A multimodal digital biomarker of functional deficits in early‐stage Alzheimer’s disease: results of the RADAR‐AD study
Srinivasan Vairavan, Manuel Lentzen, Marijn Muurling, Casper de Boer, Alankar Atreya, Jelena Curcic, Chris Hinds, Pauline Conde, Margarita Grammatikopoulou, Gaetano Scebba, Ioulietta Lazarou, Spiros Nikolopoulos, Anna‐Katharine Brem, Neva Coello, Pieter Jelle Visser, Holger Fröhlich, Vaibhav A Narayan, Gayle Wittenberg, Dag Aarsland- Psychiatry and Mental health
- Cellular and Molecular Neuroscience
- Geriatrics and Gerontology
- Neurology (clinical)
- Developmental Neuroscience
- Health Policy
- Epidemiology
Abstract
Background
Remote monitoring technologies (RMTs), such as smartphone apps, smartwatches, and in‐home sensors, are rapidly changing the way functional and cognitive performance is measured in Alzheimer’s disease (AD) patients. Here, we present results from the European RADAR‐AD study on the use of multimodal data streams for the identification of functional deficits across all syndromic stages of AD.
Method
Four study groups (Healthy controls (HC), preclinical AD (pre. AD), prodromal AD (pro. AD), and mild AD) were included in this cross‐sectional study. The RMT features (gait measures from Timed up and Go (TUG), Dual Task Effect (DTE) using physilog, acoustic features from Speech task in Mezurio, neurocognitive function using Altoida, managing finances with Banking app) with in‐clinic neuropsychological (NP) tests, activities of daily living with Amsterdam IADL and demographics (age, gender, education years) were analyzed for different combinations of the multimodal digital biomarker of disease stage in AD across different pairwise comparisons. The analysis includes data from 175 participants (HC = 67, Pre.AD = 26, Pro.AD = 50, Mild AD = 32) collected for 8 weeks. An extreme gradient boosting (XGBoost) machine learning model was trained to obtain a multimodal biomarker of AD disease stage with repeated cross‐validation (5‐fold with 4 repeats) (Figure 1). This investigation is part of the ongoing RADAR‐AD study.
Result
The multimodal combination of RMTs achieved a mean AUC of > 0.60 in all pairwise comparisons with a mean AUC > 0.65 for HC vs (Pre.AD, Pro.AD and Mild) (Figures 2 and 3). The addition of NP tests increases the performance considerably across all pairwise comparisons except HC vs Pre.AD.
Conclusion
Our results highlight the advantage of combining RMTs to identify functional deficits in the early stage of AD. In particular, in prodromal and mild AD patients, a combined signal shows much more strength compared to individual tests.
This work has received support from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking (grant No 806999). www.imi.europa.eu. This communication reflects the views of the RADAR‐AD consortium and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein.