Preoperative Neutrophil-to-Lymphocyte Ratio as a Predictive and Prognostic Factor for High-Grade Serous Ovarian Cancer

PLoS One. 2016 May 20;11(5):e0156101. doi: 10.1371/journal.pone.0156101. eCollection 2016.

Abstract

Objective: We aimed to demonstrate the clinical and prognostic significance of the preoperative neutrophil-to-lymphocyte ratio (NLR) in high-grade serous ovarian cancer (HGSC).

Methods: We retrospectively investigated 875 patients who underwent primary staging or debulking surgery for HGSC between April 2005 and June 2013 at our institution. None of these patients received neoadjuvant chemotherapy. NLR was defined as the absolute neutrophil count divided by the absolute lymphocyte count. Progression-free survival (PFS) and overall survival (OS) were analyzed with the Kaplan-Meier method and log-rank tests for univariate analyses. For multivariate analyses, Cox regression analysis was used to evaluate the effects of the prognostic factors, which were expressed as hazard ratios (HRs).

Results: The NLRs ranged from 0.30 to 24.0. The median value was 3.24 and used as the cutoff value to discriminate between the high-NLR (≥3.24) and low-NLR (<3.24) groups. A high preoperative NLR level was associated with an advanced FIGO stage, increased CA125 level, more extensive ascites, worse cytoreduction outcome and chemoresistance. For univariate analyses, a high NLR was associated with reduced PFS (p<0.001) and OS (p<0.001). In multivariate analyses, a high NLR was still an independent predictor of PFS (p = 0.011), but not OS (p = 0.148).

Conclusion: Our study demonstrated that NLR could reflect tumor burden and clinical outcomes to a certain extent and should be regarded as a predictive and prognostic parameter for HGSC.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Lymphocytes / pathology*
  • Middle Aged
  • Multivariate Analysis
  • Neutrophils / pathology*
  • Ovarian Neoplasms / pathology*
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies

Grants and funding

This work was supported by the key project of Science and Technology Commission of Shanghai Municipality (12411950300) and the leading project of Science and Technology Commission of Shanghai Municipality (15411962000) for XH Wu.