Adank, M.A.

Akdeniz, D.

Blomqvist, C.

Bojesen, S.E.

Bolla, M.K.

Brinkhuis, M.

Chang-Claude, J.

Czene, K.

Devilee, P.

Dunning, A.M.

Easton, D.F.

Eccles, D.M.

Fasching, P.A.

Figueroa, J.

Flyger, H.

Garciá-Closas, M.

Giardiello, D.

Haeberle, L.

Haiman, C.A.

Hall, P.

Hamann, U.

Hauptmann, M.

Hooning, M.J.

Hopper, J.L.

Jager, A.

Jakubowska, A.

Jung, A.

Keeman, R.

Kramer, I.

Lambrechts, D.

Le Marchand, L.

Lindblom, A.

Lubiński, J.

Manoochehri, M.

Mariani, L.

Nevanlinna, H.

Oldenburg, H.S.A.

Pelders, S.

Pharoah, P.D.P.

Schmidt, M.K.

Shah, M.

Siesling, S.

Smit, V.T.H.B.M.

Southey, M.C.

Steyerberg, E.W.

Tapper, W.J.

Tollenaar, R.A.E.M.

Van Den Broek, A.J.

Van Deurzen, C.H.M.

Van Leeuwen, F.E.

Van Ongeval, C.

Van't Veer, L.J.

Wang, Q.

Wendt, C.

Westenend, P.J.

Breast Cancer Research

English

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

Giardiello, Daniele

Steyerberg, Ewout W.

Hauptmann, Michael

Adank, Muriel A.

Akdeniz, Delal

Blomqvist, Carl

Bojesen, Stig E.

Bolla, Manjeet K.

Brinkhuis, Mariël

Chang-Claude, Jenny

Czene, Kamila

Devilee, Peter

Dunning, Alison M.

Easton, Douglas F.

Eccles, Diana M.

Fasching, Peter A.

Figueroa, Jonine

Flyger, Henrik

García-Closas, Montserrat

Haeberle, Lothar

Haiman, Christopher A.

Hall, Per

Hamann, Ute

Hopper, John L.

Jager, Agnes

Jakubowska, Anna

Jung, Audrey

Keeman, Renske

Kramer, Iris

Lambrechts, Diether

Le Marchand, Loic

Lindblom, Annika

Lubiński, Jan

Manoochehri, Mehdi

Mariani, Luigi

Nevanlinna, Heli

Oldenburg, Hester S. A.

Pelders, Saskia

Pharoah, Paul D. P.

Shah, Mitul

Siesling, Sabine

Smit, Vincent T. H. B. M.

Southey, Melissa C.

Tapper, William J.

Tollenaar, Rob A. E. M.

van den Broek, Alexandra J.

van Deurzen, Carolien H. M.

van Leeuwen, Flora E.

van Ongeval, Chantal

Van’t Veer, Laura J.

Wang, Qin

Wendt, Camilla

Westenend, Pieter J.

Hooning, Maartje J.

Schmidt, Marjanka K.

OPUS FAU - Online-Publikationssystem der Friedrich-Alexander-Universität Erlangen-Nürnberg

Prediction and clinical utility of a contralateral breast cancer risk model

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.</p

Steyerberg, Ewout W

Adank, Muriel A

Bojesen, Stig E

Bolla, Manjeet K

Dunning, Alison M

Easton, Douglas F

Eccles, Diana M

Fasching, Peter A

Haiman, Christopher A

Hopper, John L

Oldenburg, Hester S A

Pharoah, Paul D P

Smit, Vincent T H B M

Southey, Melissa C

Tapper, William J

Tollenaar, Rob A E M

van den Broek, Alexandra J

van Deurzen, Carolien H M

van Leeuwen, Flora E

Van't Veer, Laura J

Westenend, Pieter J

Hooning, Maartje J

Schmidt, Marjanka K

Southampton (e-Prints Soton)

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.</p

Garciá-Closas, Montserrat

Oldenburg, Hester S.A.

Pharoah, Paul D.P.

Smit, Vincent T.H.B.M.

Tollenaar, Rob A.E.M.

Van Den Broek, Alexandra J.

Van Deurzen, Carolien H.M.

Van Leeuwen, Flora E.

Van Ongeval, Chantal

van 't Veer, Laura J.

University of Twente Research Information

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

Apollo (Cambridge)

Prediction and clinical utility of a contralateral breast cancer risk model.

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.Genome Instability and Cance

Garcia-Closas, M.

Marchand, L. le

Lubinski, J.

Broek, A.J. van den

Deurzen, C.H.M. van

Leeuwen, F.E. van

Ongeval, C. van

Leiden University Scholary Publications

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

Giardiello, D

Steyerberg, EW

Hauptmann, M

Adank, MA

Akdeniz, D

Blomqvist, C

Bojesen, SE

Bolla, MK

Brinkhuis, M

Chang-Claude, J

Czene, K

Devilee, P

Dunning, AM

Easton, DF

Eccles, DM

Fasching, PA

Figueroa, J

Flyger, H

Garciá-Closas, M

Haeberle, L

Haiman, CA

Hall, P

Hamann, U

Hopper, JL

Jager, A

Jakubowska, A

Jung, A

Keeman, R

Kramer, I

Lambrechts, D

Le Marchand, L

Lindblom, A

Lubiński, J

Manoochehri, M

Mariani, L

Nevanlinna, H

https://www.repository.cam.ac.uk/bitstream/handle/1810/315425/13058_2019_Article_1221.pdf?sequence=4&isAllowed=y

Prediction and clinical utility of a contralateral breast cancer risk model

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OPUS FAU - Online-Publikationssystem der Friedrich-Alexander-Universität Erlangen-Nürnberg

Southampton (e-Prints Soton)

University of Twente Research Information

Apollo (Cambridge)

Leiden University Scholary Publications

University of Melbourne Institutional Repository

Lirias

Edinburgh Research Explorer

Apollo (Cambridge)