| 저자(한글) |
Patrick M.M. Bossuyt,Johannes B. Reitsma,,Kristian Linnet,Karel G.M. Moons,Department of Clinical Epidemiology, Biostatistic and Bioinformatics, Academic Medical Center,Julius Center for Health Scienc |
| 초록 |
Like any other medical technology or intervention, diagnostic tests should be thoroughly evaluated before their introduction into daily practice. Increasingly,decision makers, physicians, and other users of diagnostic tests request more than simple measures of a test’s analytical or technical performance and diagnostic accuracy; they would also like to see testing lead to health benefits. In this last article of our series, we introduce the notion of clinical utility, which expresses—preferably in a quantitative form—to what extent diagnostic testing improves health outcomes relative to the current best alternative, which could be some other form of testing or no testing at all. In most cases, diagnostic tests improve patient outcomes by providing information that can be used to identify patients who will benefit from helpful downstream management actions, such as effective treatment in individuals with positive test results and no treatment for those with negative results. We describe how comparative randomized clinical trials can be used to estimate clinical utility. We contrast the definition of clinical utility with that of the personal utility of tests and markers. We show how diagnostic accuracy can be linked to clinical utility through an appropriate definition of the target condition in diagnosticaccuracy studies. |
