Predictors of breast conservation therapy: size is not all that matters

Cancer. 2005 Mar 1;103(5):892-9. doi: 10.1002/cncr.20853.

Abstract

Background: Despite the National Institutes of Health consensus statement in 1991 that breast-conserving surgery (BCS) followed by radiotherapy is an appropriate approach to the treatment of early-stage breast carcinoma, studies have shown a relatively low rate of BCS in the United States. The current study investigated predictors of breast conservation therapy in a large, diverse patient population.

Methods: Between 1990 and 1998, 43,111 patients underwent surgery for breast carcinoma and were entered into the Cancer Surveillance Program database for Los Angeles County. Of these, 29,666 (68.3%) had complete data on patient demographics, staging, surgeon, type of surgery, and hospital. Data were collected regarding extent of disease, lymph node status, tumor size, age, race, socioeconomic status (SES), surgeon specialization, surgeon volume, hospital specialization, and hospital volume. Univariate and multivariate analyses were performed.

Results: Univariate analysis showed that extent of disease, lymph node status, tumor size, age, race, SES, surgeon and hospital specialization, and surgeon and hospital volume all were significantly associated with surgery type (P <0.0001). Multivariate analysis showed that not only did extent of disease impact choice of surgery, but so did race, SES, hospital volume, surgeon volume, and surgeon specialization (P <0.0001).

Conclusions: These results suggest that not only does the extent of locoregional disease play a role in the likelihood of a woman undergoing breast conservation therapy, but patient age, socioeconomic status, racial/ethnic factors, and the experience of both the surgeon and hospital have an effect.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Age Factors
  • Breast Neoplasms / surgery*
  • Ethnicity
  • Female
  • Hospitals
  • Humans
  • Lymphatic Metastasis
  • Mastectomy, Segmental / statistics & numerical data*
  • Multivariate Analysis
  • Socioeconomic Factors
  • United States