PDXpower: A Power Analysis Tool for Experimental Design in Pre-clinical Xenograft Studies for Uncensored and Censored Outcomes
arxiv(2024)
摘要
In cancer research, leveraging patient-derived xenografts (PDXs) in
pre-clinical experiments is a crucial approach for assessing innovative
therapeutic strategies. Addressing the inherent variability in treatment
response among and within individual PDX lines is essential. However, the
current literature lacks a user-friendly statistical power analysis tool
capable of concurrently determining the required number of PDX lines and
animals per line per treatment group in this context. In this paper, we present
a simulation-based R package for sample size determination, named
`PDXpower', which is publicly available at The Comprehensive R Archive
Network . The package is
designed to estimate the necessary number of both PDX lines and animals per
line per treatment group for the design of a PDX experiment, whether for an
uncensored outcome, or a censored time-to-event outcome. Our sample size
considerations rely on two widely used analytical frameworks: the mixed effects
ANOVA model for uncensored outcomes and Cox's frailty model for censored data
outcomes, which effectively account for both inter-PDX variability and
intra-PDX correlation in treatment response. Step-by-step illustrations for
utilizing the developed package are provided, catering to scenarios with or
without preliminary data.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要