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@ARTICLE{Hielscher:182607,
      author       = {T. Hielscher$^*$ and M. Sill$^*$ and P. Sievers$^*$ and D.
                      Stichel$^*$ and S. Brandner and D. Jones$^*$ and A. von
                      Deimling$^*$ and F. Sahm$^*$ and S. L. N. Maas},
      title        = {{C}linical implementation of integrated
                      molecular-morphologic risk prediction for meningioma.},
      journal      = {Brain pathology},
      volume       = {33},
      number       = {3},
      issn         = {1015-6305},
      address      = {Oxford},
      publisher    = {Wiley-Blackwell},
      reportid     = {DKFZ-2022-02788},
      pages        = {e13132},
      year         = {2023},
      note         = {#EA:C060#LA:B300# / 2023 May;33(3):e13132},
      abstract     = {Risk prediction for meningioma tumors was until recently
                      almost exclusively based on morphological features of the
                      tumor. To improve risk prediction, multiple models have been
                      established that incorporate morphological and molecular
                      features for an integrated risk prediction score. One such
                      model is the integrated molecular-morphologic meningioma
                      integrated score (IntS), which allocates points to the
                      histological grade, epigenetic methylation family and
                      specific copy-number variations. After publication of the
                      IntS, questions arose in the neuropathological community
                      about the practical and clinical implementation of the IntS,
                      specifically regarding the calling of CNVs, the
                      applicability of the newly available version (v12.5) of the
                      brain tumor classifier and the need for incorporation of
                      TERT-promoter and CDKN2A/B status analysis in the IntS
                      calculation. To investigate and validate these questions
                      additional analyses of the discovery (n = 514),
                      retrospective validation (n = 184) and prospective
                      validation (n = 287) cohorts used for IntS discovery and
                      validation were performed. Our findings suggest that any
                      loss over $5\%$ of the chromosomal arm suffices for the
                      calling of a CNV, that input from the v12.5 classifier is as
                      good or better than the dedicated meningioma classifier
                      (v2.4) and that there is most likely no need for additional
                      testing for TERT-promoter mutations and/or homozygous losses
                      of CDKN2A/B when defining the IntS for an individual
                      patient. The findings from this study help facilitate the
                      clinical implementation of IntS-based risk prediction for
                      meningioma patients.},
      keywords     = {brain tumors (Other) / meningioma (Other) / molecular
                      biomarkers (Other) / risk prediction (Other) / tumor
                      classification (Other)},
      cin          = {C060 / B062 / B300 / HD01 / B360},
      ddc          = {610},
      cid          = {I:(DE-He78)C060-20160331 / I:(DE-He78)B062-20160331 /
                      I:(DE-He78)B300-20160331 / I:(DE-He78)HD01-20160331 /
                      I:(DE-He78)B360-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:36377252},
      doi          = {10.1111/bpa.13132},
      url          = {https://inrepo02.dkfz.de/record/182607},
}