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首页> 外文期刊>Statistics in medicine >Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data.
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Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data.

机译:诊断测试数据的摘要接收器工作特性(SROC)曲线的属性。

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The summary receiver operating characteristic (SROC) curve has been recommended to represent the performance of a diagnostic test, based on data from a meta-analysis. However, little is known about the basic properties of the SROC curve or its estimate. In this paper, the position of the SROC curve is characterized in terms of the overall diagnostic odds ratio and the magnitude of inter-study heterogeneity in the odds ratio. The area under the curve (AUC) and an index Q(*) are discussed as potentially useful summaries of the curve. It is shown that AUC is maximized when the study odds ratios are homogeneous, and that it is quite robust to heterogeneity. An upper bound is derived for AUC based on an exact analytic expression for the homogeneous situation, and a lower bound based on the limit case Q(*), defined by the point where sensitivity equals specificity: Q(*) is invariant to heterogeneity. The standard error of AUC is derived for homogeneous studies, and shown to be a reasonable approximation with heterogeneous studies. The expressions for AUC and its standard error are easily computed in the homogeneous case, and avoid the need for numerical integration in the more general case. SE(AUC) and SE(Q(*)) are found to be numerically close, with SE(Q(*)) being larger if the odds ratio is very large. The methods are illustrated using data for the Pap smear screening test for cervical cancer, and for three tests for the diagnosis of metastases in cervical cancer patients.
机译:根据荟萃分析的数据,建议使用汇总接收机工作特性(SROC)曲线表示诊断测试的性能。但是,关于SROC曲线或其估计的基本属性知之甚少。在本文中,SROC曲线的位置通过整体诊断比值比和研究间异质性比值比来表征。曲线下的面积(AUC)和索引Q(*)被讨论为曲线的潜在有用摘要。结果表明,当研究优势比均质时,AUC最大化,并且对异质性非常鲁棒。基于对同类情况的精确解析表达式,可以得出AUC的上限,而根据灵敏度等于特异性的点(Q(*)对异质性不变)定义的极限情况Q(*)可以得出AUC的上限。 AUC的标准误差是针对均质研究得出的,对于异质研究显示是合理的近似值。在同构情况下,可以轻松计算AUC及其标准误差的表达式,而在更一般的情况下,无需进行数值积分。发现SE(AUC)和SE(Q(*))在数值上接近,如果优势比很大,则SE(Q(*))更大。使用宫颈癌的子宫颈抹片检查测试数据和宫颈癌患者转移诊断的三个测试数据说明了这些方法。

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