Addressing statistical issues when leveraging external control data in pediatric clinical trials using Bayesian dynamic borrowing
Conducting a well-powered and adequately controlled clinical trial in children is often challenging. Bayesian approaches are an attractive option for addressing such challenges as they provide a quantitatively rigorous and integrated framework that makes use of current control data to check and borrow information from historical control data. However various practical concerns and related statistical issues emerge when implementing such Bayesian borrowing approaches. In this manuscript we use a motivating case study to discuss a rigorous stepwise approach on how to address those issues within the Bayesian framework. Specifically, a comprehensive quantitative framework is proposed to assess the extent, synergy, and impact of borrowing. Steps on computing the measures to interpret borrowing are illustrated. Those measures can further help to determine whether additional discounting of external information is necessary.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:33 |
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| Enthalten in: |
Journal of biopharmaceutical statistics - 33(2023), 6 vom: 02. Nov., Seite 752-769 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Spanakis, Emmanouil [VerfasserIn] |
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| Links: |
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| Themen: |
Bayesian dynamic borrowing |
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| Anmerkungen: |
Date Completed 02.11.2023 Date Revised 14.11.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1080/10543406.2022.2152833 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Conducting a well-powered and adequately controlled clinical trial in children is often challenging. Bayesian approaches are an attractive option for addressing such challenges as they provide a quantitatively rigorous and integrated framework that makes use of current control data to check and borrow information from historical control data. However various practical concerns and related statistical issues emerge when implementing such Bayesian borrowing approaches. In this manuscript we use a motivating case study to discuss a rigorous stepwise approach on how to address those issues within the Bayesian framework. Specifically, a comprehensive quantitative framework is proposed to assess the extent, synergy, and impact of borrowing. Steps on computing the measures to interpret borrowing are illustrated. Those measures can further help to determine whether additional discounting of external information is necessary | ||
| 650 | 4 | |a Journal Article | |
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| 700 | 1 | |a Bereswill, Mareike |e verfasserin |4 aut | |
| 700 | 1 | |a Mukhopadhyay, Saurabh |e verfasserin |4 aut | |
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