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  dental pain model after naproxcinod, naproxen and placebo administration

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Nombre de messages : 515
Date d'inscription : 15/05/2008

MessageSujet: dental pain model after naproxcinod, naproxen and placebo administration   Dim 6 Fév - 19:36

Modelling of pain intensity and informative dropout in a dental pain model after naproxcinod, naproxen and placebo administration

1. Marcus A. Björnsson1,2,*,
2. Ulrika S.H. Simonsson2

DOI: 10.1111/j.1365-2125.2011.03924.x

© 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society
http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2125.2011.03924.x/abstract;jsessionid=4603C556440096B71DEFBCF49C54E0B4.d02t03
Issue
British Journal of Clinical Pharmacology
British Journal of Clinical Pharmacology

Author InformationPublication History
Author Information

1. 1

Clinical Pharmacology & DMPK, AstraZeneca R&D Södertälje, Sweden
2. 2

Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

*Correspondence: Marcus A. Björnsson,

*Correspondence: Marcus Björnsson, Clinical Pharmacology & DMPK, AstraZeneca R&D Södertälje, S-15185 Södertälje, Sweden. Tel: +46 8 55327154. Fax: +46 8 55324994. E-mail: marcus.bjornsson@astrazeneca.com

1.


2.Competing interests: MB is an employee of AstraZeneca and US was employed by AstraZeneca 2006-2008.

This is an Accepted Article that has been peer-reviewed and approved for publication in the British Journal of Clinical Pharmacology, but has yet to undergo copy-editing and proof correction. Please cite this article as an “Accepted Article”; doi: 10.1111/1365-2125.2010.03924.x

1.

Competing interests: MB is an employee of AstraZeneca and US was employed by AstraZeneca 2006-2008.
2.

This is an Accepted Article that has been peer-reviewed and approved for publication in the British Journal of Clinical Pharmacology, but has yet to undergo copy-editing and proof correction. Please cite this article as an “Accepted Article”; doi: 10.1111/1365-2125.2010.03924.x

Keywords:

* naproxen;
* naproxcinod;
* NONMEM;
* time to event;
* dropout



What is already known about this subject: Modelling has been used to describe the pain relief and dropout for a few non-steroidal anti-inflammatory drugs.

What this study adds: This study shows the relationship between dose, plasma concentration, pain intensity and dropout for naproxen and naproxcinod. It also extends previous models to using a visual analogue scale for pain intensity instead of modelling pain relief on a categorical scale, and shows the value of including informative dropout in the simulations for visual predictive checks.
Summary

Aim 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 Emax 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 µmol/L. 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 provided a good way of assessing the goodness of fit when there is informative dropout.
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