Abstract
BACKGROUND: Epidermal growth factor receptor (EGFR) mutation represents a good response to EGFR-tyrosine kinase inhibitor and an advantageous prognostic factor in advanced-stage non-small cell lung cancer (NSCLC). However, the predictive value of EGFR mutation for prognosis in NSCLC patients after complete surgery, which more reflective of natural process, remains controversial. We sought to examine the predictive value of EGFR mutation in NSCLC. Several studies with small sample sizes have been reported but small studies bring bias especially in a postoperative setting. Therefore, we sought to pool all current evidence to show the true effects. METHODS: Electronic databases were used to search the relevant articles. Disease-free survival (DFS), which will be less effected by subsequent treatments after recurrence, was the primary endpoint. The DFS between EGFR mutated and wild-type patients were compared focus on stage I patients who are rarely received adjuvant therapy. Besides, the DFS of patients with 19 exon deletion (19del) and 21 exon L858R mutation (L858R) were compared. A random effects model was used. RESULTS: A total of 19 relevant studies which involved 4,872 cases were enrolled and 2,086 patients were EGFR-mutated. The majority of studies used PCR-based methods to detect EGFR mutations. Through meta-analysis, we observed the DFS of EGFR-mutated patients were similar to wild type patients in overall population (HR 0.93, 95% CI: 0.74 to 1.17). Similar results were observed in stage I subgroup (HR 0.82, 95% CI: 0.50 to 1.33). DFS of 19 del patients were potentially inferior to L858R patients but the difference was not significant (HR 1.38, 95% CI: 0.76 to 2.52). CONCLUSIONS: There was no significant difference in postoperative DFS between EGFR-mutant patients and wild-type with resected NSCLC. In addition, there is still insufficient evidence to support different postoperative treatment strategies (especially for stage I) for both mutated and wild-type patients. However, 19 del may be a negative factor, which may require more strict management. Thus, we strongly encourage reporting specific prognostic impacts of different mutation types.