Differences in Performance of Bayesian Dynamic Borrowing and Synthetic Control Methods: A Case Study of Pediatric Atopic Dermatitis
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| Main Authors: | , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866918315808522240 |
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| author | Cizauskas, Nicole Strimenopoulou, Foteini Cherlin, Svetlana S. Wason, James M. S. |
| author_facet | Cizauskas, Nicole Strimenopoulou, Foteini Cherlin, Svetlana S. Wason, James M. S. |
| contents | Bayesian dynamic borrowing (BDB) and synthetic control methods (SCM) are both used in clinical trial design when recruitment, retention, or allocation is a challenge. The performance of these approaches has not previously been directly compared due to differences in application, product, and measurement metrics. This study aims to conduct a comparison of power and type 1 error rates of BDB (using meta-analytic predictive prior (MAP)) and SCM using a case study of Pediatric Atopic Dermatitis. Six historical randomised control trials were selected for use in both the creation of the MAP prior and synthetic control arm. The R library RBesT was used to create a MAP prior and the R library Synthpop was used to create a synthetic control arm for the SCM. Power and type 1 error rate were used as comparison metrics. BDB produced a power of 0.580 and a type 1 error rate of 0.026. SCM produced a power of 0.641 and a type 1 error rate of 0.027. In this case study, the SCM model produced a higher power than the BDB method with a similar type 1 error rate. However, the decision to use SCM or BDB should come from the specific needs of the potential trial, since their power and type 1 error rate may differ on a case-by-case basis. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2601_23021 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Differences in Performance of Bayesian Dynamic Borrowing and Synthetic Control Methods: A Case Study of Pediatric Atopic Dermatitis Cizauskas, Nicole Strimenopoulou, Foteini Cherlin, Svetlana S. Wason, James M. S. Methodology Bayesian dynamic borrowing (BDB) and synthetic control methods (SCM) are both used in clinical trial design when recruitment, retention, or allocation is a challenge. The performance of these approaches has not previously been directly compared due to differences in application, product, and measurement metrics. This study aims to conduct a comparison of power and type 1 error rates of BDB (using meta-analytic predictive prior (MAP)) and SCM using a case study of Pediatric Atopic Dermatitis. Six historical randomised control trials were selected for use in both the creation of the MAP prior and synthetic control arm. The R library RBesT was used to create a MAP prior and the R library Synthpop was used to create a synthetic control arm for the SCM. Power and type 1 error rate were used as comparison metrics. BDB produced a power of 0.580 and a type 1 error rate of 0.026. SCM produced a power of 0.641 and a type 1 error rate of 0.027. In this case study, the SCM model produced a higher power than the BDB method with a similar type 1 error rate. However, the decision to use SCM or BDB should come from the specific needs of the potential trial, since their power and type 1 error rate may differ on a case-by-case basis. |
| title | Differences in Performance of Bayesian Dynamic Borrowing and Synthetic Control Methods: A Case Study of Pediatric Atopic Dermatitis |
| topic | Methodology |
| url | https://arxiv.org/abs/2601.23021 |