Robust modeling in screening studies: estimation of sensitivity and preclinical sojourn time distribution
Robust modeling in screening studies: estimation of sensitivity and preclinical sojourn time distribution
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DOI：
10.1093/biostatistics/kxi030
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发表时间：
2005-10-01
期刊：
影响因子：
2.1
通讯作者：
Zelen, M
中科院分区：
文献类型：
--
作者：
Shen, Y;Zelen, M
在早期检测临床试验中，诸如筛查方式的灵敏度和疾病的临床前持续时间等数量对于描述疾病的自然史及其与筛查程序的相互作用是重要的。假设筛选程序的时间表是周期性的，并且在临床前状态中的逗留时间具有分段密度函数。将临床前逗留时间分布建模为分段密度函数导致分布函数的稳健估计。我们的目标是估计分段密度函数和检查的灵敏度，使用广义最小二乘法和最大似然方法。我们进行了广泛的模拟，以评估的估计方法的性能。不同的估计方法提供了互补的工具来获得未知参数。该方法适用于三个乳腺癌早期检测试验。
In early-detection clinical trials, quantities such as the sensitivity of the screening modality and the preclinical duration of the disease are important to describe the natural history of the disease and its interaction with a screening program. Assume that the schedule of a screening program is periodic and that the sojourn time in the preclinical state has a piecewise density function. Modeling the preclinical sojourn time distribution as a piecewise density function results in robust estimation of the distribution function. Our aim is to estimate the piecewise density function and the examination sensitivity using both generalized least squares and maximum likelihood methods. We carried out extensive simulations to evaluate the performance of the methods of estimation. The different estimation methods provide complimentary tools to obtain the unknown parameters. The methods are applied to three breast cancer early-detection trials.