gms | German Medical Science

64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

08. - 11.09.2019, Dortmund

Possibilities to improve sample size recalculation rules

Meeting Abstract

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  • Carolin Herrmann - Charité - Universitätsmedizin Berlin, Berlin, Germany
  • Maximilian Pilz - Institut für Medizinische Biometrie und Informatik, Universitätsklinikum Heidelberg, Heidelberg, Germany
  • Meinhard Kieser - Universität Heidelberg, Heidelberg, Germany
  • Geraldine Rauch - Charité Universitätsmedizin Berlin, Berlin, Germany

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 64. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Dortmund, 08.-11.09.2019. Düsseldorf: German Medical Science GMS Publishing House; 2019. DocAbstr. 142

doi: 10.3205/19gmds003, urn:nbn:de:0183-19gmds0032

Published: September 6, 2019

© 2019 Herrmann et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at http://creativecommons.org/licenses/by/4.0/.


Outline

Text

Introduction: Adaptive group sequential study designs can overcome planning uncertainties regarding parameter estimations for sample size calculations. At interim analyses, the underlying effect size is tested for significance and the trial is either stopped or continued. In the latter case, the sample size can be adapted. A variety of such sample size recalculation rules exists (e.g. [1], [2]). However, general points of criticism are a high variability in sample size or that the target power is not met (e.g. [3], [4]).

Methods: For a possible performance improvement, we discuss several innovative elements: First, we consider continuity correction methods to reduce the impact of steps in the recalculation function. Second, resampling arguments are explored to address the underlying randomness of the interim result. We simulated different sample size recalculation scenarios for a two-stage adaptive group sequential study design and a normally distributed outcome, and evaluated them by a conditional performance score in terms of sample size and conditional power.

Results: Depending on the underlying parameters, several considered scenarios show a relevant performance improvement. The proposed methods are easy to apply and can be combined with established recalculation scenarios.

Discussion: We present new elements to potentially improve the performance of established sample size recalculation rules in adaptive group sequential two-stage designs.

The work is supported by the German Research Foundation (grant RA 234714-1).

The authors declare that an ethics committee vote is not required.


References

1.
Mehta C, Pocock S. Adaptive increase in sample size when interim results are promising: A practical guide with examples. Statistics in Medicine. 2010;30(28):3267-3284.
2.
Jennison C, Turnbull B. Adaptive sample size modification in clinical trials: start small then ask for more? Statistics in Medicine. 2015;34(29):3793-3810.
3.
Bauer P, Kohne K. Evaluation of Experiments with Adaptive Interim Analyses. Biometrics. 1994;50(4):1029.
4.
Levin G, Emerson S, Emerson S. Adaptive clinical trial designs with pre-specified rules for modifying the sample size: understanding efficient types of adaptation. Statistics in Medicine. 2012;32(8):1259-1275.