Literature DB >> 24926735

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.

Wei Sun1, Guangyuan Hu, Guoxian Long, Junfeng Wang, Dongbo Liu, Guoqing Hu.   

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. RESEARCH DESIGN AND 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.

Entities:  

Keywords:  EGFR inhibitor; Meta-analysis; NSCLC; Prediction; Proteomic test

Mesh:

Substances:

Year:  2014        PMID: 24926735     DOI: 10.1185/03007995.2014.934792

Source DB:  PubMed          Journal:  Curr Med Res Opin        ISSN: 0300-7995            Impact factor:   2.580


  3 in total

1.  The value of proteomics in lung cancer.

Authors:  Anthonie J van der Wekken; Thijo J N Hiltermann; Harry J M Groen
Journal:  Ann Transl Med       Date:  2015-03

2.  Clinical decisions surrounding genomic and proteomic testing among United States veterans treated for lung cancer within the Veterans Health Administration.

Authors:  Olga Efimova; Brygida Berse; Daniel W Denhalter; Scott L DuVall; Kelly K Filipski; Michael Icardi; Michael J Kelley; Julie A Lynch
Journal:  BMC Med Inform Decis Mak       Date:  2017-05-30       Impact factor: 2.796

Review 3.  Non-invasive approaches to monitor EGFR-TKI treatment in non-small-cell lung cancer.

Authors:  Wei Sun; Xun Yuan; Yijun Tian; Hua Wu; Hanxiao Xu; Guoqing Hu; Kongming Wu
Journal:  J Hematol Oncol       Date:  2015-07-31       Impact factor: 17.388

  3 in total

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