Validation and diagnostic accuracy of predictive curves for age-associated longitudinal cognitive decline in older adults

BACKGROUND: The Mini-Mental State Examination continues to be used frequently to screen for cognitive impairment in older adults, but it remains unclear how to interpret changes in its score over time to distinguish age-associated cognitive decline from an early degenerative process. We aimed to generate cognitive charts for use in clinical practice for longitudinal evaluation of age-associated cognitive decline. METHODS: We used data from the Canadian Study of Health and Aging from 7569 participants aged 65 years or older who completed a Mini-Mental State Examination at baseline, and at 5 and 10 years later to develop a linear regression model for the Mini-Mental State Examination score as a function of age and education. Based on this model, we generated cognitive charts designed to optimize accuracy for distinguishing participants with dementia from healthy controls. We validated our model using a separate data set of 6501 participants from the National Alzheimer's Coordinating Center's Uniform Data Set. RESULTS: For baseline measurement, the cognitive charts had a sensitivity of 80% (95% confidence interval [CI] 75% to 84%) and a specificity of 89% (95% CI 88% to 90%) for distinguishing healthy controls from participants with dementia. Similar sensitivities and specificities were observed for a decline over time greater than 1 percentile zone from the first measurement. Results in the validation sample were comparable, albeit with lower sensitivities. Negative predictive value was 99%. INTERPRETATION: Our innovative model, which factors in age and education, showed validity and diagnostic accuracy for determining whether older patients show abnormal performance on serial Mini-Mental State Examination measurements. Similar to growth curves used in pediatrics, cognitive charts allow longitudinal cognitive evaluation and enable prompt initiation of investigation and treatment when appropriate.