uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
Multinomial logistic estimation of Markov-chain models for modeling sleep architecture in primary insomnia patients
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakometri)
Show others and affiliations
2010 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 37, no 2, 137-155 p.Article in journal (Refereed) Published
Abstract [en]

Hypnotic drug development calls for a better understanding of sleep physiology in order to improve and differentiate novel medicines for the treatment of sleep disorders. On this basis, a proper evaluation of polysomnographic data collected in clinical trials conducted to explore clinical efficacy of novel hypnotic compounds should include the assessment of sleep architecture and its drug-induced changes. This work presents a non-linear mixed-effect Markov-chain model based on multinomial logistic functions which characterize the time course of transition probabilities between sleep stages in insomniac patients treated with placebo. Polysomnography measurements were obtained from patients during one night treatment. A population approach was used to describe the time course of sleep stages (awake stage, stage 1, stage 2, slow-wave sleep and REM sleep) using a Markov-chain model. The relationship between time and individual transition probabilities between sleep stages was modelled through piecewise linear multinomial logistic functions. The identification of the model produced a good adherence of mean post-hoc estimates to the observed transition frequencies. Parameters were generally well estimated in terms of CV, shrinkage and distribution of empirical Bayes estimates around the typical values. The posterior predictive check analysis showed good consistency between model-predicted and observed sleep parameters. In conclusion, the Markov-chain model based on multinomial logistic functions provided an accurate description of the time course of sleep stages together with an assessment of the probabilities of transition between different stages.

Place, publisher, year, edition, pages
2010. Vol. 37, no 2, 137-155 p.
Keyword [en]
Markov-chain model, Multinomial logistic functions, Sleep, Insomnia, NONMEM, Polychotomous data, Categorical data
National Category
Pharmaceutical Sciences
URN: urn:nbn:se:uu:diva-137791DOI: 10.1007/s10928-009-9148-2ISI: 000277178800002OAI: oai:DiVA.org:uu-137791DiVA: diva2:378543
Available from: 2010-12-15 Created: 2010-12-15 Last updated: 2011-11-30Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Karlsson, Mats O.
By organisation
Department of Pharmaceutical Biosciences
In the same journal
Journal of Pharmacokinetics and Pharmacodynamics
Pharmaceutical Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 164 hits
ReferencesLink to record
Permanent link

Direct link