% 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{Maier:275258,
      author       = {D. Maier$^*$ and J. J. Vehreschild and B. Uhl$^*$ and S.
                      Meyer$^*$ and K. Berger-Thürmel$^*$ and M. Börries$^*$ and
                      R. Braren$^*$ and V. Grünwald$^*$ and B. Hadaschik$^*$ and
                      S. Palm$^*$ and S. Singer$^*$ and M. Stuschke$^*$ and D.
                      Juárez$^*$ and P. Delpy$^*$ and M. Lambarki$^*$ and M.
                      Hummel$^*$ and C. Engels$^*$ and S. Andreas$^*$ and N.
                      Gökbuget$^*$ and K. Ihrig$^*$ and S. Burock$^*$ and D.
                      Keune$^*$ and A. Eggert$^*$ and U. Keilholz$^*$ and H.
                      Schulz$^*$ and D. Büttner and S. Löck$^*$ and M.
                      Krause$^*$ and M. Esins and F. Ressing and M. Schuler$^*$
                      and C. Brandts$^*$ and D. P. Brucker$^*$ and G. Husmann$^*$
                      and T. Oellerich$^*$ and P. Metzger and F. Voigt$^*$ and A.
                      L. Illert$^*$ and M. Theobald$^*$ and T. Kindler$^*$ and U.
                      Sudhof and A. Reckmann$^*$ and F. Schwinghammer$^*$ and D.
                      Nasseh$^*$ and W. Weichert$^*$ and M. von
                      Bergwelt-Baildon$^*$ and M. Bitzer$^*$ and N. Malek$^*$ and
                      Ö. Öner$^*$ and K. Schulze Osthoff$^*$ and S. Bartels and
                      J. Haier and R. Ammann and A. F. Schmidt and B. Guenther and
                      M. Janning$^*$ and B. Kasper and S. Loges$^*$ and S.
                      Stilgenbauer and P. Kuhn and E. Tausch and S. Runow and A.
                      Kerscher and M. Neumann and M. Breu and M. Lablans$^*$ and
                      H. Serve$^*$},
      title        = {{P}rofile of the multicenter cohort of the {G}erman
                      {C}ancer {C}onsortium's {C}linical {C}ommunication
                      {P}latform.},
      journal      = {European journal of epidemiology},
      volume       = {38},
      number       = {5},
      issn         = {0393-2990},
      address      = {Dordrecht [u.a.]},
      publisher    = {Springer Science + Business Media B.V.},
      reportid     = {DKFZ-2023-00705},
      pages        = {573-586},
      year         = {2023},
      note         = {2023 May;38(5):573-586},
      abstract     = {Treatment concepts in oncology are becoming increasingly
                      personalized and diverse. Successively, changes in standards
                      of care mandate continuous monitoring of patient pathways
                      and clinical outcomes based on large, representative
                      real-world data. The German Cancer Consortium's (DKTK)
                      Clinical Communication Platform (CCP) provides such
                      opportunity. Connecting fourteen university hospital-based
                      cancer centers, the CCP relies on a federated
                      IT-infrastructure sourcing data from facility-based cancer
                      registry units and biobanks. Federated analyses resulted in
                      a cohort of 600,915 patients, out of which 232,991 were
                      incident since 2013 and for which a comprehensive
                      documentation is available. Next to demographic data (i.e.,
                      age at diagnosis: $2.0\%$ 0-20 years, $8.3\%$ 21-40 years,
                      $30.9\%$ 41-60 years, $50.1\%$ 61-80 years, $8.8\%$ 81+
                      years; and gender: $45.2\%$ female, $54.7\%$ male, $0.1\%$
                      other) and diagnoses (five most frequent tumor origins:
                      22,523 prostate, 18,409 breast, 15,575 lung, 13,964
                      skin/malignant melanoma, 9005 brain), the cohort dataset
                      contains information about therapeutic interventions and
                      response assessments and is connected to 287,883 liquid and
                      tissue biosamples. Focusing on diagnoses and
                      therapy-sequences, showcase analyses of diagnosis-specific
                      sub-cohorts (pancreas, larynx, kidney, thyroid gland)
                      demonstrate the analytical opportunities offered by the
                      cohort's data. Due to its data granularity and size, the
                      cohort is a potential catalyst for translational cancer
                      research. It provides rapid access to comprehensive patient
                      groups and may improve the understanding of the clinical
                      course of various (even rare) malignancies. Therefore, the
                      cohort may serve as a decisions-making tool for clinical
                      trial design and contributes to the evaluation of scientific
                      findings under real-world conditions.},
      keywords     = {Cohort profile (Other) / Federated analysis (Other) /
                      German Cancer Consortium (Other) / Pan-cancer (Other) /
                      Real-world data (Other)},
      cin          = {FM01 / MU01 / FR01 / ED01 / E260 / HD01 / BE01 / DD01 /
                      TU01 / A420},
      ddc          = {610},
      cid          = {I:(DE-He78)FM01-20160331 / I:(DE-He78)MU01-20160331 /
                      I:(DE-He78)FR01-20160331 / I:(DE-He78)ED01-20160331 /
                      I:(DE-He78)E260-20160331 / I:(DE-He78)HD01-20160331 /
                      I:(DE-He78)BE01-20160331 / I:(DE-He78)DD01-20160331 /
                      I:(DE-He78)TU01-20160331 / I:(DE-He78)A420-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:37017830},
      doi          = {10.1007/s10654-023-00990-w},
      url          = {https://inrepo02.dkfz.de/record/275258},
}