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© 1995 Oxford University Press
research-article |
Analysis of Cancer Rates Using Excess Risk Age-Period-Cohort Models
Institute of Epidemiology, College of Public Health, National Taiwan University Taipei, Taiwan, Republic of China
Reprint requests to: Dr Ruey S Lin, College of Public Health, National Taiwan University No. 1, Jen-Ai Rd, 1st Sec, Taipei, Taiwan, Republic of China.
BACKGROUND: Recently the age-period-cohort (APC) model has become a popular epidemiological tool. However, It is well known that the model suffers from the identifiability problem. The simple multiplicative formulation of the model in terms of the age, period, and cohort variables without resorting to the underlying biology also casts doubt on the interpretability of the model parameters.
METHODS: Excess risk APC models for cancers are developed based on carclnogenesls processes in human populations. These models have the beneficial feature of biological plausibility and do not suffer from the identifiability problem. Apart from the age, period, and cohort effects, a new kind of effect, the impact effect, is also introduced into the models. A computer program has been developed to fit the models which contain non-linear as well as restricted parameters.
RESULTS: Two published mortality datasets are used to demonstrate the methodology. The proposed models fit better than the conventional APC model in both examples.
CONCLUSIONS: Despite all the merits of the proposed models, several statistical issues should be investigated further before accepting this methodology as a general data-analytical tool.
Keywords age-period-cohort models, Armitage-Doll multistage carcinogenesis models, excess risk models, lung cancer, non-linear optimization, prostate cancer
Revised 1 February 1995
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