Predicting progression of Alzheimer's disease

Abstract

IntroductionClinicians need to predict prognosis of Alzheimer's disease (AD), and researchers need models of progression to develop biomarkers and clinical trials designs. We tested a calculated initial progression rate to see whether it predicted performance on cognition, function and behavior over time, and to see whether it predicted survival.MethodsWe used standardized approaches to assess baseline characteristics and to estimate disease duration, and calculated the initial (pre-progression) rate in 597 AD patients followed for up to 15 years. We designated slow, intermediate and rapidly progressing groups. Using mixed effects regression analysis, we examined the predictive value of a pre-progression group for longitudinal performance on standardized measures. We used Cox survival analysis to compare survival time by progression group.ResultsPatients in the slow and intermediate groups maintained better performance on the cognitive (ADAScog and VSAT), global (CDR-SB) and complex activities of daily living measures (IADL) (P values < 0.001 slow versus fast; P values < 0.003 to 0.03 intermediate versus fast). Interaction terms indicated that slopes of ADAScog and PSMS change for the slow group were smaller than for the fast group, and that rates of change on the ADAScog were also slower for the intermediate group, but that CDR-SB rates increased in this group relative to the fast group. Slow progressors survived longer than fast progressors (P = 0.024).ConclusionsA simple, calculated progression rate at the initial visit gives reliable information regarding performance over time on cognition, global performance and activities of daily living. The slowest progression group also survives longer. This baseline measure should be considered in the design of long duration Alzheimer's disease clinical trials.

Predictors of rapid cognitive decline in Alzheimer's disease: results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing

“…In their paper the authors noted that only a few studies had tried to define rapid cognitive decline: in an earlier paper, Soto et al (2005) proposed a 4 point or greater loss on the MMSE within 6 months and the loss of at least 1 more point on the MMSE during the following six months; Carcaillon et al (2007), in their bid to find a significant threshold of decline associated with a higher mortality rate, proposed a loss of 3 points or greater per year on the MMSE; Soto et al (2008b) concluded that the loss of 4 points or more in the MMSE during the first 6 months of follow-up was a predictor of a worse clinical course of AD. Two later papers give a definition of rapid cognitive decline based on the MMSE: Doody et al (2010) who used the same definition as in a previous study (Doody et al, 2001), dividing patients into slow progressors (decline of less than 2 points per year on the MMSE), intermediate progressors (2 to 4 points per year) and rapid progressors (≥5 points per year); and Musicco et al (2010) who considered the time-dependent probability of losing 5 points on the MMSE over two years as rapid disease progression. The rationale behind our choice of the loss of 6 points or more over 18 months is based on the fact that cognitive decline is not linear, as is demonstrated by recent research (Mendiondo et al, 2000).…”

Risk Factors for Progression of Alzheimer Disease in a Canadian Population: The Canadian Outcomes Study in Dementia (COSID)

“…8,9 Numerous risk factors were found to be related to the differential rate of Alzheimer disease progression, including age of onset, 10,11 sex, 8,12 epsilon 4 allele of the apolipoprotein E gene, 13 level of education, 14 baseline and change in MMSE score, 10 aphasia, 15,16 visuospatial processing, 17,18 neuropsychiatric symptoms, 19 hallucinations, 20 use of APs, 21 and ChEI use. 8,22 Being able to estimate disease progression is important, clinically, so that patients at high risk of progression can be identified, as well as for economic modelling, so that impact of treatments can be estimated.…”

Instantiated mixed effects modeling of Alzheimer's disease markers

“…Detailed studies into early state longitudinal Alzheimer's disease marker trajectory dynamics, using data-driven methods, have the potential to aid the effort in the development of measures that can accurately and robustly quantify indications of the disease, even before its presymtomatic and preclinal stages. Previously, hypothetical [23,24] and experimental models [13,14,50,10,20,7,25,41,21,4,5,1,12,15,53] of disease progression based on Alzheimer's disease markers, such as cerebrospinal fluid (CSF), imaging and cognitive markers have been proposed.…”

“…Recently, several approaches that regard the disease progression trajectory as a continuous process have been developed [13,14,50,10,20,7,25,41,21,4,5,1,12]. Many of the proposed frameworks rely on modeling cognitive scores such as the mini mental state examination (MMSE), Alzheimer's disease assessment scale (ADAS), clinical dementia rating sum of boxes (CDRSB), or Rey's audio visual learning test (RAVLT) among others, as surrogate measures of disease progression.…”

“…Doody et al [13] proposed the use of MMSE scores to compute an initial preprogression rate (rate of initial decline prior to first physician visit) used to classify subjects as slow, intermediate or rapid progressors. Using this estimated preprogression rate, Doody et al [14] tested the predicted survival rate of subjects and their performance on cognition, function and behavior over time. Yang et al [50] proposed an exponential model of ADAS scores and used this to estimate the disease duration and current pathological stage of a patient.…”