Reducing False-Positive Screening MRI Rate in Women with Extremely Dense Breasts Using Prediction Models Based on Data from the DENSE Trial

Authors:
  • BDBianca M. Den Dekker
    Bianca M. Den Dekker
  • MBMarije F. Bakker
    Marije F. Bakker
  • SLStéphanie V. de Lange
    Stéphanie V. de Lange
  • WVWouter B. Veldhuis
    Wouter B. Veldhuis
  • PDPaul J. van Diest
    Paul J. van Diest
  • KDKatya M. Duvivier
    Katya M. Duvivier
  • MLMarc B. I. Lobbes
    Marc B. I. Lobbes
  • CLClaudette E. Loo
    Claudette E. Loo
  • RMRitse M. Mann
    Ritse M. Mann
  • EMEvelyn M. Monninkhof
    Evelyn M. Monninkhof
  • JVJeroen Veltman
    Jeroen Veltman
  • RPRuud M. Pijnappel
    Ruud M. Pijnappel
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Abstract
Prediction models based on clinical characteristics and MRI findings may be useful to reduce the false-positive rate of first-round supplemental screening MRI in women with extremely dense breasts. Background High breast density increases breast cancer risk and lowers mammographic sensitivity. Supplemental MRI screening improves cancer detection but increases the number of false-positive scre...
Funding Information
  • University Medical Center Utrecht (UMCU DENSE)
  • Netherlands Organization for Health Research and Development (ZonMW-200320002-UMCU, ZonMW Preventie 50-53125-98-014)
  • Dutch Cancer Society (DCS-UU-2009-4348, UU-2014-6859, UU-2014-7151)
  • Dutch Pink Ribbon—A Sister’s Hope (Pink Ribbon-10074)
  • Bayer (BSP-DENSE)

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