Female breast cancer management and survival: The experience of major public hospitals in South Australia over 3 decades-trends by age and in the elderly

J Eval Clin Pract. 2017 Dec;23(6):1433-1443. doi: 10.1111/jep.12819. Epub 2017 Oct 8.

Abstract

Background: Clinical registry data from major South Australian public hospitals were used to investigate trends in invasive breast-cancer treatment and survival by age.

Methods: Disease-specific survival was calculated for the 1980 to 2013 diagnostic period using Kaplan-Meier product-limit estimates, with a censoring of live cases on December 31, 2014. Cox proportional hazards regression was used to examine differences in survival by age and tumour characteristic. First-round treatments following diagnosis were analysed, using multiple logistic regression to adjust for confounding.

Results: Five-year survival increased from 75% in the 1980s to 87% in 2000 to 2013, consistent with national trends, and with increases occurring irrespective of age. There was an increased use of breast conserving surgery, radiotherapy, chemotherapy, and hormone treatments. Five-year survival was lower for women aged 80+ years, increasing from 65% in the 1980s to 74% in 2000 to 2013. Lower survival in these older women persisted after adjusting for TNM stage, other clinical variables, and diagnostic year, without evidence of a reduced disparity over time. Older women were less likely to have surgery, radiotherapy, and chemotherapy throughout 1980 to 2013. By comparison, their use of hormone therapy was elevated. The adjusted relative odds of mastectomy (as opposed to breast conserving surgery) were lower for the 80+ year age range.

Conclusions: Breast-cancer survival increases applied to all ages, including 80+ years, but poorer outcomes persisted in this older group and the gap did not reduce. A key question is whether the best trade-off now exists between optimally therapeutic cancer treatment and accommodations for frailty and co-morbidity in the aged, or whether opportunities exist for better trade-offs and better survival. Local registry data are important for describing local service activity and outcomes by age for local service providers, health administrations and consumer groups; monitoring disparities; and indicating effects of local initiatives.

Keywords: evaluation; healthcare; public health.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / mortality*
  • Breast Neoplasms / therapy*
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Logistic Models
  • Middle Aged
  • Neoplasm Staging
  • Proportional Hazards Models
  • Registries
  • South Australia / epidemiology
  • Time Factors
  • Tumor Burden