High lymphatic vessel density and presence of lymphovascular invasion both predict poor prognosis in breast cancer

BMC Cancer. 2017 May 17;17(1):335. doi: 10.1186/s12885-017-3338-x.

Abstract

Background: Lymphatic vessel density and lymphovascular invasion are commonly assessed to identify the clinicopathological outcomes in breast cancer. However, the prognostic values of them on patients' survival are still uncertain.

Methods: Databases of PubMed, Embase, and Web of Science were searched from inception up to 30 June 2016. The hazard ratio with its 95% confidence interval was used to determine the prognostic effects of lymphatic vessel density and lymphovascular invasion on disease-free survival and overall survival in breast cancer.

Results: Nineteen studies, involving 4215 participants, were included in this study. With the combination of the results of lymphatic vessel density, the pooled hazard ratios and 95% confidence intervals were 2.02 (1.69-2.40) for disease-free survival and 2.88 (2.07-4.01) for overall survival, respectively. For lymphovascular invasion study, the pooled hazard ratios and 95% confidence intervals were 1.81 (1.57-2.08) for disease-free survival and 1.64 (1.43-1.87) for overall survival, respectively. In addition, 29.56% (827/2798) of participants presented with lymphovascular invasion in total.

Conclusions: Our study demonstrates that lymphatic vessel density and lymphovascular invasion can predict poor prognosis in breast cancer. Standardized assessments of lymphatic vessel density and lymphovascular invasion are needed.

Keywords: Breast cancer; Disease-free survival; Lymphatic vessel density; Lymphovascular invasion; Overall survival.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / mortality*
  • Breast Neoplasms / pathology*
  • Disease-Free Survival
  • Female
  • Humans
  • Lymphangiogenesis / physiology
  • Lymphatic Metastasis
  • Lymphatic Vessels / pathology*
  • Neoplasm Invasiveness / pathology
  • Proportional Hazards Models