Department of Cardiology, Division of Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA,
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Chemotherapy. 2018;63(6):324-329. doi: 10.1159/000495147. Epub 2019 Mar 7.
Cardiac ultrasound provides important structural and functional information that makes identification of cardiac abnormalities possible. Left ventricular ejection fraction (LVEF) provides the most commonly used parameter for recognition of treatment-related cardiac dysfunction. Random reading variance and physiologic factors influence LVEF and make the reported value imperfect. We attempt to quantitate the likelihood of false positive events by computer simulation.
We simulated four visits on hypothetical trials. We assumed a baseline LVEF of 55% and normal distribution with regard to reading error and physiologic variation. 1,000 trials of sample size 1,500 were simulated. In a separate simulation, 1,000 patients entered with LVEFs of 45, 43, and 41% to estimate true positive incidence.
At each examination, less than 1.0% of false positives were noted. The cumulative false positive rate over four visits was 3.60%. True cardiotoxicity identification is satisfactory only when LVEF declines substantially.
A 3.60% false positive rate in trials where the expected level of toxicity is low suggests that false positives are troubling and may exceed true positive results. Strategies to reduce the number of false positive results include making confirmatory studies mandatory. Evaluating increases along with decreases obtains some estimation of variance.
心脏超声提供了重要的结构和功能信息，使得心脏异常的识别成为可能。左心室射血分数（LVEF）提供了最常用的参数，用于识别与治疗相关的心脏功能障碍。随机读数的差异和生理因素会影响 LVEF，并使报告的值不完美。我们试图通过计算机模拟来量化假阳性事件的可能性。
我们在假设的试验中模拟了四次就诊。我们假设基线 LVEF 为 55%，并且在读取误差和生理变化方面呈正态分布。模拟了样本量为 1500 的 1000 次试验。在另一个模拟中，有 1000 名患者以 45%、43%和 41%的 LVEF 进入，以估计真正的阳性发生率。
每次检查时，假阳性的比例不到 1.0%。四次就诊的累积假阳性率为 3.60%。只有当 LVEF 显著下降时，才能准确识别心脏毒性。
在毒性预期水平较低的试验中，假阳性率为 3.60%，这表明假阳性令人困扰，可能超过真正的阳性结果。减少假阳性结果数量的策略包括强制进行确认性研究。评估增加和减少可以获得一些方差的估计。
