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Title

Predicting progression from cognitive impairment to Alzheimer's disease with the Disease State Index

Authors
Hall, Anette
Mattila, Jussi
Koikkalainen, Juha
Lötjonen, Jyrki
Wolz, Robin
Scheltens, Philip
Tsolaki, Magdalini
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Published in Current Alzheimer Research. 2015, vol. 12, no. 1, p. 69-79
Abstract We evaluated the performance of the Disease State Index (DSI) method when predicting progression to Alzheimer's disease (AD) in patients with subjective cognitive impairment (SCI), amnestic or non-amnestic mild cognitive impairment (aMCI, naMCI). The DSI model measures patients' similarity to diagnosed cases based on available data, such as cognitive tests, the APOE genotype, CSF biomarkers and MRI. We applied the DSI model to data from the DESCRIPA cohort, where non-demented patients (N=775) with different subtypes of cognitive impairment were followed for 1 to 5 years. Classification accuracies for the subgroups were calculated with the DSI using leave-one-out crossvalidation. The DSI's classification accuracy in predicting progression to AD was 0.75 (AUC=0.83) in the total population, 0.70 (AUC=0.77) for aMCI and 0.71 (AUC=0.76) for naMCI. For a subset of approximately half of the patients with high or low DSI values, accuracy reached 0.86 (all), 0.78 (aMCI), and 0.85 (naMCI). For patients with MRI or CSF biomarker data available, theywere 0.78 (all), 0.76 (aMCI) and 0.76 (naMCI), while for clear cases the accuracies rose to 0.90 (all), 0.83 (aMCI) and 0.91 (naMCI). The results show that the DSI model can distinguish between clear and ambiguous cases, assess the severity of the disease and also provide information on the effectiveness of different biomarkers. While a specific test or biomarker may confound analysis for an individual patient, combining several different types of tests and biomarkers could be able to reveal the trajectory of the disease and improve the prediction of AD progression.
Keywords AgedAged80 and overAlzheimer Disease/cerebrospinal fluid/diagnosis/physiopathologyApolipoproteins E/geneticsArea Under CurveBiomarkers/cerebrospinal fluidCognitive Dysfunction/cerebrospinal fluid/genetics/physiopathologyDisease ProgressionEuropeFemaleHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedNeuropsychological TestsPredictive Value of TestsPsychiatric Status Rating ScalesSensitivity and Specificity
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PMID: 25523428
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Research group Troubles de mémoire et maladie d'Alzeimer (935)
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HALL, Anette et al. Predicting progression from cognitive impairment to Alzheimer's disease with the Disease State Index. In: Current Alzheimer Research, 2015, vol. 12, n° 1, p. 69-79. https://archive-ouverte.unige.ch/unige:111877

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Deposited on : 2018-12-05

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