The University of Southampton
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Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts

Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts
Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts

Background: Three tools are currently available to predict the risk of contralateral breast cancer (CBC). We aimed to compare the performance of the Manchester formula, CBCrisk, and PredictCBC in patients with invasive breast cancer (BC). Methods: We analyzed data of 132,756 patients (4682 CBC) from 20 international studies with a median follow-up of 8.8 years. Prediction performance included discrimination, quantified as a time-dependent Area-Under-the-Curve (AUC) at 5 and 10 years after diagnosis of primary BC, and calibration, quantified as the expected-observed (E/O) ratio at 5 and 10 years and the calibration slope. Results: The AUC at 10 years was: 0.58 (95% confidence intervals [CI] 0.57–0.59) for CBCrisk; 0.60 (95% CI 0.59–0.61) for the Manchester formula; 0.63 (95% CI 0.59–0.66) and 0.59 (95% CI 0.56–0.62) for PredictCBC-1A (for settings where BRCA1/2 mutation status is available) and PredictCBC-1B (for the general population), respectively. The E/O at 10 years: 0.82 (95% CI 0.51–1.32) for CBCrisk; 1.53 (95% CI 0.63–3.73) for the Manchester formula; 1.28 (95% CI 0.63–2.58) for PredictCBC-1A and 1.35 (95% CI 0.65–2.77) for PredictCBC-1B. The calibration slope was 1.26 (95% CI 1.01–1.50) for CBCrisk; 0.90 (95% CI 0.79–1.02) for PredictCBC-1A; 0.81 (95% CI 0.63–0.99) for PredictCBC-1B, and 0.39 (95% CI 0.34–0.43) for the Manchester formula. Conclusions: Current CBC risk prediction tools provide only moderate discrimination and the Manchester formula was poorly calibrated. Better predictors and re-calibration are needed to improve CBC prediction and to identify low- and high-CBC risk patients for clinical decision-making.

Clinical decision-making, Contralateral breast cancer, Risk prediction, Validation
0167-6806
423-434
Giardiello, Daniele
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Hauptmann, Michael
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Steyerberg, Ewout W.
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Adank, Muriel A.
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Akdeniz, Delal
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Blom, Jannet C.
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Blomqvist, Carl
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Bojesen, Stig E.
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Bolla, Manjeet K.
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Brinkhuis, Mariël
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Chang-Claude, Jenny
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Czene, Kamila
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Devilee, Peter
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Dunning, Alison M.
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Easton, Douglas F.
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Hall, Per
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Hamann, Ute
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Jakubowska, Anna
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Jung, Audrey
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Keeman, Renske
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Koppert, Linetta B.
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Kramer, Iris
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Manoochehri, Mehdi
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Mariani, Luigi
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Oldenburg, Hester S.A.
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Pelders, Saskia
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Pharoah, Paul D.P.
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Shah, Mitul
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Southey, Melissa C.
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Tapper, William J.
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Tollenaar, Rob A.E.M.
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van den Broek, Alexandra J.
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van Deurzen, Carolien H.M.
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van Leeuwen, Flora E.
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van Ongeval, Chantal
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Van’t Veer, Laura J.
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Wang, Qin
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Wendt, Camilla
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Westenend, Pieter J.
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Hooning, Maartje J.
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Schmidt, Marjanka K.
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Giardiello, Daniele
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Hauptmann, Michael
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Steyerberg, Ewout W.
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Adank, Muriel A.
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Akdeniz, Delal
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Blom, Jannet C.
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Blomqvist, Carl
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Bojesen, Stig E.
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Bolla, Manjeet K.
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Brinkhuis, Mariël
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Chang-Claude, Jenny
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Czene, Kamila
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Devilee, Peter
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Dunning, Alison M.
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Easton, Douglas F.
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Eccles, Diana M.
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Fasching, Peter A.
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Figueroa, Jonine
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Flyger, Henrik
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García-Closas, Montserrat
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Haeberle, Lothar
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Haiman, Christopher A.
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Hall, Per
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Hamann, Ute
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Hopper, John L.
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Jager, Agnes
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Jakubowska, Anna
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Jung, Audrey
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Keeman, Renske
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Koppert, Linetta B.
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Kramer, Iris
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Lambrechts, Diether
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Le Marchand, Loic
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Lindblom, Annika
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Lubiński, Jan
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Manoochehri, Mehdi
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Mariani, Luigi
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Nevanlinna, Heli
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Oldenburg, Hester S.A.
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Pelders, Saskia
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Pharoah, Paul D.P.
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Shah, Mitul
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Siesling, Sabine
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Southey, Melissa C.
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Tapper, William J.
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Tollenaar, Rob A.E.M.
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van den Broek, Alexandra J.
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van Deurzen, Carolien H.M.
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van Leeuwen, Flora E.
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van Ongeval, Chantal
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Van’t Veer, Laura J.
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Wang, Qin
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Wendt, Camilla
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Westenend, Pieter J.
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Hooning, Maartje J.
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Schmidt, Marjanka K.
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Giardiello, Daniele, Hauptmann, Michael, Steyerberg, Ewout W., Adank, Muriel A., Akdeniz, Delal, Blom, Jannet C., 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, Koppert, Linetta B., 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. and Schmidt, Marjanka K. (2020) Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts. Breast Cancer Research and Treatment, 181 (2), 423-434. (doi:10.1007/s10549-020-05611-8).

Record type: Article

Abstract

Background: Three tools are currently available to predict the risk of contralateral breast cancer (CBC). We aimed to compare the performance of the Manchester formula, CBCrisk, and PredictCBC in patients with invasive breast cancer (BC). Methods: We analyzed data of 132,756 patients (4682 CBC) from 20 international studies with a median follow-up of 8.8 years. Prediction performance included discrimination, quantified as a time-dependent Area-Under-the-Curve (AUC) at 5 and 10 years after diagnosis of primary BC, and calibration, quantified as the expected-observed (E/O) ratio at 5 and 10 years and the calibration slope. Results: The AUC at 10 years was: 0.58 (95% confidence intervals [CI] 0.57–0.59) for CBCrisk; 0.60 (95% CI 0.59–0.61) for the Manchester formula; 0.63 (95% CI 0.59–0.66) and 0.59 (95% CI 0.56–0.62) for PredictCBC-1A (for settings where BRCA1/2 mutation status is available) and PredictCBC-1B (for the general population), respectively. The E/O at 10 years: 0.82 (95% CI 0.51–1.32) for CBCrisk; 1.53 (95% CI 0.63–3.73) for the Manchester formula; 1.28 (95% CI 0.63–2.58) for PredictCBC-1A and 1.35 (95% CI 0.65–2.77) for PredictCBC-1B. The calibration slope was 1.26 (95% CI 1.01–1.50) for CBCrisk; 0.90 (95% CI 0.79–1.02) for PredictCBC-1A; 0.81 (95% CI 0.63–0.99) for PredictCBC-1B, and 0.39 (95% CI 0.34–0.43) for the Manchester formula. Conclusions: Current CBC risk prediction tools provide only moderate discrimination and the Manchester formula was poorly calibrated. Better predictors and re-calibration are needed to improve CBC prediction and to identify low- and high-CBC risk patients for clinical decision-making.

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Accepted/In Press date: 21 March 2020
e-pub ahead of print date: 11 April 2020
Published date: June 2020
Keywords: Clinical decision-making, Contralateral breast cancer, Risk prediction, Validation

Identifiers

Local EPrints ID: 441387
URI: http://eprints.soton.ac.uk/id/eprint/441387
ISSN: 0167-6806
PURE UUID: 03bd4fe6-f5a5-4f83-8af2-10c5a8c785fe
ORCID for Diana M. Eccles: ORCID iD orcid.org/0000-0002-9935-3169
ORCID for William J. Tapper: ORCID iD orcid.org/0000-0002-5896-1889

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Date deposited: 11 Jun 2020 16:30
Last modified: 18 Mar 2024 05:26

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Contributors

Author: Daniele Giardiello
Author: Michael Hauptmann
Author: Ewout W. Steyerberg
Author: Muriel A. Adank
Author: Delal Akdeniz
Author: Jannet C. Blom
Author: Carl Blomqvist
Author: Stig E. Bojesen
Author: Manjeet K. Bolla
Author: Mariël Brinkhuis
Author: Jenny Chang-Claude
Author: Kamila Czene
Author: Peter Devilee
Author: Alison M. Dunning
Author: Douglas F. Easton
Author: Diana M. Eccles ORCID iD
Author: Peter A. Fasching
Author: Jonine Figueroa
Author: Henrik Flyger
Author: Montserrat García-Closas
Author: Lothar Haeberle
Author: Christopher A. Haiman
Author: Per Hall
Author: Ute Hamann
Author: John L. Hopper
Author: Agnes Jager
Author: Anna Jakubowska
Author: Audrey Jung
Author: Renske Keeman
Author: Linetta B. Koppert
Author: Iris Kramer
Author: Diether Lambrechts
Author: Loic Le Marchand
Author: Annika Lindblom
Author: Jan Lubiński
Author: Mehdi Manoochehri
Author: Luigi Mariani
Author: Heli Nevanlinna
Author: Hester S.A. Oldenburg
Author: Saskia Pelders
Author: Paul D.P. Pharoah
Author: Mitul Shah
Author: Sabine Siesling
Author: Vincent T.H.B.M. Smit
Author: Melissa C. Southey
Author: Rob A.E.M. Tollenaar
Author: Alexandra J. van den Broek
Author: Carolien H.M. van Deurzen
Author: Flora E. van Leeuwen
Author: Chantal van Ongeval
Author: Laura J. Van’t Veer
Author: Qin Wang
Author: Camilla Wendt
Author: Pieter J. Westenend
Author: Maartje J. Hooning
Author: Marjanka K. Schmidt

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