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

Giardiello D, Hauptmann M, Steyerberg EW, Adank MA, Akdeniz D, Blom JC, Blomqvist C, Bojesen SE, Bolla MK, Brinkhuis M, Chang-Claude J, Czene K, Devilee P, Dunning AM, Easton DF, Eccles DM, Fasching P, Figueroa J, Flyger H, Garcia-Closas M, Häberle L, Haiman CA, Hall P, Hamann U, Hopper JL, Jager A, Jakubowska A, Jung A, Keeman R, Koppert LB, Kramer I, Lambrechts D, Le Marchand L, Lindblom A, Lubinski J, Manoochehri M, Mariani L, Nevanlinna H, Oldenburg HSA, Pelders S, Pharoah PDP, Shah M, Siesling S, Smit VTHBM, Southey MC, Tapper WJ, Tollenaar RAEM, Van Den Broek AJ, Van Deurzen CHM, Van Leeuwen FE, Van Ongeval C, Van'T Veer LJ, Wang Q, Wendt C, Westenend PJ, Hooning MJ, Schmidt MK (2020)

Publication Type: Journal article

Publication year: 2020

Journal

DOI: 10.1007/s10549-020-05611-8

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.

Authors with CRIS profile

Involved external institutions

Erasmus University Medical Center (MC) Netherlands (NL) University of Cambridge United Kingdom (GB) Pathology laboratory (PAL) Netherlands (NL) Deutsches Krebsforschungszentrum (DKFZ) Germany (DE) Erasmus University Medical Center (MC) Netherlands (NL) University of Edinburgh United Kingdom (GB) University of Southern California (USC) United States (USA) (US) Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital (NKI / NKI-AVL) Netherlands (NL) Karolinska Institute Sweden (SE) Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital (NKI / NKI-AVL) Netherlands (NL) University of Hawaii (U.H.) United States (USA) (US) Copenhagen University Hospital Denmark (DK) Monash University Australia (AU) Leiden University Netherlands (NL) Leiden University Netherlands (NL) Flanders Institute for Biotechnology / Vlaams Instituut voor Biotechnologie (VIB) Belgium (BE) University of Southampton United Kingdom (GB) Helsingin yliopisto / University of Helsinki Finland (FI) University Hospital Leuven (UZ) / Universitaire ziekenhuizen Leuven Belgium (BE) Pomeranian Medical University / Pomorski Uniwersytet Medyczny w Szczecinie (PMU) Poland (PL) Medizinische Hochschule Brandenburg "Theodor Fontane" / Brandenburg Medical School "Theodor Fontane" Germany (DE) Södersjukhuset Sweden (SE) National Cancer Institute (NCI) United States (USA) (US) The University of Melbourne Australia (AU) Laboratorium Pathologie Oost-Nederland LABPON Netherlands (NL) Fondazione IRCCS: Istituto Nazionale dei Tumori Italy (IT) Netherlands Comprehensive Cancer Organisation / Integraal Kankercentrum Nederland (IKNL) Netherlands (NL)

How to cite

APA:

Giardiello, D., Hauptmann, M., Steyerberg, E.W., Adank, M.A., Akdeniz, D., Blom, J.C.,... Schmidt, M.K. (2020). Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts. Breast Cancer Research and Treatment. https://doi.org/10.1007/s10549-020-05611-8

MLA:

Giardiello, Daniele, et al. "Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts." Breast Cancer Research and Treatment (2020).

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