Zheng Yingye, Barlow William E, Cutter Gary
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue, North Seattle, Washington 98109, USA.
Biometrics. 2005 Mar;61(1):259-68. doi: 10.1111/j.0006-341X.2005.031139.x.
The performance of a medical diagnostic test is often evaluated by comparing the outcome of the test to the patient's true disease state. Receiver operating characteristic analysis may then be used to summarize test accuracy. However, such analysis may encounter several complications in actual practice. One complication is verification bias, i.e., gold standard assessment of disease status may only be partially available and the probability of ascertainment of disease may depend on both the test result and characteristics of the subject. A second issue is that tests interpreted by the same rater may not be independent. Using estimating equations, we generalize previous methods that address these problems. We contrast the performance of alternative estimators of accuracy using robust sandwich variance estimators to permit valid asymptotic inference. We suggest that in the context of an observational cohort study where rich covariate information is available, a weighted estimating equations approach may be preferable for its robustness against model misspecification. We apply the methodology to mammography as performed by community radiologists.
医学诊断测试的性能通常通过将测试结果与患者的真实疾病状态进行比较来评估。然后可以使用接受者操作特征分析来总结测试准确性。然而，这种分析在实际操作中可能会遇到几个复杂问题。一个复杂问题是验证偏倚，即疾病状态的金标准评估可能仅部分可用，并且疾病确诊的概率可能取决于测试结果和受试者的特征。第二个问题是由同一评估者解释的测试可能不独立。我们使用估计方程，推广了以前解决这些问题的方法。我们使用稳健的三明治方差估计器来对比准确性的替代估计器的性能，以允许进行有效的渐近推断。我们建议，在可获得丰富协变量信息的观察性队列研究背景下，加权估计方程方法可能因其对模型误设的稳健性而更可取。我们将该方法应用于社区放射科医生进行的乳腺X线摄影。
