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A method for estimating progression rates in Alzheimer disease.

BACKGROUND
The ability to predict progression of disease in patients with Alzheimer disease (AD) would aid clinicians, improve the validation of biomarkers, and contribute to alternative study designs for AD therapies.


OBJECTIVE
To test a calculated rate of initial decline prior to the first physician visit (preprogression rate) for its ability to predict progression during subsequent follow-up.


METHODS
We calculated preprogression rates for 298 patients with probable or possible AD (using the criteria of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Associations (NINCDS-ADRDA) with a formula using expected Mini-Mental State Examination (MMSE) scores, scores at presentation, and a standardized estimate of duration. The patients are being followed up longitudinally in our Alzheimer Disease Research Center. The time to clinically meaningful deterioration, defined as an MMSE score drop of 5 or more points, was compared for patients stratified as slow, intermediate, and rapid progressors based on the preprogression rate. Cox regression analysis was used to examine the contribution of demographic variables (age, sex, ethnicity, and level of education), initial MMSE scores, estimated symptom duration, and the calculated preprogression rate to the time it took to reach the end point across the groups.


RESULTS
Both initial MMSE (hazard ratio, 0.95 (0.002); z = 4.19; P<.001) and the calculated preprogression rate (hazard ratio, 1.06 (0.019); z = 3.16; P =.002) were significant in determining time to clinically meaningful decline during longitudinal follow-up (Cox regression analysis). Slow, intermediate, and rapid progressors (based on preprogression rates) experienced significantly different time intervals to clinically meaningful deterioration, with the slow progressors taking the longest time, the intermediate progressors in the middle, and the rapid progressors reaching the end point first (log rank chi(2)(1) = 9.81, P =.002).


CONCLUSION
An easily calculable rate of early disease progression can classify patients as rapid, intermediate, or slow progressors with good predictive value, even at initial presentation.