| Veröffentlichte Version Download ( PDF | 2MB) | Lizenz: Creative Commons Namensnennung 4.0 International |
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.
Alternative Links zum Volltext
Beteiligte Einrichtungen
Details
| Dokumentenart | Artikel | ||||
| Titel eines Journals oder einer Zeitschrift | Statistics in Biopharmaceutical Research | ||||
| Verlag: | Taylor & Francis Online | ||||
|---|---|---|---|---|---|
| Band: | 15 | ||||
| Nummer des Zeitschriftenheftes oder des Kapitels: | 3 | ||||
| Seitenbereich: | S. 596-607 | ||||
| Datum | 21 September 2022 | ||||
| Institutionen | Informatik und Data Science > Fachbereich Maschinelles Lernen und Data Science > Chair for Computational Statistics (Prof. Dr. Thomas Jaki) | ||||
| Identifikationsnummer |
| ||||
| Stichwörter / Keywords | Continuous response, Patient benefit, Rare disease, Sequential design | ||||
| Dewey-Dezimal-Klassifikation | 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik | ||||
| Status | Veröffentlicht | ||||
| Begutachtet | Ja, diese Version wurde begutachtet | ||||
| An der Universität Regensburg entstanden | Zum Teil | ||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-778398 | ||||
| Dokumenten-ID | 77839 |
Downloadstatistik
Downloadstatistik