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Biostatistics Advance Access originally published online on October 4, 2006
Biostatistics 2007 8(3):576-594; doi:10.1093/biostatistics/kxl030
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© The Author 2006. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Estimating and modeling the cure fraction in population-based cancer survival analysis

Paul C. Lambert* and John R. Thompson

Department of Health Sciences, Centre for Biostatistics and Genetic Epidemiology, University of Leicester, 22-28 Princess Road West, Leicester LE1 6TP, UK, pl4{at}le.ac.uk

Claire L. Weston

United Kingdom Children's Cancer Study Group, University of Leicester, Leicester, UK

Paul W. Dickman

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

* To whom correspondence should be addressed.

In population-based cancer studies, cure is said to occur when the mortality (hazard) rate in the diseased group of individuals returns to the same level as that expected in the general population. The cure fraction (the proportion of patients cured of disease) is of interest to patients and is a useful measure to monitor trends in survival of curable disease. There are 2 main types of cure fraction model, the mixture cure fraction model and the non-mixture cure fraction model, with most previous work concentrating on the mixture cure fraction model. In this paper, we extend the parametric non-mixture cure fraction model to incorporate background mortality, thus providing estimates of the cure fraction in population-based cancer studies. We compare the estimates of relative survival and the cure fraction between the 2 types of model and also investigate the importance of modeling the ancillary parameters in the selected parametric distribution for both types of model.

Keywords: Cure models; Relative survival; Survival analysis

Received March 9, 2006; revised August 11, 2006; accepted for publication September 29, 2006.


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