Assessing Antitumor Activity in Preclinical Tumor Xenograft Model Tumor Xenograft Model Tumor xenograft models Challenges
Robison, Barbara, Contributing Writer has reference to this Academic Journal, PHwiki organized this Journal Assessing Antitumor Activity in Preclinical Tumor Xenograft Model Department of Biostatistics St. Jude Childrens Research Hospital John(Jianrong) Wu Tumor Xenograft Model Tumor xenograft models Subcutaneous tumor model: tumor xenograft is implanted under the skin in addition to typically located on the flank of the mouse. Orthotopic tumor model: tumor xenograft is either implanted into the equivalent organ from which the cancer originated, or where metastatsese are found in patients.
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D456-cisplatin tumor xenograft model Challenges A relative small number of mice (10/per group) were tested. Missing data issue: due to mice die of toxicity or be sacrificed when tumors grow to certain size. Skewed distribution of tumor volume data Various of tumor growth patterns.
Tumor Growth Inhibition (T/C ratio) time Relative Tumor volume t Skewed tumor volume data Demidenko, 2010
Anti-tumor activity Drawback of separate analysis of tumor volume at each time point Multiple tests at different time points inflate type I error. Excluding animals with missing observation is inefficient in addition to could result a biased conclusion. T-test may be not valid due to skewed distribution of tumor volume data. Separate analysis at each time point ignores the intra-subject correlation. Using an arbitrary cut-off point to assess antitumor activity in addition to without any as long as mal statistical inference Statistical inference as long as tumor volume data Inference T/C ratio in addition to its 95% confidence interval Hothorn (2006), Wu (2009, 2010), Cheng in addition to Wu (2010) Multivariate analysis Tan et al (2002) MANOVA Heitjian et al (1995) Nonparametric multivariate analysis Koziol et al (1981)
Tumor Growth Delay (T-C) 4 Relative Tumor volume time Tumor Growth Delay Tumor doubling in addition to quadrupling time 4
Tumor quadrupling time Kaplan-Meier Event-free Survival Distributions (p<0.0001) Example: D456-cisplatin tumor xenograft model The medians of tumor quadrupling times are 8.7 (days) in addition to 24.9 (days) as long as control in addition to treatment, respectively. TGD=16.2 days with st in addition to ard error of 1.9 days The 95% confidence bootstrap percentile interval of TGD is (10.8, 21.2). Wu J, Confidence intervals as long as the difference of median failure times applied to censored tumor growth delay data, Statistics in Biopharmaceutical Research, 3:488-496, 2011 Log10 cell kill (LCK) Log10 cell kill is defined as the negative log10 fraction of tumor cells surviving (SF). We illustrate its quantification with assumptions (a) control tumor growth follows an exponential growth curve (b) treated tumor regrowth after treament approximates untreated controls, then LCK = - log10(SF) = (T C)/(3.32 DT) where DT is tumor doubling time of control. or -log(SF)=Tumor Growth Delay Rate of Growth Demidenko, 2010 Log10 cell kill Anti-tumor activity SAS macro Macro %long: trans as long as m the tumor volume data to be a longitudinal as long as m Macro %day2event: calculate tumor doubling in addition to quadrupling times. Macro %lck: calculate tumor growth delay (T-C) in addition to log10 cell kill.
References as long as T/C ratio Heitjan DF, Manni A, Santen RJ. Statistical analysis of in vivo tumor growth experiments. Cancer Research 1993;53:60426050 Houghton PJ, Morton CL, et al. (2007). The pediatric preclinical testing program: Description of models in addition to early testing results. Pediatr. Blood Cancer 49:928940. Hothorn L (2006). Statistical analysis of in vivo anticancer experiments: Tumor growth inhibition. Drug In as long as m. J. 40:229238. Wu J (2010), Statistical Inference as long as Tumor Growth Inhibition T/C Ratio, JBS, 20:954-964 Wu J in addition to Houghton PJ (2009), Interval approach to assessing antitumor activity as long as tumor xenograft studies, Pharmaceutical Statistics, 9:46-54. Tan, M., Fang, H. B., Tian, G. L., Houghton, P. J. (2002). Small-sample inference as long as incomplete longitudinal data with truncation in addition to censoring in tumor xenograft models. Biometrics 58:612620. Koziol et al. (1981). A distribution-free test as long as tumor-growth curve analyses with application to an animal tumor immunotherapy experiment. Biometrics, 37:383-390 References as long as TGD Wu J, Confidence intervals as long as the difference of median failure times applied to censored tumor growth delay data, Statistics in Biopharmaceutical Research, 3:488-496, 2011. Wu J, Assessment of antitumor activity as long as tumor xenograft studies using exponential growth models. Journal of Biopharmaceutical Statistics, 21:472-483, May, 2011. Demidenko E (2010), Three endpoints of in vivo tumor radiobiology in addition to their statistical estimation. 86:164-173. Corbett, T. H., White, K., Polin, L., Kushner, J., Paluch, J., Shih, C., Grossman, C. S. (2003).Discovery in addition to preclinical antitumor efficacy evaluations of LY32262 in addition to LY33169.Investigational New Drugs 21:3345. References as long as LCK Demidenko E (2010), Three endpoints of in vivo tumor radiology in addition to their statistical estimation, Int J Radial Biol. 86:164-173 Lloyd H (1975), Estimation of tumor cell kill from Gompertz growth curves, Cancer Chemother Rep, 59:267-277. Corbett TH et al (2003), Discovery in addition to preclinical antitumor efficacy evaluations of LY32262 in addition to LY33169. Invest New Drugs 21:33-45. Wu J (2011), Assessment of antitumor activity as long as tumor xenograft studies using exponential growth models, JBS, 1:472-483 Wu J in addition to Houghton PJ (2009), Assessing cytotoxic treatment effects in preclinical tumor xenograft models, JBS,19:755-762
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