Assessing Clinical Progression Measures in Alzheimer’s Disease Trials: A Systematic Review and Meta-Analysis
Authors: McLaughlin Jonathan , Scotton William J. , Hardy John A. , Shoai Maryam 
Published: August 2023

Clinical trials in Alzheimer’s disease (AD) aim to reduce the rate of progression of disease. This is heavily dependent on a consensus of a minimum clinically important difference as well as the ability of the cognitive and functional measures used to accurately measure progression.

In this study we perform a systematic review and meta-regression to assess the precision of measurement of AD clinical progression in clinical trials of therapeutic interventions in patients with known positive amyloid status prior to trial entry.

Meta analyses of randomised controlled trials (RCT) in AD, with amyloid positive status (Aβ+) as an inclusion criterion, were undertaken with functional, cognitive, and composite measures included in the analyses. Twenty-five RCTs were eligible for inclusion. Whilst most RCTS enrolled prodromal or mild AD patients with an average MMSE score at baseline of 27, several included average MMSE scores as low as 22. We performed meta regressions, correcting for age, gender, and stage of disease in R version 4.2.0, using themetaforandemmeanslibraries. Of the progression measures included in the meta-analyses, the FAQ, a functional measure, had the largest weighted mean change over 12-weeks followed by MMSE, whilst the most commonly used neuropsychiatric battery, NPI, failed to show sensitivity to change in the given time period. This study emphasises the necessity of appropriate composite progression measures that weigh cognitive, functional and neuropsychiatric symptoms according to their ability to detect meaningful change in symptoms and thus have a better chance of detecting meaningful change in participants of interventional RCTs.

Background

Alzheimer’s disease (AD) is a slowly progressive disease. It is now widely recognised that there is a pre-clinical phase. This phase of the disease may be apparent via biomarker testing up to 20 years before clinically evident AD. Pre-clinical AD is then followed by clinically significant cognitive decline ranging from MCI to severe AD.

The aim of randomised controlled trials (RCT) is to reduce or halt the rate of clinical progression of AD. Most of these trials have been unsuccessful. To determine the effectiveness of treatments there must be robust and reliable tools for measuring AD progression. For at least 30 years there has been recognition that the measures of progression used in AD clinical trials are problematic.

A significant concern is that current measures of clinical progression are potentially not sensitive enough in early and preclinical stages of AD and so are not reliable indicators of AD progression.

In this systematic review and meta-regression we aimed to assess the precision of measurements of clinical progression in AD clinical trials of therapeutic interventions in patients with known positive amyloid status prior to trial entry.

Methods

Meta analyses of RCTs in AD with amyloid positive status (Aβ+) as an inclusion criterion was undertaken with functional, cognitive, and composite measures included in the analyses. Twenty-five RCTs were eligible for inclusion. Statistical analyses were performed using R version 4.2.0 and themetaforandemmeanslibraries.

Findings

Of the progression measures commonly reported in RCTs, the FAQ, had the largest weighted mean change over 12-weeks followed by MMSE. Other cognitive measures were amongst the least sensitive measures over the chosen time period. As a composite score, both the iADRS and CDRSB appear to be performing better than the cognitive components they comprise. The neuropsychiatric battery analysed in this study appeared to be the least sensitive of measures of progression.

Interpretation

Functional measures, with the exception of QoL-AD, perform better than other groups of measures. Measures which rely on purely cognitive domains are not optimal for sole use in AD trials. Ideally, measures should include both cognitive and functional components to enhance sensitivity. New composite measures address the poorer performance of composite scores, as compared to their comprising functional measures, by assigning different weights to cognitive and functional change.