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异种移植动物肿瘤生长抑制模型中参数估计的改进:处理牺牲删失以及较大肿瘤尺寸实验测量所引起的误差

Improvement of Parameter Estimations in Tumor Growth Inhibition Models on Xenografted Animals: Handling Sacrifice Censoring and Error Caused by Experimental Measurement on Larger Tumor Sizes.

作者信息

Pierrillas Philippe B, Tod Michel, Amiel Magali, Chenel Marylore, Henin Emilie

机构信息

EMR 3738, Ciblage Thérapeutique en Oncologie, Faculté de Médecine et de Maïeutique Lyon-Sud Charles Mérieux, Université Claude Bernard Lyon 1, 165 chemin du Grand Revoyet-BP 12, 69921, Oullins Cedex, France.

Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France.

出版信息

AAPS J. 2016 Sep;18(5):1262-1272. doi: 10.1208/s12248-016-9936-8. Epub 2016 Jun 21.

Abstract

The purpose of this study was to explore the impact of censoring due to animal sacrifice on parameter estimates and tumor volume calculated from two diameters in larger tumors during tumor growth experiments in preclinical studies. The type of measurement error that can be expected was also investigated. Different scenarios were challenged using the stochastic simulation and estimation process. One thousand datasets were simulated under the design of a typical tumor growth study in xenografted mice, and then, eight approaches were used for parameter estimation with the simulated datasets. The distribution of estimates and simulation-based diagnostics were computed for comparison. The different approaches were robust regarding the choice of residual error and gave equivalent results. However, by not considering missing data induced by sacrificing the animal, parameter estimates were biased and led to false inferences in terms of compound potency; the threshold concentration for tumor eradication when ignoring censoring was 581 ng.ml(-1), but the true value was 240 ng.ml(-1).

摘要

本研究的目的是探讨在临床前研究的肿瘤生长实验中,因动物处牺牲而进行的数据删失对参数估计以及根据较大肿瘤的两个直径计算出的肿瘤体积的影响。同时还研究了可能出现的测量误差类型。通过随机模拟和估计过程对不同场景进行了验证。在异种移植小鼠典型肿瘤生长研究的设计下模拟了1000个数据集,然后使用八种方法对模拟数据集进行参数估计。计算估计值的分布和基于模拟的诊断结果以进行比较。不同方法在残差误差选择方面具有稳健性且给出了等效结果。然而,由于未考虑因牺牲动物而导致的缺失数据,参数估计存在偏差,并在化合物效力方面导致错误推断;忽略删失时肿瘤根除的阈值浓度为581 ng.ml(-1),但真实值为240 ng.ml(-1)。

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