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Sample size planning for phase II trials based on success probabilities for phase III

In recent years, high failure rates in phase III trials were observed. One of the main reasons is overoptimistic assumptions for the planning of phase III resulting from limited phase II information and/or unawareness of realistic success probabilities. We present an approach for planning a phase II...

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Main Authors: Götte, Heiko (Author) , Schüler, Armin (Author) , Kirchner, Marietta (Author) , Kieser, Meinhard (Author)
Format: Article (Journal)
Language:English
Published: 28 September 2015
In: Pharmaceutical statistics
Year: 2015, Volume: 14, Issue: 6, Pages: 515-524
ISSN:1539-1612
DOI:10.1002/pst.1717
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/pst.1717
Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/pst.1717
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Author Notes:Heiko Götte, Armin Schüler, Marietta Kirchner, and Meinhard Kieser

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520 |a In recent years, high failure rates in phase III trials were observed. One of the main reasons is overoptimistic assumptions for the planning of phase III resulting from limited phase II information and/or unawareness of realistic success probabilities. We present an approach for planning a phase II trial in a time-to-event setting that considers the whole phase II/III clinical development programme. We derive stopping boundaries after phase II that minimise the number of events under side conditions for the conditional probabilities of correct go/no-go decision after phase II as well as the conditional success probabilities for phase III. In addition, we give general recommendations for the choice of phase II sample size. Our simulations show that unconditional probabilities of go/no-go decision as well as the unconditional success probabilities for phase III are influenced by the number of events observed in phase II. However, choosing more than 150 events in phase II seems not necessary as the impact on these probabilities then becomes quite small. We recommend considering aspects like the number of compounds in phase II and the resources available when determining the sample size. The lower the number of compounds and the lower the resources are for phase III, the higher the investment for phase II should be. Copyright © 2015 John Wiley & Sons, Ltd. 
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