Modeling Tumor Growth and Treatment Resistance Dynamics Characterizes Different Response to Gefitinib or Chemotherapy in Non‐Small Cell Lung Cancer. (7th February 2020)

• Record Type: Journal Article
• Authors: Nagase, Mario; Aksenov, Sergey; Yan, Hong; Dunyak, James; Al‐Huniti, Nidal
• Is Part Of: CPT: pharmacometrics & systems pharmacology. Volume 9:Number 3(2020)
• Page Start: 143
• Page End: 152
• Publication Date: 2020-02-07
• Subjects: Pharmacokinetics -- Periodicals; Pharmacology -- Periodicals; Pharmacokinetics; Periodicals; 615.05
• DOI: 10.1002/psp4.12490
• Languages: English
• ISSNs: 2163-8306

Abstract

Abstract : Differences in the effect of gefitinib and chemotherapy on tumor burden in non‐small cell lung cancer remain to be fully understood. Using a Bayesian hierarchical model of tumor size dynamics, we estimated the rates of tumor growth and treatment resistance for patients in the Iressa Pan‐Asia Study study (NCT00322452). The following relationships characterize greater efficacy of gefitinib in epidermal growth factor receptor ( EGFR ) positive tumors: Maximum drug effect is, in decreasing order, gefitinib in EGFR ‐positive, chemotherapy in EGFR ‐positive, chemotherapy in EGFR ‐negative, and gefitinib in EGFR ‐negative tumors; the rate of resistance emergence is, in increasing order: gefitinib in EGFR positive, chemotherapy in EGFR positive, while each is plausibly similar to the rate in EGFR negative tumors, which are estimated with less certainty. The rate of growth is smaller in EGFR ‐positive than in EGFR ‐negative fully resistant tumors, regardless of treatment. The model can be used to compare treatment effects and resistance dynamics among different drugs.