Back to Search
Start Over
Choosing the relative survival method for cancer survival estimation
- Source :
- European Journal of Cancer. 47:2202-2210
- Publication Year :
- 2011
- Publisher :
- Elsevier BV, 2011.
-
Abstract
- Background A new net survival method has been introduced by Pohar Perme et al. (2012 [4]) and recommended to substitute the relative survival methods in current use for evaluating population-based cancer survival. Methods The new method is based on the use of continuous follow-up time, and is unbiased only under non-informative censoring of the observed survival. However, the population-based cancer survival is often evaluated based on annually or monthly tabulated follow-up intervals. An empirical investigation based on data from the Finnish Cancer Registry was made into the practical importance of the censoring and the level of data tabulation. A systematic comparison was made against the earlier recommended Ederer II method of relative survival using the two currently available computer programs (Pohar Perme (2013) [10] and Dickman et al. (2013) [11]). Results With exact or monthly tabulated data, the Pohar-Perme and the Ederer II methods give, on average, results that are at five years of follow-up less than 0.5% units and at 10 and 14 years 1–2% units apart from each other. The Pohar-Perme net survival estimator is prone to random variation and may result in biased estimates when exact follow-up times are not available or follow-up is incomplete. With annually tabulated follow-up times, estimates can deviate substantially from those based on more accurate observations, if the actuarial approach is not used. Conclusion At 5 years, both the methods perform well. In longer follow-up, the Pohar-Perme estimates should be interpreted with caution using error margins. The actuarial approach should be preferred, if data are annually tabulated.
- Subjects :
- Adult
Male
Cancer Research
Adolescent
Population
Young Adult
Age Distribution
Cause of Death
Neoplasms
Statistics
Humans
Medicine
Registries
Child
education
Finland
Survival analysis
Aged
Aged, 80 and over
education.field_of_study
Models, Statistical
Relative survival
business.industry
Estimator
Cancer survival
Middle Aged
Survival Analysis
Censoring (statistics)
Cancer registry
Oncology
Child, Preschool
Data Interpretation, Statistical
Female
business
Random variable
Algorithms
Subjects
Details
- ISSN :
- 09598049
- Volume :
- 47
- Database :
- OpenAIRE
- Journal :
- European Journal of Cancer
- Accession number :
- edsair.doi.dedup.....e7f33f282b361974f49bd81e44967ea2