For the article cited above, an error was made in listing the last author's name. The correct name is Song Iy Han. We apologize to the readers for any confusion caused by this error.
Model-based projections for deriving up-to-date cancer survival estimates: An international evaluation
✍ Scribed by Adam Gondos; Bernd Holleczek; Maryska Janssen-Heijnen; David H. Brewster; Freddie Bray; Stefano Rosso; Timo Hakulinen; Hermann Brenner
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- French
- Weight
- 173 KB
- Volume
- 125
- Category
- Article
- ISSN
- 0020-7136
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
Model‐based projections were shown to be useful for deriving most up‐to‐date population‐based cancer survival estimates. However, the performance of these projections, which can be derived by various approaches, has only been evaluated in very few cancer patient populations. Using incidence and follow‐up data for 22 common cancers from 9 long‐standing population‐based cancer registries from diverse parts of Europe, we compared the performance of model‐based period and cohort analysis for predicting 5‐year relative survival of patients diagnosed in 1996–2000 against standard survival analysis approaches (cohort, complete and period analysis). Overall, model‐based predictions provided a best estimate of the later observed actual survival in 135 of 198 occasions, compared to 25, 18 and 33 occasions for cohort, complete and period analysis, respectively. Projections based on cohort and period type modeling performed essentially equally well on average, and their performance was better for more common cancers, in registries with larger population bases, and for cancers subjected to continuous clinical progress and/or ongoing screening efforts. Projections from model‐based analysis may contribute to improved timeliness of monitoring of concurrent trends in population‐based cancer survival in cancer registries operating in different populations and socioeconomic environments. © 2009 UICC
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