Xuan-Anh Phi1, Nehmat Houssami2, Maartje J Hooning3, Christopher C Riedl4, Martin O Leach5, Francesco Sardanelli6, Ellen Warner7, Isabelle Trop8, Sepideh Saadatmand9, Madeleine M A Tilanus-Linthorst9, Thomas H Helbich4, Edwin R van den Heuvel10, Harry J de Koning11, Inge-Marie Obdeijn12, Geertruida H de Bock13. 1. Department of Epidemiology, University of Groningen, University Medical Center Groningen, Postbus 30 001, 9700RB, Groningen, The Netherlands. Electronic address: x.a.phi@umcg.nl. 2. Screening and Test Evaluation Program (STEP), School of Public Health, Sydney Medical School, Edward Ford Building (A27), The University of Sydney, NSW, 2006, Australia. 3. Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Groene Hilledijk 301, 3075EA, Rotterdam, The Netherlands. 4. Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Währinger Gürtel 18-20, Floor 7F, 1090, Vienna, Austria. 5. On Behalf of the MARIBS Study, CRUK Cancer Imaging Centre, Institute of Cancer Research, The Royal Marsden NHS Foundation Trust, 123 Old Brompton Road, London, SW7 3RP, UK. 6. On Behalf of the HIBCRIT-1 Study, Department of Biomedical Sciences for Health, University of Milan School of Medicine, Scientific Institute (IRCCS) Policlinico San Donato, Unit of Radiology, Via Morandi 30, 20097, San Donato Milanese, Milan, Italy. 7. Department of Medicine, Division of Medical Oncology, Sunnybrook Health Sciences Centre, University of Toronto, 2075, Bayview Avenue, Toronto, Ontario, M4N 3M5, Canada. 8. Department of Radiology, Breast Imaging Division, Centre Hospitalier of the University of Montreal (CHUM), Montreal, Tour Viger, Pavillion R, 900 Saint Denis Street, Montreal, Quebec H2X 0A9, Canada. 9. On Behalf of MRISC Study, Department of Surgical Oncology, Erasmus University Medical Center Rotterdam, Groene Hilledijk 301, 3075 EA, Rotterdam, The Netherlands. 10. Department of Mathematics and Computer Science, Eindhoven University of Technology, Den Dolech 2, 5600 MB, Eindhoven, The Netherlands. 11. Department of Public Health, Erasmus University Medical Center, 's-Gravendijkwal 230, 3015 CE, Rotterdam, The Netherlands. 12. Department of Radiology, Erasmus University Medical Center, Groene Hilledijk 301, 3075 EA, Rotterdam, The Netherlands. 13. Department of Epidemiology, University of Groningen, University Medical Center Groningen, Postbus 30 001, 9700RB, Groningen, The Netherlands.
Abstract
INTRODUCTION: Women with a strong family history of breast cancer (BC) and without a known gene mutation have an increased risk of developing BC. We aimed to investigate the accuracy of screening using annual mammography with or without magnetic resonance imaging (MRI) for these women outside the general population screening program. METHODS: An individual patient data (IPD) meta-analysis was conducted using IPD from six prospective screening trials that had included women at increased risk for BC: only women with a strong familial risk for BC and without a known gene mutation were included in this analysis. A generalised linear mixed model was applied to estimate and compare screening accuracy (sensitivity, specificity and predictive values) for annual mammography with or without MRI. RESULTS: There were 2226 women (median age: 41 years, interquartile range 35-47) with 7478 woman-years of follow-up, with a BC rate of 12 (95% confidence interval 9.3-14) in 1000 woman-years. Mammography screening had a sensitivity of 55% (standard error of mean [SE] 7.0) and a specificity of 94% (SE 1.3). Screening with MRI alone had a sensitivity of 89% (SE 4.6) and a specificity of 83% (SE 2.8). Adding MRI to mammography increased sensitivity to 98% (SE 1.8, P < 0.01 compared to mammography alone) but lowered specificity to 79% (SE 2.7, P < 0.01 compared with mammography alone). CONCLUSION: In this population of women with strong familial BC risk but without a known gene mutation, in whom BC incidence was high both before and after age 50, adding MRI to mammography substantially increased screening sensitivity but also decreased its specificity.
INTRODUCTION:Women with a strong family history of breast cancer (BC) and without a known gene mutation have an increased risk of developing BC. We aimed to investigate the accuracy of screening using annual mammography with or without magnetic resonance imaging (MRI) for these women outside the general population screening program. METHODS: An individual patient data (IPD) meta-analysis was conducted using IPD from six prospective screening trials that had included women at increased risk for BC: only women with a strong familial risk for BC and without a known gene mutation were included in this analysis. A generalised linear mixed model was applied to estimate and compare screening accuracy (sensitivity, specificity and predictive values) for annual mammography with or without MRI. RESULTS: There were 2226 women (median age: 41 years, interquartile range 35-47) with 7478 woman-years of follow-up, with a BC rate of 12 (95% confidence interval 9.3-14) in 1000 woman-years. Mammography screening had a sensitivity of 55% (standard error of mean [SE] 7.0) and a specificity of 94% (SE 1.3). Screening with MRI alone had a sensitivity of 89% (SE 4.6) and a specificity of 83% (SE 2.8). Adding MRI to mammography increased sensitivity to 98% (SE 1.8, P < 0.01 compared to mammography alone) but lowered specificity to 79% (SE 2.7, P < 0.01 compared with mammography alone). CONCLUSION: In this population of women with strong familial BC risk but without a known gene mutation, in whom BC incidence was high both before and after age 50, adding MRI to mammography substantially increased screening sensitivity but also decreased its specificity.
Authors: Anna M Chiarelli; Kristina M Blackmore; Derek Muradali; Susan J Done; Vicky Majpruz; Ashini Weerasinghe; Lucia Mirea; Andrea Eisen; Linda Rabeneck; Ellen Warner Journal: J Natl Cancer Inst Date: 2020-02-01 Impact factor: 13.506