Period versus cohort modeling of up-to-date cancer survival.

Recently, 2 modeling strategies have been proposed and shown to be useful to increase precision of up-to-date cancer survival estimates and to predict cancer patient survival: modeled period analysis and modeled cohort analysis. We aimed to compare the performance of both types of modeling for providing up-to-date and precise cancer survival estimates. Data from the nationwide Finnish Cancer Registry were used to assess how well both approaches would have been able to predict 5-year relative survival of concurrently diagnosed patients if they had been applied for that purpose throughout the past decades. Analyses were carried out for 20 common forms of cancer. For each cancer, 5-year relative survival was modeled with either approach for each single calendar year from 1962 to 1997. Mean differences and mean squared differences from 5-year relative survival later observed for patients diagnosed in the 5-year period around those calendar years were calculated. Survival estimates obtained by period modeling had much lower standard errors than those obtained by cohort modeling. Furthermore, for a clear majority of cancers, period modeling on average also provided better prediction of 5-year relative survival than cohort modeling. We conclude that, although both modeling strategies have their merits and specific indications, period modeling of survival has distinct advantages for up-to-date and precise estimation of cancer survival in population-based cancer survival studies.
((c) 2007 Wiley-Liss, Inc.)