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Original Investigation
October 16, 2017

Interpreting Biomarker Results in Individual Patients With Mild Cognitive Impairment in the Alzheimer’s Biomarkers in Daily Practice (ABIDE) Project

Author Affiliations
  • 1Department of Neurology and Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
  • 2Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
  • 3Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
  • 4Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
  • 5Institutes of Neurology and Healthcare Engineering, University College London, London, England
JAMA Neurol. Published online October 16, 2017. doi:10.1001/jamaneurol.2017.2712
Key Points

Question  Magnetic resonance imaging and cerebrospinal fluid measures are associated with an increased risk of progression to Alzheimer disease dementia, but how can we interpret biomarker findings in individual patients with mild cognitive impairment?

Findings  This cohort modelling study constructed biomarker-based prognostic models (cerebrospinal fluid model, magnetic resonance imaging model, and a combined model) that can be applied in individual patients with mild cognitive impairment, taking into account patient characteristics (age, sex, and Mini-Mental State Examination score). The models show particularly high negative predictive values, and external validation showed that our models were highly robust.

Meaning  These practical models could support clinical decision making and facilitate application of magnetic resonance imaging and cerebrospinal fluid biomarkers in daily practice.

Abstract

Importance  Biomarkers do not determine conversion to Alzheimer disease (AD) perfectly, and criteria do not specify how to take patient characteristics into account. Consequently, biomarker use may be challenging for clinicians, especially in patients with mild cognitive impairment (MCI).

Objective  To construct biomarker-based prognostic models that enable determination of future AD dementia in patients with MCI.

Design, Setting, and Participants  This study is part of the Alzheimer’s Biomarkers in Daily Practice (ABIDE) project. A total of 525 patients with MCI from the Amsterdam Dementia Cohort (longitudinal cohort, tertiary referral center) were studied. All patients had their baseline visit to a memory clinic from September 1, 1997, through August 31, 2014. Prognostic models were constructed by Cox proportional hazards regression with patient characteristics (age, sex, and Mini-Mental State Examination [MMSE] score), magnetic resonance imaging (MRI) biomarkers (hippocampal volume, normalized whole-brain volume), cerebrospinal fluid (CSF) biomarkers (amyloid-β1-42, tau), and combined biomarkers. Data were analyzed from November 1, 2015, to October 1, 2016.

Main Outcomes and Measures  Clinical end points were AD dementia and any type of dementia after 1 and 3 years.

Results  Of the 525 patients, 210 (40.0%) were female, and the mean (SD) age was 67.3 (8.4) years. On the basis of age, sex, and MMSE score only, the 3-year progression risk to AD dementia ranged from 26% (95% CI, 19%-34%) in younger men with MMSE scores of 29 to 76% (95% CI, 65%-84%) in older women with MMSE scores of 24 (1-year risk: 6% [95% CI, 4%-9%] to 24% [95% CI, 18%-32%]). Three- and 1-year progression risks were 86% (95% CI, 71%-95%) and 27% (95% CI, 17%-41%) when MRI results were abnormal, 82% (95% CI, 73%-89%) and 26% (95% CI, 20%-33%) when CSF test results were abnormal, and 89% (95% CI, 79%-95%) and 26% (95% CI, 18%-36%) when the results of both tests were abnormal. Conversely, 3- and 1-year progression risks were 18% (95% CI, 13%-27%) and 3% (95% CI, 2%-5%) after normal MRI results, 6% (95% CI, 3%-9%) and 1% (95% CI, 0.5%-2%) after normal CSF test results, and 4% (95% CI, 2%-7%) and 0.5% (95% CI, 0.2%-1%) after combined normal MRI and CSF test results. The prognostic value of models determining any type of dementia were in the same order of magnitude although somewhat lower. External validation in Alzheimer’s Disease Neuroimaging Initiative 2 showed that our models were highly robust.

Conclusions and Relevance  This study provides biomarker-based prognostic models that may help determine AD dementia and any type of dementia in patients with MCI at the individual level. This finding supports clinical decision making and application of biomarkers in daily practice.

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