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A Method for Estimating Progression Rates in Alzheimer Disease
Rachelle Smith Doody, MD, PhD;
Paul Massman, PhD;
J. Kay Dunn, PhD
Arch Neurol. 2001;58:449-454.
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 21 = 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.
From the Departments of Neurology, Alzheimer's Disease Research Center
(Drs Doody and Massman), and Internal Medicine, Division of Design and Analysis
(Dr Dunn), Baylor College of Medicine, Houston, Tex.
Reprints: Rachelle Smith Doody, MD, PhD, Baylor College of Medicine,
Department of Neurology, 6550 Fannin St, Suite 1801, Houston, TX 77030.
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