TY - JOUR
T1 - Evaluating combinations of diagnostic tests to discriminate different dementia types
AU - Bruun, Marie
AU - Rhodius-Meester, Hanneke F.M.
AU - Koikkalainen, Juha
AU - Baroni, Marta
AU - Gjerum, Le
AU - Lemstra, Afina W.
AU - Barkhof, Frederik
AU - Remes, Anne M.
AU - Urhemaa, Timo
AU - Tolonen, Antti
AU - Rueckert, Daniel
AU - van Gils, Mark
AU - Frederiksen, Kristian S.
AU - Waldemar, Gunhild
AU - Scheltens, Philip
AU - Mecocci, Patrizia
AU - Soininen, Hilkka
AU - Lötjönen, Jyrki
AU - Hasselbalch, Steen G.
AU - van der Flier, Wiesje M.
N1 - Funding Information:
This project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreements no 611005 (PredictND). For development of the PredictND tool, the VTT Technical Research Center of Finland Ltd has received funding from European Union's Seventh Framework Programme for research, technological development, and demonstration under grant agreements 601055 (VPH-DARE@IT), 224328, and 611005. The PredictND consortium consisted of collaborates from the VTT Technical Research Center of Finland, GE Healthcare Ltd, Imperial College London, Alzheimer Europe, Alzheimer Center–VU University Medical Center, Amsterdam, the Netherlands, the Danish Dementia Research Center, Copenhagen University Hospital, Denmark, the Department of Gerontology and Geriatrics of the University of Perugia, “S. Maria della Misericordia” Hospital of Perugia, Italy, the Department of Neurology from the University of Eastern Finland.
Funding Information:
Author disclosures: M. Bruun, H.F.M.R.-M., M. Baroni, L.G., A.W.L., A.M.R., T.U., A.T., D.R., M.v.G., K.S.R., G.W., P.M., and S.G.H. report no disclosures. F.B. is supported by the NIHR UCLH Biomedical Research Centre. H.S. has served in advisory boards for AC Immune, MSD, and Orion Pharma. P.S. has served as a consultant for Wyeth-Elan, Genentech, Danone, and Novartis and received funding for travel from Pfizer, Elan, Janssen, and Danone Research. J.L. and J.K. are shareholders in Combinostics Oy that owns the following IPR related to the patent: (1) J. Koikkalainen and J. Lotjonen—A method for inferring the state of a system, US7,840,510 B2, PCT/FI2007/050277. (2) J. Lotjonen, J. Koikkalainen, and J. Mattila—State Inference in a heterogeneous system, PCT/FI2010/050545, FI20125177. W.M.v.d.F. performs contract research for Biogen. Research programs of W.M.v.d.F. have been funded by ZonMW, NWO, EU-FP7, Alzheimer Nederland, CardioVascular Onderzoek Nederland, Stichting Dioraphte, Gieskes-Strijbis fonds, Boehringer Ingelheim, Piramal Neuroimaging, Roche BV, Janssen Stellar, and Combinostics. All funding is paid to her institution.
Publisher Copyright:
© 2018 The Authors
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Introduction: We studied, using a data-driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia. Methods: In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types. Results: Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%. Discussion: Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further.
AB - Introduction: We studied, using a data-driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia. Methods: In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types. Results: Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%. Discussion: Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further.
KW - Alzheimer's disease
KW - Biomarkers
KW - Clinical decision support system
KW - CSF
KW - Dementia with Lewy bodies
KW - Diagnostic test assessment
KW - Differential diagnosis
KW - Frontotemporal dementia
KW - MRI
KW - Vascular dementia
UR - http://www.scopus.com/inward/record.url?scp=85054439727&partnerID=8YFLogxK
U2 - 10.1016/j.dadm.2018.07.003
DO - 10.1016/j.dadm.2018.07.003
M3 - Article
AN - SCOPUS:85054439727
VL - 10
SP - 509
EP - 518
JO - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
JF - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
SN - 2352-8729
ER -