Abstract
Background 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.
Methods 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.
Findings We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0.62, 95% CI 0.59-0.65), validated hippocampal volume model (0.67, 0.62-0.72), and updated CSF biomarkers model (0.72, 0.68-0.74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0.74, 0.71-0.76).
Interpretation We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour. Copyright (C) 2019 Elsevier Ltd. All rights reserved.
Original language | English |
---|---|
Pages (from-to) | 1034-1044 |
Number of pages | 11 |
Journal | Lancet Neurology |
Volume | 18 |
Issue number | 11 |
DOIs | |
Publication status | Published - Nov 2019 |
Keywords
- ALZHEIMERS-DISEASE
- CSF BIOMARKERS
- DEMENTIA
- PROGRESSION
- DIAGNOSIS
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In: Lancet Neurology, Vol. 18, No. 11, 11.2019, p. 1034-1044.
Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Biomarker-based prognosis for people with mild cognitive impairment (ABIDE)
T2 - a modelling study
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 - Wiftfang, Jens
AU - Maier, Wolfgang
AU - Peters, Oliver
AU - ROther, 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 - Kloszewska, Iwona
AU - Mecocci, Patrizia
AU - Vellas, Bruno
AU - Lovestone, Simon
AU - Gailuzzi, Samantha
AU - Herukka, Sanna-Kaisa
AU - Santana, Isabel
AU - Baldeiras, Ines
AU - de Mendonca, 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 - Alzheimer's Disease Neuroimaging Initiative
N1 - Funding Information: All declared interests are outside of the submitted work. CET has functioned in advisory boards of Fujirebio and Roche, received non-financial support in the form of research consumables from ADxNeurosciences and Euroimmun, and performed contract research or received grants from Probiodrug, Janssen Prevention Center, Boehringer, Brains Online, Axon Neurosciences, EIP Pharma, and Roche. PS has acquired grant support (for the institution) from GE Healthcare, Danone Research, Piramal, and MERCK. In the past 2 years, he has received consultancy or speaker fees (paid to the institution) from Lilly, GE Healthcare, Novartis, Sanofi, Nutricia, Probiodrug, Biogen, Roche, Avraham, and EIP Pharma. FB is a board member for Brain, Eur Radiology, Neurology, Multiple Sclerosis Journal, and Radiology; and reports personal fees from Bayer-Schering, Biogen-Idec, TEVA, Merck-Serono, Novartis, Roche, Jansen Research, Genzyme-Sanfoni, IXICO, GeNeuro, and Apitope; and grants from AMYPAD (IMI), EuroPOND (H2020), UK MS Society, Dutch MS Society, PICTURE (IMDI-NWO), National Institute for Health Research UCLH Biomedical Research Center, and ECTRIMS-MAGNIMS. LF has received research funding, consultancy fees, or speech honoraria from Allergan, Avid-Eli Lilly, Avanir, Avraham Pharmaceuticals, Axon Neuroscience, Axovant, Biogen, Boehringer Ingelheim, Eisai, Functional Neuromodulation, GE Healthcare, Lundbeck, Merck Sharpe & Dohme, Novartis, Pfizer, Piramal Imaging, Roche, and Schwabe Pharma. JW has acquired research support (for the institution) from Immungenetics and TECAN-IBL; consultancy fees from Lilly, Roche Pharma, Merck Sharp & Dohme, Boehringer-Ingelheim, and Abbot EPD; speech honoraria from Roche Pharma, Helios Klinikum Wuppertal, Vitos Kurhessen-Bad Emstal, Pfizer, Janssen, AGNP, and Actelion; and has two patents (PCT/EP 2011 001724: new formulations for diagnosis of Alzheimer's disease and PCT/EP 2015 052945: biosensor for conformation and secondary structure analysis). OP reports grants and personal fees from Roche and Biogen and grants from Novartis, Eisai, Lilly, and Pharmatrophix. HH is an employee of Eisai and serves as Senior Associate Editor for the Journal Alzheimer's & Dementia; he has received lecture fees from Biogen, Roche, and Eisai; research grants from Pfizer, Avid, and MSD Avenir (paid to the institution); travel funding from Functional Neuromodulation, Axovant, Eli Lilly, Takeda and Zinfandel, GE Healthcare, and Oryzon Genomics, consultancy fees from Qynapse, Jung Diagnostics, Cytox, Axovant, Anavex, Takeda and Zinfandel, GE Healthcare and Oryzon Genomics, and Functional Neuromodulation; and has participated in scientific advisory boards for Functional Neuromodulation, Axovant, Eli Lilly, Cytox, GE Healthcare, Takeda and Zinfandel, Oryzon Genomics, and Roche Diagnostics. HH is co-inventor in the following patents as a scientific expert and has received no royalties: in vitro multiparameter determination method for the diagnosis and early diagnosis of neurodegenerative disorders patent number: 8916388; in vitro procedure for diagnosis and early diagnosis of neurodegenerative diseases patent number: 8298784; neurodegenerative markers for psychiatric conditions publication number: 20120196300; in vitro multiparameter determination method for the diagnosis and early diagnosis of neurodegenerative disorders publication number: 20100062463; in vitro method for the diagnosis and early diagnosis of neurodegenerative disorders publication number: 20100035286; in vitro procedure for diagnosis and early diagnosis of neurodegenerative diseases publication number: 20090263822; in vitro method for the diagnosis of neurodegenerative diseases patent number: 7547553; CSF diagnostic in vitro method for diagnosis of dementias and neuroinflammatory diseases publication number: 20080206797; in vitro method for the diagnosis of neurodegenerative diseases publication number: 20080199966; and neurodegenerative markers for psychiatric conditions publication number: 20080131921. BV reports grants and personal fees from Biogen, MSD, Lily, and Roche. SL has, within the past 5 years, held research grants with funding from multiple industry partners through the IMI funding scheme and with AstraZeneca. He is currently an employee of Janssen R&D. GC reports grants from Institut National de la Santé et de la Recherche Médicale (Inserm); Fondation Plan Alzheimer ( Alzheimer Plan 2008-2012 ); Programme Hospitalier de Recherche Clinique ( PHRCN 2011-A01493-38 and PHRCN 2012 12-006-0347 ); Agence Nationale de la Recherche (LONGVIE 2007); Région Basse-Normandie; Association France Alzheimer et maladies apparentées; Fondation Vaincre Alzheimer; and the European Commission (H2020 PHC22, Medit-Ageing study, grant agreement N667696). OH has acquired research support (for the institution) from Roche, GE Healthcare, Biogen, AVID Radiopharmaceuticals, Fujirebio, and Euroimmun. In the past 2 years, he has received consultancy or speaker fees (paid to the institution) from Biogen, Roche, and Fujirebio. WMvdF does contract research for Biogen MA. Research programmes of WMvdF have been funded by ZonMW, Health Holland, Pasman stichting, NWO, EU-FP7, EU-JPND, Alzheimer Nederland, Cardiovasculair Onderzoek Nederland, stichting Dioraphte, Gieskes-Strijbis fonds, Boehringer Ingelheim, Piramal Neuroimaging, Roche BV, Janssen Stellar, and Combinostics; all funding is paid to her institution. All remaining authors declare no competing interests. Funding Information: Research of the Alzheimer Center Amsterdam is part of the neurodegeneration research programme of Amsterdam Neuroscience. The Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting VUmc Fonds. WMvdF and ISvM were recipients of a grant by the Joint Program—Neurodegenerative Disease Research (JPND ADDITION; project no 733051083) and WMvdF is a recipient of a grant by ZonMWMemorabel (ABIDE; project no 733050201), a project in the context of the Dutch Deltaplan Dementie. FB is supported by the NIHR Biomedical Research Centre at University College London Hospital. HH is supported by the AXA Research Fund, the Fondation partenariale Sorbonne Université, and the Fondation pour la Recherche sur Alzheimer, Paris, France. This work has received support within the “Investissement d'Avenir” (ANR-10-AIHU-06) French program (Agence Nationale de la Recherche-10-IA Agence Institut Hospitalo-Universitaire-6). Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database . As such, the investigators within the ADNI contributed to the design and implementation of ADNI or provided data but did not participate in analysis or writing of this report. A complete list of ADNI investigators can be found online . Data collection and sharing for this project was funded by the ADNI (National Institutes of Health Grant U01 AG024904 ) and Department of Defense ADNI (award number W81XWH-12-2-0012 ). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following organisations: AbbVie, Alzheimer's Association, Alzheimer's Drug Discovery Foundation, Araclon Biotech, BioClinica, Biogen, Bristol-Myers Squibb, CereSpir, Cogstate, Eisai, Elan Pharmaceuticals, Eli Lilly, EuroImmun, F Hoffmann-La Roche and its affiliated company Genentech, Fujirebio, GE Healthcare, IXICO, Janssen Alzheimer Immunotherapy Research & Development, Johnson & Johnson Pharmaceutical Research & Development, Lumosity, Lundbeck, Merck & Co, Meso Scale Diagnostics, NeuroRx Research, Neurotrack Technologies, Novartis Pharmaceuticals Corporation, Pfizer, Piramal Imaging, Servier, Takeda Pharmaceutical Company, and Transition Therapeutics. The Canadian Institutes of Health Research provides funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ). The grantee organisation is the Northern California Institute for Research and Education and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This study resulted from a collaboration between centres of the European Alzheimer's Disease Consortium. The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement number 115372, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme ( FP7/2007-2013 ) and EFPIA companies' in-kind contribution. The DESCRIPA study was funded by the European Commission within the 5th framework programme ( QLRT-2001- 2455 ). The Coimbra Centre was funded by the European Regional Development Fund, through the Centro 2020 Regional Operational Programme under project CENTRO-01-0145-FEDER-000008:BrainHealth 2020, and through the COMPETE 2020—Operational Programme for Competitiveness and Internationalisation and Portuguese national funds via FCT – Fundação para a Ciência e a Tecnologia, under projects POCI-01-0145-FEDER-007440. The Centre de la mémoire of Geneva University Hospitals is funded by Association Suisse pour la Recherche sur Alzheimer; Fondation Segré; Ivan Pictet; Fondazione Agusta; Fondation Chmielewski; Fondation VELUX; and the Swiss National Science Foundation. The IMAP Study was funded by Programme Hospitalier de Recherche Clinique ( PHRCN 2011-A01493-38 and PHRCN 2012 12-006-0347 ), Agence Nationale de la Recherche (LONGVIE 2007), Région Basse-Normandie and Fondation Plan Alzheimer ( Alzheimer Plan 2008-2012 ). The Dementia Competence Network has been supported by a grant from the German Federal Ministry of Education and Research: Kompetenznetz Demenzen (01GI0420). The BioFINDER study was supported by the European Research Council, the Swedish Research Council, the Knut and Alice Wallenberg Foundation, the Marianne and Marcus Wallenberg Foundation, the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson's disease) at Lund University, the Swedish Alzheimer Foundation, the Swedish Brain Foundation, the Parkinson Foundation of Sweden, the Skåne University Hospital Foundation, and the Swedish Federal Government under the ALF agreement. Publisher Copyright: © 2019 Elsevier Ltd
PY - 2019/11
Y1 - 2019/11
N2 - Background 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.Methods 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.Findings We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0.62, 95% CI 0.59-0.65), validated hippocampal volume model (0.67, 0.62-0.72), and updated CSF biomarkers model (0.72, 0.68-0.74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0.74, 0.71-0.76).Interpretation We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour. Copyright (C) 2019 Elsevier Ltd. All rights reserved.
AB - Background 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.Methods 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.Findings We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0.62, 95% CI 0.59-0.65), validated hippocampal volume model (0.67, 0.62-0.72), and updated CSF biomarkers model (0.72, 0.68-0.74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0.74, 0.71-0.76).Interpretation We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour. Copyright (C) 2019 Elsevier Ltd. All rights reserved.
KW - ALZHEIMERS-DISEASE
KW - CSF BIOMARKERS
KW - DEMENTIA
KW - PROGRESSION
KW - DIAGNOSIS
U2 - 10.1016/S1474-4422(19)30283-2
DO - 10.1016/S1474-4422(19)30283-2
M3 - Article
SN - 1474-4422
VL - 18
SP - 1034
EP - 1044
JO - Lancet Neurology
JF - Lancet Neurology
IS - 11
ER -