Evaluating combinations of diagnostic tests to discriminate different dementia types

Marie Bruun; Hanneke F.M. Rhodius-Meester; Juha Koikkalainen; Marta Baroni; Le Gjerum; Afina W. Lemstra; Frederik Barkhof; Anne M. Remes; Timo Urhemaa; Antti Tolonen; Daniel Rueckert; Mark van Gils; Kristian S. Frederiksen; Gunhild Waldemar; Philip Scheltens; Patrizia Mecocci; Hilkka Soininen; Jyrki Lötjönen; Steen G. Hasselbalch; Wiesje M. van der Flier

doi:10.1016/j.dadm.2018.07.003

Evaluating combinations of diagnostic tests to discriminate different dementia types

Marie Bruun, Hanneke F.M. Rhodius-Meester, Juha Koikkalainen, Marta Baroni, Le Gjerum, Afina W. Lemstra, Frederik Barkhof, Anne M. Remes, Timo Urhemaa, Antti Tolonen, Daniel Rueckert, Mark van Gils, Kristian S. Frederiksen, Gunhild Waldemar, Philip Scheltens, Patrizia Mecocci, Hilkka Soininen, Jyrki Lötjönen, Steen G. Hasselbalch, Wiesje M. van der Flier

Research output: Contribution to journal › Article › Scientific › peer-review

24 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	509-518
Number of pages	10
Journal	Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Volume	10
DOIs	https://doi.org/10.1016/j.dadm.2018.07.003
Publication status	Published - 2018
Externally published	Yes
Publication type	A1 Journal article-refereed

Funding

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. 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. 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.

Keywords

Alzheimer's disease
Biomarkers
Clinical decision support system
CSF
Dementia with Lewy bodies
Diagnostic test assessment
Differential diagnosis
Frontotemporal dementia
MRI
Vascular dementia

ASJC Scopus subject areas

Clinical Neurology
Psychiatry and Mental health

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.dadm.2018.07.003

Cite this

Bruun, M., Rhodius-Meester, H. F. M., Koikkalainen, J., Baroni, M., Gjerum, L., Lemstra, A. W., Barkhof, F., Remes, A. M., Urhemaa, T., Tolonen, A., Rueckert, D., van Gils, M., Frederiksen, K. S., Waldemar, G., Scheltens, P., Mecocci, P., Soininen, H., Lötjönen, J., Hasselbalch, S. G., & van der Flier, W. M. (2018). Evaluating combinations of diagnostic tests to discriminate different dementia types. Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, 10, 509-518. https://doi.org/10.1016/j.dadm.2018.07.003

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title = "Evaluating combinations of diagnostic tests to discriminate different dementia types",

abstract = "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.",

keywords = "Alzheimer's disease, Biomarkers, Clinical decision support system, CSF, Dementia with Lewy bodies, Diagnostic test assessment, Differential diagnosis, Frontotemporal dementia, MRI, Vascular dementia",

author = "Marie Bruun and Rhodius-Meester, {Hanneke F.M.} and Juha Koikkalainen and Marta Baroni and Le Gjerum and Lemstra, {Afina W.} and Frederik Barkhof and Remes, {Anne M.} and Timo Urhemaa and Antti Tolonen and Daniel Rueckert and {van Gils}, Mark and Frederiksen, {Kristian S.} and Gunhild Waldemar and Philip Scheltens and Patrizia Mecocci and Hilkka Soininen and Jyrki L{\"o}tj{\"o}nen and Hasselbalch, {Steen G.} and {van der Flier}, {Wiesje M.}",

note = "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. 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: 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. Publisher Copyright: {\textcopyright} 2018 The Authors",

year = "2018",

doi = "10.1016/j.dadm.2018.07.003",

language = "English",

volume = "10",

pages = "509--518",

}

Bruun, M, Rhodius-Meester, HFM, Koikkalainen, J, Baroni, M, Gjerum, L, Lemstra, AW, Barkhof, F, Remes, AM, Urhemaa, T, Tolonen, A, Rueckert, D, van Gils, M, Frederiksen, KS, Waldemar, G, Scheltens, P, Mecocci, P, Soininen, H, Lötjönen, J, Hasselbalch, SG & van der Flier, WM 2018, 'Evaluating combinations of diagnostic tests to discriminate different dementia types', Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, vol. 10, pp. 509-518. https://doi.org/10.1016/j.dadm.2018.07.003

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: 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. 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: 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. Publisher Copyright: © 2018 The Authors

PY - 2018

Y1 - 2018

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

SN - 2352-8729

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

ER -

Evaluating combinations of diagnostic tests to discriminate different dementia types

Abstract

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

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