Tan Ming, Fang Hong-Bin, Tian Guo-Liang, Houghton Peter J
Division of Biostatistics, University of Maryland Greenebaum Cancer Center, 22 South Greene Street, Baltimore, MD 21201, USA.
Stat Med. 2005 Jan 15;24(1):109-19. doi: 10.1002/sim.1775.
In cancer drug development, xenograft experiments (models) where mice are grafted with human cancer cells are used to elucidate the mechanism of action and/or to assess efficacy of a promising compound. Demonstrated activity in this model is an important step to bring a promising compound to humans. A key outcome variable in these experiments is tumour volumes measured over a period of time, while mice are treated with an anticancer agent following certain schedules. However, a mouse may die during the experiment or may be sacrificed when its tumour volume quadruples and then incomplete repeated measurements arise. The incompleteness or missingness is also caused by drastic tumour shrinkage (<0.01 cm3) or random truncation. In addition, if no treatment were given to the tumour-bearing mice, the tumours would keep growing until the mice die or are sacrificed. This intrinsic growth of tumour in the absence of treatment constrains the parameters in the regression and causes further difficulties in statistical analysis. We develop a maximum likelihood method based on the expectation/conditional maximization (ECM) algorithm to estimate the dose-response relationship while accounting for the informative censoring and the constraints of model parameters. A real xenograft study on a new anti-tumour agent temozolomide combined with irinotecan is analysed using the proposed method.
在癌症药物研发中，将人类癌细胞移植到小鼠体内的异种移植实验（模型）被用于阐明作用机制和/或评估一种有前景的化合物的疗效。在该模型中证明的活性是将一种有前景的化合物应用于人体的重要一步。这些实验中的一个关键结果变量是在一段时间内测量的肿瘤体积，在此期间小鼠按照特定方案接受抗癌药物治疗。然而，小鼠可能在实验过程中死亡，或者当肿瘤体积增大四倍时可能被处死，从而导致重复测量不完整。不完整或缺失也可能由肿瘤急剧缩小（<0.01 cm³）或随机截断引起。此外，如果不给荷瘤小鼠进行治疗，肿瘤会持续生长直至小鼠死亡或被处死。在无治疗情况下肿瘤的这种内在生长限制了回归中的参数，并给统计分析带来了进一步困难。我们基于期望/条件最大化（ECM）算法开发了一种最大似然方法，以估计剂量反应关系，同时考虑信息删失和模型参数的约束。使用所提出的方法对一项关于新型抗肿瘤药物替莫唑胺联合伊立替康的真实异种移植研究进行了分析。
