Personalized risk for clinical progression in cognitively normal subjects - The ABIDE project

Ingrid S. van Maurik, Rosalinde E. R. Slot, Sander C. J. Verfaillie, Marissa D. Zwan, Femke H. Bouwman, Niels D. Prins, Charlotte E. Teunissen, Philip Scheltens, Frederik Barkhof, Mike P. Wattjes, Jose Luis Molinuevo, Lorena Rami, Steffen Wolfsgruber, Oliver Peters, Frank Jessen, Johannes Berkhof, Wiesje M. van der Flier

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Background: Biomarkers such as cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) have predictive value for progression to dementia in patients with mild cognitive impairment (MCI). The pre-dementia stage takes far longer, and the interpretation of biomarker findings is particular relevant for individuals who present at a memory clinic, but are deemed cognitively normal. The objective of the current study is to construct biomarker-based prognostic models for personalized risk of clinical progression in cognitively normal individuals presenting at a memory clinic. Methods: We included 481 individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort. Prognostic models were developed by Cox regression with patient characteristics, MRI, and/or CSF biomarkers to predict clinical progression to MCI or dementia. We estimated 5- and 3-year individualized risks based on patient-specific values. External validation was performed on Alzheimer's Disease Neuroimaging Initiative (ADNI) and an European dataset. Results: Based on demographics only (Harrell's C = 0.70), 5- and 3-year progression risks varied from 6% [3-11] and 4% [2-8] (age 55, MMSE 30) to 38% [29-49] and 28% [21-37] (age 70, MMSE 27). Normal CSF biomarkers strongly decreased progression probabilities (Harrell's C = 0.82). By contrast, abnormal CSF markedly increased risk (5 years, 96% [56-100]; 3 years, 89% [44-99]). The CSF model could reclassify 58% of the individuals with an "intermediate" risk (35-65%) based on the demographic model. MRI measures were not retained in the models. Conclusion: The current study takes the first steps in a personalized approach for cognitively normal individuals by providing biomarker-based prognostic models.
Original languageEnglish
Article number33
JournalAlzheimer's Research and Therapy
Issue number1
Publication statusPublished - 2019


  • Biomarkers
  • Cerebrospinal fluid
  • Magnetic resonance imaging
  • Progression

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