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Title: | Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts. | Authors: | Smit V.T.H.B.M.;Pharoah P.D.P.;Shah M.;Siesling S.;Southey M.C.;Schmidt M.K.;Hooning M.J.;Westenend P.J.;Wendt C.;Wang Q.;Van't Veer L.J.;van Ongeval C.;van Leeuwen F.E.;van Deurzen C.H.M.;van den Broek A.J.;Tollenaar R.A.E.M.;Tapper W.J.;Giardiello D.;Hauptmann M.;Steyerberg E.W.;Adank M.A.;Akdeniz D.;Blom J.C.;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.;Garcia-Closas M.;Haeberle L.;Haiman C.A.;Hall P.;Hamann U.;Hopper J.L.;Jager A.;Jakubowska A.;Jung A.;Keeman R.;Koppert L.B.;Kramer I.;Lambrechts D.;Le Marchand L.;Lindblom A.;Lubinski J.;Manoochehri M.;Mariani L.;Nevanlinna H.;Oldenburg H.S.A.;Pelders S. | Monash Health Department(s): | Monash University - School of Clinical Sciences at Monash Health | Institution: | (Giardiello, Keeman, Kramer, van den Broek, Van't Veer, Schmidt) Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, Netherlands (Giardiello, Steyerberg) Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands (Hauptmann) Brandenburg Medical School, Institute of Biostatistics and Registry Research, Neuruppin, Germany (Hauptmann) Department of Epidemiology and Biostatistics, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, Netherlands (Steyerberg) Department of Public Health, Erasmus MC Cancer Institute, Rotterdam, Netherlands (Adank) Family Cancer Clinic, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, Netherlands (Akdeniz, Blom, Pelders, Hooning) Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, Netherlands (Blomqvist) Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland (Blomqvist) Department of Oncology, Orebro University Hospital, Orebro, Sweden (Bojesen) Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark (Bojesen) Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark (Bojesen) Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark (Bolla, Easton, Pharoah, Wang) Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom (Brinkhuis) Laboratory for Pathology, East-Netherlands, Hengelo, Netherlands (Chang-Claude, Jung) Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany (Chang-Claude) University Medical Center Hamburg-Eppendorf, Cancer Epidemiology, University Cancer Center Hamburg (UCCH), Hamburg, Germany (Czene, Hall) Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Devilee, Smit) Department of Pathology, Leiden University Medical Center, Leiden, Netherlands (Devilee) Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands (Dunning, Easton, Pharoah, Shah) Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom (Eccles) Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton, United Kingdom (Fasching) David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California At Los Angeles, Los Angeles, CA, United States (Fasching, Haeberle) University Hospital Erlangen, Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany (Figueroa) The University of Edinburgh Medical School, Usher Institute of Population Health Sciences and Informatics, Edinburgh, United Kingdom (Figueroa) Cancer Research UK Edinburgh Centre, Edinburgh, United Kingdom (Figueroa, Garcia-Closas) Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States (Flyger) Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark (Garcia-Closas) Division of Genetics and Epidemiology, Institute of Cancer Research, London, United Kingdom (Haiman) Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States (Hall) Department of Oncology, Sodersjukhuset, Stockholm, Sweden (Hamann, Manoochehri) Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany (Hopper) Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia (Jager) Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, Netherlands (Jakubowska, Lubinski) Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland (Jakubowska) Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland (Koppert) Department of Surgical Oncology, Erasmus MC Cancer Institute, Rotterdam, Netherlands (Lambrechts) VIB Center for Cancer Biology, Leuven, Belgium (Lambrechts) Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, Leuven, Belgium (Le Marchand) Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, United States (Lindblom) Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden (Lindblom) Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden (Mariani) Unit of Clinical Epidemiology and Trial Organization, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy (Nevanlinna) Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland (Oldenburg) Department of Surgical Oncology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, Netherlands (Siesling) Department of Research, Netherlands Comprehensive Cancer Organisation, Utrecht, Netherlands (Southey) Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia (Southey) Department of Clinical Pathology, The University of Melbourne, Melbourne, VIC, Australia (Tapper) Faculty of Medicine, University of Southampton, Southampton, United Kingdom (Tollenaar) Department of Surgery, Leiden University Medical Center, Leiden, Netherlands (van Deurzen) Department of Pathology, Erasmus MC Cancer Institute, Rotterdam, Netherlands (van Leeuwen, Schmidt) Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, Netherlands (van Ongeval) Leuven Cancer Institute, Leuven Multidisciplinary Breast Center, Department of Oncology, University Hospitals Leuven, Leuven, Belgium (Wendt) Department of Clinical Science and Education, Karolinska Institutet, Sodersjukhuset, Stockholm, Sweden (Westenend) Laboratory for Pathology, Dordrecht, Netherlands (Schmidt) Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, Netherlands | Issue Date: | 13-May-2020 | Copyright year: | 2020 | Publisher: | Springer | Place of publication: | United States | Publication information: | Breast Cancer Research and Treatment. 181 (2) (pp 423-434), 2020. Date of Publication: 01 Jun 2020. | Journal: | Breast Cancer Research and Treatment | 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). Method(s): 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. Result(s): 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. Conclusion(s): 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.Copyright © 2020, Springer Science+Business Media, LLC, part of Springer Nature. | DOI: | http://monash.idm.oclc.org/login?url=http://dx.doi.org/10.1007/s10549-020-05611-8 | PubMed URL: | 32279280 [http://www.ncbi.nlm.nih.gov/pubmed/?term=32279280] | ISSN: | 0167-6806 | URI: | https://repository.monashhealth.org/monashhealthjspui/handle/1/29278 | Type: | Article | Subjects: | controlled study *breast cancer/di [Diagnosis] female follow up high risk patient BRCA2 protein/ec [Endogenous Compound] calculator *contralateral breast cancer/di [Diagnosis] *contralateral breast cancer/et [Etiology] *breast cancer/et [Etiology] cohort analysis clinical decision making cancer risk calibration article adult human low risk patient major clinical study mutational analysis population research primary tumor/di [Diagnosis] primary tumor/et [Etiology] priority journal validation study BRCA1 protein/ec [Endogenous Compound] breast cancer high risk patient BRCA2 protein calculator contralateral breast cancer breast cancer clinical decision making cancer risk calibration low risk patient mutational analysis research primary tumor validation study BRCA1 protein follow up adult Article *breast cancer / *diagnosis / *etiology calibration cancer risk clinical decision making cohort analysis controlled study female high risk patient human low risk patient major clinical study mutational analysis population research primary tumor / diagnosis / etiology priority journal validation study |
Type of Clinical Study or Trial: | Observational study (cohort, case-control, cross sectional or survey) |
Appears in Collections: | Articles |
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