Literature DB >> 11180028

Clinical trial simulation of docetaxel in patients with cancer as a tool for dosage optimization.

C Veyrat-Follet1, R Bruno, R Olivares, G R Rhodes, P Chaikin.   

Abstract

BACKGROUND: Pharmacokinetic and pharmacodynamic analyses conducted during the development of docetaxel showed that patients with non-small-cell lung cancer with high baseline alpha1-acid glycoprotein levels had shorter time to progression and time to death. To assess whether such patients might benefit from dose intensification, we initiated a series of clinical trial simulations.
METHODS: Pharmacokinetic and pharmacodynamic models for time to progression, death, and drop-out were developed and validated with the use of phase II data from 151 patients with non-small-cell lung cancer. The simulation process, in which these models were combined with a previously reported model for safety, was evaluated by comparison of the original phase II data with the predicted results. Simulations were undertaken for the evaluation of whether a trial (phase III) of 125 mg/m2 of docetaxel versus 100 mg/m2 of docetaxel in patients with high alpha1-acid glycoprotein levels would show improved survival.
RESULTS: The hazard models showed that lower alpha1-acid glycoprotein levels, fewer number of organs involved, and higher docetaxel cumulative area under plasma concentration-time curve were significantly associated with enhanced time to progression and time to death. The simulation process produced data patterns similar to actual patterns. In the simulated phase III trial, although median survival was slightly longer in the 125 mg/m2 docetaxel group than in the 100 mg/m2 group (5.49 months versus 5.31 months, respectively), the difference was significant in only 6 of 100 trials.
CONCLUSIONS: The low power to detect a difference due to dose intensification was the basis for the decision not to perform such a trial. The simulation exercise yielded valuable insight into how pharmacokinetic- and pharmacodynamic-based simulation of clinical trials may have an impact on decision making in drug development.

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Year:  2000        PMID: 11180028     DOI: 10.1067/mcp.2000.111948

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


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