4.6 Article

Estimation of Renal Cell Carcinoma Treatment Effects From Disease Progression Modeling

期刊

CLINICAL PHARMACOLOGY & THERAPEUTICS
卷 93, 期 4, 页码 345-351

出版社

WILEY
DOI: 10.1038/clpt.2012.263

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资金

  1. National Cancer Institute Mentored Career Development Award [K23CA124802]
  2. University of Chicago Cancer Research Center [P30-CA014599]
  3. Indiana Clinical and Translational Sciences Institute through Eli Lilly and Company [UL1RR025761-01]
  4. Merck through the Regenstrief Institute
  5. National Institute of Child Health and Human Development
  6. [T32GM007019]

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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 Ill trial of sorafenib in RCC. The best-fit model was externally evaluated on 145 placebo-treated patients in a phase Ill 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 alpha = 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.

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