Alzheimer Disease Biomarkers as Outcome Measures for Clinical Trials in MCI

Abstract

Background: The aim of this study was to compare the performance and power of the best-established diagnostic biological markers as outcome measures for clinical trials in patients with mild cognitive impairment (MCI).

Methods: Magnetic resonance imaging, F-18 fluorodeoxyglucose positron emission tomography markers, and Alzheimer's Disease Assessment Scale-cognitive subscale were compared in terms of effect size and statistical power over different follow-up periods in 2 MCI groups, selected from Alzheimer's Disease Neuroimaging Initiative data set based on cerebrospinal fluid (abnormal cerebrospinal fluid Aβ1-42 concentration-ABETA+) or magnetic resonance imaging evidence of Alzheimer disease (positivity to hippocampal atrophy-HIPPO+). Biomarkers progression was modeled through mixed effect models. Scaled slope was chosen as measure of effect size. Biomarkers power was estimated using simulation algorithms.

Results: Seventy-four ABETA+ and 51 HIPPO+ MCI patients were included in the study. Imaging biomarkers of neurodegeneration, especially MR measurements, showed highest performance. For all biomarkers and both MCI groups, power increased with increasing follow-up time, irrespective of biomarker assessment frequency.

Conclusion: These findings provide information about biomarker enrichment and outcome measurements that could be employed to reduce MCI patient samples and treatment duration in future clinical trials.

Figure 1

Scaled slopes for individual biomarkers with 95% credible regions, estimated in MCI patients with abnormal CSF Aβ 1-42 concentration (ABETA+, A) or positive to hippocampal atrophy (HIPPO+, B) using all data available in the T0-T6-T12 time set, given the estimated intercept (intercept of 0 for KN-BSI). ADAS-cog=Alzheimer's Disease Assessment Scale-cognitive subscale; logPALZ=log-transformed PMOD Alzheimer score ; HCI=hypometabolic convergence index ; MetaROI=FDG-PET summary metric based on meta-analitically derived regions of interest reflecting AD hypometabolism pattern ; Hipp. volume=hippocampal volume automatically computed by Freesurfer algorithm; KN-BSI=brain atrophy rate measured by KN boundary shift integral technique . MR biomarkers showed highest effect size in both MCI groups.

Figure 2

Estimated power of a hypothetical clinical trial designed to detect 20% reduction in biomarker slope in MCI patients with abnormal CSF Aβ 1-42 concentration (ABETA+, A) or positive to hippocampal atrophy (HIPPO+, B), as a function of sample size (per treatment arm) and follow-up time sets. Significance level was set to α = 0.05. ADAS-cog=Alzheimer's Disease Assessment Scale-cognitive subscale; logPALZ=log-transformed PMOD Alzheimer score ; HCI=hypometabolic convergence index ; MetaROI=FDG-PET summary metric based on meta-analitically derived regions of interest reflecting AD hypometabolism pattern ; Hipp. volume=hippocampal volume automatically computed by Freesurfer algorithm; KN-BSI=brain atrophy rate measured by KN boundary shift integral technique ; T0=baseline, Tn=n-month follow-up. For all biomarkers and both MCI groups, the power increased with increasing follow-up time, irrespective of biomarker assessment frequency. MR measures showed highest power (with KN-BSI outperforming hippocampal volume), and a nonlinear trend.