The prognostic value of interleukin-17 in lung cancer: A systematic review with meta-analysis based on Chinese patients.

Published online

Journal Article (Review)

BACKGROUND: Interleukin-17 (IL-17) plays an important role in cancer progression. Previous studies remained controversial regarding the correlation between IL-17 expression and lung cancer (LC) prognosis. To comprehensively and quantitatively summarize the prognostic value of IL-17 expression in LC patients, a systematic review and meta-analysis were performed. METHODS: We identified the relevant literatures by searching the PubMed, EMBASE, Cochrane Library, SinoMed, China National Knowledge Infrastructure (CNKI) and Wanfang Data databases, up until April 1, 2017. Overall survival (OS), disease free survival (DFS) and clinicopathological characteristics were collected from relevant studies. Pooled hazard ratios (HR) and corresponding 95% confidence intervals (CI) were calculated to estimate the effective value of IL-17 expression on clinical outcomes. RESULTS: Six studies containing 479 Chinese LC patients were involved in this meta-analysis. The results indicated high IL-17 expression was independently correlated with poorer OS (HR = 1.82, 95% CI 1.44-2.29, P < 0.00001) and shorter DFS (HR = 2.41, 95% CI 1.42-4.08, P = 0.001) in LC patients. Further, when stratified by LC histological type (non-small cell lung cancer and small cell lung cancer), tumor stage (Ⅰ-Ⅲ,Ⅰ-Ⅳ and Ⅳ), detection specimen (serum, intratumoral tissue and pleural effusion), test method (immunological histological chemistry and enzyme linked immunosorbent assay), and HR estimated method (reported and estimated), all of the results were statistically significant. These data indicated that elevated IL-17 expression is correlated with poor clinical outcomes in LC. The meta-analysis did not show heterogeneity or publication bias. CONCLUSIONS: The present meta-analysis revealed that high IL-17 expression was an indicator of poor prognosis for Chinese patients with LC. It could potentially help to assess patients' prognosis and estimate treatment efficacy in therapeutic interventions.

Full Text

Duke Authors

Cited Authors

  • Wang, X-F; Zhu, Y-T; Wang, J-J; Zeng, D-X; Mu, C-Y; Chen, Y-B; Lei, W; Zhu, Y-H; Huang, J-A

Published Date

  • 2017

Published In

Volume / Issue

  • 12 / 9

Start / End Page

  • e0185168 -

PubMed ID

  • 28934305

Pubmed Central ID

  • 28934305

Electronic International Standard Serial Number (EISSN)

  • 1932-6203

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0185168

Language

  • eng

Conference Location

  • United States