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Competing Risk Methods in Early Breast Cancer Trials

  • R. L. Prentice
Conference paper
Part of the Lecture Notes in Medical Informatics book series (LNMED, volume 4)

Summary

Recent work on the analysis of failure time data with competing risks is reviewed and is discussed in relation to early breast cancer trials. Central to the discussion is the modelling, estimation and interpretation of cause-specific failure rates. Possible uses of such failure rate estimators are indicated for the study of differential treatment effects on local and distant recurrence and for the identification of dependent censorship.

Keywords

Failure Time Distant Recurrence Risk Indicator Failure Type Failure Time Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Cox, D.R. (1972). Regression models and life tables (with discussion). Journal of the Royal Statistical Society, Series B 34, 187–220.Google Scholar
  2. Peto, R., Pike, M.C., Armitage, P., Breslow, N.E., Cox, D.R., Howard, S.V., Mantel, N., McPherson, K., Peto, J., and Smith, P.G. (1976). Design and analysis of randomized clinical trials requiring prolonged observation of each patient. Part 1. Introduction and design. British Journal of Cancer 34, 585–612.Google Scholar
  3. Prentice, R.L., Kalbfleisch, J.D., Petersen, A.V., Flournoy, N., Farewell, V.T. and Breslow, N.E. (1978). The analysis of failure times in the presence of competing risks. Biometrics 34, 541–554.PubMedCrossRefGoogle Scholar
  4. Turnbull, B.W. and Mitchell, T.J. (1978). Exploratory analysis of disease prevalence from survival/sacrifice data. Biometrics 34, 555–570.Google Scholar
  5. Wong, O. (1977). A competing-risk model based on the life table procedure in epidemiological studies. International Journal of Epidemiology 6, 153–159.PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1979

Authors and Affiliations

  • R. L. Prentice
    • 1
    • 2
  1. 1.Fred Hutchinson Cancer Research CenterSeattleUSA
  2. 2.Department of BiostatisticsUniversity of WashingtonSeattleUSA

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