@article{GrabenhenrichReichFischeretal.2014,
  author    = {Grabenhenrich, Linus B. and Reich, Andreas and Fischer, Felix and Zepp, Fred and Forster, Johannes and Schuster, Antje and Bauer, Carl-Peter and Bergmann, Renate L. and Bergmann, Karl E. and Wahn, Ulrich and Keil, Thomas and Lau, Susanne},
  title     = {The Novel 10-Item Asthma Prediction Tool: External Validation in the German MAS Birth Cohort},
  series = {PLOS ONE},
  volume    = {9},
  journal   = {PLOS ONE},
  number    = {12},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0115852},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-114202},
  pages     = {e115852},
  year      = {2014},
  abstract  = {Background: A novel non-invasive asthma prediction tool from the Leicester Cohort, UK, forecasts asthma at age 8 years based on 10 predictors assessed in early childhood, including current respiratory symptoms, eczema, and parental history of asthma. Objective: We aimed to externally validate the proposed asthma prediction method in a German birth cohort. Methods: The MAS-90 study (Multicentre Allergy Study) recorded details on allergic diseases prospectively in about yearly follow-up assessments up to age 20 years in a cohort of 1,314 children born 1990. We replicated the scoring method from the Leicester cohort and assessed prediction, performance and discrimination. The primary outcome was defined as the combination of parent-reported wheeze and asthma drugs (both in last 12 months) at age 8. Sensitivity analyses assessed model performance for outcomes related to asthma up to age 20 years. Results: For 140 children parents reported current wheeze or cough at age 3 years. Score distribution and frequencies of later asthma resembled the Leicester cohort: 9\% vs. 16\% (MAS-90 vs. Leicester) of children at low risk at 3 years had asthma at 8 years, at medium risk 45\% vs. 48\%. Performance of the asthma prediction tool in the MAS-90 cohort was similar (Brier score 0.22 vs. 0.23) and discrimination slightly better than in the original cohort (area under the curve, AUC 0.83 vs. 0.78). Prediction and discrimination were robust against changes of inclusion criteria, scoring and outcome definitions. The secondary outcome 'physicians' diagnosed asthma at 20 years' showed the highest discrimination (AUC 0.89). Conclusion: The novel asthma prediction tool from the Leicester cohort, UK, performed well in another population, a German birth cohort, supporting its use and further development as a simple aid to predict asthma risk in clinical settings.},
  language  = {en}
}
@article{LuekeHallerUtpateletal.2022,
  author    = {L{\"u}ke, Florian and Haller, Florian and Utpatel, Kirsten and Krebs, Markus and Meidenbauer, Norbert and Scheiter, Alexander and Spoerl, Silvia and Heudobler, Daniel and Sparrer, Daniela and Kaiser, Ulrich and Keil, Felix and Schubart, Christoph and T{\"o}gel, Lars and Einhell, Sabine and Dietmaier, Wolfgang and Huss, Ralf and Dintner, Sebastian and Sommer, Sebastian and Jordan, Frank and Goebeler, Maria-Elisabeth and Metz, Michaela and Haake, Diana and Scheytt, Mithun and Gerhard-Hartmann, Elena and Maurus, Katja and Br{\"a}ndlein, Stephanie and Rosenwald, Andreas and Hartmann, Arndt and M{\"a}rkl, Bruno and Einsele, Hermann and Mackensen, Andreas and Herr, Wolfgang and Kunzmann, Volker and Bargou, Ralf and Beckmann, Matthias W. and Pukrop, Tobias and Trepel, Martin and Evert, Matthias and Claus, Rainer and Kerscher, Alexander},
  title     = {Identification of disparities in personalized cancer care — a joint approach of the German WERA consortium},
  series = {Cancers},
  volume    = {14},
  journal   = {Cancers},
  number    = {20},
  issn      = {2072-6694},
  doi       = {10.3390/cancers14205040},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-290311},
  year      = {2022},
  abstract  = {(1) Background: molecular tumor boards (MTBs) are crucial instruments for discussing and allocating targeted therapies to suitable cancer patients based on genetic findings. Currently, limited evidence is available regarding the regional impact and the outreach component of MTBs; (2) Methods: we analyzed MTB patient data from four neighboring Bavarian tertiary care oncology centers in W{\"u}rzburg, Erlangen, Regensburg, and Augsburg, together constituting the WERA Alliance. Absolute patient numbers and regional distribution across the WERA-wide catchment area were weighted with local population densities; (3) Results: the highest MTB patient numbers were found close to the four cancer centers. However, peaks in absolute patient numbers were also detected in more distant and rural areas. Moreover, weighting absolute numbers with local population density allowed for identifying so-called white spots—regions within our catchment that were relatively underrepresented in WERA MTBs; (4) Conclusions: investigating patient data from four neighboring cancer centers, we comprehensively assessed the regional impact of our MTBs. The results confirmed the success of existing collaborative structures with our regional partners. Additionally, our results help identifying potential white spots in providing precision oncology and help establishing a joint WERA-wide outreach strategy.},
  language  = {en}
}