Analysis of patient derived xenograft studies in Oncology drug development: impact on design and interpretation of future studies

Abstract

BackgroundPreclinical Oncology drug development is heavily reliant on xenograft studies to assess the anti-tumour effect of new compounds. Patient derived xenograft (PDX) have become popular as they may better represent the clinical disease, however variability is greater than in cell-line derived xenografts. The typical approach of analysing these studies involves performing an un-paired t-test on the mean tumour volumes between the treated and control group at the end of the study. This approach ignores the time-series and may result in false conclusions, especially when considering the increased variability of PDX studies.\n\nAimTo test the hypothesis that a model-based analysis provides increased power than analysis of final day volumes and to provide insights into more efficient PDX study designs.\n\nMethodsData was extracted from tumour xenograft time-series data from a large publicly available PDX drug treatment database released by Novartis. For all 2-arm studies the percent tumour growth inhibition (TGI) at two time-points, day 10 and day 14 was calculated. For each study, the effect of treatment was calculated using an un-paired t-test and also a model-based analysis using the likelihood ratio-test. In addition a simulation study was also performed to assess the difference in power between the two data-analysis approaches for different levels of TGI for PDX or standard cell-line derived xenografts (CDX).\n\nResultsThe model-based analysis had greater statistical power than the un-paired t-test approach within the PDX data-set. The model-based approach was able to detect TGI values as low as 25 percent whereas the un-paired t-test approach required at least 50 percent TGI. These findings were confirmed within the simulation study performed which also highlighted that CDX studies require less animals than PDX studies which show the equivalent level of TGI.\n\nConclusionThe analysis of 59 2-arm PDX studies highlighted that taking a model-based approach gave increased statistical power over simply performing an un-paired t-test on the final study day. Importantly the model-based approach was able to detect smaller size of effect compared to the un-paired t-test approach is which maybe common of such studies. These findings were confirmed within simulated studies which also highlighted the same sample size used for CDX studies would lead to inadequately powered PDX studies. Application of a model-based analysis should allow studies to use less animals and run experiments for a shorter period thus providing effective insight into compound anti-tumour activity