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来自不精确数据的可靠建议:检测/治疗决策

Solid recommendations from soft numbers: the test/treatment decision.

作者信息

Nease R F, Bonduelle Y

机构信息

Department of Engineering-Economic Systems, Stanford University, California 94305.

出版信息

Med Decis Making. 1987 Oct-Dec;7(4):220-33. doi: 10.1177/0272989X8700700404.

Abstract

The authors review the probability threshold approach to test/treatment decisions developed by Pauker and Kassirer, emphasizing that certain aspects of the nature of medical decisions call for a new approach. The utility threshold approach, while maintaining all the advantages of threshold methods in general, brings improvements. It diminishes the need to accurately assess one of the decision's parameters: the patient's utility for the outcome states. For a simple case of one disease with three outcome states (cured, diseased, dead) and one test, three utility thresholds are derived. The treat/no treat threshold, denoted by u, separates the utility space in two. If the patient's value for the diseased state is greater than u, the analyst can feel confident in recommending the patient forego treatment. Similar interpretations are developed for u1, the no treatment/test utility threshold (the value u must take, given a positive test result, for the patient to be indifferent between foregoing and receiving treatment), and u2, the test/treatment utility threshold (the value u must take, given a negative test result, for the patient to be indifferent between foregoing and receiving treatment.

摘要

作者回顾了由帕克和卡西勒提出的用于检验/治疗决策的概率阈值方法,并强调医学决策本质的某些方面需要一种新方法。效用阈值方法在总体上保持了阈值方法的所有优点的同时,还带来了改进。它减少了准确评估决策参数之一的必要性:患者对结果状态的效用。对于一种有三种结果状态(治愈、患病、死亡)的单一疾病和一项检验的简单情况,推导出了三个效用阈值。治疗/不治疗阈值,用u表示,将效用空间一分为二。如果患者对患病状态的估值大于u,分析人员可以放心地建议患者放弃治疗。对于u1(不治疗/检验效用阈值,即给定阳性检验结果时,u必须取的值,以使患者在放弃和接受治疗之间无差异)和u2(检验/治疗效用阈值,即给定阴性检验结果时,u必须取的值,以使患者在放弃和接受治疗之间无差异)也有类似的解释。

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