Predicting Amyloid Burden to Accelerate Recruitment of Secondary Prevention Clinical Trials.

ABSTRACT:

Background

Screening to identify individuals with elevated brain amyloid (Aβ+) for clinical trials in Preclinical Alzheimer's Disease (PAD), such as the Anti-Amyloid Treatment in Asymptomatic Alzheimer's disease (A4) trial, is slow and costly. The Trial-Ready Cohort in Preclinical/Prodromal Alzheimer's Disease (TRC-PAD) aims to accelerate and reduce costs of AD trial recruitment by maintaining a web-based registry of potential trial participants, and using predictive algorithms to assess their likelihood of suitability for PAD trials.

Objectives

Here we describe how algorithms used to predict amyloid burden within TRC-PAD project were derived using screening data from the A4 trial.

Design

We apply machine learning techniques to predict amyloid positivity. Demographic

SUBMITTER: Langford O 

PROVIDER: S-EPMC7745538 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature