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Jackson, Holly ; Jaki, Thomas

An Alternative to Traditional Sample Size Determination for Small Patient Populations

Jackson, Holly und Jaki, Thomas (2022) An Alternative to Traditional Sample Size Determination for Small Patient Populations. Statistics in Biopharmaceutical Research 15 (3), S. 596-607.

Veröffentlichungsdatum dieses Volltextes: 25 Sep 2025 12:15
Artikel
DOI zum Zitieren dieses Dokuments: 10.5283/epub.77839


Zusammenfassung

The majority of phase III clinical trials use a 2-arm randomized controlled trial with 50% allocation between the control treatment and experimental treatment. The sample size calculated for these clinical trials normally guarantee a power of at least 80% for a certain Type I error, usually 5%. However, these sample size calculations, do not typically take into account the total patient ...

The majority of phase III clinical trials use a 2-arm randomized controlled trial with 50% allocation between the control treatment and experimental treatment. The sample size calculated for these clinical trials normally guarantee a power of at least 80% for a certain Type I error, usually 5%. However, these sample size calculations, do not typically take into account the total patient population that may benefit from the treatment investigated. In this article, we discuss two methods, which optimize the sample size of phase III clinical trial designs, to maximize the benefit to patients for the total patient population. We do this for trials that use a continuous endpoint, when the total patient population is small (i.e., for rare diseases). One approach uses a point estimate for the treatment effect to optimize the sample size and the second uses a distribution on the treatment effect in order to account for the uncertainty in the estimated treatment effect. Both one-stage and two-stage clinical trials, using three different stopping boundaries are investigated and compared, using efficacy and ethical measures. A completed clinical trial in patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is used to demonstrate the use of the method. Supplementary materials for this article are available online.



Beteiligte Einrichtungen


Details

DokumentenartArtikel
Titel eines Journals oder einer ZeitschriftStatistics in Biopharmaceutical Research
Verlag:Taylor & Francis Online
Band:15
Nummer des Zeitschriftenheftes oder des Kapitels:3
Seitenbereich:S. 596-607
Datum21 September 2022
InstitutionenInformatik und Data Science > Fachbereich Maschinelles Lernen und Data Science > Chair for Computational Statistics (Prof. Dr. Thomas Jaki)
Identifikationsnummer
WertTyp
10.1080/19466315.2022.2107565DOI
Stichwörter / KeywordsContinuous response, Patient benefit, Rare disease, Sequential design
Dewey-Dezimal-Klassifikation000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik
StatusVeröffentlicht
BegutachtetJa, diese Version wurde begutachtet
An der Universität Regensburg entstandenZum Teil
URN der UB Regensburgurn:nbn:de:bvb:355-epub-778398
Dokumenten-ID77839

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