Modeling of Pain Intensity Measured on a Visual Analogue Scale and Informative Dropout in a Dental Pain Model after Naproxcinod and Naproxen Administration
M.A. Björnsson(1,2), U.S.H. Simonsson(2)
(1)Clinical Pharmacology & DMPK, AstraZeneca R&D Södertälje, Sweden; (2)Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
Objectives: The objective of this model was to describe the pain intensity (PI) and dropout due to request of rescue medication after administration of naproxcinod, naproxen or placebo after wisdom tooth removal.
Methods: In a double-blind dose-finding study 242 patients that requested pain relief after removal of mandibular wisdom teeth were randomised to naproxcinod 375, 750, 1500 or 2250 mg, naproxen 500 mg, or placebo . Plasma was collected for analysis of total and unbound naproxen plasma concentrations, and PI were measured on a 100 mm visual analogue scale (VAS) for up to 8 hours post-dose. Patients needing additional pain relief could request rescue medication, and the time of requesting rescue medication was recorded. The pharmacokinetic/pharmacodynamic (PK/PD) analysis was performed using NONMEM VI. Goodness of fit was assessed using objective function values, standard errors, graphics and visual predictive checks (VPC).
Results: A one-compartment model with transit compartment absorption and saturable protein binding described the concentrations of naproxen. An exponential model described the placebo response on the PI, and the drug effect was described using a sigmoid Emax model. Typical maximal placebo effect was a decrease in PI by 20.2 %, and EC50 was 0.135 μmol/L. The dropout was modelled using a Weibull time-to-event model, where the hazard was dependent on the model predicted PI as well as baseline PI. Since the dropout was not at random, it was necessary to include the simulated dropout in the VPCs of PI.
Conclusions: This model provides a pharmacometric platform that describes the placebo effects and relationship between PI measured on a VAS and dropout after dental extraction. The effects of naproxcinod and naproxen on PI and dropout were well described. VPCs created by simultaneous simulations of a continuous variable and time to event provide a good way of assessing the goodness of fit when there is informative dropout.
 Hill et al., Clinical Therapeutics 2006; 28:1279-1295