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Lifetime Data Analysis

, Volume 25, Issue 1, pp 1–25 | Cite as

Vertical modeling: analysis of competing risks data with a cure fraction

  • Mioara Alina NicolaieEmail author
  • Jeremy M. G. Taylor
  • Catherine Legrand
Article
  • 275 Downloads

Abstract

In this paper, we extend the vertical modeling approach for the analysis of survival data with competing risks to incorporate a cure fraction in the population, that is, a proportion of the population for which none of the competing events can occur. The proposed method has three components: the proportion of cure, the risk of failure, irrespective of the cause, and the relative risk of a certain cause of failure, given a failure occurred. Covariates may affect each of these components. An appealing aspect of the method is that it is a natural extension to competing risks of the semi-parametric mixture cure model in ordinary survival analysis; thus, causes of failure are assigned only if a failure occurs. This contrasts with the existing mixture cure model for competing risks of Larson and Dinse, which conditions at the onset on the future status presumably attained. Regression parameter estimates are obtained using an EM-algorithm. The performance of the estimators is evaluated in a simulation study. The method is illustrated using a melanoma cancer data set.

Keywords

Mixture cure model Competing risks Cumulative incidences 

Notes

Acknowledgements

Funding was provided by IAP grant (Grant No. P7/06).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Mioara Alina Nicolaie
    • 1
    Email author
  • Jeremy M. G. Taylor
    • 2
  • Catherine Legrand
    • 1
  1. 1.Institute of Statistics, Biostatistics and Actuarial SciencesCatholic University of LouvainLouvain-la-NeuveBelgium
  2. 2.School of Public HealthUniversity of MichiganAnn ArborUSA

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