PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Daniele Giardiello, Maartje J. Hooning, Michael Hauptmann, Renske Keeman, B. A.M. Heemskerk-Gerritsen, Heiko Becher, Carl Blomqvist, Stig E. Bojesen, Manjeet K. Bolla, Nicola J. Camp, Kamila Czene, Peter Devilee, Diana M. Eccles, Peter A. Fasching, Jonine D. Figueroa, Henrik Flyger, Montserrat García-Closas, Christopher A. Haiman, Ute Hamann, John L. HopperAnna Jakubowska, Floor E. Leeuwen, Annika Lindblom, Jan Lubiński, Sara Margolin, Maria Elena Martinez, Heli Nevanlinna, Ines Nevelsteen, Saskia Pelders, Paul D.P. Pharoah, Sabine Siesling, Melissa C. Southey, Annemieke H. van der Hout, Liselotte P. van Hest, Jenny Chang-Claude, Per Hall, Douglas F. Easton, Ewout W. Steyerberg, Marjanka K. Schmidt*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background: Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors.

Methods: We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models.

Results: The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56–0.74) versus 0.63 (95%PI 0.54–0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34–2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.

Conclusions: Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.

Original languageEnglish
Article number69
Number of pages14
JournalBreast cancer research
Volume24
DOIs
Publication statusPublished - Dec-2022

Keywords

  • BCAC
  • BRCA1/2 germline mutation
  • Breast Cancer Association Consortium
  • Breast cancer genetic predisposition
  • Clinical decision-making
  • Contralateral breast cancer
  • Contralateral preventive mastectomy
  • Polygenic risk score
  • Prediction performance
  • Risk prediction

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