PurposeTo evaluate the positive predictive value and factors predictive of malignancy of additional calcifications in the pre-therapeutic work-up of a synchronous breast cancer. Materials and methodsInstitutional review board approval was obtained for this retrospective study and informed consent was waved. Consecutive patients referred to our center between January 1st 2018 and December 31st 2022 for a breast cancer and who presented additional calcifications detected during the pretreatment work-up were eligible for inclusion in this study. Morphology, distribution and BI-RADS category of the calcifications were assessed in consensus by 3 radiologists specialized in breast imaging. Side and distance from the cancer were collected. The predictive value of malignancy of the calcifications was calculated for each BI-RADS category. Factors associated with malignancy were evaluated by logistic non-conditional regression on univariate and multivariate analysis. ResultsOne hundred and thirteen clusters of calcifications in 103 patients were included. Among the groups of calcifications 41 % were malignant, 31 % benign and 28 % were atypia on biopsy. After exclusion of the non-operated atypia, 50.5 % of additional calcifications were ultimately malignant and 49.5 % were benign. The predictive value of malignancy was 20.7 %; 40.7 %; 63 %; 85.7 % and 100 % for category BI-RADS 3, 4a, 4B, 4c and 5 respectively. On multivariate analysis, multifocality or centricity of the index tumour (P = 0.01), BI-RADS classifications (P = 0.0001) and location ipsilateral less than 35 mm to the index cancer (P = 0.008) of the additional calcifications were found to be independent predictors of malignancy. Sixty percent of calcifications were not described on the initial out-center diagnostic work-up. ConclusionAdditional calcifications detected during the pretreatment work-up of a breast cancer are associated with a higher probability of malignancy than in a screening population and require biopsy even when demonstrating probably benign (BI-RADS 3) features.
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