Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models
Open Access
- 22 June 2011
- journal article
- Published by Springer Nature in BMC Medical Research Methodology
- Vol. 11 (1), 96
- https://doi.org/10.1186/1471-2288-11-96
Abstract
When the mortality among a cancer patient group returns to the same level as in the general population, that is, the patients no longer experience excess mortality, the patients still alive are considered "statistically cured". Cure models can be used to estimate the cure proportion as well as the survival function of the "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be specified. It can sometimes be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagnosis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models.Keywords
This publication has 17 references indexed in Scilit:
- Estimating the Cure Fraction in Population-Based Cancer Studies by Using Finite Mixture ModelsJournal of the Royal Statistical Society Series C: Applied Statistics, 2009
- Temporal trends in the proportion cured for cancer of the colon and rectum: A population‐based study using data from the Finnish Cancer RegistryInternational Journal of Cancer, 2007
- Estimating and modeling the cure fraction in population-based cancer survival analysisBiostatistics, 2006
- Interpreting trends in cancer patient survivalJournal of Internal Medicine, 2006
- Cure fraction estimation from the mixture cure models for grouped survival dataStatistics in Medicine, 2004
- Estimation in a Cox Proportional Hazards Cure ModelBiometrics, 2000
- A Nonparametric Mixture Model for Cure Rate EstimationBiometrics, 2000
- Mixture models for cancer survival analysis: application to population-based data with covariatesStatistics in Medicine, 1999
- A Proportional Hazards Model Taking Account of Long-Term SurvivorsBiometrics, 1998
- The cure for colon cancer: Results from the EUROCARE studyInternational Journal of Cancer, 1998