BACKGROUND: A mathematical model was developed to describe the longitudinal response in Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) obtained from the Alzheimer's Disease Neuroimaging Initiative. METHODS: The model was fit to the longitudinal ADAS-cog scores from 817 patients. Risk factors (age, apolipoprotein ɛ4 [APOE ɛ4] genotype, gender, family history of AD, years of education) and baseline severity were tested as covariates. RESULTS: Rate of disease progression increased with baseline severity. Age, APOE ɛ4 genotype, and gender were identified as potential covariates influencing disease progression. The rate of disease progression in patients with mild to moderate AD was estimated as approximately 5.5 points/yr. CONCLUSIONS: A disease progression model adequately described the natural decline of ADAS-cog observed in Alzheimer's Disease Neuroimaging Initiative. Baseline severity is an important covariate to predict a curvilinear rate of disease progression in normal elderly, mild cognitive impairment, and AD patients. Age, APOE ɛ4 genotype, and gender also influence the rate of disease progression.
BACKGROUND: A mathematical model was developed to describe the longitudinal response in Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) obtained from the Alzheimer's Disease Neuroimaging Initiative. METHODS: The model was fit to the longitudinal ADAS-cog scores from 817 patients. Risk factors (age, apolipoprotein ɛ4 [APOE ɛ4] genotype, gender, family history of AD, years of education) and baseline severity were tested as covariates. RESULTS: Rate of disease progression increased with baseline severity. Age, APOE ɛ4 genotype, and gender were identified as potential covariates influencing disease progression. The rate of disease progression in patients with mild to moderate AD was estimated as approximately 5.5 points/yr. CONCLUSIONS: A disease progression model adequately described the natural decline of ADAS-cog observed in Alzheimer's Disease Neuroimaging Initiative. Baseline severity is an important covariate to predict a curvilinear rate of disease progression in normal elderly, mild cognitive impairment, and ADpatients. Age, APOE ɛ4 genotype, and gender also influence the rate of disease progression.
Authors: Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Enchi Liu; John C Morris; Ronald C Petersen; Andrew J Saykin; Mark E Schmidt; Leslie Shaw; Judith A Siuciak; Holly Soares; Arthur W Toga; John Q Trojanowski Journal: Alzheimers Dement Date: 2011-11-02 Impact factor: 21.566
Authors: James A Rogers; Daniel Polhamus; William R Gillespie; Kaori Ito; Klaus Romero; Ruolun Qiu; Diane Stephenson; Marc R Gastonguay; Brian Corrigan Journal: J Pharmacokinet Pharmacodyn Date: 2012-07-21 Impact factor: 2.745
Authors: Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Jesse Cedarbaum; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; Johan Luthman; John C Morris; Ronald C Petersen; Andrew J Saykin; Leslie Shaw; Li Shen; Adam Schwarz; Arthur W Toga; John Q Trojanowski Journal: Alzheimers Dement Date: 2015-06 Impact factor: 21.566
Authors: Richard Dodel; Axel Rominger; Peter Bartenstein; Frederik Barkhof; Kaj Blennow; Stefan Förster; Yaroslav Winter; Jan-Philipp Bach; Julius Popp; Judith Alferink; Jens Wiltfang; Katharina Buerger; Markus Otto; Piero Antuono; Michael Jacoby; Ralph Richter; James Stevens; Isaac Melamed; Jerome Goldstein; Stefan Haag; Stefan Wietek; Martin Farlow; Frank Jessen Journal: Lancet Neurol Date: 2013-01-31 Impact factor: 44.182