Clinicopathologic study of angiogenesis in Japanese patients with breast cancer

World J Surg. 1997 Jan;21(1):49-56. doi: 10.1007/s002689900192.

Abstract

To evaluate the clinicopathologic significance of angiogenesis as a prognostic factor and the objective methods for evaluating angiogenesis, we immunohistochemically stained a representative section of breast tumors with factor VIII-related antigen staining. There were 109 patients with primary breast cancer from 1971 to 1979. The two methods of identifying angiogenesis were the average microvessel count per square millimeter (AMC) and the highest microvessel count per square millimeter (HMC). There was no relation between microvessel count (AMC or HMC) or age, menopausal status, clinical tumor size (T), histologic classification, nuclear grade, node status, histologic grade (HG), mitosis index, or lymphatic invasion (LI). There was a relation between microvessel count and blood vessel invasion (BVI) (HMC:p = 0.0007) and tumor necrosis (TN) (HMC:p = 0.0050). Univariate analysis showed that AMC or HMC was a statistically significant predictor of overall survival in all patients (p = 0.0086 and p = 0.0307, respectively). Multivariate analysis showed that AMC was an independent predictor of node status when we fitted a model with node status, BVI, and either AMC or HMC; but HMC was not independent. However, when we fitted a model including all 11 of the other indicators and AMC or HMC, the node status, HG, and LI were independent predictors, but AMC and HMC were not. Although AMC was a better method than HMC for evaluating angiogenesis, we cannot confirm angiogenesis as a significant independent prognostic factor associated with long-term survival in Japanese breast cancer patients.

MeSH terms

  • Adult
  • Aged
  • Analysis of Variance
  • Breast Neoplasms / blood supply*
  • Breast Neoplasms / mortality
  • Breast Neoplasms / pathology
  • Female
  • Humans
  • Japan
  • Microcirculation
  • Middle Aged
  • Neoplasm Staging
  • Neovascularization, Pathologic*
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies
  • Survival Analysis