Predicting cancer incidence in regions without population-based cancer registries using mortality

IF 1.5 3区 数学 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS Journal of the Royal Statistical Society Series A-Statistics in Society Pub Date : 2023-06-05 DOI:10.1093/jrsssa/qnad077
Garazi Retegui, J. Etxeberria, A. Riebler, M. Ugarte
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Abstract

Cancer incidence numbers are routinely recorded by national or regional population-based cancer registries (PBCRs). However, in most southern European countries, the local PBCRs cover only a fraction of the country. Therefore, national cancer incidence can be only obtained through estimation methods. In this paper, we predict incidence rates in areas without cancer registry using multivariate spatial models modelling jointly cancer incidence and mortality. To evaluate the proposal, we use cancer incidence and mortality data from all the German states. We also conduct a simulation study by mimicking the real case of Spain considering different scenarios depending on the similarity of spatial patterns between incidence and mortality, the levels of lethality, and varying the amount of incidence data available. The new proposal provides good interval estimates in regions without PBCRs and reduces the relative error in estimating national incidence compared to one of the most widely used methodologies.
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使用死亡率预测没有基于人口的癌症登记的地区的癌症发病率
癌症发病率由国家或地区基于人口的癌症登记处(pbcr)例行记录。然而,在大多数南欧国家,地方pbcr只覆盖了该国的一小部分。因此,全国癌症发病率只能通过估算方法来获得。在本文中,我们使用多变量空间模型联合建模癌症发病率和死亡率来预测没有癌症登记的地区的发病率。为了评估这一建议,我们使用了德国各州的癌症发病率和死亡率数据。我们还进行了一项模拟研究,通过模仿西班牙的真实案例,根据发病率和死亡率之间的空间格局相似性、致死率水平以及不同的发病率数据量,考虑不同的情景。与最广泛使用的一种方法相比,新建议在没有pbcr的地区提供了良好的间隔估计,并减少了估计全国发病率的相对误差。
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来源期刊
CiteScore
2.90
自引率
5.00%
发文量
136
审稿时长
>12 weeks
期刊介绍: Series A (Statistics in Society) publishes high quality papers that demonstrate how statistical thinking, design and analyses play a vital role in all walks of life and benefit society in general. There is no restriction on subject-matter: any interesting, topical and revelatory applications of statistics are welcome. For example, important applications of statistical and related data science methodology in medicine, business and commerce, industry, economics and finance, education and teaching, physical and biomedical sciences, the environment, the law, government and politics, demography, psychology, sociology and sport all fall within the journal''s remit. The journal is therefore aimed at a wide statistical audience and at professional statisticians in particular. Its emphasis is on well-written and clearly reasoned quantitative approaches to problems in the real world rather than the exposition of technical detail. Thus, although the methodological basis of papers must be sound and adequately explained, methodology per se should not be the main focus of a Series A paper. Of particular interest are papers on topical or contentious statistical issues, papers which give reviews or exposés of current statistical concerns and papers which demonstrate how appropriate statistical thinking has contributed to our understanding of important substantive questions. Historical, professional and biographical contributions are also welcome, as are discussions of methods of data collection and of ethical issues, provided that all such papers have substantial statistical relevance.
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