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@ARTICLE{Hurson:168129,
      author       = {A. N. Hurson and P. Pal Choudhury and C. Gao and A.
                      Hüsing$^*$ and M. Eriksson and M. Shi and M. E. Jones and
                      D. G. R. Evans and R. L. Milne and M. M. Gaudet and C. M.
                      Vachon and D. I. Chasman and D. F. Easton and M. K. Schmidt
                      and P. Kraft and M. Garcia-Closas and N. Chatterjee},
      collaboration = {B. R. M. Group},
      title        = {{P}rospective evaluation of a breast-cancer risk model
                      integrating classical risk factors and polygenic risk in 15
                      cohorts from six countries.},
      journal      = {International journal of epidemiology},
      volume       = {50},
      number       = {6},
      issn         = {1464-3685},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {DKFZ-2021-00697},
      pages        = {1897–1911},
      year         = {2021},
      note         = {Volume 50, Issue 6, December 2021, Pages 1897–1911},
      abstract     = {Rigorous evaluation of the calibration and discrimination
                      of breast-cancer risk-prediction models in prospective
                      cohorts is critical for applications under clinical
                      guidelines. We comprehensively evaluated an integrated model
                      incorporating classical risk factors and a 313-variant
                      polygenic risk score (PRS) to predict breast-cancer
                      risk.Fifteen prospective cohorts from six countries with 239
                      340 women (7646 incident breast-cancer cases) of European
                      ancestry aged 19-75 years were included. Calibration of
                      5-year risk was assessed by comparing expected and observed
                      proportions of cases overall and within risk categories.
                      Risk stratification for women of European ancestry aged
                      50-70 years in those countries was evaluated by the
                      proportion of women and future cases crossing clinically
                      relevant risk thresholds.Among women <50 years old, the
                      median (range) expected-to-observed ratio for the integrated
                      model across 15 cohorts was 0.9 (0.7-1.0) overall and 0.9
                      (0.7-1.4) at the highest-risk decile; among women ≥50
                      years old, these were 1.0 (0.7-1.3) and 1.2 (0.7-1.6),
                      respectively. The proportion of women identified above a
                      $3\%$ 5-year risk threshold (used for recommending
                      risk-reducing medications in the USA) ranged from $7.0\%$ in
                      Germany (∼841 000 of 12 million) to $17.7\%$ in the USA
                      (∼5.3 of 30 million). At this threshold, $14.7\%$ of US
                      women were reclassified by adding the PRS to classical risk
                      factors, with identification of $12.2\%$ of additional
                      future cases.Integrating a 313-variant PRS with classical
                      risk factors can improve the identification of
                      European-ancestry women at elevated risk who could benefit
                      from targeted risk-reducing strategies under current
                      clinical guidelines.},
      keywords     = {Breast cancer (Other) / iCARE (Other) / model validation
                      (Other) / polygenic risk score (Other) / risk prediction
                      (Other) / risk stratification (Other)},
      cin          = {C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:33755131},
      doi          = {10.1093/ije/dyab036},
      url          = {https://inrepo02.dkfz.de/record/168129},
}