% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{KoppSchneider:282347,
      author       = {A. Kopp-Schneider$^*$ and M. Wiesenfarth$^*$ and L. Held
                      and S. Calderazzo$^*$},
      title        = {{S}imulating and reporting frequentist operating
                      characteristics of clinical trials that borrow external
                      information: {T}owards a fair comparison in case of one-arm
                      and hybrid control two-arm trials.},
      journal      = {Pharmaceutical statistics},
      volume       = {23},
      number       = {1},
      issn         = {1539-1604},
      address      = {New York, NY},
      publisher    = {Wiley},
      reportid     = {DKFZ-2023-01731},
      pages        = {4-19},
      year         = {2024},
      note         = {#EA:C060#LA:C060# / 2024 Jan-Feb;23(1):4-19},
      abstract     = {Borrowing information from historical or external data to
                      inform inference in a current trial is an expanding field in
                      the era of precision medicine, where trials are often
                      performed in small patient cohorts for practical or ethical
                      reasons. Even though methods proposed for borrowing from
                      external data are mainly based on Bayesian approaches that
                      incorporate external information into the prior for the
                      current analysis, frequentist operating characteristics of
                      the analysis strategy are often of interest. In particular,
                      type I error rate and power at a prespecified point
                      alternative are the focus. We propose a procedure to
                      investigate and report the frequentist operating
                      characteristics in this context. The approach evaluates type
                      I error rate of the test with borrowing from external data
                      and calibrates the test without borrowing to this type I
                      error rate. On this basis, a fair comparison of power
                      between the test with and without borrowing is achieved. We
                      show that no power gains are possible in one-sided one-arm
                      and two-arm hybrid control trials with normal endpoint, a
                      finding proven in general before. We prove that in one-arm
                      fixed-borrowing situations, unconditional power (i.e., when
                      external data is random) is reduced. The Empirical Bayes
                      power prior approach that dynamically borrows information
                      according to the similarity of current and external data
                      avoids the exorbitant type I error inflation occurring with
                      fixed borrowing. In the hybrid control two-arm trial we
                      observe power reductions as compared to the test calibrated
                      to borrowing that increase when considering unconditional
                      power.},
      keywords     = {Bayesian dynamic borrowing of information (Other) /
                      external information (Other) / frequentist operating
                      characteristics (Other) / power gain (Other) / type I error
                      inflation (Other)},
      cin          = {C060},
      ddc          = {610},
      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:37632266},
      doi          = {10.1002/pst.2334},
      url          = {https://inrepo02.dkfz.de/record/282347},
}