The role of the systemic inflammatory response in predicting outcomes in patients with operable cancer: Systematic review and meta-analysis

Sci Rep. 2017 Dec 1;7(1):16717. doi: 10.1038/s41598-017-16955-5.

Abstract

Cancer remains a leading causes of death worldwide and an elevated systemic inflammatory response (SIR) is associated with reduced survival in patients with operable cancer. This review aims to examine the evidence for the role of systemic inflammation based prognostic scores in patients with operable cancers. A wide-ranging literature review using targeted medical subject headings for human studies in English was carried out in the MEDLINE, EMBASE, and CDSR databases until the end of 2016. The SIR has independent prognostic value, across tumour types and geographical locations. In particular neutrophil lymphocyte ratio (NLR) (n = 158), platelet lymphocyte ratio (PLR) (n = 68), lymphocyte monocyte ratio (LMR) (n = 21) and Glasgow Prognostic Score/ modified Glasgow Prognostic Score (GPS/mGPS) (n = 60) were consistently validated. On meta-analysis there was a significant relationship between elevated NLR and overall survival (OS) (p < 0.00001)/ cancer specific survival (CSS) (p < 0.00001), between elevated LMR and OS (p < 0.00001)/CSS (p < 0.00001), and elevated PLR and OS (p < 0.00001)/CSS (p = 0.005). There was also a significant relationship between elevated GPS/mGPS and OS (p < 0.00001)/CSS (p < 0.00001). These results consolidate the prognostic value of the NLR, PLR, LMR and GPS/mGPS in patients with resectable cancers. This is particularly true for the NLR/GPS/mGPS which should form part of the routine preoperative and postoperative workup.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Biomarkers, Tumor / metabolism
  • Blood Platelets / cytology
  • Humans
  • Kaplan-Meier Estimate
  • Lymphocytes / cytology
  • Monocytes / cytology
  • Neoplasms / mortality
  • Neoplasms / pathology*
  • Neoplasms / surgery
  • Neutrophils / cytology
  • Prognosis

Substances

  • Biomarkers, Tumor