Accounting for dropout in xenografted tumour efficacy studies: integrated endpoint analysis, reduced bias and better use of animals.
Accounting for dropout in xenografted tumour efficacy studies: integrated endpoint analysis, reduced bias and better use of animals.
复制标题
考虑到异种移植肿瘤功效研究的辍学：综合终点分析，偏见减少和更好地使用动物。
DOI：
10.1007/s00280-016-3059-x
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发表时间：
2016-07
影响因子：
3
通讯作者：
Yates JW
中科院分区：
文献类型：
--
作者：
Martin EC;Aarons L;Yates JW
异种移植研究通常用于评估新化合物的功效并表征其剂量反应关系。分析通常涉及比较不同剂量组的最终肿瘤大小。这可能会导致偏差，因为在异种移植研究中，出于伦理原因通常会施加肿瘤负荷限制（TBL），导致肿瘤最大的动物被排除在最终分析之外。这意味着平均肿瘤大小，特别是对照组的平均肿瘤大小被低估，导致治疗效果被低估。提出了四种解释 TBL 导致的丢失的方法，这些方法使用所有可用数据而不仅仅是最终观察结果：建模、模式混合模型、使用 M3 方法将丢失视为审查以及肿瘤生长和丢失的联合建模。这些方法适用于模拟数据集和真实示例。所有四种提出的方法都改善了模拟数据中治疗效果的估计。联合建模方法表现最强，审查方法也提供了治疗效果的良好估计，但不确定性较高。在真实数据示例中，使用审查和联合建模方法估计的剂量反应高于根据平均最终测量估计的非常平坦的曲线。使用所提出的审查或联合建模方法来考虑退出，可以在研究中恢复治疗效果，因为治疗效果可能由于 TBL 引起的退出而被掩盖。本文的在线版本 (doi:10.1007/s00280-016-3059-x) 包含补充材料，可供授权用户使用。
Xenograft studies are commonly used to assess the efficacy of new compounds and characterise their dose–response relationship. Analysis often involves comparing the final tumour sizes across dose groups. This can cause bias, as often in xenograft studies a tumour burden limit (TBL) is imposed for ethical reasons, leading to the animals with the largest tumours being excluded from the final analysis. This means the average tumour size, particularly in the control group, is underestimated, leading to an underestimate of the treatment effect. Four methods to account for dropout due to the TBL are proposed, which use all the available data instead of only final observations: modelling, pattern mixture models, treating dropouts as censored using the M3 method and joint modelling of tumour growth and dropout. The methods were applied to both a simulated data set and a real example. All four proposed methods led to an improvement in the estimate of treatment effect in the simulated data. The joint modelling method performed most strongly, with the censoring method also providing a good estimate of the treatment effect, but with higher uncertainty. In the real data example, the dose–response estimated using the censoring and joint modelling methods was higher than the very flat curve estimated from average final measurements. Accounting for dropout using the proposed censoring or joint modelling methods allows the treatment effect to be recovered in studies where it may have been obscured due to dropout caused by the TBL. The online version of this article (doi:10.1007/s00280-016-3059-x) contains supplementary material, which is available to authorized users.