The estimation of diagnostic sensitivity using stability data: an application to major depressive disorder.
The estimation of diagnostic sensitivity using stability data: an application to major depressive disorder.
复制标题
使用稳定性数据估计诊断敏感性：在重度抑郁症中的应用。
DOI：
10.1016/0022-3956(87)90080-x
复制
发表时间：
1987
影响因子：
4.8
通讯作者：
Rochberg,N
中科院分区：
文献类型：
--
作者：
Rice,JP;Endicott,J;Knesevich,MA;Rochberg,N
解释精神障碍终生诊断的可靠性/稳定性的一个困难是缺乏理论视角。由于缺乏“黄金标准”，用三个未知数（敏感性、特异性和真实碱基率）表示的模型是有问题的，因此只能估计其中的两个未知数。我们扩展此模型以允许临床协变量增加时间 1 的阳性病例在时间 2 呈阳性的可能性。假设所有观察到的病例都是最高协变量值的真实病例，我们获得敏感性的直接估计，以便可以估计所有未知数。此外，我们然后计算具有给定协变量水平的观察案例实际上是真实案例的可能性。给出了诊断错误对发病率和人口率估计以及遗传模型拟合的影响。这些方法应用于作为 NIMH 抑郁症心理生物学项目一部分收集的稳定性数据。共有 982 名亲属接受了评估，访谈间隔为 6 年。使用逻辑函数对 264 名终生首次诊断为重度抑郁症的亲属的稳定性进行建模。逐步分析中的显着协变量预测因素是最严重发作时抑郁症状的数量、发作次数以及最严重发作时接受的药物治疗。敏感性估计为 0.918，特异性估计为 0.940。然而，即使有这些高值，在报告的具有 3 种症状且未接受药物治疗的首发病例中，真实病例还不到一半。这些数据表明，诊断错误的建模以及包括临床协变量将有助于分析精神疾病的流行病学或家庭数据。
A difficulty in the interpretation of the reliability/stability of a lifetime diagnosis of mental disorders is the lack of a theoretical perspective. A model expressed in terms of the three unknowns—sensitivity, specificity and true base rate—is problematic due to the lack of a “gold standard”, so that only two of these unknowns can be estimated. We extend this model to allow for clinical covariates that increase the likelihood that a positive case at time 1 will be positive at time 2. Under the assumption that all observed cases are true cases at the highest covariate values, we obtain a direct estimate of the sensitivity, so that all unknowns can be estimated. Moreover, we then calculate the likelihood that an observed case with given covariate levels is in fact a true case. The implications of diagnostic error for the estimation of incidence and population rates and the fitting of genetic models are given.These methods are applied to stability data collected as part of the NIMH Psychobiology of Depression Program. A total of 982 relatives have been assessed with interviews separated by a 6 year interval. A logistic function was used to model the stability in 264 relatives with an initial lifetime diagnosis of Major Depressive Disorder. The significant covariate predictors in a step-wise analysis were the number of depressive symptoms in the worst episode, the number of episodes and receiving medication for the worst episode. The sensitivity was estimated to be 0.918 and the specificity was estimated to be 0.940. However, even with these high values, less than half of the reported first episode cases with 3 symptoms who did not receive medication are true cases. These data illustrate that the modelling of diagnostic error, as well as including clinical covariates, will be useful in analyzing epidemiologic or family data for psychiatric illnesses.
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影响因子：
6.6
作者：
J. Wing;P. Bebbington
通讯作者：
P. Bebbington
影响因子：
--
作者：
N. Andreasen;J. Rice;J. Endicott;W. Coryell;W. Grove;T. Reich
通讯作者：
T. Reich
后续研究中诊断一致性的评估：I.因果分析的一般模型和方法论批判。
影响因子：
4.8
作者：
C. Robert Cloninger;J. Miller;R. Wette;R. Martin;S. Guze
通讯作者：
S. Guze
多变量分析：理论与实践
影响因子：
6.1
作者：
V.Kerry Smith
通讯作者：
V.Kerry Smith