Improved Utilization of ADAS-cog Assessment Data through Item Response Theory based Pharmacometric Modeling
2014 (English)In: Pharmaceutical research, ISSN 0724-8741, E-ISSN 1573-904X, Vol. 31, no 8, 2152-2165 p.Article in journal (Refereed) Published
This work investigates improved utilization of ADAS-cog data (the primaryoutcome in Alzheimer's disease (AD) trials of mild and moderate AD) by combiningpharmacometric modeling and item response theory (IRT).
A baseline IRT model characterizing the ADAS-cog was built based on datafrom 2744 individuals. Pharmacometric methods were used to extend the baseline IRTmodel to describe longitudinal ADAS-cog scores from an 18-month clinical study with322 patients. Sensitivity of the ADAS-cog items in different patient populations as wellas the power to detect a drug effect in relation to total score base methods wereassessed with IRT based models.
IRT analysis was able to describe both total and item level baseline ADAS-cogdata. Longitudinal data were also well described. Differences in the informationcontent of the item level components could be quantitatively characterized and rankedfor mild cognitively impairment and mild AD populations. Based on clinical trialsimulations with a theoretical drug effect, the IRT method demonstrated a significantlyhigher power to detect drug effect compared to the traditional method of analysis.
A combined framework of IRT and pharmacometric modeling permits amore effective and precise analysis than total score based methods and thereforeincreases the value of ADAS-cog data.
Place, publisher, year, edition, pages
Springer, 2014. Vol. 31, no 8, 2152-2165 p.
Alzheimer's disease, Item response theory, ADAS-cog, pharmacometrics, nonlinear mixed effect models
Research subject Pharmaceutical Science
IdentifiersURN: urn:nbn:se:uu:diva-216524DOI: 10.1007/s11095-014-1315-5ISI: 000341712400026OAI: oai:DiVA.org:uu-216524DiVA: diva2:690155
FunderEU, FP7, Seventh Framework Programme, 115156