@article{GroebnerWorstWeischenfeldtetal.2018,
  author    = {Gr{\"o}bner, Susanne N. and Worst, Barbara C. and Weischenfeldt, Joachim and Buchhalter, Ivo and Kleinheinz, Kortine and Rudneva, Vasilisa A. and Johann, Pascal D. and Balasubramanian, Gnana Prakash and Segura-Wang, Maia and Brabetz, Sebastian and Bender, Sebastian and Hutter, Barbara and Sturm, Dominik and Pfaff, Elke and H{\"u}bschmann, Daniel and Zipprich, Gideon and Heinold, Michael and Eils, J{\"u}rgen and Lawerenz, Christian and Erkek, Serap and Lambo, Sander and Waszak, Sebastian and Blattmann, Claudia and Borkhardt, Arndt and Kuhlen, Michaela and Eggert, Angelika and Fulda, Simone and Gessler, Manfred and Wegert, Jenny and Kappler, Roland and Baumhoer, Daniel and Stefan, Burdach and Kirschner-Schwabe, Renate and Kontny, Udo and Kulozik, Andreas E. and Lohmann, Dietmar and Hettmer, Simone and Eckert, Cornelia and Bielack, Stefan and Nathrath, Michaela and Niemeyer, Charlotte and Richter, G{\"u}nther H. and Schulte, Johannes and Siebert, Reiner and Westermann, Frank and Molenaar, Jan J. and Vassal, Gilles and Witt, Hendrik and Burkhardt, Birgit and Kratz, Christian P. and Witt, Olaf and van Tilburg, Cornelis M. and Kramm, Christof M. and Fleischhack, Gudrun and Dirksen, Uta and Rutkowski, Stefan and Fr{\"u}hwald, Michael and Hoff, Katja von and Wolf, Stephan and Klingebeil, Thomas and Koscielniak, Ewa and Landgraf, Pablo and Koster, Jan and Resnick, Adam C. and Zhang, Jinghui and Liu, Yanling and Zhou, Xin and Waanders, Angela J. and Zwijnenburg, Danny A. and Raman, Pichai and Brors, Benedikt and Weber, Ursula D. and Northcott, Paul A. and Pajtler, Kristian W. and Kool, Marcel and Piro, Rosario M. and Korbel, Jan O. and Schlesner, Matthias and Eils, Roland and Jones, David T. W. and Lichter, Peter and Chavez, Lukas and Zapatka, Marc and Pfister, Stefan M.},
  title     = {The landscape of genomic alterations across childhood cancers},
  series = {Nature},
  volume    = {555},
  journal   = {Nature},
  organization    = {ICGC PedBrain-Seq Project, ICGC MMML-Seq Project,},
  doi       = {10.1038/nature25480},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229579},
  pages     = {321-327},
  year      = {2018},
  abstract  = {Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adolescents, and young adults, comprising 24 distinct molecular types of cancer. Using a standardized workflow, we identified marked differences in terms of mutation frequency and significantly mutated genes in comparison to previously analysed adult cancers. Genetic alterations in 149 putative cancer driver genes separate the tumours into two classes: small mutation and structural/copy-number variant (correlating with germline variants). Structural variants, hyperdiploidy, and chromothripsis are linked to TP53 mutation status and mutational signatures. Our data suggest that 7-8\% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50\% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.},
  language  = {en}
}
@article{SommerAmrBavendieketal.2022,
  author    = {Sommer, Kim K. and Amr, Ali and Bavendiek, Udo and Beierle, Felix and Brunecker, Peter and Dathe, Henning and Eils, J{\"u}rgen and Ertl, Maximilian and Fette, Georg and Gietzelt, Matthias and Heidecker, Bettina and Hellenkamp, Kristian and Heuschmann, Peter and Hoos, Jennifer D. E. and Keszty{\"u}s, Tibor and Kerwagen, Fabian and Kindermann, Aljoscha and Krefting, Dagmar and Landmesser, Ulf and Marschollek, Michael and Meder, Benjamin and Merzweiler, Angela and Prasser, Fabian and Pryss, R{\"u}diger and Richter, Jendrik and Schneider, Philipp and St{\"o}rk, Stefan and Dieterich, Christoph},
  title     = {Structured, harmonized, and interoperable integration of clinical routine data to compute heart failure risk scores},
  series = {Life},
  volume    = {12},
  journal   = {Life},
  number    = {5},
  issn      = {2075-1729},
  doi       = {10.3390/life12050749},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-275239},
  year      = {2022},
  abstract  = {Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format. In this work, we demonstrate the feasibility of a multi-site solution to derive and calculate two exemplary HF scores from clinical routine data (MAGGIC score with six continuous and eight categorical variables; Barcelona Bio-HF score with five continuous and six categorical variables). Within HiGHmed, a German Medical Informatics Initiative consortium, we implemented an interoperable solution, collecting a harmonized HF-phenotypic core data set (CDS) within the openEHR framework. Our approach minimizes the need for manual data entry by automatically retrieving data from primary systems. We show, across five participating medical centers, that the implemented structures to execute dedicated data queries, followed by harmonized data processing and score calculation, work well in practice. In summary, we demonstrated the feasibility of clinical routine data usage across multiple partner sites to compute HF risk scores. This solution can be extended to a large spectrum of applications in clinical care.},
  language  = {en}
}