Measuring clinical progression in MCI and pre-MCI populations: enrichment and optimizing clinical outcomes over time

Suzanne B Hendrix

doi:10.1186/alzrt127

Abstract

Recent biomarker research has improved the identification of individuals with very early stages of Alzheimer's disease (AD) and has demonstrated that biomarkers are sensitive for measuring progression in the pre-dementia or mild cognitive impairment (MCI) stage and even pre-symptomatic or pre-MCI stage of AD. Because there are no validated biomarkers in AD, it is important to seek out clinical outcomes that are also sensitive for measuring progression in these very early stages of disease. Clinical outcomes are more subjective and more affected by measurement error than biomarkers but represent the core aspects of the disease and are critical for validation of biomarkers and for evaluation of clinical relevance. Identification of individuals with pre-MCI stages of AD will need to continue to rely on biomarkers, but the identification of individuals with MCI who will progress to AD can be achieved with biomarkers or clinical criteria. Although standard clinical outcomes have been shown to be less sensitive to progression than biomarker outcomes in MCI and pre-MCI populations, non-standard scoring has improved the performance of the Alzheimer's Disease Assessment Scale cognitive subscale, making it more sensitive to progression. Neuropsychological cognitive testing items are optimal for measuring progression in pre-MCI populations, and current research is exploring the best ways to combine these items into a composite cognitive score with maximum responsiveness. In an MCI stage, cognitive, functional, and global items all change, and the best single composite score for measuring progression may involve all of these aspects of the disease. The best chance of success in demonstrating treatment effects in clinical trials will be achieved in a well-defined pre-MCI or MCI population and with an outcome that tracks well with clinical progression over time and with time. A partial least squares model can be used to identify these optimal weighted combinations.

Highlights

Introduction e development ofAlzheimer’s disease (AD) therapies with putative disease-modifying mechanisms has led to the strategy of testing these therapies in early stages of the disease in order to give them the best chance of affecting the disease before it is fully established
Evaluation of clinical progression outcomes No standard clinical outcomes are currently established in mild cognitive impairment (MCI) and pre-MCI populations
The responsiveness of the scale, both external and internal, should be assessed [14,15] (The article by Coley and colleagues [15] interprets internal and external responsiveness differently.) Because this field is rich in reliable and validated neuropsychological tests, the focus should be on improving responsiveness as the primary challenge in measuring progression in MCI and pre-MCI populations

Summary

Introduction

Introduction e development ofAlzheimer’s disease (AD) therapies with putative disease-modifying mechanisms has led to the strategy of testing these therapies in early stages of the disease in order to give them the best chance of affecting the disease before it is fully established. As we consider clinical trial design, the available research helps us make decisions of two different types: how do we enrich the subject population being selected for the study, and what is the best way to measure the progression of subjects over time?

Results

Conclusion