4.7 Article

Nomogram for Predicting the Risk of Local Recurrence After Breast-Conserving Surgery for Ductal Carcinoma In Situ

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JOURNAL OF CLINICAL ONCOLOGY
卷 28, 期 23, 页码 3762-3769

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AMER SOC CLINICAL ONCOLOGY
DOI: 10.1200/JCO.2009.26.8847

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Purpose While the mortality associated with ductal carcinoma in situ (DCIS) is minimal, the risk of ipsilateral breast tumor recurrence (IBTR) after breast-conserving surgery (BCS) is relatively high. Radiation therapy (RT) and antiestrogen agents reduce the risk of IBTR and are considered standard treatment options after BCS. However, they have never been proven to improve survival, and in themselves carry rare but serious risks. Individualized estimation of IBTR risk would assist in decision making regarding the various treatment options for women with DCIS. Patients and Methods From 1991 to 2006, 1,868 consecutive patients treated with BCS for DCIS were identified. A multivariate Cox proportional hazards model was constructed using the 1,681 in whom data were complete. Ten clinical, pathologic, and treatment variables were built into a nomogram estimating probability of IBTR at 5 and 10 years after BCS. The model was validated for discrimination and calibration using bootstrap resampling. Results The DCIS nomogram for prediction of 5- and 10-year IBTR probabilities demonstrated good calibration and discrimination, with a concordance index of 0.704 (bootstrap corrected, 0.688) and a concordance probability estimate of 0.686. Factors with the greatest influence on risk of IBTR in the model included adjuvant RT or endocrine therapy, age, margin status, number of excisions, and treatment time period. Conclusion The DCIS nomogram integrates 10 clinicopathologic variables to provide an individualized risk estimate of IBTR in a woman with DCIS treated with BCS. This tool may assist in individual decision making regarding various treatment options and help avoid over-and undertreatment of noninvasive breast cancer. J Clin Oncol 28: 3762-3769. (C) 2010 by American Society of Clinical Oncology

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