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@ARTICLE{Pllen:147733,
      author       = {L. Püllen and J. P. Radtke$^*$ and M. Wiesenfarth$^*$ and
                      M. J. Roobol and J. F. M. Verbeek and A. Wetter and N.
                      Guberina and A. Pandey and C. Hüttenbrink and S.
                      Tschirdewahn and S. Pahernik and B. A. Hadaschik and F. A.
                      Distler},
      title        = {{E}xternal validation of novel {MRI}-based models for
                      prostate cancer prediction.},
      journal      = {BJU international},
      volume       = {125},
      number       = {3},
      issn         = {1464-4096},
      address      = {Oxford},
      publisher    = {Wiley-Blackwell39962},
      reportid     = {DKFZ-2019-02710},
      pages        = {407-416},
      year         = {2020},
      note         = {2020 Mar;125(3):407-416},
      abstract     = {To validate three novel risk models (RM) combining mpMRI
                      and clinical parameters to predict significant prostate
                      cancer (sPC) through an external cohort, including the
                      recently updated European Randomised Study of Screening for
                      PC (ERSPC) risk-calculator.We retrospectively analyzed 307
                      men who underwent mpMRI prior to transperineal ultrasound
                      fusion biopsy between 10/2015 and 07/2018 at two German
                      centers. mpMRI was rated by PI-RADSv2.0 and sPC was defined
                      as ISUP Gleason grade group ≥2.The prediction performance
                      of the three models (MRI-ERSPC-3/4, RM by Radtke et al. and
                      RM by Distler et al.) were compared using ROC-curve-analyses
                      with area under the curve (AUC), calibration curve analyses
                      and decision curves to assess net-benefit.ROC-AUCs of the
                      three novel models (MRI-ERSPC-3/4; Radtke's RM and Distler's
                      RM were 0.82; 0.85 and 0.83, respectively). Calibration
                      curve analyses showed the best intercept for MRI-ERSPC-3 and
                      -4 of 0.35 and 0.76. Net benefit analyses indicated clear
                      benefit of MRI-ERSPC-3/4-RM compared to the other two
                      validated models. The MRI-ERSPC-RC-3/4 demonstrated a
                      discrimination benefit for a risk threshold of up to $15\%$
                      for sPC as compared to the other RMs.In our external
                      validation of three novel prostate cancer risk calculators,
                      which include mpMRI-findings in their models, head-to-head
                      comparison of these models indicated that especially
                      MRI-ERSPC-3/4 can help to reduce unnecessary biopsies.},
      cin          = {E010 / C060},
      ddc          = {610},
      cid          = {I:(DE-He78)E010-20160331 / I:(DE-He78)C060-20160331},
      pnm          = {319H - Addenda (POF3-319H)},
      pid          = {G:(DE-HGF)POF3-319H},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31758738},
      doi          = {10.1111/bju.14958},
      url          = {https://inrepo02.dkfz.de/record/147733},
}