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癌症预测有效吗?

Do cancer predictions work?

作者信息

Dyba Tadeusz, Hakulinen Timo

机构信息

Finnish Cancer Registry, Liisankatu 21 B, FI-00170 Helsinki, Finland.

出版信息

Eur J Cancer. 2008 Feb;44(3):448-53. doi: 10.1016/j.ejca.2007.11.014. Epub 2007 Dec 20.

Abstract

Two different types of simple extrapolation models were investigated as tools for cancer incidence prediction. The number of incident cancer cases by sex and site in Finland was predicted using a prediction interval for each year from 1967 to 2003 on the basis of historical cancer incidence data obtained 5 to 15 years earlier. Cancer sites where major human-made changes in aetiology and diagnostics had occurred were analysed separately. Assuming that such changes had not occurred, the 95% prediction intervals based on normal errors of the age-standardised rate and on Poisson models included the observed number in 65-100% of the years. The Poisson models produced, on average, shorter intervals and were more capable of indicating a site where the model assumptions did not hold true. Simple extrapolation models may be used with some caution on coverage when there are no known factors that might make abrupt changes in the temporal development of cancer incidence. On the other hand, they may be used for detecting the effects of such factors.

摘要

研究了两种不同类型的简单外推模型,作为癌症发病率预测的工具。利用1967年至2003年每年的预测区间,根据5至15年前获得的历史癌症发病率数据,预测了芬兰按性别和部位划分的新发癌症病例数。对病因和诊断方面发生了重大人为变化的癌症部位进行了单独分析。假设未发生此类变化,基于年龄标准化率的正态误差和泊松模型的95%预测区间在65%-100%的年份包含了观察到的病例数。泊松模型平均产生的区间更短,并且更能够指出模型假设不成立的部位。当没有已知因素可能导致癌症发病率的时间发展发生突然变化时,简单外推模型在覆盖率方面使用时可能需要谨慎。另一方面,它们可用于检测此类因素的影响。

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