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本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。

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分类依据与纠错

AI 根据所提供的论文材料归类:摘要中的风险指癌症流行病学风险,未涉及金融风险或明确的因果识别方法。

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正在核对关联版本…

代码、数据与补充材料

正在核对对应版本的资源…

关注这篇论文的作者
Colin B. Begg
Jaya M. Satagopan
Marianne Berwick

评估癌症流行病学风险因素贡献的新策略:黑色素瘤应用

研究问题
如何量化癌症风险在人群中的总体变异,并以此衡量单个或多个已知风险因素对该变异的贡献?
方法与思路
作者提出随机框架,用第二原发黑色素瘤的标准化发病比估计总体风险变异系数,并构造单因素贡献的非参数估计。
材料陈述的贡献
摘要称连续因素分类会明显削弱贡献估计;黑色素瘤应用显示已知因素解释的风险变异比例较小,与常见观点不同。
阅读关注点
应核对总体风险变异估计所需的简化假设、病例对照抽样的处理,以及单因素与多因素贡献如何定义和比较。
阅读边界
仅据版本未注明的 OpenAlex 索引摘要;简化假设与应用数值未说明,风险变异贡献不能直接解释为因果贡献。

原文摘要

A new stochastic framework is proposed for evaluating the individual and collective impact of cancer risk factors, and is applied to data on the incidence of melanoma. It is demonstrated that the standardized incidence ratio of second primary melanoma can be used to estimate the total coefficient of variation in risk in the population, subject to some simplifying assumptions. The coefficient of variation estimated in this manner thus can be used as a benchmark against which to judge the contributions to this total variance of individual risk factors. A nonparametric estimator of the coefficient of variation attributable to a single risk factor on the basis of data from a case-control study is derived, and its statistical properties are examined using simulations. It is shown that the categorization of a continuous risk factor can attenuate the estimate substantially, and that estimation of the joint contribution of several risk factors will usually require statistical modeling. Applying the methods to the epidemiology of melanoma, the results indicate that the known risk factors for melanoma explain only a relatively small fraction of the population variation in risk, in contrast to conventional views on this topic.

笔记与分组
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