Normalized Mini-Mental State Examination for Assessing Cognitive Change in Population-Based Brain Aging Studies

Abstract

Background: The Mini-Mental State Examination (MMSE) is widely used in population-based longitudinal studies to quantify cognitive change. However, its poor metrological properties, mainly ceiling/floor effects and varying sensitivity to change, have largely restricted its usefulness. We propose a normalizing transformation that corrects these properties, and makes possible the use of standard statistical methods to analyze change in MMSE scores. Methods: The normalizing transformation designed to correct at best the metrological properties of MMSE was estimated and validated on two population-based studies (n = 4,889, 20-year follow-up) by cross-validation. The transformation was also validated on two external studies with heterogeneous samples mixing normal and pathological aging, and samples including only demented subjects. Results: The normalizing transformation provided correct inference in contrast with models analyzing the change in crude MMSE that most often lead to biased estimates of risk factors and incorrect conclusions. Conclusions: Cognitive change can be easily and properly assessed with the normalized MMSE using standard statistical methods such as linear (mixed) models.