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.

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Keywords Breast neoplasms, Early detection of cancer, Genetic predisposition to disease, Magnetic resonance imaging, Mammography, Meta-analysis
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Journal European Journal of Cancer
Phi, X.-A, Houssami, N, Hooning, M.J, Riedl, C.C, Leach, M.O, Sardanelli, F, … de Bock, G.H. (2017). Accuracy of screening women at familial risk of breast cancer without a known gene mutation: Individual patient data meta-analysis. European Journal of Cancer (Vol. 85, pp. 31–38). doi:10.1016/j.ejca.2017.07.055