Methods to crosswalk between cognitive test scores using data from the Alzheimer's Disease Neuroimaging Cohort

Abstract

INTRODUCTION

Studies use multiple different instruments to measure dementia-related outcomes, making head-to-head comparisons of interventions difficult.

METHODS

To address this gap, we developed two methods to crosswalk estimated treatment effects on cognitive outcomes that are flexible, broadly applicable, and do not rely on strong distributional assumptions.

RESULTS

We present two methods to crosswalk effect estimates using one measure to estimates using another measure, illustrated with global cognitive measures from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, we develop crosswalks for the following measures and associated change scores over time: the clinical dementia rating scale sum of box (CDR-SB), Montreal Cognitive Assessment (MoCA), and Mini-Mental State Examination (MMSE) scores. Finally, a setting in which crosswalking is not appropriate is illustrated with plasma phosphorylated tau (p-tau) concentration and global cognitive measures.

DISCUSSION

Given the inconsistent collection and reporting of dementia and cognitive outcomes across studies, these crosswalking methods offer a valuable approach to harmonizing and comparing results reported on different scales.

Highlights

• Developed methods to crosswalk from one cognitive outcome to another in studies of dementia interventions.
• Methods illustrated using combinations of global cognitive tests: the CDR-SB, MoCA, and MMSE.
• Illustrates scenarios where crosswalking may not be appropriate for certain combinations of measures.
• Crosswalking methods support comparison of interventions with accurate error propagation.
• Facilitates inclusion of more studies in meta-analyses by increasing data comparability.