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Modelling of pain intensity and informative dropout in a dental pain model after naproxcinod, naproxen and placebo administration
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.
2011 (English)In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 71, no 6, 899-906 p.Article in journal (Refereed) Published
Abstract [en]

AIMS To describe pain intensity (PI) measured on a visual analogue scale (VAS) and dropout due to request for rescue medication after administration of naproxcinod, naproxen or placebo in 242 patients after wisdom tooth removal. METHODS Non-linear mixed effects modelling was used to describe the plasma concentrations of naproxen, either formed from naproxcinod or from naproxen itself, and their relationship to PI and dropout. Goodness of fit was assessed by simultaneous simulations of PI and dropout. RESULTS Baseline PI for the typical patient was 52.7 mm. The PI was influenced by placebo effects, using an exponential model, and by naproxen concentrations using a sigmoid E-max model. Typical maximal placebo effect was a decrease in PI by 20.2%, with an onset rate constant of 0.237 h-1. EC50 was 0.135 mu mol l-1. A Weibull time-to-event model was used for the dropout, where the hazard was dependent on the predicted PI and by the PI at baseline. Since the dropout was not at random, it was necessary to include the simulated dropout in visual predictive checks (VPC) of PI. CONCLUSIONS This model describes the relationship between drug effects, PI and the likelihood of dropout after naproxcinod, naproxen and placebo administration. The model provides an opportunity to describe the effects of other doses or formulations, after dental extraction. VPC created by simultaneous simulations of PI and dropout provides a good way of assessing the goodness of fit when there is informative dropout.

Place, publisher, year, edition, pages
2011. Vol. 71, no 6, 899-906 p.
Keyword [en]
dropout, naproxcinod, naproxen, NONMEM, time to event
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-154347DOI: 10.1111/j.1365-2125.2011.03924.xISI: 000290449500012PubMedID: 21272053OAI: oai:DiVA.org:uu-154347DiVA: diva2:420100
Available from: 2011-05-31 Created: 2011-05-31 Last updated: 2017-12-11Bibliographically approved
In thesis
1. Pharmacometric Models in Anesthesia and Analgesia
Open this publication in new window or tab >>Pharmacometric Models in Anesthesia and Analgesia
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Modeling is a valuable tool in drug development, to support decision making, improving study design, and aid in regulatory approval and labeling. This thesis describes the development of pharmacometric models for drugs used in anesthesia and analgesia.

Models describing the effects on anesthetic depth, measured by the bispectral index (BIS), for a commonly used anesthetic, propofol, and for a novel anesthetic, AZD3043, were developed. The propofol model consisted of two effect-site compartments, and could describe the effects of propofol when the rate of infusion is changed during treatment. AZD3043 had a high clearance and a low volume of distribution, leading to a short half-life. The distribution to the effect site was fast, and together with the short plasma half-life leading to a fast onset and offset of effects. It was also shown that BIS after AZD3043 treatment is related to the probability of unconsciousness similar to propofol.

In analgesia studies dropout due to lack of efficacy is common. This dropout is not at random and needs to be taken into consideration in order to avoid bias. A model was developed describing the PK, pain intensity and dropout hazard for placebo, naproxen and a novel analgesic compound, naproxcinod, after removal of a wisdom tooth. The model provides an opportunity to describe the effects of other doses or formulations. Visual predictive checks created by simultaneous simulations of PI and dropout provided a good way of assessing the goodness of fit when there is informative dropout.

The performance of non-linear mixed effects models in the presence of informative dropout, with and without including models that describe such informative dropout was investigated by simulations and re-estimations. When a dropout model was not included there was in general more bias. The bias increased with decreasing number of observations per subject, increasing placebo effect and increasing dropout rate. Bias was relatively unaffected by the number of subjects in the study. The bias had, in general, little effect on simulations of the underlying efficacy score, but a dropout model would still be needed in order to make realistic simulations.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2013. 56 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 173
Keyword
Pharmacometrics, Anesthesia, Analgesia, Dropout, NONMEM
National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
Identifiers
urn:nbn:se:uu:diva-205580 (URN)978-91-554-8726-3 (ISBN)
Public defence
2013-10-04, B22, Uppsala Biomedicinska Centrum (BMC), Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2013-09-13 Created: 2013-08-20 Last updated: 2014-01-22

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