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: urn:nbn:de:0183-09gmds1193

Veröffentlicht: 2. September 2009

© 2009 Friede et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen ( Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.



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.


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