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Extension of a conditional performance score for sample size recalculation rules to the setting of binary endpoints.
Bokelmann, Björn; Rauch, Geraldine; Meis, Jan; Kieser, Meinhard; Herrmann, Carolin.
Afiliação
  • Bokelmann B; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Biometry and Clinical Epidemiology, Charitéplatz 1, Berlin, 10117, Germany. bjoern.bokelmann@charite.de.
  • Rauch G; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Biometry and Clinical Epidemiology, Charitéplatz 1, Berlin, 10117, Germany.
  • Meis J; Technische Universität Berlin, Straße des 17. Juni 135, 10623, Berlin, Germany.
  • Kieser M; Institute of Medical Biometry, University Medical Center Ruprechts-Karls University Heidelberg, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany.
  • Herrmann C; Institute of Medical Biometry, University Medical Center Ruprechts-Karls University Heidelberg, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany.
BMC Med Res Methodol ; 24(1): 15, 2024 Jan 19.
Article em En | MEDLINE | ID: mdl-38243169
ABSTRACT

BACKGROUND:

Sample size calculation is a central aspect in planning of clinical trials. The sample size is calculated based on parameter assumptions, like the treatment effect and the endpoint's variance. A fundamental problem of this approach is that the true distribution parameters are not known before the trial. Hence, sample size calculation always contains a certain degree of uncertainty, leading to the risk of underpowering or oversizing a trial. One way to cope with this uncertainty are adaptive designs. Adaptive designs allow to adjust the sample size during an interim analysis. There is a large number of such recalculation rules to choose from. To guide the choice of a suitable adaptive design with sample size recalculation, previous literature suggests a conditional performance score for studies with a normally distributed endpoint. However, binary endpoints are also frequently applied in clinical trials and the application of the conditional performance score to binary endpoints is not yet investigated.

METHODS:

We extend the theory of the conditional performance score to binary endpoints by suggesting a related one-dimensional score parametrization. We moreover perform a simulation study to evaluate the operational characteristics and to illustrate application.

RESULTS:

We find that the score definition can be extended without modification to the case of binary endpoints. We represent the score results by a single distribution parameter, and therefore derive a single effect measure, which contains the difference in proportions [Formula see text] between the intervention and the control group, as well as the endpoint proportion [Formula see text] in the control group.

CONCLUSIONS:

This research extends the theory of the conditional performance score to binary endpoints and demonstrates its application in practice.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Projetos de Pesquisa Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article