Literature DB >> 25907643

Cause-specific or relative survival setting to estimate population-based net survival from cancer? An empirical evaluation using women diagnosed with breast cancer in Geneva between 1981 and 1991 and followed for 20 years after diagnosis.

Robin Schaffar1, Bernard Rachet2, Aurélien Belot2, Laura Woods2.   

Abstract

BACKGROUND: Both cause-specific and relative survival settings can be used to estimate net survival, the survival that would be observed if the only possible underlying cause of death was the disease under study. Both resulting net survival estimators are biased by informative censoring and prone to biases related to the data settings within which each is derived. We took into account informative censoring to derive theoretically unbiased estimators and examine which of the two data settings was the most robust against incorrect assumptions in the data. PATIENTS AND METHODS: We identified 2489 women in the Geneva Cancer Registry, diagnosed with breast cancer between 1981 and 1991, and estimated net survival up to 20-years using both cause-specific and relative survival settings, by tackling the informative censoring with weights. To understand the possible origins of differences between the survival estimates, we performed sensitivity analyses within each setting. We evaluated the impact of misclassification of cause of death and of using inappropriate life tables on survival estimates.
RESULTS: Net survival was highest using the cause-specific setting, by 1% at one year and by up to around 11% twenty years after diagnosis. Differences between both sets of net survival estimates were eliminated after recoding between 15% and 20% of the non-specific deaths as breast cancer deaths. By contrast, a dramatic increase in the general population mortality rates was needed to see the survival estimates based on relative survival setting become closer to those derived from cause-specific setting.
CONCLUSION: Net survival estimates derived using the cause-specific setting are very sensitive to misclassification of cause of death. Net survival estimates derived using the relative-survival setting were robust to large changes in expected mortality. The relative survival setting is recommended for estimation of long-term net survival among patients with breast cancer.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Breast cancer; Cause-specific; Informative censoring; Net survival; Relative survival

Mesh:

Year:  2015        PMID: 25907643     DOI: 10.1016/j.canep.2015.04.001

Source DB:  PubMed          Journal:  Cancer Epidemiol        ISSN: 1877-7821            Impact factor:   2.984


  4 in total

1.  Differences in Cancer Survival with Relative versus Cause-Specific Approaches: An Update Using More Accurate Life Tables.

Authors:  Gonçalo Forjaz de Lacerda; Nadia Howlader; Angela B Mariotto
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-06-20       Impact factor: 4.254

2.  Estimation of net survival for cancer patients: Relative survival setting more robust to some assumption violations than cause-specific setting, a sensitivity analysis on empirical data.

Authors:  Robin Schaffar; Bernard Rachet; Aurélien Belot; Laura M Woods
Journal:  Eur J Cancer       Date:  2016-12-24       Impact factor: 9.162

3.  Correcting for misclassification and selection effects in estimating net survival in clinical trials.

Authors:  Juste Aristide Goungounga; Célia Touraine; Nathalie Grafféo; Roch Giorgi
Journal:  BMC Med Res Methodol       Date:  2019-05-16       Impact factor: 4.615

4.  Cause of death for patients with breast cancer: discordance between death certificates and medical files, and impact on survival estimates.

Authors:  Geert Silversmit; Freija Verdoodt; Hava Izci; Tim Tambuyzer; Jessica Vandeven; Jérôme Xicluna; Hans Wildiers; Kevin Punie; Nynke Willers; Eva Oldenburger; Els Van Nieuwenhuysen; Patrick Berteloot; Ann Smeets; Ines Nevelsteen; Anne Deblander; Harlinde De Schutter; Patrick Neven
Journal:  Arch Public Health       Date:  2021-06-23
  4 in total

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