Faraone S V, Tsuang M T
Harvard Institute of Psychiatric Epidemiology and Genetics, Department of Psychiatry, Harvard Medical School, Massachusetts Mental Health Center, Boston.
Am J Psychiatry. 1994 May;151(5):650-7. doi: 10.1176/ajp.151.5.650.
As the nation debates issues of national health care reform, psychiatrists seek equal status with other medical colleagues. To defend psychiatry in the national arena, the accuracy of psychiatric diagnoses must be measured. Indexes of accuracy such as sensitivity and specificity provide valuable information, yet they are rarely computed because there is no "gold standard" with which to compare them. The goal of this article is to show how this problem can be overcome and to encourage nosologists to use accuracy statistics in assessing the adequacy of psychiatric diagnoses.
The authors reviewed the literature on medical decision making to find methodological approaches to assessing diagnostic accuracy in the absence of gold standards.
A lack of such standards is not unique to psychiatry and has been addressed with a variety of novel analytic procedures. Although these methods differ in many respects, each recognizes that the conventional 2 x 2 table of interrater agreement does not provide enough data for estimating diagnostic accuracy. After defining the data needed, each method provides a mathematical model that estimates accuracy statistics and the prevalence of a disorder. Most of these methods are variants of latent class analysis. The authors reanalyzed data from one of the reviewed papers to show that similar inferences about accuracy of diagnoses could be drawn from a conventional latent class analysis.
There are potential pitfalls in using latent structure methods, but their cautious use would provide valuable information for psychiatric nosology. These methods supplement, but do not replace, data about outcome, family history, laboratory studies, and other validating criteria in making accurate diagnoses.
在国家对医疗保健改革问题进行辩论之际，精神科医生寻求与其他医学同行享有平等地位。为在国家层面捍卫精神病学，必须衡量精神科诊断的准确性。诸如敏感度和特异度等准确性指标能提供有价值的信息，但由于没有可与之比较的“金标准”，这些指标很少被计算。本文的目的是展示如何克服这一问题，并鼓励疾病分类学家在评估精神科诊断的充分性时使用准确性统计数据。
作者回顾了关于医疗决策的文献，以找到在缺乏金标准的情况下评估诊断准确性的方法。
缺乏此类标准并非精神科所独有，并且已经通过各种新颖的分析程序得到解决。尽管这些方法在许多方面存在差异，但每种方法都认识到传统的评价者间一致性2×2表格无法提供足够的数据来估计诊断准确性。在定义所需数据后，每种方法都提供了一个数学模型，用于估计准确性统计数据和疾病的患病率。这些方法大多是潜在类别分析的变体。作者重新分析了一篇被审查论文中的数据，以表明从传统的潜在类别分析中可以得出关于诊断准确性的类似推断。
使用潜在结构方法存在潜在的陷阱，但谨慎使用这些方法将为精神科疾病分类学提供有价值的信息。在做出准确诊断时，这些方法补充但不取代关于预后、家族史、实验室检查和其他验证标准的数据。
