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Updated: May 29, 2026
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A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Basic clinical parameters predict gefitinib efficacy in non-small cell lung cancer
Andreas Pircher1, Ernst Ulsperger, Rene Hack
1Medical University of Innsbruck, Department of Internal Medicine V/ Haematology and Oncology, Anichstrasse 35, A-6020 Innsbruck, Austria. andreas.pircher@i-med.ac.at
Anticancer Research
|August 27, 2011
Summary
Gefitinib is effective for non-small cell lung cancer (NSCLC). Clinical factors like gender, smoking history, and skin reactions predict treatment response, offering value when EGFR mutation status is unknown.
Area of Science:
- Oncology
- Pharmacology
Background:
- Epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) is treated with gefitinib.
- Retrospective analysis of 82 advanced NSCLC patients treated with gefitinib.
Purpose of the Study:
- Correlate gefitinib benefits with clinical baseline and therapy-related parameters.
- Identify predictors of treatment response in NSCLC patients.
Main Methods:
- Retrospective analysis of 82 advanced NSCLC patients.
- Data collected on patient demographics, smoking history, cancer histology, and treatment outcomes.
- Correlation of clinical parameters with gefitinib efficacy.
Main Results:
- Partial remission in 10%, stable disease in 29%. Median progression-free survival (PFS) 3.1 months, overall survival (OS) 9.2 months.
- Gefitinib more efficacious in women, never-smokers, and bronchoalveolar carcinoma patients.
- Anemia and elevated C-reactive protein were unfavorable. Skin reactions correlated with better response and survival.
Conclusions:
- Basic clinical parameters predict response to EGFR tyrosine-kinase inhibitor therapy.
- These predictors are valuable when EGFR mutation status is unavailable.
