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000153731 037__ $$aDKFZ-2020-00428
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000153731 1001_ $$aGiardiello, Daniele$$b0
000153731 245__ $$aPrediction and clinical utility of a contralateral breast cancer risk model.
000153731 260__ $$aLondon$$bBioMed Central$$c2019
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000153731 520__ $$aBreast 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.
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000153731 7001_ $$aSteyerberg, Ewout W$$b1
000153731 7001_ $$aHauptmann, Michael$$b2
000153731 7001_ $$aAdank, Muriel A$$b3
000153731 7001_ $$aAkdeniz, Delal$$b4
000153731 7001_ $$aBlomqvist, Carl$$b5
000153731 7001_ $$aBojesen, Stig E$$b6
000153731 7001_ $$aBolla, Manjeet K$$b7
000153731 7001_ $$aBrinkhuis, Mariël$$b8
000153731 7001_ $$0P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253$$aChang-Claude, Jenny$$b9$$udkfz
000153731 7001_ $$aCzene, Kamila$$b10
000153731 7001_ $$aDevilee, Peter$$b11
000153731 7001_ $$aDunning, Alison M$$b12
000153731 7001_ $$aEaston, Douglas F$$b13
000153731 7001_ $$aEccles, Diana M$$b14
000153731 7001_ $$aFasching, Peter A$$b15
000153731 7001_ $$aFigueroa, Jonine$$b16
000153731 7001_ $$aFlyger, Henrik$$b17
000153731 7001_ $$aGarcía-Closas, Montserrat$$b18
000153731 7001_ $$aHaeberle, Lothar$$b19
000153731 7001_ $$aHaiman, Christopher A$$b20
000153731 7001_ $$aHall, Per$$b21
000153731 7001_ $$0P:(DE-He78)537e07b3e57b16c7b214fc2242e4326b$$aHamann, Ute$$b22$$udkfz
000153731 7001_ $$aHopper, John L$$b23
000153731 7001_ $$aJager, Agnes$$b24
000153731 7001_ $$aJakubowska, Anna$$b25
000153731 7001_ $$0P:(DE-He78)bce1fdec5ce564e2666156d96aeabec9$$aJung, Audrey$$b26$$udkfz
000153731 7001_ $$aKeeman, Renske$$b27
000153731 7001_ $$aKramer, Iris$$b28
000153731 7001_ $$aLambrechts, Diether$$b29
000153731 7001_ $$aLe Marchand, Loic$$b30
000153731 7001_ $$aLindblom, Annika$$b31
000153731 7001_ $$aLubiński, Jan$$b32
000153731 7001_ $$0P:(DE-He78)16b8745cffb0db0d366978d3afe17ebc$$aManoochehri, Mehdi$$b33$$udkfz
000153731 7001_ $$aMariani, Luigi$$b34
000153731 7001_ $$aNevanlinna, Heli$$b35
000153731 7001_ $$aOldenburg, Hester S A$$b36
000153731 7001_ $$aPelders, Saskia$$b37
000153731 7001_ $$aPharoah, Paul D P$$b38
000153731 7001_ $$aShah, Mitul$$b39
000153731 7001_ $$aSiesling, Sabine$$b40
000153731 7001_ $$aSmit, Vincent T H B M$$b41
000153731 7001_ $$aSouthey, Melissa C$$b42
000153731 7001_ $$aTapper, William J$$b43
000153731 7001_ $$aTollenaar, Rob A E M$$b44
000153731 7001_ $$avan den Broek, Alexandra J$$b45
000153731 7001_ $$avan Deurzen, Carolien H M$$b46
000153731 7001_ $$avan Leeuwen, Flora E$$b47
000153731 7001_ $$avan Ongeval, Chantal$$b48
000153731 7001_ $$aVan't Veer, Laura J$$b49
000153731 7001_ $$aWang, Qin$$b50
000153731 7001_ $$aWendt, Camilla$$b51
000153731 7001_ $$aWestenend, Pieter J$$b52
000153731 7001_ $$aHooning, Maartje J$$b53
000153731 7001_ $$aSchmidt, Marjanka K$$b54
000153731 773__ $$0PERI:(DE-600)2041618-0$$a10.1186/s13058-019-1221-1$$gVol. 21, no. 1, p. 144$$n1$$p144$$tBreast cancer research$$v21$$x1465-542X$$y2019
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