Population estimates of survival in women with screen-detected and symptomatic breast cancer taking account of lead time and length bias

Breast Cancer Res Treat. 2009 Jul;116(1):179-85. doi: 10.1007/s10549-008-0100-8. Epub 2008 Jul 12.


Background: Evidence of the impact of breast screening is limited by biases inherent in non-randomised studies and often by lack of complete population data. We address this by estimating the effect of screen detection on cause-specific fatality in breast cancer, corrected for all potential biases, using population cancer registry data.

Methods: Subjects (N = 26,766) comprised all breast cancers notified to the West Midlands Cancer Intelligence Unit and diagnosed in women aged 50-74, from 1988 to 2004. These included 10,100 screen-detected and 15,862 symptomatic breast cancers (6,009 women with interval cancers and 9,853 who had not attended screening). Our endpoint was survival to death from breast cancer. We estimated the relative risk (RR) of 10-year cause-specific fatality (screen-detected compared to symptomatic cancers) correcting for lead time bias and performing sensitivity analyses for length bias. To exclude self-selection bias, survival analyses were also performed with interval cancers as the comparator symptomatic women.

Findings: Uncorrected RR associated with screen-detection was 0.34 (95% CI 0.31-0.37). Correcting for lead time, RR was 0.49 (95% CI 0.45-0.53); length bias analyses gave a range of RR corrected for both phenomena of 0.49-0.59, with a median of 0.51. Self-selection bias-corrected estimates yielded a median RR of 0.68.

Interpretation: After adjusting for various potential biases, women with screen-detected breast cancer have a substantial survival advantage over those with symptomatic breast cancer.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Bias*
  • Breast Neoplasms / diagnosis*
  • Breast Neoplasms / mortality*
  • Cohort Studies
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Mammography*
  • Mass Screening*
  • Middle Aged
  • Research Design*
  • Risk
  • Survival Analysis
  • Time