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28-10-2017 | Ductal carcinoma in situ | Article

Clinical risk score to predict likelihood of recurrence after ductal carcinoma in situ treated with breast-conserving surgery

Journal:
Breast Cancer Research and Treatment

Authors: Rinaa S. Punglia, Wei Jiang, Stuart R. Lipsitz, Melissa E. Hughes, Stuart J. Schnitt, Michael J. Hassett, Larissa Nekhlyudov, Ninah Achacoso, Stephen Edge, Sara H. Javid, Joyce C. Niland, Richard L. Theriault, Yu-Ning Wong, Laurel A. Habel

Publisher: Springer US

Abstract

Purpose

A majority of women with ductal carcinoma in situ (DCIS) receive breast-conserving surgery (BCS) but then face a risk of ipsilateral breast tumor recurrence (IBTR) which can be either recurrence of DCIS or invasive breast cancer. We developed a score to provide individualized information about IBTR risk to guide treatment decisions.

Methods

Data from 2762 patients treated with BCS for DCIS at centers within the National Comprehensive Cancer Network (NCCN) were used to identify statistically significant non-treatment-related predictors for 5-year IBTR. Factors most associated with IBTR were estrogen-receptor status of the DCIS, presence of comedo necrosis, and patient age at diagnosis. These three parameters were used to create a point-based risk score. Discrimination of this score was assessed in a separate DCIS population of 301 women (100 with IBTR and 200 without) from Kaiser Permanente Northern California (KPNC).

Results

Using NCCN data, the 5-year likelihood of IBTR without adjuvant therapy was 9% (95% CI 5–12%), 23% (95% CI 13–32%), and 51% (95% CI 26–75%) in the low, intermediate, and high-risk groups, respectively. Addition of the risk score to a model including only treatment improved the C-statistic from 0.69 to 0.74 (improvement of 0.05). Cross-validation of the score resulted in a C-statistic of 0.76. The score had a c-statistic of 0.67 using the KPNC data, revealing that it discriminated well.

Conclusions

This simple, no-cost risk score may be used by patients and physicians to facilitate preference-based decision-making about DCIS management informed by a more accurate understanding of risks.

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