Properties of the Projected Length of the Curve (PLC) and Area Swept out by the Curve (ASC) Indices for the Receiver Operating Characteristic (SROC) Curve

IF 1.2 4区 数学 International Journal of Biostatistics Pub Date : 1900-01-01 DOI:10.2202/1557-4679.1096
Xuan Zhang, S. Walter, R. Agnihotram
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Abstract

Several measures have been proposed to summarize the Receiver Operating Characteristic (ROC) curve, including the Projected Length of the Curve (PLC) and the Area Swept out by the Curve (ASC). These indices were first proposed by Lee (Epidemiology 1996; 7:605-611) to avoid certain deficiencies of the traditional Area Under the Curve (AUC) summary measure. More recently meta-analysis methods for assessing diagnostic test accuracy have been developed and the Summary Receiver Operating Characteristic (SROC) curve has been recommended to represent the performance of a diagnostic test. Some properties of the SROC curve were discussed by Walter (Statist. Med. 2002; 21:1237-1256). Here we extend that work to focus on properties of PLC and ASC in the context of SROC curve. Mathematical expressions for these two indices and their variances are derived in terms of the overall diagnostic odds ratio and the magnitude of inter-study heterogeneity in the odds ratio. Expressions for PLC and ASC and their variances are easily computed in homogeneous studies, and their values provide good approximations to the corresponding values for heterogeneous studies in most practical situations. General variances of PLC and ASC are derived by using delta methods, and are found to be smaller if the odds ratio is large. The methods are illustrated using data from two studies, the first being a meta-analysis on the detection of metastases in cervical cancer patients, and the second being a single study of HPV infection and pre-invasive cervical lesions.
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曲线的投影长度(PLC)和被曲线扫过的面积(ASC)的性质。接收者工作特性(SROC)曲线的指标
提出了几种方法来总结受试者工作特征(ROC)曲线,包括曲线的投影长度(PLC)和曲线扫过的面积(ASC)。这些指标最早由Lee (Epidemiology 1996;7:605-611),以避免传统的曲线下面积(AUC)汇总测量的某些缺陷。最近,用于评估诊断测试准确性的荟萃分析方法得到了发展,并推荐了总接受者工作特征(SROC)曲线来表示诊断测试的性能。Walter (Statist)讨论了SROC曲线的一些性质。医学。2002;21:1237 - 1256)。在这里,我们将这项工作扩展到关注PLC和ASC在SROC曲线背景下的特性。这两个指标及其方差的数学表达式是根据总体诊断优势比和优势比中研究间异质性的大小推导出来的。PLC和ASC的表达式及其方差很容易在同质研究中计算出来,在大多数实际情况下,它们的值很好地近似于异质研究的相应值。PLC和ASC的一般方差是通过使用delta方法推导出来的,如果比值比较大,则发现方差较小。这些方法是用两项研究的数据来说明的,第一个是关于宫颈癌患者转移检测的荟萃分析,第二个是关于HPV感染和侵袭前宫颈病变的单一研究。
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来源期刊
International Journal of Biostatistics
International Journal of Biostatistics Mathematics-Statistics and Probability
CiteScore
2.30
自引率
8.30%
发文量
28
期刊介绍: The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.
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