Pepe M S, Alonzo T A
University of Washington, Department of Biostatistics, Box 357232, Seattle, WA 98195-7232, USA.
Biostatistics. 2001 Sep;2(3):249-60. doi: 10.1093/biostatistics/2.3.249.
Disease screening is a fundamental part of health care. To evaluate the accuracy of a new screening modality, ideally the results of the screening test are compared with those of a definitive diagnostic test in a set of study subjects. However, definitive diagnostic tests are often invasive and cannot be applied to subjects whose screening tests are negative for disease. For example, in cancer screening, the assessment of true disease status requires a biopsy sample, which for ethical reasons can only be obtained if a subject's screening test indicates presence of cancer. Although the absolute accuracy of screening tests cannot be evaluated in such circumstances, it is possible to compare the accuracies of screening tests. Specifically, using relative true positive rate (the ratio of the true positive rate of one test to another) and relative false positive rate (the ratio of the false positive rates of two tests) as measures of relative accuracy, we show that inference about relative accuracy can be made from such studies. Analogies with case-control studies can be drawn where inference about absolute risk cannot be made, but inference about relative risk can. In this paper, we develop a marginal regression analysis framework for making inference about relative accuracy when only screen positives are followed for true disease. In this context factors influencing the relative accuracies of tests can be evaluated. It is important to determine such factors in order to understand circumstances in which one test is preferable to another. The methods are applied to two cancer screening studies, one concerning the effect of race on screening for prostate cancer and the other concerning the effect of tumour grade on the detection of cervical cancer with cytology versus cervicography screening.
疾病筛查是医疗保健的基本组成部分。为了评估一种新的筛查方式的准确性，理想情况下，在一组研究对象中，将筛查测试的结果与确定性诊断测试的结果进行比较。然而，确定性诊断测试往往具有侵入性，不能应用于筛查测试疾病呈阴性的对象。例如，在癌症筛查中，评估真正的疾病状态需要活检样本，出于伦理原因，只有在受试者的筛查测试表明存在癌症时才能获取活检样本。尽管在这种情况下无法评估筛查测试的绝对准确性，但可以比较筛查测试的准确性。具体而言，使用相对真阳性率（一种测试的真阳性率与另一种测试的真阳性率之比）和相对假阳性率（两种测试的假阳性率之比）作为相对准确性的度量，我们表明可以从这类研究中得出关于相对准确性的推断。这类似于病例对照研究，在病例对照研究中无法得出关于绝对风险的推断，但可以得出关于相对风险的推断。在本文中，我们开发了一个边际回归分析框架，用于在仅对筛查呈阳性者追踪真正疾病时对相对准确性进行推断。在此背景下，可以评估影响测试相对准确性的因素。确定这些因素很重要，以便了解在哪种情况下一种测试比另一种测试更可取。这些方法应用于两项癌症筛查研究，一项涉及种族对前列腺癌筛查的影响，另一项涉及肿瘤分级对细胞学与宫颈造影筛查检测宫颈癌的影响。
