Szatmari P, Volkmar F, Walter S
Department of Psychiatry, McMaster University, Hamilton, Ontario, Canada.
J Am Acad Child Adolesc Psychiatry. 1995 Feb;34(2):216-22. doi: 10.1097/00004583-199502000-00017.
To illustrate the use of latent class models for comparing alternative diagnostic criteria for autism. The models are based on the notion that the "true" classification of an individual is unknown but does exist at some unobserved, or "latent," level. Estimates of sensitivity and specificity are obtained for each set of diagnostic criteria through maximum likelihood techniques in relation to the latent standard.
In this paper, latent class models are used to compare DSM-III, DSM-III-R, and ICD-10 criteria for autism in a sample of 342 individuals with autism or other developmental disabilities. The diagnoses were made by one or more child psychiatrists who evaluated each patient and assigned a diagnosis of autism based on their own expert clinical judgment. In addition, the raters also determined whether criteria were met for the various diagnostic systems.
The results indicate that the ICD-10 criteria agree best with the latent standard and a diagnosis based on expert opinion.
It is suggested that latent class models can be usefully applied to the evaluation of other psychiatric disorders as well and represent an important new tool in evaluating diagnostic criteria by providing a way of dealing with data lacking an observable gold standard.
阐述潜在类别模型在比较自闭症替代诊断标准中的应用。这些模型基于这样一种观念，即个体的“真实”分类是未知的，但确实存在于某个未被观察到的或“潜在”的层面。通过与潜在标准相关的最大似然技术，为每组诊断标准获得敏感性和特异性估计值。
在本文中，潜在类别模型用于比较342名患有自闭症或其他发育障碍个体样本中的自闭症诊断标准DSM-III、DSM-III-R和ICD-10。诊断由一名或多名儿童精神科医生做出，他们对每位患者进行评估，并根据自己的专家临床判断给出自闭症诊断。此外，评估者还确定各种诊断系统的标准是否得到满足。
结果表明，ICD-10标准与潜在标准以及基于专家意见的诊断最为一致。
建议潜在类别模型也可有效地应用于其他精神疾病的评估，并且通过提供一种处理缺乏可观察金标准数据的方法，代表了评估诊断标准的一种重要新工具。
