Dervaux B, Leleu H, Lebrun T, Levi S, Grandjean H
CRESGE, Department of Health Economics, Catholic University of Lille, France.
Ann N Y Acad Sci. 1998 Jun 18;847:125-35. doi: 10.1111/j.1749-6632.1998.tb08933.x.
In this paper, we show that the ratio of the number of fetal anomalies detected by ultrasounds (US) to the total number of cases is not a consistent estimator of the US sensitivity. As Eddy pointed out, when the disease evolves over time, the sensitivity of a test also varies over time according to the development of the disease. To assess correctly the detection capability of a test, it is therefore necessary to estimate a time continuous function (sensitivity function) instead of a single parameter. From a methodological point of view, by considering the "detectability" time of a fetal anomaly as a random variable and parametrizing its distribution function, we estimate the probability that an anomaly is detected conditional upon the precise timing of actually performed US during pregnancy. We fit this model with Eurofetus data (about 7,300 abnormal fetuses), and we compare estimations for different kinds of anomalies (classification based on the system involved and/or severity of the handicap). To allow for heterogeneity of anomalies regarding the detectability time, we generally adopt mixture models. For instance, we select a bi-gamma distribution for major malformations and estimate that 63% of such anomalies are detectable quite early in pregnancy (conditional mean: 15.2 weeks of amenorrhea (WA) +/- 4.2 WA), the others becoming detectable later (30.3 WA +/- 6.4 WA). Such results are then integrated in a cost-effectiveness analysis.
在本文中,我们表明超声(US)检测出的胎儿异常数量与病例总数的比率并非超声敏感度的一致估计量。正如埃迪所指出的,当疾病随时间演变时,一项检测的敏感度也会根据疾病的发展随时间变化。因此,为了正确评估一项检测的检测能力,有必要估计一个时间连续函数(敏感度函数)而非单个参数。从方法学角度来看,通过将胎儿异常的“可检测性”时间视为一个随机变量并对其分布函数进行参数化,我们估计在孕期实际进行超声检查的精确时间条件下检测到异常的概率。我们用欧洲胎儿数据(约7300例异常胎儿)拟合此模型,并比较不同类型异常(基于所涉及的系统和/或残疾严重程度进行分类)的估计值。为了考虑异常在可检测性时间方面的异质性,我们通常采用混合模型。例如,对于严重畸形我们选择双伽马分布,并估计63%的此类异常在孕期相当早的时候就可检测到(条件均值:停经15.2周(WA)±4.2WA),其他异常则在稍后可检测到(30.3WA±6.4WA)。然后将这些结果纳入成本效益分析中。