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@ARTICLE{KoppSchneider:144259,
      author       = {A. Kopp-Schneider$^*$ and S. Calderazzo$^*$ and M.
                      Wiesenfarth$^*$},
      title        = {{P}ower gains by using external information in clinical
                      trials are typically not possible when requiring strict type
                      {I} error control.},
      journal      = {Biometrical journal},
      volume       = {62},
      number       = {2},
      issn         = {1521-4036},
      address      = {Berlin},
      publisher    = {Wiley-VCH},
      reportid     = {DKFZ-2019-01779},
      pages        = {361-374},
      year         = {2020},
      note         = {2020 Mar;62(2):361-374#EA:C060#LA:C060#},
      abstract     = {In the era of precision medicine, novel designs are
                      developed to deal with flexible clinical trials that
                      incorporate many treatment strategies for multiple diseases
                      in one trial setting. This situation often leads to small
                      sample sizes in disease-treatment combinations and has
                      fostered the discussion about the benefits of borrowing of
                      external or historical information for decision-making in
                      these trials. Several methods have been proposed that
                      dynamically discount the amount of information borrowed from
                      historical data based on the conformity between historical
                      and current data. Specifically, Bayesian methods have been
                      recommended and numerous investigations have been performed
                      to characterize the properties of the various borrowing
                      mechanisms with respect to the gain to be expected in the
                      trials. However, there is common understanding that the risk
                      of type I error inflation exists when information is
                      borrowed and many simulation studies are carried out to
                      quantify this effect. To add transparency to the debate, we
                      show that if prior information is conditioned upon and a
                      uniformly most powerful test exists, strict control of type
                      I error implies that no power gain is possible under any
                      mechanism of incorporation of prior information, including
                      dynamic borrowing. The basis of the argument is to consider
                      the test decision function as a function of the current data
                      even when external information is included. We exemplify
                      this finding in the case of a pediatric arm appended to an
                      adult trial and dichotomous outcome for various methods of
                      dynamic borrowing from adult information to the pediatric
                      arm. In conclusion, if use of relevant external data is
                      desired, the requirement of strict type I error control has
                      to be replaced by more appropriate metrics.},
      cin          = {C060},
      ddc          = {570},
      cid          = {I:(DE-He78)C060-20160331},
      pnm          = {313 - Cancer risk factors and prevention (POF3-313)},
      pid          = {G:(DE-HGF)POF3-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31265159},
      doi          = {10.1002/bimj.201800395},
      url          = {https://inrepo02.dkfz.de/record/144259},
}