BACKGROUND: Convincing data on epidermal growth factor receptor (EGFR) mutations in Chinese patients with non-small-cell lung cancer (NSCLC) remain limited. We investigated the relevance of demographic characteristics and EGFR mutations, correlations between the efficacy of gefitinib and EGFR mutations in NSCLC, and to identify individuals who would likely benefit from gefitinib. METHODS: We conducted a meta-analysis based on updated individual patient data from six medical centers in mainland China. Outcome measures included the EGFR mutation status, demographic characteristics, response, and survival. RESULTS: Among 506 patients with NSCLC who received EGFR mutation analysis, the EGFR mutation rate was 30.04%. Patients with adenocarcinoma had a higher mutation rate than those with non-adenocarcinoma (44.1% vs 9.2%; p < 0.00001). The EGFR mutation rate for smokers was 15.1%, lower than that for non-smokers (45.5%) (p < 0.00001). Male patients had a lower mutation rate than female patients (23.1% vs 42.9%; p < 0.0001). Multivariate analysis showed that "adenocarcinoma" and "non-smoker" were independent predictors of EGFR mutations. In a subgroup of 57 patients with complete treatment data, the response rate to gefitinib in the EGFR mutant group was 60.7%, significantly higher than that in the wild-type EGFR group (17.2%) (odds ratio, 5.78; 95% CI, 1.95-17.13; p = 0.002). "EGFR mutation", "adenocarcinoma," and "non-smoker" were independent predictors of response. Overall survival in the EGFR mutant group and the wild-type group did not differ significantly (hazard ratio, 0.60; 95% CI, 0.32-1.12; p = 0.110). "Adenocarcinoma status" was an independent prognostic factor for survival. CONCLUSIONS: In mainland China, "adenocarcinoma" and "non-smoker" are independent predictors for EGFR mutations. Response to gefitinib favors patients with EGFR mutations. The clinical selected populations for gefitinib are non-smokers with adenocarcinoma.
BACKGROUND: Convincing data on epidermal growth factor receptor (EGFR) mutations in Chinese patients with non-small-cell lung cancer (NSCLC) remain limited. We investigated the relevance of demographic characteristics and EGFR mutations, correlations between the efficacy of gefitinib and EGFR mutations in NSCLC, and to identify individuals who would likely benefit from gefitinib. METHODS: We conducted a meta-analysis based on updated individual patient data from six medical centers in mainland China. Outcome measures included the EGFR mutation status, demographic characteristics, response, and survival. RESULTS: Among 506 patients with NSCLC who received EGFR mutation analysis, the EGFR mutation rate was 30.04%. Patients with adenocarcinoma had a higher mutation rate than those with non-adenocarcinoma (44.1% vs 9.2%; p < 0.00001). The EGFR mutation rate for smokers was 15.1%, lower than that for non-smokers (45.5%) (p < 0.00001). Male patients had a lower mutation rate than female patients (23.1% vs 42.9%; p < 0.0001). Multivariate analysis showed that "adenocarcinoma" and "non-smoker" were independent predictors of EGFR mutations. In a subgroup of 57 patients with complete treatment data, the response rate to gefitinib in the EGFR mutant group was 60.7%, significantly higher than that in the wild-type EGFR group (17.2%) (odds ratio, 5.78; 95% CI, 1.95-17.13; p = 0.002). "EGFR mutation", "adenocarcinoma," and "non-smoker" were independent predictors of response. Overall survival in the EGFR mutant group and the wild-type group did not differ significantly (hazard ratio, 0.60; 95% CI, 0.32-1.12; p = 0.110). "Adenocarcinoma status" was an independent prognostic factor for survival. CONCLUSIONS: In mainland China, "adenocarcinoma" and "non-smoker" are independent predictors for EGFR mutations. Response to gefitinib favors patients with EGFR mutations. The clinical selected populations for gefitinib are non-smokers with adenocarcinoma.
Authors: Ellen T Chang; Sarah J Shema; Heather A Wakelee; Christina A Clarke; Scarlett Lin Gomez Journal: Cancer Epidemiol Biomarkers Prev Date: 2009-07-21 Impact factor: 4.254