American Journal of Epidemiology Advance Access originally published online on July 13, 2006
American Journal of Epidemiology 2006 164(7):689-696; doi:10.1093/aje/kwj243
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Practice of Epidemiology |
Up-to-date and Precise Estimates of Cancer Patient Survival: Model-based Period Analysis
1 Department of Epidemiology, German Centre for Research on Ageing, Heidelberg, Germany
2 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
3 Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland
Correspondence to Dr. Hermann Brenner, Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Bergheimer Strasse 20, D-69115 Heidelberg, Germany (e-mail: h.brenner{at}dkfz-heidelberg.de).
Monitoring of progress in cancer patient survival by cancer registries should be as up-to-date as possible. Period analysis has been shown to provide more up-to-date survival estimates than do traditional methods of survival analysis. However, there is a trade-off between up-to-dateness and the precision of period estimates, in that increasing the up-to-dateness of survival estimates by restricting the analysis to a relatively short, recent time period, such as the most recent calendar year for which cancer registry data are available, goes along with a loss of precision. The authors propose a model-based approach to maximize the up-to-dateness of period estimates at minimal loss of precision. The approach is illustrated for monitoring of 5-year relative survival of patients diagnosed with one of 20 common forms of cancer in Finland between 1953 and 2002 by use of data from the nationwide Finnish Cancer Registry. It is shown that the model-based approach provides survival estimates that are as up-to-date as the most up-to-date conventional period estimates and at the same time much more precise than the latter. The modeling approach may further enhance the use of period analysis for deriving up-to-date cancer survival rates.
epidemiologic methods; models, statistical; neoplasms; prognosis; registries; survival
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