Direkt zum Inhalt

Owner only: item control page
Jackson, Holly ; Jaki, Thomas

An Alternative to Traditional Sample Size Determination for Small Patient Populations

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

Date of publication of this fulltext: 25 Sep 2025 12:15
Article
DOI to cite this document: 10.5283/epub.77839


Abstract

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.



Involved Institutions


Details

Item typeArticle
Journal or Publication TitleStatistics in Biopharmaceutical Research
Publisher:Taylor & Francis Online
Open Access Type:CC-License
Volume:15
Number of Issue or Book Chapter:3
Page Range:pp. 596-607
Date21 September 2022
InstitutionsInformatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki)
Identification Number
ValueType
10.1080/19466315.2022.2107565DOI
KeywordsContinuous response, Patient benefit, Rare disease, Sequential design
Dewey Decimal Classification000 Computer science, information & general works > 004 Computer science
StatusPublished
RefereedYes, this version has been refereed
Created at the University of RegensburgPartially
URN of the UB Regensburgurn:nbn:de:bvb:355-epub-778398
Item ID77839

Export bibliographical data

Owner only: item control page

nach oben