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Comparing the differential drug effect model to the proportional odds model
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakometri)ORCID iD: 0000-0003-3531-9452
(Farmakometri)
(Farmakometri)
(English)Manuscript (Other academic)
National Category
Clinical Medicine
Identifiers
URN: urn:nbn:se:uu:diva-93721OAI: oai:DiVA.org:uu-93721DiVA: diva2:167289
Available from: 2005-11-11 Created: 2005-11-11 Last updated: 2015-01-23
In thesis
1. Models for Ordered Categorical Pharmacodynamic Data
Open this publication in new window or tab >>Models for Ordered Categorical Pharmacodynamic Data
2005 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In drug development clinical trials are designed to investigate whether a new treatment is safe and has the desired effect on the disease in the target patient population. Categorical endpoints, for example different ranking scales or grading of adverse events, are commonly used to measure effects in the trials.

Pharmacokinetic/Pharmacodynamic (PK/PD) models are used to describe the plasma concentration of a drug over time and its relationship to the effect studied. The models are utilized both in drug development and in discussions with drug regulating authorities. Methods for incorporation of ordered categorical data in PK/PD models were studied using a non-linear mixed effects modelling approach as implemented in the software NONMEM. The traditionally used proportional odds model was used for analysis of a 6-grade sedation scale in acute stroke patients and for analysis of a T-cell receptor expression in patients with Multiple Sclerosis, where the results also were compared with an analysis of the data on a continuous scale. Modifications of the proportional odds model were developed to enable analysis of a spontaneously reported side-effect and to analyze situations where the scale used is heterogeneous or where the drug affects the different scores in the scale in a non-proportional way. The new models were compared with the proportional odds model and were shown to give better predictive performances in the analyzed situations.

The results in this thesis show that categorical data obtained in clinical trials with different design and different categorical endpoints successfully can be incorporated in PK/PD models. The models developed can also be applied to analyses of other ordered categorical scales than those presented.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2005. 60 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 20
Keyword
Pharmacokinetics/Pharmacotherapy, Pharmacodynamic, Modelling, Categorical data, NONMEM, Proportional odds model, Markov model, Differential drug effect model, Farmakokinetik/Farmakoterapi
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-6125 (URN)91-554-6394-0 (ISBN)
Public defence
2005-12-02, B42, BMC, Husargatan 3, Uppsala, 09:15
Opponent
Supervisors
Available from: 2005-11-11 Created: 2005-11-11 Last updated: 2011-07-08Bibliographically approved

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Kjellsson, Maria C.Karlsson, Mats O.

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