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

• Published in: Alzheimer's research & therapy Vol. 11; no. 1; p. 33
• Main Authors: van Maurik, Ingrid S, Slot, Rosalinde E R, Verfaillie, Sander C J, Zwan, Marissa D, Bouwman, Femke H, Prins, Niels D, Teunissen, Charlotte E, Scheltens, Philip, Barkhof, Frederik, Wattjes, Mike P, Molinuevo, Jose Luis, Rami, Lorena, Wolfsgruber, Steffen, Peters, Oliver, Jessen, Frank, Berkhof, Johannes, van der Flier, Wiesje M
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 16.04.2019; BioMed Central; BMC
• Subjects: Aged; Aging; Alzheimer's disease; Atrophy; Biological markers; Biomarkers; Biomarkers - cerebrospinal fluid; Brain - diagnostic imaging; Brain research; Caregivers; Cerebrospinal fluid; Cognitive ability; Cognitive disorders; Cognitive Dysfunction - cerebrospinal fluid; Cognitive Dysfunction - diagnosis; Cognitive Dysfunction - diagnostic imaging; Dementia; Dementia - cerebrospinal fluid; Dementia - diagnosis; Dementia - diagnostic imaging; Development and progression; Diagnostic imaging; Disease Progression; Female; Humans; Magnetic resonance imaging; Male; Medical imaging equipment; Medical prognosis; Memory; Middle Aged; Neurology; NMR; Nuclear magnetic resonance; Pathology; Patients; Precision Medicine; Progression; Risk Factors; Progression; Biomarkers; Cerebrospinal fluid; Magnetic resonance imaging
• ISSN: 1758-9193; 1758-9193
• DOI: 10.1186/s13195-019-0487-y

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. 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. 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. The current study takes the first steps in a personalized approach for cognitively normal individuals by providing biomarker-based prognostic models.