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Lewis Sheiner


2018
Montreux, Switzerland



2017
Budapest, Hungary

2016
Lisboa, Portugal

2015
Hersonissos, Crete, Greece

2014
Alicante, Spain

2013
Glasgow, Scotland

2012
Venice, Italy

2011
Athens, Greece

2010
Berlin, Germany

2009
St. Petersburg, Russia

2008
Marseille, France

2007
K°benhavn, Denmark

2006
Brugge/Bruges, Belgium

2005
Pamplona, Spain

2004
Uppsala, Sweden

2003
Verona, Italy

2002
Paris, France

2001
Basel, Switzerland

2000
Salamanca, Spain

1999
Saintes, France

1998
Wuppertal, Germany

1997
Glasgow, Scotland

1996
Sandwich, UK

1995
Frankfurt, Germany

1994
Greenford, UK

1993
Paris, France

1992
Basel, Switzerland



Printable version

PAGE. Abstracts of the Annual Meeting of the Population Approach Group in Europe.
ISSN 1871-6032

Reference:
PAGE 25 (2016) Abstr 3687 [www.page-meeting.org/?abstract=3687]


Oral: Drug/Disease modelling


D-08 Marc Vandemeulebroecke A longitudinal Item Response Theory model to characterize cognition over time in elderly subjects

Marc Vandemeulebroecke, Johanna Mielke, Peter Quarg, Tillmann Krahnke, Bj÷rn Bornkamp, Andreas Monsch

Novartis Pharma AG; Memory Clinic Basel

Objectives: The goals of this work were to investigate which cognitive domains carry most information on earliest signs of cognitive decline in the elderly, to characterize the subjects' cognitive trajectory over time and to understand which subject characteristics impact this trajectory. This is relevant for better understanding whom to treat and what to measure in early intervention trials in slowly progressing neurodegenerative diseases such as Alzheimer’s disease (AD).

Methods: A longitudinal Item Response Theory (IRT) model was developed for cognitive data from the BASEL study, in which 1750 mostly healthy elderly subjects were observed over up to 14 years per subject. The model extends an earlier cross-sectional model [1] (which was inspired by [2]) into a fully longitudinal IRT model, in which the multifaceted nature of the response and its longitudinal trajectory are modeled jointly. It was implemented in a Bayesian framework with noninformative priors, using WinBUGS, JAGS and STAN.

Results: 'CVLT-Word List Learning' and 'CERAD-Word List Learning' as well as 'CVLT-Word List Long Delay Free Recall' and 'CERAD-Word List Delayed Recall' carried most information in the BASEL sample (15.5%, 13.1%, 10.3% and 8.8%, respectively, of the total amount of information). The Mini Mental Status Examination (MMSE) and word list recognition tasks were informative only in the range of low cognitive abilities. Greater age at baseline, positive APOE4 carrier status, and less years of education were significantly associated with a faster cognitive decline. WinBugs, JAGS and STAN provided virtually identical results. JAGS provided the best compromise between efficiency and practicality.

Conclusions: Fully longitudinal IRT modeling, as applied here in a mostly healthy elderly population, is a suitable method to capture the multifaceted nature of cognition and its longitudinal trajectory jointly. It is computationally more intensive than cross-sectional IRT models (such as [1] and [2]), but it allows the estimation of the IRT parameters based on all data. It would be of interest to apply this method also to a cohort with prodromal or mild AD.



References:
[1] Vandemeulebroecke M, Mielke J, Krahnke T, Monsch AU (2014). Identifying neuropsychological domains with high information on early signs of cognitive decline. PAGE conference
[2] Ueckert S, Plan EL, Ito K, Karlsson MO, Corrigan B, Hooker AC (2013). Benefits of an Item Response Theory Based Analysis of ADAS-Cog Assessments. American Conference on Pharmacometrics