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GMDS 2014: 59. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

07. - 10.09.2014, Göttingen

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The application of non-mixture cure fraction models in population-based studies

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  • R. Westerman - Philipps-Universität Marburg, Marburg

GMDS 2014. 59. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Göttingen, 07.-10.09.2014. Düsseldorf: German Medical Science GMS Publishing House; 2014. DocAbstr. 261

doi: 10.3205/14gmds154, urn:nbn:de:0183-14gmds1549

Published: September 4, 2014

© 2014 Westerman.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.

Outline

Text

Non-mixture cure models (NMCMs) are sophisticated in taking account for the time period after the treatment (probably sucessfully) for cancer. In that certain situation these models consider the exact time period from the end of treatment to the time of first recurrence of cancer under the condition of a proportion of those treated are completely cured. Also in many situations the overall survival is a good indicator for the sucess in treatment.

Estimations for the overall survival can be realized with a two stage NMCM, as a combination of two cure models with the first section from the end of the treatment to the first recurrence and second section from the first recurrence to death. Combing these two components is still a challenging problem. These could be minimized by applying specific link function to account for the overall survival. For short follow-up times the model fitting should be still treated with caution. Applying directly the overall survival the two-stage model provide more stable estimates in comparison to the one-stage model.

Outline

References

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