Nature Communications (Feb 2023)

Forecasting individual progression trajectories in Alzheimer’s disease

  • Etienne Maheux,
  • Igor Koval,
  • Juliette Ortholand,
  • Colin Birkenbihl,
  • Damiano Archetti,
  • Vincent Bouteloup,
  • Stéphane Epelbaum,
  • Carole Dufouil,
  • Martin Hofmann-Apitius,
  • Stanley Durrleman

DOI
https://doi.org/10.1038/s41467-022-35712-5
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 15

Abstract

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Accurate prediction of disease progression in Alzheimer’s disease (AD) is necessary for optimal recruitment of patients to clinical trials. Here, the authors present AD Course Map, a statistical model which helps to predict disease progression in participants, thus decreasing the required sample size for a hypothetical trial.