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Prediction of contralateral breast cancer: external validation of risk calculators in 20 international cohorts.
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; Lubinski, 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.
Afiliação
  • Giardiello D; Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
  • Hauptmann M; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
  • Steyerberg EW; Brandenburg Medical School, Institute of Biostatistics and Registry Research, Neuruppin, Germany.
  • Adank MA; Department of Epidemiology and Biostatistics, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
  • Akdeniz D; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
  • Blom JC; Department of Public Health, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
  • Blomqvist C; Family Cancer Clinic, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
  • Bojesen SE; Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
  • Bolla MK; Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
  • Brinkhuis M; Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.
  • Chang-Claude J; Department of Oncology, Örebro University Hospital, Örebro, Sweden.
  • Czene K; Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.
  • Devilee P; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.
  • Dunning AM; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
  • Easton DF; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Eccles DM; Laboratory for Pathology, East-Netherlands, Hengelo, The Netherlands.
  • Fasching PA; Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Figueroa J; University Medical Center Hamburg-Eppendorf, Cancer Epidemiology, University Cancer Center Hamburg (UCCH), Hamburg, Germany.
  • Flyger H; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • García-Closas M; Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.
  • Haeberle L; Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
  • Haiman CA; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
  • Hall P; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Hamann U; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
  • Hopper JL; Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK.
  • Jager A; David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California At Los Angeles, Los Angeles, CA, USA.
  • Jakubowska A; University Hospital Erlangen, Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany.
  • Jung A; The University of Edinburgh Medical School, Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK.
  • Keeman R; Cancer Research UK Edinburgh Centre, Edinburgh, UK.
  • Koppert LB; Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Kramer I; Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.
  • Lambrechts D; Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Le Marchand L; Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK.
  • Lindblom A; University Hospital Erlangen, Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany.
  • Lubinski J; Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Manoochehri M; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Mariani L; Department of Oncology, Södersjukhuset, Stockholm, Sweden.
  • Nevanlinna H; Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Oldenburg HSA; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
  • Pelders S; Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
  • Pharoah PDP; Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland.
  • Shah M; Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland.
  • Siesling S; Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Smit VTHBM; Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
  • Southey MC; Department of Surgical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
  • Tapper WJ; Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni Van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
  • Tollenaar RAEM; VIB Center for Cancer Biology, Leuven, Belgium.
  • van den Broek AJ; Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, Leuven, Belgium.
  • van Deurzen CHM; Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA.
  • van Leeuwen FE; Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.
Breast Cancer Res Treat ; 181(2): 423-434, 2020 Jun.
Article em En | MEDLINE | ID: mdl-32279280
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Segunda Neoplasia Primária / Medição de Risco / Tomada de Decisão Clínica Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Segunda Neoplasia Primária / Medição de Risco / Tomada de Decisão Clínica Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article