% 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{Ahrens:154458,
      author       = {W. Ahrens and K. H. Greiser$^*$ and J. Linseisen and T.
                      Pischon and I. Pigeot},
      title        = {[{T}he investigation of health outcomes in the {G}erman
                      {N}ational {C}ohort: the most relevant endpoints and their
                      assessment].},
      journal      = {Bundesgesundheitsblatt, Gesundheitsforschung,
                      Gesundheitsschutz},
      volume       = {63},
      number       = {4},
      issn         = {1437-1588},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {DKFZ-2020-00780},
      pages        = {376 - 384},
      year         = {2020},
      abstract     = {The focus of the German National Cohort, the largest
                      population-based cohort study in Germany to date, is the
                      investigation of the most important widespread diseases,
                      such as cardiovascular diseases, diabetes, cancer,
                      neurological and psychiatric disorders, and frequent
                      respiratory and infectious diseases. This cohort will answer
                      questions on the development of these diseases and on the
                      impact of genetic, environmental and lifestyle-related risk
                      factors. Another focus is on the identification of early,
                      subclinical markers of emerging diseases. To answer these
                      questions, a comprehensive assessment of these health
                      outcomes as well as of all potential determinants and
                      precursors is mandatory.This paper describes the various
                      health outcomes that are assessed in the German National
                      Cohort, as well as the examination modules that are applied
                      for deep phenotyping of study participants. Repeated
                      collection of biosamples as well as functional measurements
                      and application of modern imaging techniques at various time
                      points allow for assessing the dynamics of physiological
                      changes related to the individuals' health status. The
                      prognostic value of these changes for disease development
                      will be explored and translated to novel approaches for
                      prevention and personalised medicine. Incident diseases are
                      being assessed through self-reports by study participants
                      and through record linkage with data from health insurances
                      and cancer registries. Additional information about clinical
                      diagnoses is obtained from the treating physicians to ensure
                      the highest possible validity.},
      subtyp        = {Review Article},
      cin          = {C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331},
      pnm          = {313 - Cancer risk factors and prevention (POF3-313)},
      pid          = {G:(DE-HGF)POF3-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32157353},
      doi          = {10.1007/s00103-020-03111-0},
      url          = {https://inrepo02.dkfz.de/record/154458},
}