Comparison of different approaches to estimating age standardized net survival

Age-standardized net survival provides an important population-based summary of cancer survival that appropriately accounts for differences in other-cause mortality rates and standardizes the population age distribution to allow fair comparisons. Recently, there has been debate over the most appropr...

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Bibliographic Details
Published in:BMC medical research methodology 2015-08, Vol.15 (1), p.64-64, Article 64
Main Authors: Lambert, Paul C, Dickman, Paul W, Rutherford, Mark J
Format: Article
Language:English
Subjects:
Adolescent
Adult
Age Distribution
Age Factors
Aged
Aged, 80 and over
Algorithms
Censorship
Child
Child, Preschool
Comparative analysis
Computer Simulation
Epidemiology
Health aspects
Humans
Infant
Infant, Newborn
Methods
Middle Aged
Models, Theoretical
Neoplasms - mortality
Registries - statistics & numerical data
Survival Analysis
Survival Rate
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Summary:Age-standardized net survival provides an important population-based summary of cancer survival that appropriately accounts for differences in other-cause mortality rates and standardizes the population age distribution to allow fair comparisons. Recently, there has been debate over the most appropriate method for estimating this quantity, with the traditional Ederer II approach being shown to have potential bias. We compare lifetable-based estimates (Ederer II), a new unbiased method based on inverse probability of censoring weights (Pohar Perme) and model-based estimates. We make the comparison in a simulation setting; generating scenarios where we would expect to see a large theoretical bias. Our simulations demonstrate that even in relatively extreme scenarios there is negligible bias in age-standardized net survival when using the age-standardized Ederer II method, modelling with continuous age or using the Pohar Perme method. However, both the Ederer II and modelling approaches have some advantages over the Pohar Perme method in terms of greater precision, particularly for longer-term follow-up (10 and 15 years). Our results show that, when age-standardizing, concern over bias with the traditional methods is unfounded. We have also shown advantages in using the more traditional and modelling methods.
ISSN:1471-2288
1471-2288
DOI:10.1186/s12874-015-0057-3