Abstract

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
Volume11
Issue number1
DOIs
Publication statusPublished - 2019

Cite this

@article{8d5053621bb64c2fa03283963608d5cf,
title = "Personalized risk for clinical progression in cognitively normal subjects - The ABIDE project",
abstract = "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.",
author = "{van Maurik}, {Ingrid S.} and Slot, {Rosalinde E. R.} and Verfaillie, {Sander C. J.} and Zwan, {Marissa D.} and Bouwman, {Femke H.} and Prins, {Niels D.} and Teunissen, {Charlotte E.} and Philip Scheltens and Frederik Barkhof and Wattjes, {Mike P.} and Molinuevo, {Jose Luis} and Lorena Rami and Steffen Wolfsgruber and Oliver Peters and Frank Jessen and Johannes Berkhof and {van der Flier}, {Wiesje M.}",
year = "2019",
doi = "10.1186/s13195-019-0487-y",
language = "English",
volume = "11",
journal = "Alzheimer's Research & Therapy",
issn = "1758-9193",
publisher = "BioMed Central",
number = "1",

}

TY - JOUR

T1 - Personalized risk for clinical progression in cognitively normal subjects - The ABIDE project

AU - van Maurik, Ingrid S.

AU - Slot, Rosalinde E. R.

AU - Verfaillie, Sander C. J.

AU - Zwan, Marissa D.

AU - Bouwman, Femke H.

AU - Prins, Niels D.

AU - Teunissen, Charlotte E.

AU - Scheltens, Philip

AU - Barkhof, Frederik

AU - Wattjes, Mike P.

AU - Molinuevo, Jose Luis

AU - Rami, Lorena

AU - Wolfsgruber, Steffen

AU - Peters, Oliver

AU - Jessen, Frank

AU - Berkhof, Johannes

AU - van der Flier, Wiesje M.

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85064386406&origin=inward

UR - https://www.ncbi.nlm.nih.gov/pubmed/30987684

U2 - 10.1186/s13195-019-0487-y

DO - 10.1186/s13195-019-0487-y

M3 - Article

VL - 11

JO - Alzheimer's Research & Therapy

JF - Alzheimer's Research & Therapy

SN - 1758-9193

IS - 1

M1 - 33

ER -