Predictive value of different prognostic factors in breast cancer recurrences: multivariate analysis using a logistic regression model

Anticancer Res. 2001 Nov-Dec;21(6A):4105-8.

Abstract

Background: The aim of this study was to compare the sensitivity of different pre-operative parameters in patients with breast cancer (BC) recurrence using univariate and multivariate analysis.

Materials and methods: We retrospectively analyzed a series of 387 women (median age 60 years, range 35-83 years) who underwent curative surgery for pT1-2 BC. The patients were divided into two groups: Group 1: 325 (84.0%) patients with no evidence of disease during a median follow-up of 53 months (range 25-149 months) and Group 2: 62 (16.0%) patients who developed local or distant recurrences.

Results: Univariate analysis showed significant (p<0.01) differences between the two Groups in age, size and grading of the tumor and hormone receptor rate. MIB1 proliferation rate, serum markers CEA and CA 15-3, and lymph node status were not useful in predicting relapse. Multivariate analysis using a logistic regression model showed that only age, size of the tumor and hormone receptor rate independently correlate with the onset of recurrences.

Conclusion: There is no clear correlation between BC recurrence and the majority of the prognostic factors available. Multivariate analysis of several pre-operative parameters may help to correctly select the high risk population.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / diagnosis*
  • Breast Neoplasms / pathology
  • Breast Neoplasms / surgery
  • Female
  • Humans
  • Logistic Models
  • Middle Aged
  • Multivariate Analysis
  • Neoplasm Recurrence, Local / diagnosis*
  • Neoplasm Recurrence, Local / pathology
  • Neoplasm Recurrence, Local / surgery
  • Predictive Value of Tests
  • Prognosis
  • Risk Factors