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Predicting disease progression in behavioral variant frontotemporal dementia

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Predicting disease progression in behavioral variant frontotemporal dementia. / Anderl-Straub, Sarah; Lausser, Ludwig; Lombardi, Jolina; Uttner, Ingo; Fassbender, Klaus; Fliessbach, Klaus; Huppertz, Hans-Jürgen; Jahn, Holger; Kornhuber, Johannes; Obrig, Hellmuth; Schneider, Anja; Semler, Elisa; Synofzik, Matthis; Danek, Adrian; Prudlo, Johannes; Kassubek, Jan; Landwehrmeyer, Bernhard; Lauer, Martin; Volk, Alexander E; Wiltfang, Jens; Diehl-Schmid, Janine; Ludolph, Albert C; Schroeter, Matthias L; Kestler, Hans A; Otto, Markus; FTLD consortium.

In: ALZH DEMENT-DADM, Vol. 13, No. 1, 2021, p. e12262.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Anderl-Straub, S, Lausser, L, Lombardi, J, Uttner, I, Fassbender, K, Fliessbach, K, Huppertz, H-J, Jahn, H, Kornhuber, J, Obrig, H, Schneider, A, Semler, E, Synofzik, M, Danek, A, Prudlo, J, Kassubek, J, Landwehrmeyer, B, Lauer, M, Volk, AE, Wiltfang, J, Diehl-Schmid, J, Ludolph, AC, Schroeter, ML, Kestler, HA, Otto, M & FTLD consortium 2021, 'Predicting disease progression in behavioral variant frontotemporal dementia', ALZH DEMENT-DADM, vol. 13, no. 1, pp. e12262. https://doi.org/10.1002/dad2.12262

APA

Anderl-Straub, S., Lausser, L., Lombardi, J., Uttner, I., Fassbender, K., Fliessbach, K., Huppertz, H-J., Jahn, H., Kornhuber, J., Obrig, H., Schneider, A., Semler, E., Synofzik, M., Danek, A., Prudlo, J., Kassubek, J., Landwehrmeyer, B., Lauer, M., Volk, A. E., ... FTLD consortium (2021). Predicting disease progression in behavioral variant frontotemporal dementia. ALZH DEMENT-DADM, 13(1), e12262. https://doi.org/10.1002/dad2.12262

Vancouver

Anderl-Straub S, Lausser L, Lombardi J, Uttner I, Fassbender K, Fliessbach K et al. Predicting disease progression in behavioral variant frontotemporal dementia. ALZH DEMENT-DADM. 2021;13(1):e12262. https://doi.org/10.1002/dad2.12262

Bibtex

@article{1bf6d58da06c43528ea7ab2e3554064b,
title = "Predicting disease progression in behavioral variant frontotemporal dementia",
abstract = "Introduction: The behavioral variant of frontotemporal dementia (bvFTD) is a rare neurodegenerative disease. Reliable predictors of disease progression have not been sufficiently identified. We investigated multivariate magnetic resonance imaging (MRI) biomarker profiles for their predictive value of individual decline.Methods: One hundred five bvFTD patients were recruited from the German frontotemporal lobar degeneration (FTLD) consortium study. After defining two groups ({"}fast progressors{"} vs. {"}slow progressors{"}), we investigated the predictive value of MR brain volumes for disease progression rates performing exhaustive screenings with multivariate classification models.Results: We identified areas that predict disease progression rate within 1 year. Prediction measures revealed an overall accuracy of 80% across our 50 top classification models. Especially the pallidum, middle temporal gyrus, inferior frontal gyrus, cingulate gyrus, middle orbitofrontal gyrus, and insula occurred in these models.Discussion: Based on the revealed marker combinations an individual prognosis seems to be feasible. This might be used in clinical studies on an individualized progression model.",
author = "Sarah Anderl-Straub and Ludwig Lausser and Jolina Lombardi and Ingo Uttner and Klaus Fassbender and Klaus Fliessbach and Hans-J{\"u}rgen Huppertz and Holger Jahn and Johannes Kornhuber and Hellmuth Obrig and Anja Schneider and Elisa Semler and Matthis Synofzik and Adrian Danek and Johannes Prudlo and Jan Kassubek and Bernhard Landwehrmeyer and Martin Lauer and Volk, {Alexander E} and Jens Wiltfang and Janine Diehl-Schmid and Ludolph, {Albert C} and Schroeter, {Matthias L} and Kestler, {Hans A} and Markus Otto and {FTLD consortium}",
note = "{\textcopyright} 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.",
year = "2021",
doi = "10.1002/dad2.12262",
language = "English",
volume = "13",
pages = "e12262",
journal = "ALZH DEMENT-DADM",
issn = "2352-8729",
publisher = "Elsevier BV",
number = "1",

}

RIS

TY - JOUR

T1 - Predicting disease progression in behavioral variant frontotemporal dementia

AU - Anderl-Straub, Sarah

AU - Lausser, Ludwig

AU - Lombardi, Jolina

AU - Uttner, Ingo

AU - Fassbender, Klaus

AU - Fliessbach, Klaus

AU - Huppertz, Hans-Jürgen

AU - Jahn, Holger

AU - Kornhuber, Johannes

AU - Obrig, Hellmuth

AU - Schneider, Anja

AU - Semler, Elisa

AU - Synofzik, Matthis

AU - Danek, Adrian

AU - Prudlo, Johannes

AU - Kassubek, Jan

AU - Landwehrmeyer, Bernhard

AU - Lauer, Martin

AU - Volk, Alexander E

AU - Wiltfang, Jens

AU - Diehl-Schmid, Janine

AU - Ludolph, Albert C

AU - Schroeter, Matthias L

AU - Kestler, Hans A

AU - Otto, Markus

AU - FTLD consortium

N1 - © 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.

PY - 2021

Y1 - 2021

N2 - Introduction: The behavioral variant of frontotemporal dementia (bvFTD) is a rare neurodegenerative disease. Reliable predictors of disease progression have not been sufficiently identified. We investigated multivariate magnetic resonance imaging (MRI) biomarker profiles for their predictive value of individual decline.Methods: One hundred five bvFTD patients were recruited from the German frontotemporal lobar degeneration (FTLD) consortium study. After defining two groups ("fast progressors" vs. "slow progressors"), we investigated the predictive value of MR brain volumes for disease progression rates performing exhaustive screenings with multivariate classification models.Results: We identified areas that predict disease progression rate within 1 year. Prediction measures revealed an overall accuracy of 80% across our 50 top classification models. Especially the pallidum, middle temporal gyrus, inferior frontal gyrus, cingulate gyrus, middle orbitofrontal gyrus, and insula occurred in these models.Discussion: Based on the revealed marker combinations an individual prognosis seems to be feasible. This might be used in clinical studies on an individualized progression model.

AB - Introduction: The behavioral variant of frontotemporal dementia (bvFTD) is a rare neurodegenerative disease. Reliable predictors of disease progression have not been sufficiently identified. We investigated multivariate magnetic resonance imaging (MRI) biomarker profiles for their predictive value of individual decline.Methods: One hundred five bvFTD patients were recruited from the German frontotemporal lobar degeneration (FTLD) consortium study. After defining two groups ("fast progressors" vs. "slow progressors"), we investigated the predictive value of MR brain volumes for disease progression rates performing exhaustive screenings with multivariate classification models.Results: We identified areas that predict disease progression rate within 1 year. Prediction measures revealed an overall accuracy of 80% across our 50 top classification models. Especially the pallidum, middle temporal gyrus, inferior frontal gyrus, cingulate gyrus, middle orbitofrontal gyrus, and insula occurred in these models.Discussion: Based on the revealed marker combinations an individual prognosis seems to be feasible. This might be used in clinical studies on an individualized progression model.

U2 - 10.1002/dad2.12262

DO - 10.1002/dad2.12262

M3 - SCORING: Journal article

C2 - 35005196

VL - 13

SP - e12262

JO - ALZH DEMENT-DADM

JF - ALZH DEMENT-DADM

SN - 2352-8729

IS - 1

ER -