The role of smoking status on the progression-free survival of non-small cell lung cancer patients harboring activating epidermal growth factor receptor (EGFR) mutations receiving first-line EGFR tyrosine kinase inhibitor versus platinum doublet chemotherapy: a meta-analysis of prospective randomized trials

Abstract

Background: Univariate analyses from several randomized phase III trials seemed to suggest ever-smokers with advanced mutated epidermal growth factor receptor (EGFRm) non-small cell lung cancer (NSCLC) did not seem to benefit from EGFR tyrosine kinase inhibitors (TKIs) as first-line treatment when compared with platinum-doublet chemotherapy as measured by progression-free survival (PFS).

Methods: A literature-based meta-analysis of PFS outcomes as measured by log-transformed pooled hazard ratio (HR) was performed using a random-effect model. Pooled HRs for smoking status, age, gender, ethnicity, type of EGFR mutation, and EGFR TKI were obtained. Comparison of the pooled HR was performed by metaregression analysis.

Results: Among the 1,649 EGFRm NSCLC patients analyzed from 7 prospective randomized trials (WJTOG3405, NEJ002, EURTAC, OPTIMAL, LUX Lung-3, LUX Lung-6, and ENSURE), 83.7% were Asians, and 30.0% were ever-smokers. An equal percentage of ever-smokers received doublet chemotherapy (30.2%) or EGFR TKI (30.0%). The pooled HR for PFS was 0.29 (95% confidence interval [CI]: 0.21-0.39) for never-smokers and 0.54 (95% CI: 0.38-0.76) for ever-smokers (p < .007 by metaregression). The pooled PFS HR for exon 19 deletion was 0.25 (95% CI: 0.19-0.31) and 0.44 for exon 21 substitution (95% CI: 0.34-0.57) (p < .001 by metaregression analysis). The pooled PFS HR was 0.33 (95% CI: 0.24-0.46) for Asians and 0.48 for non-Asians (95% CI: 0.28-0.84) (p = .261 by metaregression analysis).

Conclusion: EGFRm NSCLC patients derived significant PFS benefit from TKI over platinum-doublet chemotherapy as first-line treatment regardless of smoking status; however, PFS benefit is significantly better in never-smokers by metaregression analysis.

Keywords: Afatinib; EGFR TKIs; EGFR mutant non-small cell lung cancer; Erlotinib; Gefitinib; Meta-analysis; Smoking status.

Figure 1.

Trial selection process. Abbreviations: EGFR, epidermal growth factor receptor; EGFRm, mutated EGFR; TKI, tyrosine kinase inhibitor.

Figure 2.

Pooled hazard ratios (HRs) and metaregression analysis of pooled HRs of EGFR TKI compared with platinum-doublet chemotherapy. (A): HRs and metaregression analysis according to smoking status. (B): HRs and metaregression analysis according to two common types of EGFR mutation. (C): HRs and metaregression analysis according to ethnicity. (D): HRs and metaregression analysis according to age. (E): HRs and metaregression analysis according to gender. (F): HRs and metaregression analysis according to type of EGFR TKI. Abbreviations: CI, confidence interval; EGFR, epidermal growth factor receptor; TKI, tyrosine kinase inhibitor.

Figure 2.

Pooled hazard ratios (HRs) and metaregression analysis of pooled HRs of EGFR TKI compared with platinum-doublet chemotherapy. (A): HRs and metaregression analysis according to smoking status. (B): HRs and metaregression analysis according to two common types of EGFR mutation. (C): HRs and metaregression analysis according to ethnicity. (D): HRs and metaregression analysis according to age. (E): HRs and metaregression analysis according to gender. (F): HRs and metaregression analysis according to type of EGFR TKI. Abbreviations: CI, confidence interval; EGFR, epidermal growth factor receptor; TKI, tyrosine kinase inhibitor.