Assessing cytotoxic treatment effects in preclinical tumor xenograft models

Jianrong Wu, Peter J. Houghton

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In preclinical solid tumor xenograft experiments, tumor response to cytotoxic agents is often assessed by tumor cell kill. Log10 cell kill (LCK) is commonly used to quantify the tumor cell kill in such experiments. For comparisons of antitumor activity between tumor lines, the LCK values are converted to an arbitrary rating; for example, the treatment effect is considered significant if the LCK>0.7 (Corbett et al., 2003). The drawback of using such a predefined cutoff point is that it does not account for the true variation of the experiments. In this article, a nonparametric bootstrap percentile interval of the LCK is proposed. The cytotoxic treatment effect can be assessed by the confidence limits of the LCK. Monte Carlo simulations are conducted to study the coverage probabilities of the proposed interval for small samples. Tumor xenograft data from a real experiment are analyzed to illustrate the proposed method.

Original languageEnglish
Pages (from-to)755-762
Number of pages8
JournalJournal of Biopharmaceutical Statistics
Volume19
Issue number5
DOIs
StatePublished - Sep 2009

Bibliographical note

Funding Information:
The authors are thankful to the editor and anonymous referees whose careful reading and constructive comments improved the earlier version of this article. The work was supported in part by National Cancer Institute (NCI) support grants CA21765 and N01-CM-42216 and the American Lebanese Syrian Associated Charities (ALSAC).

Keywords

  • Bootstrap
  • Confidence interval
  • Log10 cell kill
  • Right censoring
  • Xenograft

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)

Fingerprint

Dive into the research topics of 'Assessing cytotoxic treatment effects in preclinical tumor xenograft models'. Together they form a unique fingerprint.

Cite this