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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
  • The University of Chicago
  • University of Pittsburgh
  • Pfizer
  • Merck

Research output: Contribution to journalArticlepeer-review

17 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
Pages (from-to)345-351
Number of pages7
JournalClinical Pharmacology and Therapeutics
Volume93
Issue number4
DOIs
StatePublished - Apr 2013

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