Deprivation and survival from breast cancer

Br J Cancer. 1995 Sep;72(3):738-43. doi: 10.1038/bjc.1995.403.


We studied the association between deprivation and survival from breast cancer in 29,676 women aged 30 and over who were diagnosed during the period 1980-89 in the area covered by the South Thames Regional Health Authority. The measure of deprivation was the Carstairs Index of the census enumeration district of each woman's residence at diagnosis. We studied the impact of stage at diagnosis, morphology and type of treatment on this association, with the relative survival rate and the hazard ratio as measures of outcome. There was a clear gradient in survival, with better survival for women from more affluent areas. At all ages, women in the most deprived category had a 35% greater hazard of death than women from the most affluent areas after adjustment for stage at diagnosis, morphological type and type of treatment. In younger women (30-64 years), the survival gradient by deprivation category cannot be explained by these prognostic factors. In older women (65-99 years), part of the unadjusted gradient in survival can be explained by differences in the stage of disease: older women in the most deprived category were more often diagnosed with advanced disease. Other factors, so far unidentified, are responsible for the gradient in breast cancer survival by deprivation category. The potential effect on breast cancer mortality of eliminating the gradient in survival by deprivation category is substantial (7.4%). In women aged 30-64 years, 10% of all deaths within 5 years might be avoidable, while in older women this figure is 5.8%.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / mortality*
  • Breast Neoplasms / pathology
  • England / epidemiology
  • Female
  • Humans
  • Middle Aged
  • Neoplasm Staging
  • Poverty
  • Prognosis
  • Proportional Hazards Models
  • Psychosocial Deprivation*
  • Socioeconomic Factors
  • Survival Analysis