Assessment of lead-time bias in estimates of relative survival for breast cancer
- PMID: 28027488
- DOI: 10.1016/j.canep.2016.12.004
Assessment of lead-time bias in estimates of relative survival for breast cancer
Abstract
Relative survival ratios (RSRs) can be useful for evaluating the impact of changes in cancer care on the prognosis of cancer patients or for comparing the prognosis for different subgroups of patients, but their use is problematic for cancer sites where screening has been introduced due to the potential of lead-time bias. Lead-time is survival time that is added to a patient's survival time because of an earlier diagnosis irrespective of a possibly postponed time of death. In the presence of screening it is difficult to disentangle how much of an observed improvement in survival is real and how much is due to lead-time bias. Even so, RSRs are often presented for breast cancer, a site where screening has led to early diagnosis, with the assumption that the lead-time bias is small. We describe a simulation-based framework for studying the lead-time bias due to mammography screening on RSRs of breast cancer based on a natural history model developed in a Swedish setting. We have performed simulations, using this framework, under different assumptions for screening sensitivity and breast cancer survival with the aim of estimating the lead-time bias. Screening every second year among ages 40-75 was introduced assuming that screening had no effect on survival, except for lead-time bias. Relative survival was estimated both with and without screening to enable quantification of the lead-time bias. Scenarios with low, moderate and high breast cancer survival, and low, moderate and high screening sensitivity were simulated, and the lead-time bias assessed in all scenarios.
Keywords: Breast cancer; Lead time; Mammography screening; Relative survival; Simulation study.
Copyright © 2016 Elsevier Ltd. All rights reserved.
Similar articles
-
Assessing lead time bias due to mammography screening on estimates of loss in life expectancy.Breast Cancer Res. 2022 Feb 23;24(1):15. doi: 10.1186/s13058-022-01505-3. Breast Cancer Res. 2022. PMID: 35197123 Free PMC article.
-
Mammography service screening and breast cancer mortality in New Zealand: a National Cohort Study 1999-2011.Br J Cancer. 2017 Mar 14;116(6):828-839. doi: 10.1038/bjc.2017.6. Epub 2017 Feb 9. Br J Cancer. 2017. PMID: 28183141 Free PMC article.
-
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. Breast Cancer Res Treat. 2009. PMID: 18622697
-
Reducing the effects of lead-time bias, length bias and over-detection in evaluating screening mammography: a censored bivariate data approach.Stat Methods Med Res. 2008 Dec;17(6):643-63. doi: 10.1177/0962280207087309. Epub 2008 Apr 29. Stat Methods Med Res. 2008. PMID: 18445697 Review.
-
Evidence for reducing cancer-specific mortality due to screening for breast cancer in Europe: A systematic review.Eur J Cancer. 2020 Mar;127:191-206. doi: 10.1016/j.ejca.2019.12.010. Epub 2020 Jan 10. Eur J Cancer. 2020. PMID: 31932175
Cited by
-
Assessing lead time bias due to mammography screening on estimates of loss in life expectancy.Breast Cancer Res. 2022 Feb 23;24(1):15. doi: 10.1186/s13058-022-01505-3. Breast Cancer Res. 2022. PMID: 35197123 Free PMC article.
-
The contribution of prognostic factors to socio-demographic inequalities in breast cancer survival in Victoria, Australia.Cancer Med. 2023 Jul;12(14):15371-15383. doi: 10.1002/cam4.6092. Epub 2023 Jul 17. Cancer Med. 2023. PMID: 37458115 Free PMC article.
-
A natural history and copula-based joint model for regional and distant breast cancer metastasis.Stat Methods Med Res. 2022 Dec;31(12):2415-2430. doi: 10.1177/09622802221122410. Epub 2022 Sep 18. Stat Methods Med Res. 2022. PMID: 36120891 Free PMC article.
-
Evaluation of optimal strategies for breast cancer screening in Ghana: A simulation study based on a continuous tumor growth model.PLoS One. 2025 Jun 17;20(6):e0323485. doi: 10.1371/journal.pone.0323485. eCollection 2025. PLoS One. 2025. PMID: 40526619 Free PMC article.
-
Early Detection of Ovarian Cancer.Hematol Oncol Clin North Am. 2018 Dec;32(6):903-914. doi: 10.1016/j.hoc.2018.07.003. Epub 2018 Sep 28. Hematol Oncol Clin North Am. 2018. PMID: 30390764 Free PMC article. Review.
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical