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Model free audit methodology for bias evaluation of tumour progression in oncology

机译:用于评估肿瘤学中肿瘤进展的免费模型审计方法

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摘要

Many oncology studies incorporate a blinded independent central review (BICR) to make an assessment of the integrity of the primary endpoint, progression free survival. Recently, it has been suggested that, in order to assess the potential for bias amongst investigators, a BICR amongst only a sample of patients could be performed; if evidence of bias is detected, according to a predefined threshold, the BICR is then assessed in all patients, otherwise, it is concluded that the sample was sufficient to rule out meaningful levels of bias. In this paper, we present an approach that adapts a method originally created for defining futility bounds in group sequential designs. The hazard ratio ratio, the ratio of the hazard ratio (HR) for the treatment effect estimated from the BICR to the corresponding HR for the investigator assessments, is used as the metric to define bias. The approach is simple to implement and ensures a high probability that a substantial true bias will be detected. In the absence of bias, there is a high probability of accepting the accuracy of local evaluations based on the sample, in which case an expensive BICR of all patients is avoided. The properties of the approach are demonstrated by retrospective application to a completed Phase III trial in colorectal cancer. The same approach could easily be adapted for other disease settings, and for test statistics other than the hazard ratio. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译:许多肿瘤学研究都采用了独立的双盲中央评价(BICR),以评估主要终点,无进展生存期的完整性。最近,有人建议,为了评估研究者之间可能存在的偏见,只能在患者样本中进行BICR。如果检测到偏倚的证据,则根据预定义的阈值,对所有患者进行BICR评估,否则,得出结论,样本足以排除有意义的偏倚水平。在本文中,我们提出了一种方法,该方法适用于最初创建的用于在组顺序设计中定义无效边界的方法。危险比,即从BICR估计的治疗效果的危险比(HR)与研究者评估的相应HR的比,用作定义偏差的度量。该方法易于实施,并确保了检测到真实偏差的可能性很高。在没有偏差的情况下,很有可能接受基于样本的局部评估的准确性,在这种情况下,可以避免所有患者的BICR昂贵。通过回顾性应用到已完成的大肠癌III期试验中,证明了该方法的特性。相同的方法可以很容易地适用于其他疾病背景,以及危险比以外的测试统计数据。版权所有(c)2015 John Wiley&Sons,Ltd.

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