Predicting Progression from Cognitive Impairment to Alzheimer's Disease with the Disease State Index

Research output: Contribution to journalArticle

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 DE-SCRIPA 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 cross-validation. 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, they were 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.

Details

Authors
  • Anette Hall
  • Jussi Mattila
  • Juha Koikkalainen
  • Jyrki Loejonen
  • Robin Wolz
  • Philip Scheltens
  • Giovanni Frisoni
  • Magdalini Tsolaki
  • Flavio Nobili
  • Yvonne Freund-Levi
  • Lennart Minthon
  • Lutz Froelich
  • Harald Hampel
  • Pieter Jelle Visser
  • Hilkka Soininen
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Neurology

Keywords

  • Alzheimer's disease, cerebrospinal fluid (CSF), computer-assisted, diagnosis, dementia, DESCRIPA, magnetic resonance imaging (MRI), mild, cognitive impairment (MCI)
Original languageEnglish
Pages (from-to)69-79
JournalCurrent Alzheimer Research
Volume12
Issue number1
Publication statusPublished - 2015
Publication categoryResearch
Peer-reviewedYes