Journal article
Prediction of AD dementia by biomarkers following the NIA-AA and IWG diagnostic criteria in MCI patients from three European memory clinics.
- Prestia A Laboratory of Epidemiology and Neuroimaging, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
- Caroli A Medical Imaging Unit, Biomedical Engineering Department, IRCCS Mario Negri Institute for Pharmacological Research, Bergamo, Italy.
- Wade SK Department of Engineering, University of Cambridge, Cambridge, UK; Department of Decision Science, Bocconi University, Milan, Italy.
- van der Flier WM Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands; Department of Epidemiology & Biostatistics, VU University Medical Center, Amsterdam, The Netherlands.
- Ossenkoppele R Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands; Department of Radiology and Nuclear Medicine and PET research, VU University Medical Center, Amsterdam, The Netherlands.
- Van Berckel B Department of Radiology and Nuclear Medicine and PET research, VU University Medical Center, Amsterdam, The Netherlands.
- Barkhof F Department of Radiology and Nuclear Medicine and PET research, VU University Medical Center, Amsterdam, The Netherlands.
- Teunissen CE Department of Clinical Chemistry, VU University Medical Center, Amsterdam, The Netherlands.
- Wall A PET-Center, Section of Nuclear Medicine & PET, Department of Radiology, Oncology and Radiation Sciences, Uppsala University, Uppsala, Sweden.
- Carter SF Karolinska Institutet, Alzheimer Neurobiology Center, Stockholm, Sweden.
- Schöll M Karolinska Institutet, Alzheimer Neurobiology Center, Stockholm, Sweden.
- Choo IH Karolinska Institutet, Alzheimer Neurobiology Center, Stockholm, Sweden; Department of Neuropsychiatry, School of Medicine, Chosun University, Gwangju, Republic of Korea.
- Nordberg A Karolinska Institutet, Alzheimer Neurobiology Center, Stockholm, Sweden; Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden.
- Scheltens P Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands.
- Frisoni GB Laboratory of Epidemiology and Neuroimaging, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Departments of Internal Medicine and Psychiatry, University Hospitals and University of Geneva, Geneve, Switzerland. Electronic address: gfrisoni@fatebenefratelli.it.
- 2015-02-04
Published in:
- Alzheimer's & dementia : the journal of the Alzheimer's Association. - 2015
Alzheimer's disease
Diagnostic accuracy
Diagnostic criteria
MCI
MRI
PET
Aged
Aged, 80 and over
Alzheimer Disease
Amyloid beta-Peptides
Amyloidosis
Atrophy
Biomarkers
Disease Progression
Fluorodeoxyglucose F18
Hippocampus
Humans
Male
Middle Aged
Positron-Emission Tomography
Predictive Value of Tests
Prognosis
Sensitivity and Specificity
tau Proteins
English
INTRODUCTION
Proposed diagnostic criteria (international working group and National Institute on Aging and Alzheimer's Association) for Alzheimer's disease (AD) include markers of amyloidosis (abnormal cerebrospinal fluid [CSF] amyloid beta [Aβ]42) and neurodegeneration (hippocampal atrophy, temporo-parietal hypometabolism on [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET), and abnormal CSF tau). We aim to compare the accuracy of these biomarkers, individually and in combination, in predicting AD among mild cognitive impairment (MCI) patients.
METHODS
In 73 MCI patients, followed to ascertain AD progression, markers were measured. Sensitivity and specificity, positive (LR+) and negative (LR-) likelihood ratios, and crude and adjusted hazard ratios were computed.
RESULTS
Twenty-nine MCI patients progressed and 44 remained stable. Positivity to any marker achieved the lowest LR- (0.0), whereas the combination Aβ42 plus FDG-PET achieved the highest LR+ (6.45). In a survival analysis, positivity to any marker was associated with 100% conversion rate, whereas negativity to all markers was associated with 100% stability.
DISCUSSION
The best criteria combined amyloidosis and neurodegeneration biomarkers, whereas the individual biomarker with the best performance was FDG-PET.
Proposed diagnostic criteria (international working group and National Institute on Aging and Alzheimer's Association) for Alzheimer's disease (AD) include markers of amyloidosis (abnormal cerebrospinal fluid [CSF] amyloid beta [Aβ]42) and neurodegeneration (hippocampal atrophy, temporo-parietal hypometabolism on [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET), and abnormal CSF tau). We aim to compare the accuracy of these biomarkers, individually and in combination, in predicting AD among mild cognitive impairment (MCI) patients.
METHODS
In 73 MCI patients, followed to ascertain AD progression, markers were measured. Sensitivity and specificity, positive (LR+) and negative (LR-) likelihood ratios, and crude and adjusted hazard ratios were computed.
RESULTS
Twenty-nine MCI patients progressed and 44 remained stable. Positivity to any marker achieved the lowest LR- (0.0), whereas the combination Aβ42 plus FDG-PET achieved the highest LR+ (6.45). In a survival analysis, positivity to any marker was associated with 100% conversion rate, whereas negativity to all markers was associated with 100% stability.
DISCUSSION
The best criteria combined amyloidosis and neurodegeneration biomarkers, whereas the individual biomarker with the best performance was FDG-PET.
- Language
-
- English
- Open access status
- closed
- Identifiers
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- DOI 10.1016/j.jalz.2014.12.001
- PMID 25646957
- Persistent URL
- https://sonar.ch/global/documents/216056
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