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dc.contributor.authorGiardiello, Daniele
dc.contributor.authorSteyerberg, Ewout W.
dc.contributor.authorHauptmann, Michael
dc.contributor.authorAdank, Muriel A.
dc.contributor.authorAkdeniz, Delal
dc.contributor.authorBlomqvist, Carl
dc.contributor.authorBojesen, Stig E.
dc.contributor.authorBolla, Manjeet K.
dc.contributor.authorBrinkhuis, Mariël
dc.contributor.authorChang-Claude, Jenny
dc.contributor.authorCzene, Kamila
dc.contributor.authorDevilee, Peter
dc.contributor.authorDunning, Alison M.
dc.contributor.authorEaston, Douglas F.
dc.contributor.authorEccles, Diana M.
dc.contributor.authorFasching, Peter A.
dc.contributor.authorFigueroa, Jonine
dc.contributor.authorFlyger, Henrik
dc.contributor.authorGarcía-Closas, Montserrat
dc.contributor.authorHaeberle, Lothar
dc.contributor.authorHaiman, Christopher A.
dc.contributor.authorHall, Per
dc.contributor.authorHamann, Ute
dc.contributor.authorHopper, John L.
dc.contributor.authorJager, Agnes
dc.contributor.authorJakubowska, Anna
dc.contributor.authorJung, Audrey
dc.contributor.authorKeeman, Renske
dc.contributor.authorKramer, Iris
dc.contributor.authorLambrechts, Diether
dc.contributor.authorLe Marchand, Loic
dc.contributor.authorLindblom, Annika
dc.contributor.authorLubiński, Jan
dc.contributor.authorManoochehri, Mehdi
dc.contributor.authorMariani, Luigi
dc.contributor.authorNevanlinna, Heli
dc.contributor.authorOldenburg, Hester S. A.
dc.contributor.authorPelders, Saskia
dc.contributor.authorPharoah, Paul D. P.
dc.contributor.authorShah, Mitul
dc.contributor.authorSiesling, Sabine
dc.contributor.authorSmit, Vincent T. H. B. M.
dc.contributor.authorSouthey, Melissa C.
dc.contributor.authorTapper, William J.
dc.contributor.authorTollenaar, Rob A. E. M.
dc.contributor.authorvan den Broek, Alexandra J.
dc.contributor.authorvan Deurzen, Carolien H. M.
dc.contributor.authorvan Leeuwen, Flora E.
dc.contributor.authorvan Ongeval, Chantal
dc.contributor.authorVan’t Veer, Laura J.
dc.contributor.authorWang, Qin
dc.contributor.authorWendt, Camilla
dc.contributor.authorWestenend, Pieter J.
dc.contributor.authorHooning, Maartje J.
dc.contributor.authorSchmidt, Marjanka K.
dc.date.accessioned2020-12-22T18:56:19Z
dc.date.available2020-12-22T18:56:19Z
dc.date.issued2019-12-17
dc.date.submitted2019-06-07
dc.identifier.others13058-019-1221-1
dc.identifier.other1221
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/315425
dc.description.abstractAbstract: Background: 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. Methods: 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. Results: 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. Conclusions: 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.
dc.languageen
dc.publisherBioMed Central
dc.subjectResearch Article
dc.subjectContralateral breast cancer
dc.subjectRisk prediction model
dc.subjectClinical decision-making
dc.subjectBRCA mutation carriers
dc.titlePrediction and clinical utility of a contralateral breast cancer risk model
dc.typeArticle
dc.date.updated2020-12-22T18:56:19Z
prism.issueIdentifier1
prism.publicationNameBreast Cancer Research
prism.volume21
dc.identifier.doi10.17863/CAM.62532
dcterms.dateAccepted2019-10-29
rioxxterms.versionofrecord10.1186/s13058-019-1221-1
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.identifier.eissn1465-542X
pubs.funder-project-idKWF Kankerbestrijding (6253)


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