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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.

Modeling Tumor Growth and Treatment Resistance Dynamics Characterizes Different Response to Gefitinib or Chemotherapy in Non‐Small Cell Lung Cancer