Comparison of Preoperative Neutrophil-Lymphocyte and Platelet-Lymphocyte Ratios in Bladder Cancer Patients Undergoing Radical Cystectomy

Biomed Res Int. 2019 Oct 2:2019:3628384. doi: 10.1155/2019/3628384. eCollection 2019.

Abstract

Introduction: Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been proven to be significant prognostic factors in many cancers. We aimed to retrospectively investigate the prognostic value of NLR and PLR in patients with bladder cancer undergoing radical cystectomy.

Materials and methods: The study comprised patients from 2010 to 2018 who were diagnosed with bladder cancer and received radical cystectomy. Clinical and pathological parameters were collected. Receiver operating characteristic curves of NLR and PLR were plotted for overall survival (OS) and cancer-specific survival (CSS). The best cutoff value of NLR and PLR were determined using X-tile software. The prognostic value of NLR and PLR for OS and CSS was analyzed using the Kaplan-Meier method and Cox regression models.

Results: A total of 223 patients were enrolled with a medium follow-up period of 57 months. Receiver operating characteristic curves showed that PLR was superior to NLR as a prognostic factor in patients with bladder cancer undergoing radical cystectomy. Univariate analysis revealed that NLR (p=0.032 and p=0.041) and PLR (p=0.003 and p=0.003) were significantly associated with both OS and CSS, respectively. Multivariate analysis identified only PLR as independent prognostic factors for OS (p=0.046) and CSS (p=0.039), respectively.

Conclusions: The present findings suggested that compared with NLR, PLR was a superior prognostic factor of OS and CSS in bladder cancer patients indicated to radical cystectomy.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Blood Cell Count*
  • Cystectomy / methods*
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Lymphocyte Count*
  • Male
  • Middle Aged
  • Neutrophils*
  • Platelet Count*
  • Prognosis
  • Proportional Hazards Models
  • ROC Curve
  • Regression Analysis
  • Urinary Bladder Neoplasms / blood*