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Published in: Cancer Chemotherapy and Pharmacology 3/2016

01-09-2016 | Original Article

Model-based prediction of progression-free survival in patients with first-line renal cell carcinoma using week 8 tumor size change from baseline

Authors: Laurent Claret, Jenny Zheng, Francois Mercier, Pascal Chanu, Ying Chen, Brad Rosbrook, Pithavala Yazdi, Peter A. Milligan, Rene Bruno

Published in: Cancer Chemotherapy and Pharmacology | Issue 3/2016

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Abstract

Purpose

To assess the link between early tumor shrinkage (ETS) and progression-free survival (PFS) based on historical first-line metastatic renal cell carcinoma (mRCC) data.

Methods

Tumor size data from 921 patients with first-line mRCC who received interferon-alpha, sunitinib, sorafenib or axitinib in two Phase III studies were modeled. The relationship between model-based estimates of ETS at week 8 as well as the baseline prognostic factors and PFS was tested in multivariate log-logistic models. Model performance was evaluated using simulations of PFS distributions and hazard ratio (HR) across treatments for the two studies. In addition, an external validation was conducted using data from an independent Phase II RCC study. The relationship between expected HR of an investigational treatment vs. sunitinib and the differences in ETS was simulated.

Results

A model with a nonlinear ETS-PFS link was qualified to predict PFS distribution by ETS quartiles as well as to predict HRs of sunitinib vs. interferon-alpha and axitinib vs. sorafenib. The model also performed well in simulations of an independent study of axitinib (external validation). The simulations suggested that if a new investigational treatment could further reduce the week 8 ETS by 30 % compared with sunitinib, an expected HR [95 % predictive interval] of the new treatment vs. sunitinib would be 0.59 [0.46, 0.79].

Conclusion

A model has been developed that uses early changes in tumor size to predict the HR for PFS differences between treatment arms for first-line mRCC. Such a model may have utility in predicting the outcome of ongoing studies (e.g., as part of interim futility analyses), supporting early decision making and future study design for investigational agents in development for this indication.
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Metadata
Title
Model-based prediction of progression-free survival in patients with first-line renal cell carcinoma using week 8 tumor size change from baseline
Authors
Laurent Claret
Jenny Zheng
Francois Mercier
Pascal Chanu
Ying Chen
Brad Rosbrook
Pithavala Yazdi
Peter A. Milligan
Rene Bruno
Publication date
01-09-2016
Publisher
Springer Berlin Heidelberg
Published in
Cancer Chemotherapy and Pharmacology / Issue 3/2016
Print ISSN: 0344-5704
Electronic ISSN: 1432-0843
DOI
https://doi.org/10.1007/s00280-016-3116-5

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