Screening for Alzheimer's Disease Relation to Risk, Benefit Age and Genotype October 8, 2004 J. Wesson Ashford, M.D., Ph.D. Stanford / VA Alzheimer’s Center.

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Screening for Alzheimer's Disease Relation to Risk, Benefit Age and Genotype October 8, 2004 J. Wesson Ashford, M.D., Ph.D. Stanford / VA Alzheimer’s Center VAMC, Palo Alto, California Slides at:

Why Diagnose AD Early? Safety (driving, compliance, cooking, etc.) Family stress and misunderstanding (blame, denial) Early education of caregivers of how to handle patient (choices, getting started) Advance planning while patient is competent (will, proxy, power of attorney, advance directives) Patient’s and Family’s right to know Promotes advocacy for research and treatment development Specific treatments now available –May slow underlying disease process, the sooner the better –May delay nursing home placement longer if started earlier –May prevent conversion from Mild Cognitive Impairment to AD

BRIEF CLINICAL TOOLS FOR COGNITIVE ASSESSMENT MINI-MENTAL STATE EXAM CLOCK DRAWING ANIMAL NAMING (1 minute) MATTIS DEMENTIA RATING SCALE ALZHEIMER’S DISEASE ASSESSEMENT SCALE (ADAS) ACTIVITIES OF DAILY LIVING GLOBAL CLINICAL SCALE CLINICAL DEMENTIA RATING SCALE GLOBAL DETERIORATION SCALE / FAST

Available Screening Tests MMSE min Too long 7-Minute Screen 7 – 10 min Too complex Clock Drawing Test 2 – 4 min Not sensitive Mini-cog 3 – 5 min Complex scoring, unclear adequacy Memory Impairment Screen 4 min Need for slightly shorter, easier test (a suitably accurate test that takes less than 2 minutes is not available)

Need to Develop Better Screening and Early Assessment Tools Genetic vulnerability testing (trait risk) Vulnerability factors (education, occupation, head injury) Early recognition (10 warning signs) Screening tools (6th vital sign in elderly) Positive diagnostic tests –CSF – tau levels elevated, amyloid levels low –Brain scan – PET – DDNP, Congo-red derivatives Mild Dementia severity assessments Detecting early change over time –predicting progression, measuring rate

Yesavavage et al., 2002 Markov Chain model

AAMI / MCI DEMENTIA ALZHEIMER’S DISEASE Ashford et al., 1995

Mini-Mental State Exam items

JW Ashford, MD PhD, 2001

Brief Alzheimer Screen (BAS) Repeat these three words: “apple, table, penny”. So you will remember these words, repeat them again. What is today’s date? D = 1 if within 2 days. Spell the word “WORLD” backwards S = 1 point for each word in correct order “Name as many animals as you can in 30 seconds, GO!” A = number of animals “What were the 3 words I asked you to repeat?” (no prompts) R = 1 point for each word recalled BAS = 3 x R + 2/3 x A + 5 x D + 2 x S Mendiondo et al., J Alz Dis 5:391, 2003

JW Ashford, MD PhD, 2001 Mendiondo et al., 2004

JW Ashford, MD PhD, 2003

CONCLUSIONS on the BAS A single cut-off score provides reasonable sensitivity and specificity for the diagnosis of AD within 2 – 3 minutes Two cut-off points divide the population into 3 tiers –the first cut-off indicates a low likelihood of dementia –the second indicates a high likelihood of dementia –the remaining group falls into a ‘gray area’ in need of closer scrutiny, follow-up, and more extensive testing A suitably short screen can be administered yearly to individuals over 60 y/o as a 6 th vital sign Next direction – use of IRT to locate level of impairment

MEMTRAX - Memory Test (to detect AD onset) New test to screen patients for AD: –World-Wide Web – based testing, –CD-distribution –KIOSK administration Determine level of ability / impairment Test takes about 1-minute Test can be repeated often (e.g., quarterly) Any change over time can be detected Free test is at:

Issues in Screening ROC analysis provides independent values for how the screening test values affect the normal and patient populations, then plots their relationship with respect to each other (specificity vs sensitivity respectively) The value of the test must be calculated with respect to the risk of the disease –Risk is affected by age, genotype, many other factors –Accounting for a priori probability is Bayesian analysis The cost of the applying the test and the costs of false positive and false negative results as well as the benefits of correct positive and negative results must be assessed Alzheimer’s disease is not a dichotomous diagnosis in early stages, but a continuum, which would be better assessed with a probabilistic statement, that would be better calculated from Item Response Theory Item Response Theory allows combination of many items

RELATIVE RISK FACTORS FOR ALZHEIMER’S DISEASE Family history of dementia3.5 ( ) Family history – Downs2.7 ( ) Family history - Parkinson’s2.4 ( ) Maternal age > 40 years1.7 ( ) Head trauma (with LOC)1.8 ( ) History of depression1.8 ( ) History of hypothyroidism2.3 ( ) History of severe headache0.7 ( ) NSAID use or statin use0.2 (0.05 – 0.83) Roca, 1994, t’Veldt, 2002

JW Ashford, 2004, J. Molecular Neurosci. 23:

Genes and Alzheimer’s disease (60% - 80 % of causation) Familial AD (onset < 60 y/o) (<5%) all known autosomal dominant genes relate to  amyloid –Presenilin I, II (ch 14, 1) –APP (ch 21) Non-familial (late onset) –APOE Clinical studies suggest 40 – 50% due to  4 If  is considered, may be 95% of causation Population studies suggest 10 – 20% cause Evolution over last 300,000 to 200,000 years –At least 20 other genes suspected of relating to AD Ashford & Mortimer, 2002, J. Alz. Dis. 4:1-9.

APO-E genotype and AD risk 46 Million in US > 60 y/o //// 4 Million have AD (data from Saunders et al., 1993; Farrer et al., 1997) Ashford & Mortimer, 2002, J. Alz. Dis. 4:1-9. Raber, Huang, Ashford, 2004, Neurobiol Aging. 25:

Mortality Equations t = age in years Td = time for mortality rate to double Ro = mortality rate at time zero alpha = ln(2) / Td Mortality rate u(t) R = Ro x exp (alpha x t) Survival curve s(t) S = exp ( - Ro/alpha x (exp (alpha x t) –1 )) Number of deaths per year d(t) D = -ds/dt = ( Ro + alpha x ln (1/s(t) )) x s(t) = u(t) x s(t)

J. W. Ashford, 2004

Raber, Huang, Ashford, 2004, Neurobiol Aging. 25:

Are we ready to do genetic testing to predict AD? The family members want it –They consider recommendations against genetic testing to be “paternalistic” Family members can make more powerful financial decisions based on this knowledge than the relevance of insurance companies implementing changes in actuarial calculations Those at risk can seek more frequent testing –This is the best opportunity for early recognition Those at risk will be better advocates for research Specific preventive treatments can be developed for each genetic factor

Control: What happens without testing? Total Population Risk=P P Have AD No effective intervention Do not have AD P’ Helena Kraemer, 2003

Testing: What happens with testing? Total Population No AD AD Unnecessary intervention OKNo effective interventionEffective intervention $ Testing$Testing$ Testing $ Testing $ Intervention Iatragenic Damage?Clinical WashClinical Wash Clinical Gain Major(?) LossMinor (?) LossMinor(?) Loss Major(?) Gain PP’ Se Se’ SpSp’ Helena Kraemer, 2003

Cost – Benefit Calculation I = incidence P = Total Population X = cost of test, time to take (subject, ? Tester) Sn = sensitivity of test = 1- False negative (Fn) Sp = specificity of test = 1- False positive (Fp) Cost: –Total cost of test = P*X –Fp = $1000 * P * (1-I) * (1-Sp) (+false hope) –Tn = 0 (real peace of mind) –Fn = false peace of mind –Tp = (-$49000 * P * I * Sn) => $50,000 = NH cost/1year Avg Person Benefit= 49000*I*SN -X -1000*(1-I)*(1-Sp)

Sp X I Sn

Future Directions for Alzheimer’s Disease Need more precise assessment of cognition from normal to severe dementia Need to use Item Response Theory and Computerized Adaptive Testing Screening tests need to be widely used, that implement computer administration Test analyses need to be risk/benefit-related Better tests will lead to better treatments Better treatments will lead to prevention