Estimation of renal cell carcinoma treatment effects from disease progression modeling

M. L. Maitland, K. Wu, M. R. Sharma, Y. Jin, S. P. Kang, W. M. Stadler, T. G. Karrison, M. J. Ratain, R. R. Bies

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

To improve future drug development efficiency in renal cell carcinoma (RCC), a disease-progression model was developed with longitudinal tumor size data from a phase III trial of sorafenib in RCC. The best-fit model was externally evaluated on 145 placebo-treated patients in a phase III trial of pazopanib; the model incorporated baseline tumor size, a linear disease-progression component, and an exponential drug effect (DE) parameter. With the model-estimated effect of sorafenib on RCC growth, we calculated the power of randomized phase II trials between sorafenib and hypothetical comparators over a range of effects. A hypothetical comparator with 80% greater DE than sorafenib would have 82% power (one-sided α = 0.1) with 50 patients per arm. Model-based quantitation of treatment effect with computed tomography (CT) imaging offers a scaffold on which to develop new, more efficient, phase II trial end points and analytic strategies for RCC.

Original languageEnglish (US)
Pages (from-to)345-351
Number of pages7
JournalClinical Pharmacology and Therapeutics
Volume93
Issue number4
DOIs
StatePublished - Apr 2013

ASJC Scopus subject areas

  • Pharmacology
  • Pharmacology (medical)

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  • Cite this

    Maitland, M. L., Wu, K., Sharma, M. R., Jin, Y., Kang, S. P., Stadler, W. M., Karrison, T. G., Ratain, M. J., & Bies, R. R. (2013). Estimation of renal cell carcinoma treatment effects from disease progression modeling. Clinical Pharmacology and Therapeutics, 93(4), 345-351. https://doi.org/10.1038/clpt.2012.263