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Breast Cancer Research and Treatment

, Volume 116, Issue 1, pp 179–185 | Cite as

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

  • Gill Lawrence
  • Matthew Wallis
  • Prue Allgood
  • Iris D. Nagtegaal
  • Jane Warwick
  • Fay H. Cafferty
  • Nehmat Houssami
  • Olive Kearins
  • Nancy Tappenden
  • Emma O’Sullivan
  • Stephen W. Duffy
Epidemiology

Abstract

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.

Keywords

Population screening Mammography Lead-time bias Length bias Self-selection bias 

Notes

Acknowledgments

Prue Allgood was supported by a grant from the Princess Grace Hospital, London. Iris Nagtegaal was supported by the Dutch Cancer Society. The screening histories project at the West Midlands QA Reference Centre is supported by a grant from the Breast Cancer Research Trust. The authors are grateful to NHS Trusts, private hospitals and NHS breast screening services in the West Midlands for providing cancer registration and breast screening data and to Rosie Day at the WMCIU for extracting the breast cancer data used in this study from the WMCIU’s cancer registration database.

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Copyright information

© Springer Science+Business Media, LLC. 2008

Authors and Affiliations

  • Gill Lawrence
    • 1
  • Matthew Wallis
    • 2
  • Prue Allgood
    • 3
  • Iris D. Nagtegaal
    • 4
  • Jane Warwick
    • 3
  • Fay H. Cafferty
    • 3
  • Nehmat Houssami
    • 5
  • Olive Kearins
    • 1
  • Nancy Tappenden
    • 6
  • Emma O’Sullivan
    • 1
  • Stephen W. Duffy
    • 3
  1. 1.West Midlands Cancer Intelligence Unit, Public Health BuildingThe University of BirminghamBirminghamUnited Kingdom
  2. 2.Breast Screening UnitUniversity Hospitals Coventry and WarwickshireCoventryUnited Kingdom
  3. 3.Cancer Research UK Centre for Epidemiology, Mathematics and StatisticsWolfson Institute of Preventive MedicineLondonUnited Kingdom
  4. 4.Department of Pathology 824University Medical Centre St. RadboudNijmegenThe Netherlands
  5. 5.Screening & Test Evaluation Program, School of Public Health A27University of SydneySydneyAustralia
  6. 6.The Planning Office, Academic servicesThe University of BirminghamBirminghamUnited Kingdom

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