Calling all calcifications: A retrospective case control study Journal Article

Authors: Narayan, A. K.; Keating, D. M.; Morris, E. A.; Mango, V. L.
Article Title: Calling all calcifications: A retrospective case control study
Abstract: Introduction: The majority of recalls from screening mammography do not result in biopsy recommendation. The purpose of this study was to evaluate if calcifications recalled from screening mammography are more likely to result in biopsy recommendations than other findings. Methods: IRB-approved electronic medical record search was performed to obtain a random sample of screening mammograms assigned BI-RADS 0 assessment during 2014–2015. Primary reason for recall was classified as mass, asymmetry, focal asymmetry, calcifications, or distortion. Primary outcome was biopsy performed after diagnostic work-up. Secondary outcome was proportion of biopsies performed that were positive for cancer, positive predictive value 3 (PPV3). Logistic regression was used to compare reasons for recall (calcifications vs other findings) with biopsy recommendation proportions. Results: Random database sampling yielded 402 screening examinations with BI-RADS 0 assessments with 449 total findings. Reasons for recall included calcifications (14.0%, 63/449), masses (15.8%, 71/449), asymmetries (50.8%, 228/449), focal asymmetries (14.3%, 64/449) and architectural distortions (5.1%, 23/449). Overall, 21.6% of recalls led to image-guided biopsy (87/402). Recalls for calcifications were more likely to result in biopsy compared with other types of findings (Adjusted OR 8.56, 95% CI 4.58 to 16.0, p < 0.001). No statistically significant differences were found in PPV3 proportions between calcification and non-calcification findings (p = 0.812). Conclusion: Recalls for calcifications are much more likely to undergo biopsy compared with other findings. Increased biopsy rates for calcifications should be considered when recalling a patient from mammography screening in the context of practice specific positive predictive values and cancer detection rates. © 2018 Elsevier Inc.
Keywords: breast cancer; biopsy; electronic medical record; mammography; screening; bone; medical computing; positive predictive values; diseases; statistically significant difference; mammography screening; calcifications; calcification (biochemistry); biomineralization; architectural distortions; recalls; screening examinations
Journal Title: Clinical Imaging
Volume: 53
ISSN: 0899-7071
Publisher: Elsevier Inc.  
Date Published: 2019-01-01
Start Page: 151
End Page: 154
Language: English
DOI: 10.1016/j.clinimag.2018.09.016
PROVIDER: scopus
PUBMED: 30340079
Notes: Article -- Export Date: 1 November 2018 -- Source: Scopus
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MSK Authors
  1. Elizabeth A Morris
    242 Morris
  2. Victoria Lee Mango
    14 Mango