Background: Emerging evidence indicates that chemotherapy for lung cancer may alter EGFR mutation status. However, whether chemotherapy as a firstline treatment may increase or reduce the frequency of EGFR mutations in NSCLC remains uncertain. Therefore, we conducted a meta-analysis to evaluate whether chemotherapy leads to altered EGFR mutation status. Methods: A systematic literature search was performed using the PubMed, OVID, Science Direct, Cochrane Library, and CNKI databases for studies on pre- and post-chemotherapy EGFR mutation status. Relevant studies documenting perichemotherapy EGFR mutation ratios were included. Analyses of pooled odds ratios (OR) were performed. Results: Six studies involving 656 patients were included in this meta-analysis. It was found that chemotherapy may alter EGFR status (OR = 1.93, 95% CI 1.05 - 3.56; p < 0.0001). No significant differences in EGFR mutation alterations were observed in terms of gender, smoking history, EGFR loci, or chemotherapy response in NSCLC patients. Conclusions: Chemotherapy may contribute to altered EGFR status. NSCLC patients with EGFR mutations might need to be considered for EGFR status redeterminations prior to second-line EGFR-TKI treatment or upon tumor recurrence after chemotherapy. Further randomized clinical trials should investigate the impact of neoadjuvant or first-line chemotherapy on EGFR mutation status in NSCLC patients.
Lung cancer causes the majority of cancer deaths in China and worldwide [
Recent studies have investigated whether EGFR mutations may be altered by chemotherapy. The efficacy of EGFR-TKIs has been shown to be less potent when used as second-line treatment for NSCLC patients refractory to or intolerant of platinum-based combination chemotherapy [
The aim of the present study was to systemically combine data from published articles to evaluate the impact of chemotherapy on EGFR mutation status in NSCLC. This meta-analysis is the first attempt to assess the role of chemotherapy in EGFR mutation alterations after standard chemotherapy, using evidence- based methods.
Relevant studies in English and Chinese were extracted from the PubMed, OVID, Science Direct, Cochrane Library, and China National Knowledge Infrastructure (CNKI) databases using the following terms: “non-small cell lung cancer”, “NSCLC”, “carcinoma”, “neoplasm”, “EGFR mutation”, and “chemotherapy”. The final search was conducted on June 24, 2016. All non-English and non-Chinese articles were excluded. To identify possible outcomes from unpublished trials containing potentially useful data, we also reviewed abstract books and presentations from major recent meetings of the American Society of Clinical Oncology (ASCO), the European Society for Medical Oncology (ESMO), and the World Conference on Lung Cancer. When the same patients were included in different publications, the most recent study was selected.
Eligible studies were gathered based on the following inclusion criteria: 1) standard chemotherapy as first-line treatment in chemo-naïve or radio-naïve NSCLC patients, 2) EGFR mutation status before and after chemotherapy, 3) any EGFR mutation subtype, 4) standard chemotherapy defined as platinum- based third-generation doublets, and 5) publication in English or Chinese. The exclusion criteria were: 1) duplicate reports, conference abstracts or papers, editorials, or reviews and 2) studies with insufficient data for pooled analysis.
To identify all eligible research, two investigators (Xiaoshun Shi and Haiyun Mo) independently extracted the data and reached a consensus based on the inclusion criteria. The quality of each study was assessed using the Newcastle Ottawa Quality Assessment Scale. Cases of disagreement were resolved by discussion with a third author. The following information was extracted from the eligible studies: first author’s surname, publication year, geographic region, chemotherapy agents used, EGFR detection method, and number of EGFR mutations before and after chemotherapy.
Analysis for the forest plot was conducted using Review Manager 5.2 (Cochrane Collaboration, Oxford, UK). For predictable heterogeneity, pooled odds ratios (ORs) were calculated for all included parameters and presented by random effect models, as this generates wider confidence intervals and minimizes the risk of Type I errors. Heterogeneity among studies was evaluated with Cochran’s Q test and the I2 statistic. For the subgroup analysis with high heterogeneity, we used both the random-effect model and the fixed-effect model to examine the final conclusion. Publication bias was assessed by Egger’s test. The analysis of publication bias was done with STATA version 12.0. Additionally, the trim-and-fill method was used to adjust the risk estimates when the tests for publication bias were statistically significant [
A total of 4983 articles were identified in the initial literature search, of which 4970 were rejected based on the exclusion criteria. Two articles were excluded because they belonged to conference abstracts and were subgroups in one of the included articles [