Estimation of renal cell carcinoma treatment effects from disease progression modeling

Clin Pharmacol Ther. 2013 Apr;93(4):345-51. doi: 10.1038/clpt.2012.263. Epub 2012 Dec 27.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Antineoplastic Agents / therapeutic use
  • Carcinoma, Renal Cell / drug therapy*
  • Clinical Trials, Phase II as Topic / statistics & numerical data
  • Clinical Trials, Phase III as Topic / statistics & numerical data*
  • Disease Progression*
  • Kidney Neoplasms / drug therapy*
  • Models, Statistical*
  • Niacinamide / analogs & derivatives*
  • Niacinamide / therapeutic use
  • Phenylurea Compounds / therapeutic use*
  • Sorafenib


  • Antineoplastic Agents
  • Phenylurea Compounds
  • Niacinamide
  • Sorafenib