Once neuroprotective treatments are available for AD, reliable early detection will become a key component of the treatment strategy. We recently conducted a pilot survey eliciting attitudes and beliefs toward an unspecified and hypothetical predictive test for AD. The survey was completed by a convenience sample of 176 individuals, aged 22-77, which was 75% female, 30% African-American, and of which 33% had a family member with AD. The survey revealed that 69% of this sample would elect to obtain predictive testing for AD if the test were 100% accurate. Individuals were more likely to desire predictive testing if they had an a priori belief that they would develop AD (p = 0.0001), had a lower educational level (p = 0.003), were worried that they would develop AD (p = 0.02), had a self-defined history of depression (p = 0.04), and had a family member with AD (p = 0.04). However, the desire for predictive testing was not significantly associated with age, gender, ethnicity, or income. The desire to obtain predictive testing for AD decreased as the assumed accuracy of the hypothetical test decreased. A better short-term strategy for early detection of AD may be computer-based neuropsychological screening of at-risk (older aged) individuals to identify very early cognitive impairment. Individuals identified in this manner could be referred for diagnostic evaluation and early cases of AD could be identified and treated. A new self-administered, touch-screen, computer-based, neuropsychological screening instrument called Neurobehavioral Evaluation System-3 is described, which may facilitate this type of screening.
authors.affiliation: Memory Assessment Clinic, College of Health and Human Sciences, Georgia State University, Atlanta 30303, USA.
authors.forename: R C
authors.initials: RC
authors.lastname: Green
authors.forename: V C
authors.initials: VC
authors.lastname: Clarke
authors.forename: N J
authors.initials: NJ
authors.lastname: Thompson
authors.forename: J L
authors.initials: JL
authors.lastname: Woodard
authors.forename: R
authors.initials: R
authors.lastname: Letz
mesh_terms: D000328:Adult; D000368:Aged; D000544:Alzheimer Disease / Q000175:diagnosis / Q000503:physiopathology / Q000517:prevention & control / Q000523:psychology; D001294:Attitude to Health; D015415:Biomarkers; D001921:Brain / Q000503:physiopathology; D003936:Diagnosis, Computer-Assisted; D005260:Female; D019538:Health Care Surveys; D006801:Humans; D008297:Male; D008403:Mass Screening / Q000379:methods / Q000523:psychology; D008875:Middle Aged; D009483:Neuropsychological Tests; D010865:Pilot Projects; D011237:Predictive Value of Tests; D012044:Regression Analysis
chemical_list: D015415:Biomarkers