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The tyranny of the averages and the indiscriminate use of risk factors in public health: The case of coronary heart disease

机译:平均数的暴政和公共卫生中危险因素的滥用:冠心病案例

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摘要

Modern medicine is overwhelmed by a plethora of both established risk factors and novel biomarkers for diseases. The majority of this information is expressed by probabilistic measures of association such as the odds ratio (OR) obtained by calculating differences in average “risk” between exposed and unexposed groups. However, recent research demonstrates that even ORs of considerable magnitude are insufficient for assessing the ability of risk factors or biomarkers to distinguish the individuals who will develop the disease from those who will not. In regards to coronary heart disease (CHD), we already know that novel biomarkers add very little to the discriminatory accuracy (DA) of traditional risk factors. However, the value added by traditional risk factors alongside simple demographic variables such as age and sex has been the subject of less discussion. Moreover, in public health, we use the OR to calculate the population attributable fraction (PAF), although this measure fails to consider the DA of the risk factor it represents. Therefore, focusing on CHD and applying measures of DA, we re-examine the role of individual demographic characteristics, risk factors, novel biomarkers and PAFs in public health and epidemiology. In so doing, we also raise a more general criticism of the traditional risk factors’ epidemiology. We investigated a cohort of 6103 men and women who participated in the baseline (1991–1996) of the Malmö Diet and Cancer study and were followed for 18 years. We found that neither traditional risk factors nor biomarkers substantially improved the DA obtained by models considering only age and sex. We concluded that the PAF measure provided insufficient information for the planning of preventive strategies in the population. We need a better understanding of the individual heterogeneity around the averages and, thereby, a fundamental change in the way we interpret risk factors in public health and epidemiology.
机译:现代医学被众多既定的风险因素和疾病的新生物标记所淹没。此信息的大部分通过概率关联度来表示,例如通过计算暴露和未暴露组之间的平均“风险”差异而获得的优势比(OR)。但是,最近的研究表明,即使是相当大的OR,也不足以评估风险因素或生物标记物区分将要患这种疾病的人和不会患这种疾病的人的能力。关于冠心病(CHD),我们已经知道,新型生物标志物几乎没有增加传统危险因素的辨别准确性(DA)。但是,传统风险因素与简单的人口变量(例如年龄和性别)所增加的价值一直是讨论较少的话题。此外,在公共卫生中,尽管此度量未能考虑其代表的危险因素的DA,但我们使用OR来计算人口归因分数(PAF)。因此,我们将重点放在冠心病和应用DA的措施上,重新检验个人人口统计学特征,危险因素,新型生物标志物和PAF在公共卫生和流行病学中的作用。在此过程中,我们也对传统危险因素的流行病学提出了更普遍的批评。我们调查了6103名男性和女性,他们参加了马尔默饮食与癌症研究的基线(1991年至1996年),并随访了18年。我们发现,传统的危险因素和生物标志物都没有显着改善仅考虑年龄和性别的模型获得的DA。我们得出的结论是,PAF措施无法为人群的预防策略规划提供足够的信息。我们需要更好地理解平均值附近的个体异质性,从而从根本上改变我们解释公共卫生和流行病学风险因素的方式。

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