Prognostic value of the Glasgow prognostic score in lung cancer: evidence from 10 studies

Int J Biol Markers. 2018 May;33(2):201-207. doi: 10.5301/ijbm.5000308. Epub 2017 Oct 24.

Abstract

Objective: To conduct a meta-analysis of prospective and retrospective studies to reveal the relationship between the Glasgow prognostic score (GPS) and overall survival (OS) or progression-free survival (PFS) in patients with lung cancer.

Methods: Correlative studies were included by searching the databases of PubMed, Web of Science, Embase, and PubMed Cochrane Library until April 16, 2017. We combined the hazard ratios (HRs) and 95% confidence intervals (CIs) to assess the correlation between GPS and OS or PFS in patients with lung cancer.

Results: Ten studies involving 5,369 participants from several regions were identified through searching databases. In a pooled analysis of all studies, elevated GPS was associated with poorer OS (HR = 2.058; 95% CI, 1.51-2.80; p<0.05). However, the combined data showed no significant relationship between the GPS of 1 or 2, and PFS, respectively. Subgroup analysis showed that the patients with GPS ≥1 had poorer OS compared with those with GPS = 0 (HR = 2.01; 95% CI, 1.75-2.32; p<0.001). A similar trend was observed in patients receiving chemotherapy (HR = 1.66; 95% CI, 1.17-2.36; p<0.05) and surgery (HR = 2.88; 95% CI, 1.59-5.22; p<0.001) when stratified by treatment.

Conclusions: Increased level of GPS may have a prognostic value in lung cancer. We detected a statistical difference in the association of elevated GPS and poorer OS, though the association was not significant in PFS settings. However, further studies are warranted to draw firm conclusions.

Keywords: GPS; Lung cancer; Prognosis; Systemic inflammation.

Publication types

  • Meta-Analysis

MeSH terms

  • Disease-Free Survival
  • Female
  • Humans
  • Lung Neoplasms / diagnosis*
  • Lung Neoplasms / pathology
  • Male
  • Neoplasm Recurrence, Local / diagnosis*
  • Neoplasm Recurrence, Local / pathology
  • Predictive Value of Tests
  • Prognosis*
  • Proportional Hazards Models