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 biom arkers, 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 progressio n 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 Rel ated Disorders Associations (NINCDS-ADRDA) with a formula using expected Mi ni-Mental State Examination (MMSE) scores, scores at presentation, and a st andardized Estimate of duration. The patients are being followed up longitu dinally in our Alzheimer Disease Research Center. The time to clinically me aningful deterioration, defined as an MMSE score drop of 5 or more points, was compared for patients stratified as slow, intermediate, and rapid progr essors based on the preprogression rate. Cox regression analysis was used t o examine the contribution of demographic variables (age, sex, ethnicity, a nd level of education), initial MMSE scores, estimated symptom duration, an d the calculated preprogression rate to the time it took to reach the end p oint 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 = 3.1 6; P = .002) were significant in determining time to clinically meaningful decline during longitudinal follow-up (Cox regression analysis). Slow, inte rmediate, and rapid progressors (based on preprogression rates) experienced significantly different time intervals to clinically meaningful deteriorat ion, with the slow progressors taking the longest time, the intermediate pr ogressors in the middle, and the rapid progressors reaching the end point f irst (log rank X-1(2) = 9.81, P = .002). Conclusion: An easily calculable rate of early disease progression can clas sify patients as rapid, intermediate, or slow progressors with good predict ive value, even at initial presentation.