gms | German Medical Science

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

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

07. bis 10.09.2009, Essen

Blinded sample size reestimation with count data: Methods and applications in multiple sclerosis

Meeting Abstract

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  • Tim Friede - University of Warwick, Coventry
  • Heinz Schmidli - Novartis Pharma AG, Basel

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 54. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds). Essen, 07.-10.09.2009. Düsseldorf: German Medical Science GMS Publishing House; 2009. Doc09gmds119

doi: 10.3205/09gmds119, urn:nbn:de:0183-09gmds1193

Published: September 2, 2009

© 2009 Friede et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.


Outline

Text

Sample size estimation in clinical trials depends critically on nuisance parameters such as variances or overall event rates, which have to be guessed or estimated from previous studies in the planning phase of a trial. Blinded sample size reestimation estimates these nuisance parameters based on blinded data from the ongoing trial, and allows to adjust the sample size based on the acquired information [1]. In the present paper, this methodology is developed for clinical trials with count data as the primary endpoint. In multiple sclerosis such endpoints are commonly used in phase 2 trials (lesion counts in magnetic resonance imaging (MRI)) and phase 3 trials (relapse counts) [2]. Sample size adjustment formulas are presented for both Poisson distributed data and for overdispersed Poisson distributed data. The latter arise from sometimes considerable between-patient heterogeneity, which can be observed in particular in MRI lesion counts [3]. The operation characteristics of the procedure are evaluated by simulations. The results suggest that blinded sample size reestimation for count data allows to maintain the required power without an increase in the type I error rate.


References

1.
Friede T, Kieser M. Sample size recalculation in internal pilot study designs: A review. Biometrical Journal. 2006;48:537–55.
2.
Committee for Medicinal Products for Human Use (CHMP). Guideline on clinical investiagation of medicinal products for the treatment of multiple sclerosis. London; 2005.
3.
van den Elskamp IJ, Knol DL, Uitdehaag BMJ, Barkhof F. The distribution of new enhancing lesion counts in multiple sclerosis: further explorations. Multiple Sclerosis. 2009;15:42–9. DOI: 10.1177/1352458508096683 External link