Comparison of Clinical Performance of AQT-CF, MMSE, and ADAS-cog: Preliminary Results Niels Peter Nielsen, M.D. Siegbert Warkentin, Ph.D. James Jacobson,

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Comparison of Clinical Performance of AQT-CF, MMSE, and ADAS-cog: Preliminary Results Niels Peter Nielsen, M.D. Siegbert Warkentin, Ph.D. James Jacobson, M.D. Lennart Minthon, M.D., Ph.D. Elisabeth H. Wiig, Ph.D. Copyright RAN Diagnostics, Inc.

Objectives 1.Compare the diagnostic utility of three measures of cognition (AQT-CF, MMSE, and ADAS-cog), used alone, for differentiating patients with Alzheimer’s Disease from normal patients. 2.Determine if a combination of tests provides better diagnostic utility than a single test. 3.Suggest a testing strategy for clinical application of these cognitive measures.

Sample Population NormalADP value n4633 LanguageSwedish Education> 11 yrs Age70.85+/ /- 7.04P<0.02

Cognitive Measures AQTMMSEADAS ProbeTemporo- parietal dysfunction Cognitive impairment Comprehensive testing for AD TestColor-form naming MeasureTime (sec)Point scoreBehavior rating Normal< <10 AD>70< Test time3-5 min10 min45 min

Color-Form Naming Tests Test Plates (40 items each)

General Results NormalADP Value AQT-CF51.21+/ / < MMSE / /- 3.64< ADAS-cog7.4 +/ /- 9.14< 0.001

Sensitivity Analysis Sensitivity (%) Specificity (%) Predictive Value (%) AQT-CF MMSE ADAS-cog959897

Receiver Operator Curve False Alarm Diagnosis

Stepwise Discriminant Analysis Y(0,1) = B 0 + B 1 X 1 + B 2 X 2 +B 3 X 3 …+B i X i Variables = age, gender, AQT-CF, MMSE, ADAS-cog Y(0,1) = (ADAS-cog) +.030(AQT-CF) Best discrimination by ADAS-cog & AQT-CF AGE, gender, MMSE not included

Sensitivity Analysis: AQT-CF and ADAS-cog NormalAD Normal210 Spec= 100% AD144 Sens= 98% Predicted Actual AQT-CF and ADAS-cog: Predictive Value = 98.5%

Measure Characteristics AQT-CFMMSEADAS-cog Time3-5 min10 min45 min MonitorNonmedicalProfessional CostLowModerateHigh Conflicts Factors NoneAge, education, culture, literacy Judgment, experience PV(alone/ combo) 95/98.587/NA97/98.5 ScreeningYes No DiagnosisYes

Summary 1.Used alone, AQT-CF and ADAS-cog have comparable predictive value, superior to MMSE. 2.Used in combination, the best PV value is obtained by using AQT-CF and ADAS-cog. 3.For screening, AQT-CF is preferred because of short test time, independence from a medical professional, and high predictive value. 4.For final diagnosis, the combination of AQT-CF and ADAS-cog provides the highest predictive value.

Conclusions 1.AQT-CF is a powerful clinical tool to assess cognitive functions associated with temporo-parietal activation. 2.Test characteristics of AQT-CF make it especially valuable as an initial screening test for both normal individuals and suspected AD patients. 3.For final diagnosis, the best predictive value is provided by use of both the AQT-CF and ADAS-cog.