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临床实践指南制定中的模型。

Models in the development of clinical practice guidelines.

出版信息

Ann Intern Med. 2014 Dec 2;161(11):812-8. doi: 10.7326/M14-0845.

Abstract

Clinical practice guidelines should be based on the best scientific evidence derived from systematic reviews of primary research. However, these studies often do not provide evidence needed by guideline development groups to evaluate the tradeoffs between benefits and harms. In this article, the authors identify 4 areas where models can bridge the gaps between published evidence and the information needed for guideline development applying new or updated information on disease risk, diagnostic test properties, and treatment efficacy; exploring a more complete array of alternative intervention strategies; assessing benefits and harms over a lifetime horizon; and projecting outcomes for the conditions for which the guideline is intended. The use of modeling as an approach to bridge these gaps (provided that the models are high-quality and adequately validated) is considered. Colorectal and breast cancer screening are used as examples to show the utility of models for these purposes. The authors propose that a modeling study is most useful when strong primary evidence is available to inform the model but critical gaps remain between the evidence and the questions that the guideline group must address. In these cases, model results have a place alongside the findings of systematic reviews to inform health care practice and policy.

摘要

临床实践指南应基于从系统评价初级研究中得出的最佳科学证据。然而,这些研究通常不能为指南制定小组提供评估获益与危害之间权衡所需的证据。在本文中,作者确定了 4 个领域,模型可以在发表的证据和指南制定所需的信息之间架起桥梁,这些信息应用了关于疾病风险、诊断测试特性和治疗效果的新信息或更新信息;探索更完整的替代干预策略组合;评估终生的获益与危害;并预测指南所针对的疾病的结果。考虑了使用建模作为弥合这些差距的方法(前提是模型是高质量的并且经过充分验证)。结直肠癌和乳腺癌筛查被用作示例,展示了模型在这些目的中的用途。作者提出,当有强有力的初级证据可用于为模型提供信息,但证据与指南制定小组必须解决的问题之间仍存在关键差距时,建模研究最有用。在这些情况下,模型结果与系统评价的结果一起,为医疗保健实践和政策提供信息。

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