A simulation-based sample size calculation method for pre-clinical tumor xenograft experiments

Abstract

ABSTRACTPre-clinical tumor xenograft experiments usually require a small sample size that is rarely greater than 20, and data generated from such experiments very often do not have censored observations. Many statistical tests can be used for analyzing such data, but most of them were developed based on large sample approximation. We demonstrate that the type-I error rates of these tests can substantially deviate from the designated rate, especially when the data to be analyzed has a skewed distribution. Consequently, the sample size calculated based on these tests can be erroneous. We propose a modified signed log-likelihood ratio test (MSLRT) to meet the type-I error rate requirement for analyzing pre-clinical tumor xenograft data. The MSLRT has a consistent and symmetric type-I error rate that is very close to the designated rate for a wide range of sample sizes. By simulation, we generated a series of sample size tables based on scenarios commonly expected in tumor xenograft experiments, and we expect that these tables can be used as guidelines for making decisions on the numbers of mice used in tumor xenograft experiments.