Pre-clinical animal models are poor predictors of human toxicities in phase 1 oncology clinical trials

Johnique T. Atkins, Goldy C. George, Kenneth Hess, Kathrina L. Marcelo-Lewis, Ying Yuan, Gautam Borthakur, Sean Khozin, Patricia LoRusso, David S. Hong

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Background: Our objective was to determine the correlation between preclinical toxicity found in animal models (mouse, rat, dog and monkey) and clinical toxicity reported in patients participating in Phase 1 oncology clinical trials. Methods: We obtained from two major early-Phase clinical trial centres, preclinical toxicities from investigational brochures and clinical toxicities from published Phase 1 trials for 108 drugs, including small molecules, biologics and conjugates. Toxicities were categorised according to Common Terminology Criteria for Adverse Events version 4.0. Human toxicities were also categorised based on their reported clinical grade (severity). Positive predictive values (PPV) and negative predictive values (NPV) were calculated to determine the probability that clinical studies would/would not show a particular toxicity category given that it was seen in preclinical toxicology analysis. Statistical analyses also included kappa statistics, and Matthews (MCC) and Spearman correlation coefficients. Results: Overall, animal toxicity did not show strong correlation with human toxicity, with a median PPV of 0.65 and NPV of 0.50. Similar results were obtained based on kappa statistics and MCC. Conclusions: There is an urgent need to assess more novel approaches to the type and conduct of preclinical toxicity studies in an effort to provide better predictive value for human investigation.

Original languageEnglish (US)
Pages (from-to)1496-1501
Number of pages6
JournalBritish journal of cancer
Volume123
Issue number10
DOIs
StatePublished - Nov 10 2020

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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