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@ARTICLE{Giardiello:153731,
      author       = {D. Giardiello and E. W. Steyerberg and M. Hauptmann and M.
                      A. Adank and D. Akdeniz and C. Blomqvist and S. E. Bojesen
                      and M. K. Bolla and M. Brinkhuis and J. Chang-Claude$^*$ and
                      K. Czene and P. Devilee and A. M. Dunning and D. F. Easton
                      and D. M. Eccles and P. A. Fasching and J. Figueroa and H.
                      Flyger and M. García-Closas and L. Haeberle and C. A.
                      Haiman and P. Hall and U. Hamann$^*$ and J. L. Hopper and A.
                      Jager and A. Jakubowska and A. Jung$^*$ and R. Keeman and I.
                      Kramer and D. Lambrechts and L. Le Marchand and A. Lindblom
                      and J. Lubiński and M. Manoochehri$^*$ and L. Mariani and
                      H. Nevanlinna and H. S. A. Oldenburg and S. Pelders and P.
                      D. P. Pharoah and M. Shah and S. Siesling and V. T. H. B. M.
                      Smit and M. C. Southey and W. J. Tapper and R. A. E. M.
                      Tollenaar and A. J. van den Broek and C. H. M. van Deurzen
                      and F. E. van Leeuwen and C. van Ongeval and L. J. Van't
                      Veer and Q. Wang and C. Wendt and P. J. Westenend and M. J.
                      Hooning and M. K. Schmidt},
      title        = {{P}rediction and clinical utility of a contralateral breast
                      cancer risk model.},
      journal      = {Breast cancer research},
      volume       = {21},
      number       = {1},
      issn         = {1465-542X},
      address      = {London},
      publisher    = {BioMed Central},
      reportid     = {DKFZ-2020-00428},
      pages        = {144},
      year         = {2019},
      abstract     = {Breast cancer survivors are at risk for contralateral
                      breast cancer (CBC), with the consequent burden of further
                      treatment and potentially less favorable prognosis. We aimed
                      to develop and validate a CBC risk prediction model and
                      evaluate its applicability for clinical decision-making.We
                      included data of 132,756 invasive non-metastatic breast
                      cancer patients from 20 studies with 4682 CBC events and a
                      median follow-up of 8.8 years. We developed a
                      multivariable Fine and Gray prediction model (PredictCBC-1A)
                      including patient, primary tumor, and treatment
                      characteristics and BRCA1/2 germline mutation status,
                      accounting for the competing risks of death and distant
                      metastasis. We also developed a model without BRCA1/2
                      mutation status (PredictCBC-1B) since this information was
                      available for only $6\%$ of patients and is routinely
                      unavailable in the general breast cancer population.
                      Prediction performance was evaluated using calibration and
                      discrimination, calculated by a time-dependent area under
                      the curve (AUC) at 5 and 10 years after diagnosis of
                      primary breast cancer, and an internal-external
                      cross-validation procedure. Decision curve analysis was
                      performed to evaluate the net benefit of the model to
                      quantify clinical utility.In the multivariable model,
                      BRCA1/2 germline mutation status, family history, and
                      systemic adjuvant treatment showed the strongest
                      associations with CBC risk. The AUC of PredictCBC-1A was
                      0.63 $(95\%$ prediction interval (PI) at 5 years,
                      0.52-0.74; at 10 years, 0.53-0.72).
                      Calibration-in-the-large was -0.13 $(95\%$
                      PI: -1.62-1.37), and the calibration slope was 0.90
                      $(95\%$ PI: 0.73-1.08). The AUC of Predict-1B at 10 years
                      was 0.59 $(95\%$ PI: 0.52-0.66); calibration was slightly
                      lower. Decision curve analysis for preventive contralateral
                      mastectomy showed potential clinical utility of
                      PredictCBC-1A between thresholds of $4-10\%$ 10-year CBC
                      risk for BRCA1/2 mutation carriers and non-carriers.We
                      developed a reasonably calibrated model to predict the risk
                      of CBC in women of European-descent; however, prediction
                      accuracy was moderate. Our model shows potential for
                      improved risk counseling, but decision-making regarding
                      contralateral preventive mastectomy, especially in the
                      general breast cancer population where limited information
                      of the mutation status in BRCA1/2 is available, remains
                      challenging.},
      cin          = {C020 / B072 / B070},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331 / I:(DE-He78)B072-20160331 /
                      I:(DE-He78)B070-20160331},
      pnm          = {319H - Addenda (POF3-319H)},
      pid          = {G:(DE-HGF)POF3-319H},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31847907},
      pmc          = {pmc:PMC6918633},
      doi          = {10.1186/s13058-019-1221-1},
      url          = {https://inrepo02.dkfz.de/record/153731},
}