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Commentary: trials versus models in appraising screening programmes

机译:评论:评估筛查程序中的试验与模型

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摘要

Sherlaw-Johnson and colleagues raise some important issues about methods for assessing screening programmes and, indeed, any healthcare intervention. Does the standard approach for assessment—the experimental trial—have a competitor in the mathematical model? Experimentation is an investigatory method whose strengths, especially in its gold standard, the randomised control trial, are well known. It frequently offers the most reliable route to establishing the impact of a healthcare intervention, particularly in areas without a strong theoretical underpinning, which are all too common in health care. Yet experiments have their weaknesses. Trials can be expensive, can present ethical difficulties, and can take a long time—even to the extent that the intervention under investigation has been superseded before the trial ends. It can be difficult to extrapolate from study findings about aggregated groups of people to subgroups, let alone to individual patients. Trials can generally test only a small number of intervention options.
机译:Sherlaw-Johnson及其同事提出了有关评估筛查程序的方法以及实际上任何医疗干预措施的一些重要问题。标准的评估方法(实验试验)在数学模型中是否具有竞争对手?实验是一种调查方法,其优势尤其是在其金标准中(随机对照试验)是众所周知的。它通常为确立医疗保健干预措施的影响提供最可靠的途径,尤其是在没有强大理论基础的地区,这些领域在医疗保健中太普遍了。然而实验有其弱点。审判可能会很昂贵,可能会带来道德上的困难,并且可能会花费很长时间,甚至达到在调查结束之前已取代正在调查的干预措施的程度。从关于人群总数的研究结果中很难推断出亚组,更不用说对个别患者了。试验通常只能测试少量干预选项。

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