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.

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“…Philipps et al [5] have addressed this problem with a normalizing transformation of MMSE scores. They estimated these scores and validated them using two population-based studies (the PAQUID and the Three-City Study in southwestern France) with a 20-year follow-up to estimate cognitive change.…”

“…Could the effect of education on dementia risk actually be partly an artifact of the measurement properties of the MMSE? The normalizing transformation proposed by Phillips et al [5] suggests at a minimum that studies using raw MMSE scores as outcomes should be reexamined and reestimated using this MMSE normalizing transformation.…”

“…Phillips et al [5] suggest that this transformation of MMSE scores should apply to any valid translation of the MMSE, even though it was developed and validated on the French-language version. They provide both a convenient look-up table as well as an R package that will compute the normalized transformation for the crude MMSE scale.…”