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Modeling and simulations relating overall survival to tumor growth inhibition in renal cell carcinoma patients

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Abstract

Purpose

To assess the link between tumor growth inhibition (TGI) and overall survival (OS) based on historical renal cell carcinoma (RCC) data. To illustrate how simulations can help to identify TGI thresholds based on target OS benefit [i.e., hazard ratio (HR) compared with standard of care] to support new drug development in RCC.

Methods

Tumor size (TS) data were modeled from 2552 patients with first-line or refractory RCC who received temsirolimus, interferon, sunitinib, sorafenib or axitinib in 10 Phase II or Phase III studies. Three model-based TGI metrics estimates [early tumor shrinkage (ETS) at week 8, 10 or 12, time to tumor growth (TTG) and growth rate] as well as baseline prognostic factors were tested in multivariate lognormal models of OS. Model performance was evaluated by posterior predictive check of the OS distributions and hazard ratio across treatments.

Results

TTG was the best TGI metric to predict OS. However, week 8 ETS had a satisfactory performance and was employed in order to maximize clinical utilization. The week 8 ETS to OS model was then used to simulate clinically relevant ETS thresholds for future Phase II studies with investigational treatments.

Conclusions

The published OS model and resultant simulations can be leveraged to support Phase II design and predict expected OS and HR (based on early observed TGI data obtained in Phase II or Phase III studies), thereby informing important mRCC development decisions, e.g., Go/No Go and dose regimen selection.

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Acknowledgments

The authors thank one of the reviewers for helpful comments motivating additional analyses that improved the paper.

Author information

Author notes

  1. Francois Mercier

    Present address: Roche, pRED, Basel, Switzerland

Authors and Affiliations

  1. Pharsight Consulting Services, Pharsight, a Certara™ Company, 84 Chemin des Grives, 13013, Marseille, France

    Laurent Claret & Rene Bruno

  2. Pharsight Consulting Services, Pharsight, a Certara™ Company, Wintzenheim, France

    Francois Mercier

  3. Pfizer Global Clinical Pharmacology, La Jolla, CA, USA

    Brett E. Houk

  4. Pfizer Pharmacometrics, Global Clinical Pharmacology, Sandwich, UK

    Peter A. Milligan

Authors
  1. Laurent Claret
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  2. Francois Mercier
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  4. Peter A. Milligan
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  5. Rene Bruno
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Corresponding author

Correspondence to Rene Bruno.

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Research support

Pfizer Pharmacometrics.

Financial interest disclosures

LC, FM and RB were employees of Pharsight Consulting Services at the time this research was conducted and were paid contractors to Pfizer in connection with the study and the development of this manuscript. BH and PM are full-time employees of Pfizer and may hold stocks or stock options.

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Claret, L., Mercier, F., Houk, B.E. et al. Modeling and simulations relating overall survival to tumor growth inhibition in renal cell carcinoma patients. Cancer Chemother Pharmacol 76, 567–573 (2015). https://doi.org/10.1007/s00280-015-2820-x

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  • DOI: https://doi.org/10.1007/s00280-015-2820-x

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