TY  - JOUR
AU  - van Maurik, Ingrid S
AU  - Vos, Stephanie J
AU  - Bos, Isabelle
AU  - Bouwman, Femke H
AU  - Teunissen, Charlotte E
AU  - Scheltens, Philip
AU  - Barkhof, Frederik
AU  - Frolich, Lutz
AU  - Kornhuber, Johannes
AU  - Wiltfang, Jens
AU  - Maier, Wolfgang
AU  - Peters, Oliver
AU  - Rüther, Eckart
AU  - Nobili, Flavio
AU  - Frisoni, Giovanni B
AU  - Spiru, Luiza
AU  - Freund-Levi, Yvonne
AU  - Wallin, Asa K
AU  - Hampel, Harald
AU  - Soininen, Hilkka
AU  - Tsolaki, Magda
AU  - Verhey, Frans
AU  - Kłoszewska, Iwona
AU  - Mecocci, Patrizia
AU  - Vellas, Bruno
AU  - Lovestone, Simon
AU  - Galluzzi, Samantha
AU  - Herukka, Sanna-Kaisa
AU  - Santana, Isabel
AU  - Baldeiras, Ines
AU  - de Mendonça, Alexandre
AU  - Silva, Dina
AU  - Chetelat, Gael
AU  - Egret, Stephanie
AU  - Palmqvist, Sebastian
AU  - Hansson, Oskar
AU  - Visser, Pieter Jelle
AU  - Berkhof, Johannes
AU  - van der Flier, Wiesje M
AU  - Initiative, Alzheimer's Disease Neuroimaging
TI  - Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling study.
JO  - The lancet  / Neurology
VL  - 18
IS  - 11
SN  - 1474-4422
CY  - London
PB  - Lancet Publ. Group
M1  - DZNE-2020-07881
SP  - 1034-1044
PY  - 2019
AB  - Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia.In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models-a demographics model, a hippocampal volume model, and a CSF biomarkers model-by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework.We included all 2611 individuals with MCI in the four cohorts, 1007 (39
KW  - Aged
KW  - Aged, 80 and over
KW  - Alzheimer Disease: cerebrospinal fluid
KW  - Alzheimer Disease: epidemiology
KW  - Alzheimer Disease: pathology
KW  - Amyloid beta-Peptides: cerebrospinal fluid
KW  - Biomarkers: cerebrospinal fluid
KW  - Cognitive Dysfunction: cerebrospinal fluid
KW  - Cognitive Dysfunction: pathology
KW  - Disease Progression
KW  - Europe: epidemiology
KW  - Female
KW  - Follow-Up Studies
KW  - Hippocampus: pathology
KW  - Humans
KW  - Kaplan-Meier Estimate
KW  - Magnetic Resonance Imaging
KW  - Male
KW  - Middle Aged
KW  - Multicenter Studies as Topic: statistics & numerical data
KW  - Nerve Degeneration
KW  - Neuroimaging
KW  - North America: epidemiology
KW  - Organ Size
KW  - Peptide Fragments: cerebrospinal fluid
KW  - Phosphorylation
KW  - Prognosis
KW  - Proportional Hazards Models
KW  - Protein Processing, Post-Translational
KW  - tau Proteins: cerebrospinal fluid
KW  - tau Proteins: chemistry
LB  - PUB:(DE-HGF)16
C6  - pmid:31526625
DO  - DOI:10.1016/S1474-4422(19)30283-2
UR  - https://pub.dzne.de/record/141557
ER  -