title: Predictive value of a serum-based proteomic test in non-small-cell lung cancer patients treated with epidermal growth factor receptor tyrosine kinase inhibitors: a meta-analysis.
abstract: OBJECTIVE
  Several studies have demonstrated that a serum-based proteomic test (VeriStrat * ) is able to predict the clinical outcome of non-small-cell lung cancer (NSCLC) patients treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). However, these studies have limited power to draw a precise conclusion because of their small sample sizes and inconsistent results. Therefore, a meta-analysis was carried out in an attempt to provide more persuasive evidence.
  
  
  METHODS
  Electronic searches for relevant articles in PubMed, Embase, Medline, and Web of Science published up to May 2013 were conducted. Stata Statistical Software version 12.0 was applied for statistical analysis. The combined hazard ratio (HR) and 95% confidence interval (CI) were estimated using fixed-effects models.
  
  
  RESULTS
  Eleven cohorts involving 706 patients collected from seven studies were subjected to final analysis. This serum-based proteomic test's 'good' status predicted a better clinical outcome with a pooled HR of 0.40 (95% CI 0.32 to 0.49; p < 0.001) for overall survival (OS), and 0.49 (95% CI 0.39 to 0.60; p < 0.001) for progression-free survival (PFS). There was no significant heterogeneity, but a slight publication bias in this study.
  
  
  CONCLUSIONS
  Our meta-analysis demonstrated that this serum-based proteomic test has a predictive value for NSCLC patients treated with EGFR-TKIs. Future data are needed to validate and update our results.
authors.affiliation: Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology , Hubei, Wuhan , China.
authors.forename: Wei
authors.initials: W
authors.lastname: Sun
authors.forename: Guangyuan
authors.initials: G
authors.lastname: Hu
authors.forename: Guoxian
authors.initials: G
authors.lastname: Long
authors.forename: Junfeng
authors.initials: J
authors.lastname: Wang
authors.forename: Dongbo
authors.initials: D
authors.lastname: Liu
authors.forename: Guoqing
authors.initials: G
authors.lastname: Hu
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology; D002289:Carcinoma, Non-Small-Cell Lung / Q000188:drug therapy / Q000378:metabolism; D018572:Disease-Free Survival; D066246:ErbB Receptors / Q000037:antagonists & inhibitors*; D000069347:Erlotinib Hydrochloride; D000077156:Gefitinib; D006801:Humans; D008175:Lung Neoplasms / Q000188:drug therapy / Q000378:metabolism; D011237:Predictive Value of Tests; D040901:Proteomics / Q000379:methods*; D011799:Quinazolines / Q000494:pharmacology*
chemical_list: D000970:Antineoplastic Agents; D011799:Quinazolines; D000069347:Erlotinib Hydrochloride; D066246:ErbB Receptors; D000077156:Gefitinib
keywords: EGFR inhibitor; Meta-analysis; NSCLC; Prediction; Proteomic test