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@ARTICLE{Giardiello:182208,
author = {D. Giardiello and M. J. Hooning and M. Hauptmann and R.
Keeman and B. A. M. Heemskerk-Gerritsen and H. Becher and C.
Blomqvist and S. E. Bojesen and M. K. Bolla and N. J. Camp
and K. Czene and P. Devilee and D. M. Eccles and P. A.
Fasching and J. D. Figueroa and H. Flyger and M.
García-Closas and C. A. Haiman and U. Hamann$^*$ and J. L.
Hopper and A. Jakubowska and F. E. Leeuwen and A. Lindblom
and J. Lubiński and S. Margolin and M. E. Martinez and H.
Nevanlinna and I. Nevelsteen and S. Pelders and P. D. P.
Pharoah and S. Siesling and M. C. Southey and A. H. van der
Hout and L. P. van Hest and J. Chang-Claude$^*$ and P. Hall
and D. F. Easton and E. W. Steyerberg and M. K. Schmidt},
title = {{P}redict{CBC}-2.0: a contralateral breast cancer risk
prediction model developed and validated in ~ 200,000
patients.},
journal = {Breast cancer research},
volume = {24},
number = {1},
issn = {1465-5411},
address = {London},
publisher = {BioMed Central},
reportid = {DKFZ-2022-02502},
pages = {69},
year = {2022},
abstract = {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.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.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.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.},
keywords = {BCAC (Other) / BRCA1/2 germline mutation (Other) / Breast
Cancer Association Consortium (Other) / Breast cancer
genetic predisposition (Other) / Clinical decision-making
(Other) / Contralateral breast cancer (Other) /
Contralateral preventive mastectomy (Other) / Polygenic risk
score (Other) / Prediction performance (Other) / Risk
prediction (Other)},
cin = {B070 / B072 / C020},
ddc = {610},
cid = {I:(DE-He78)B070-20160331 / I:(DE-He78)B072-20160331 /
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:36271417},
doi = {10.1186/s13058-022-01567-3},
url = {https://inrepo02.dkfz.de/record/182208},
}