首页> 外文期刊>International Journal of Cancer =: Journal International du Cancer >Model-based projections for deriving up-to-date cancer survival estimates: an international evaluation.
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Model-based projections for deriving up-to-date cancer survival estimates: an international evaluation.

机译:基于模型的预测,用于导出最新的癌症生存估算:国际评估。

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摘要

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.
机译:基于模型的预测被证明可用于导出最新的群体癌症生存估计。然而,这些突起可以通过各种方法来源的这些突出物的性能仅在很少甚至的癌症患者群体中进行了评估。从欧洲各种各样的癌症中,22种常见癌症的发病率和后续数据来自来自欧洲各种各样的群体的癌症,我们比较了模型的期间和队列分析的性能,以预测诊断为患者的患者的5年相对存活1996 - 2000年反对标准生存分析方法(队列,完整和期间分析)。总体而言,基于模型的预测,为198年的135中的后期观察到的实际存活率的最佳估计分别为25,18和33个分别为25,18和33场所。基于群组和期间型建模的预测平均同样良好,其性能更好地为更多常见的癌症,具有较大人口基础的注册管理机构,以及对持续临床进展和/或正在进行的筛查努力进行癌症的癌症。基于模型的分析的预测可能有助于改善在不同人群和社会经济环境中运作的癌症注册管理机构中癌症癌症生存中同时趋势的改善的及时性。

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