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使用常规收集的数据预测乳腺癌筛查的参与率。

Predicting attendance for breast screening using routinely collected data.

作者信息

van der Pol Marjon, Cairns John

机构信息

Health Economics Research Unit, University of Aberdeen, Scotland.

出版信息

Health Care Manag Sci. 2003 Nov;6(4):229-36. doi: 10.1023/a:1026229624136.

Abstract

The aim of this paper is to predict attendance if the age range for routine invitation to breast screening were to be extended. The response to the most recent screening invitation is modelled for women eligible for screening if the age range were extended. The independent variables include (i) the woman's characteristics: her screening history; the deprivation score of the area she lives in and (ii) the characteristics of the screening: whether the screening took place in a mobile van or at a static site; and time of the year. The predictive ability of the regression model is tested by goodness of fit measures and by predicting attendance for a holdout sample of the data and for women who participated in a demonstration project. The modelling of attendance is quite successful in that most hypothesised variables have the expected sign. Moreover, the predictive ability of the model is satisfactory in terms of goodness of fit statistics and in terms of accuracy of predictions for a holdout sample. The model predicts less well for the demonstration project possibly because it is less representative of usual screening practice.

摘要

本文的目的是预测如果扩大常规乳腺癌筛查邀请的年龄范围,其参与率将会怎样。针对年龄范围扩大后符合筛查条件的女性,对她们最近一次筛查邀请的回应进行建模。自变量包括:(i)女性的特征:她的筛查史;她居住地区的贫困得分;以及(ii)筛查的特征:筛查是在移动筛查车还是在固定地点进行;以及一年中的时间。通过拟合优度指标以及对数据的保留样本和参与示范项目的女性的参与率进行预测,来检验回归模型的预测能力。参与率建模相当成功,因为大多数假设变量都有预期的符号。此外,就拟合优度统计量和保留样本预测的准确性而言,该模型的预测能力令人满意。该模型对示范项目的预测效果较差,可能是因为它不太能代表常规筛查实践。

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