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@ARTICLE{Calderazzo:286009,
author = {S. Calderazzo$^*$ and M. Wiesenfarth$^*$ and A.
Kopp-Schneider$^*$},
title = {{R}obust incorporation of historical information with known
type {I} error rate inflation.},
journal = {Biometrical journal},
volume = {66},
number = {1},
issn = {0323-3847},
address = {Berlin},
publisher = {Wiley-VCH},
reportid = {DKFZ-2023-02586},
pages = {e2200322},
year = {2024},
note = {#EA:C060#LA:C060# / 2024 Jan;66(1):e2200322},
abstract = {Bayesian clinical trials can benefit from available
historical information through the specification of
informative prior distributions. Concerns are however often
raised about the potential for prior-data conflict and the
impact of Bayes test decisions on frequentist operating
characteristics, with particular attention being assigned to
inflation of type I error (TIE) rates. This motivates the
development of principled borrowing mechanisms, that strike
a balance between frequentist and Bayesian decisions.
Ideally, the trust assigned to historical information
defines the degree of robustness to prior-data conflict one
is willing to sacrifice. However, such relationship is often
not directly available when explicitly considering inflation
of TIE rates. We build on available literature relating
frequentist and Bayesian test decisions, and investigate a
rationale for inflation of TIE rate which explicitly and
linearly relates the amount of borrowing and the amount of
TIE rate inflation in one-arm studies. A novel dynamic
borrowing mechanism tailored to hypothesis testing is
additionally proposed. We show that, while dynamic borrowing
prevents the possibility to obtain a simple closed-form TIE
rate computation, an explicit upper bound can still be
enforced. Connections with the robust mixture prior
approach, particularly in relation to the choice of the
mixture weight and robust component, are made. Simulations
are performed to show the properties of the approach for
normal and binomial outcomes, and an exemplary application
is demonstrated in a case study.},
keywords = {Bayesian trial design (Other) / borrowing of historical
information (Other) / robust borrowing (Other) / type I
error rate (Other)},
cin = {C060},
ddc = {570},
cid = {I:(DE-He78)C060-20160331},
pnm = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
pid = {G:(DE-HGF)POF4-313},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:38063813},
doi = {10.1002/bimj.202200322},
url = {https://inrepo02.dkfz.de/record/286009},
}