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A Model to Predict the Risk of Upgrade to Malignancy at Surgery in Atypical Breast Lesions Discovered on Percutaneous Biopsy Specimens

  • Breast Oncology
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

When any atypical feature is identified on a percutaneous biopsy specimen of a suspicious breast lesion, surgical excision is mandatory, leading to unnecessary surgeries in 70–90 % of the cases. The purpose of this study was to develop a model to predict the presence of cancer at surgery that would be applicable to all atypical lesions.

Methods

We collected complete clinical, radiological, and double-reading histological data concerning all patients with a diagnosis of a pure atypical lesion on image-guided biopsy performed at the One-Stop Breast Care Unit between 2004 and 2011.

Results

Among the 204 eligible patients, 49 cancers (24 %) had been diagnosed at definitive surgery (20 ductal carcinoma in situ, 20 invasive ductal, and 9 invasive lobular carcinoma). The univariate analysis retrieved age (p = 0.03), the focus size in mm (p = 0.02), the number of biopsy cores (p = 0.02), the disappearance of radiological anomalies after biopsy (p = 0.05), the mean number of atypical foci (p = 0.05) and the percentage of atypical lobules and ducts for lobular neoplasia (p = 0.04) as factors associated with cancer at surgery, whereas neither Ki67 nor ALDH1 expression was significantly correlated. The final most informative nomogram comprised information on patient age, the disappearance of radiological anomalies after biopsy and a focus size >15 mm. For the optimal threshold (risk of cancer = 21 %), sensitivity, specificity, positive predictive value, and negative predictive value were 78, 66, 36, and 90 %, respectively.

Conclusions

After validation, this model could help to identify a subset of patients with premalignant disease who could be spared surgery.

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Acknowledgment

The authors thank Lorna Saint Ange for editing and Ariane Dunant for statistical reviewing.

Conflict of interest

The authors have no conflicts of interest and no financial disclosure to declare.

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Authors and Affiliations

  1. Department of Surgery, Institut Gustave Roussy and University Paris Sud, Villejuif Cedex, France

    Catherine Uzan MD, PhD & Chafika Mazouni MD, PhD

  2. Department of Pathology, Institut Gustave Roussy, Villejuif, France

    Malek Ferchiou MD, Marie-Christine Mathieu MD & Philippe Vielh MD

  3. Department of Imaging, Institut Gustave Roussy, Villejuif, France

    Laura Ciolovan MD & Corinne Balleyguier MD

  4. Integrated Biobank, Institut Gustave Roussy, Villejuif, France

    Philippe Vielh MD

  5. Department of Medical Oncology, Institut Gustave Roussy, Villejuif, France

    Suzette Delaloge MD

  6. Breast Cancer Unit, Institut Gustave Roussy, Villejuif, France

    Catherine Uzan MD, PhD, Chafika Mazouni MD, PhD, Malek Ferchiou MD, Laura Ciolovan MD, Corinne Balleyguier MD, Marie-Christine Mathieu MD, Philippe Vielh MD & Suzette Delaloge MD

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  1. Catherine Uzan MD, PhD
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  2. Chafika Mazouni MD, PhD
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  3. Malek Ferchiou MD
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Correspondence to Catherine Uzan MD, PhD.

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Uzan, C., Mazouni, C., Ferchiou, M. et al. A Model to Predict the Risk of Upgrade to Malignancy at Surgery in Atypical Breast Lesions Discovered on Percutaneous Biopsy Specimens. Ann Surg Oncol 20, 2850–2857 (2013). https://doi.org/10.1245/s10434-013-2989-3

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  • DOI: https://doi.org/10.1245/s10434-013-2989-3

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