Prognostic significance of neutrophil-lymphocyteratio/platelet-lymphocyteratioin lung cancers: a meta-analysis

Oncotarget. 2016 Nov 22;7(47):76769-76778. doi: 10.18632/oncotarget.12526.

Abstract

Setting: For now, hematological markers of inflammatory response have emerged as prognostic factors for patients with cancer. Many articles have confirm that neutrophil to lymphocyte ratio(NLR) and platelet-lymphocyte ratio (PLR) are relate with poor prognosis in various types of tumors.

Objective: To investigate the association between NLR/PLR and progression free survival (PFS), overall survival (OS) and clinicopathologic parameters in lung cancer patients.

Design: We performed relevant searches in PubMed database, Google Scholar, Springer Link. We included retrospective cohort studies that reported hazard ratios with 95% confidence intervals for the NLR or PLR and PFS or OS.

Results: Both high NLR (P < 0.00001) and high PLR (P = 0.01) were significantly predictive of poorer OS. It also demonstrated that elevated NLR predicted poorer PFS (P = 0.0002). High NLR was significantly associated with deeper Invasive of tumor, (P = 0.006) extensive lymph nodetastasis(N2-3) (P = 0.01), poor differentiation (P = 0.0002) and vascular invasion(P = 0.002).There was no evidence of publication bias. Subgroup analysis indicated that little evidence of heterogeneity. However, PLR has no prognostic significance for SCLC.

Conclusions: We provides further evidence in support of elevated NLR and PLR were predictors of poor OS and PFS in patients with lung cancer. Given this, NLR and PLR may be markers to report treatment outcomes.

Keywords: NLR; OS; PLR; clinicopathologic parameters; lung cancers.

Publication types

  • Meta-Analysis

MeSH terms

  • Humans
  • Leukocyte Count*
  • Lung Neoplasms / blood*
  • Lung Neoplasms / diagnosis
  • Lung Neoplasms / mortality*
  • Lymphocytes*
  • Neoplasm Grading
  • Neoplasm Invasiveness
  • Neoplasm Metastasis
  • Neoplasm Staging
  • Neutrophils*
  • Odds Ratio
  • Platelet Count*
  • Prognosis
  • Proportional Hazards Models
  • Publication Bias