Frontiers in pharmacology
Exploratory machine-learning analysis of bevacizumab exposure and circulating VEGF dynamics in patients with cancer
Par Theofili I, Liolis E, Koutras A et 2 autres.
Contenu en anglais
Résumé
Introduction
This study explored pharmacokinetic and pharmacodynamic factors associated with circulating vascular endothelial growth factor (VEGF) dynamics during bevacizumab treatment.
Methods
A secondary analysis was conducted using data from 74 patients with breast, ovarian, cervical, non-small cell lung, or colorectal cancer. Paired pre- and post-infusion serum concentrations of bevacizumab and VEGF were measured by ELISA. Exploratory dimensionality-reduction methods and supervised tree-based models were applied. Artificial neural networks were used only as a complementary exploratory analysis on the same dataset.