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Anderl-Straub S, Lausser L, Lombardi J, et al. Predicting disease progression in behavioral variant frontotemporal dementia. Alzheimers Dement (Amst). 2021;13(1):e12262doi: 10.1002/dad2.12262.
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., Wiltfang, J., Diehl-Schmid, J., Ludolph, A. C., Schroeter, M. L., Kestler, H. A., Otto, M. (2021). Predicting disease progression in behavioral variant frontotemporal dementia. Alzheimer's & dementia (Amsterdam, Netherlands), 13(1), e12262. https://doi.org/10.1002/dad2.12262
Anderl-Straub, Sarah, et al. "Predicting disease progression in behavioral variant frontotemporal dementia." Alzheimer's & dementia (Amsterdam, Netherlands) vol. 13,1 (2021): e12262. doi: https://doi.org/10.1002/dad2.12262
Anderl-Straub S, Lausser L, Lombardi J, Uttner I, Fassbender K, Fliessbach K, Huppertz HJ, 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. Predicting disease progression in behavioral variant frontotemporal dementia. Alzheimers Dement (Amst). 2021 Dec 31;13(1):e12262. doi: 10.1002/dad2.12262. eCollection 2021. PMID: 35005196; PMCID: PMC8719425.
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Alzheimers Dement (Amst). 2021 Dec 31;13(1):e12262. doi: 10.1002/dad2.12262. eCollection 2021.

Predicting disease progression in behavioral variant frontotemporal dementia.

Alzheimer's & dementia (Amsterdam, Netherlands)

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

Affiliations

  1. Department of Neurology University of Ulm Ulm Germany.
  2. Institute of Medical Systems Biology University of Ulm Ulm Germany.
  3. Department of Neurology Saarland University Homburg Germany.
  4. Clinic for Neurodegenerative Diseases and Geriatric Psychiatry University Hospital Bonn Bonn Germany.
  5. Swiss Epilepsy Clinic Zurich Switzerland.
  6. Department of Psychiatry and Psychotherapy University Hospital Hamburg Eppendorf Hamburg Germany.
  7. Department of Psychiatry and Psychotherapy University Erlangen Erlangen Germany.
  8. Max-Planck-Institute of Human Cognitive and Brain Sciences & Clinic for Cognitive Neurology University Hospital Leipzig Leipzig Germany.
  9. German Center for Neurodegenerative Diseases (DZNE) Bonn Germany.
  10. Department of Neurodegenerative Diseases Center of Neurology and Hertie-Institute for Clinical Brain Research University Tübingen Germany.
  11. German Center for Neurodegenerative Diseases (DZNE) Tübingen Germany.
  12. Department of Neurology Ludwig-Maximilians-Universität München Munich Germany.
  13. Department of Neurology Rostock University Medical Center and German Center for Neurodegenerative Diseases (DZNE) Rostock Germany.
  14. Department of Psychiatry and Psychotherapy University of Würzburg Würzburg Germany.
  15. Institute for Human Genetics University Hospital Hamburg Eppendorf Hamburg Germany.
  16. Department of Psychiatry and Psychotherapy University Medical Center Göttingen (UMG) Göttingen Germany.
  17. German Center for Neurodegenerative Diseases (DZNE) Göttingen Germany.
  18. Neurosciences and Signaling Group Institute of Biomedicine (iBiMED) Department of Medical Sciences University of Aveiro Aveiro Portugal.
  19. Department of Psychiatry and Psychotherapy Technical University of Munich Munich Germany.
  20. Department of Neurology Martin Luther University Halle-Wittenberg University clinic Halle Halle (Saale) Germany.

PMID: 35005196 PMCID: PMC8719425 DOI: 10.1002/dad2.12262

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.

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

Keywords: behavioral variant frontotemporal dementia; brain volume; classification models; disease progression; frontotemporal dementia; prognosis

Conflict of interest statement

The authors declare no conflicts of interest.

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