Bayesian methods for pharmacokinetic/ pharmacodynamic modeling of pazopanib-induced increases in blood pressure and transaminases

A. Benjamin Suttle, Paul De Souza, Thangam Arumugham

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    Relationships between plasma pazopanib concentrations and the probability of elevations in blood pressure, a marker of vascular endothelial growth factor receptor inhibition, and alanine aminotransferase (ALT) were investigated with logistic regression models. Data from a Phase I dose-escalation study in cancer patients (n = 57) were examined to determine the relationship between steady-state trough plasma pazopanib concentrations (Cτ) and a clinically significant blood pressure increase, using a Bayesian logistic regression model. Data from 5 monotherapy studies in cancer patients (n = 344) were pooled to investigate the relationship between Cτ and maximum ALT ≥ 3× the upper limit of normal (ULN), using a Bayesian logistic regression model incorporating an asymptote. Both models were fit using WinBUGS. The median (95% credible interval, CrI) Cτ at which the probability of a clinically significant increase in blood pressure was 50% (EC50) was 12.3 µg/mL (6.12, 18.4). The median (95% CrI) EC50 for the maximum probability of ALT ≥ 3× ULN was 15.4 µg/mL (3.8, 41.2) and the median (95% CrI) maximum probability of ALT ≥ 3× ULN was 21% (14.5, 43.1). Results suggest that dose adjustments could be useful in managing the potential for hepatotoxicity.
    Original languageEnglish
    Pages (from-to)377-384
    Number of pages8
    JournalJournal of Clinical Pharmacology
    Volume53
    Issue number4
    DOIs
    Publication statusPublished - 2013

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