Nomogram for Predicting the Risk of Locoregional Recurrence in Patients Treated With Accelerated Partial-Breast Irradiation

Purpose To develop a nomogram taking into account clinicopathologic features to predict locoregional recurrence (LRR) in patients treated with accelerated partial-breast irradiation (APBI) for early-stage breast cancer. Methods and Materials A total of 2000 breasts (1990 women) were treated with APB...

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Published inInternational journal of radiation oncology, biology, physics Vol. 91; no. 2; pp. 312 - 318
Main Authors Wobb, Jessica L., MD, Chen, Peter Y., MD, FACR, Shah, Chirag, MD, Moran, Meena S., MD, Shaitelman, Simona F., MD, Vicini, Frank A., MD, FACR, Mbah, Alfred K., PhD, Lyden, Maureen, MS, Beitsch, Peter, MD
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.02.2015
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Summary:Purpose To develop a nomogram taking into account clinicopathologic features to predict locoregional recurrence (LRR) in patients treated with accelerated partial-breast irradiation (APBI) for early-stage breast cancer. Methods and Materials A total of 2000 breasts (1990 women) were treated with APBI at William Beaumont Hospital (n=551) or on the American Society of Breast Surgeons MammoSite Registry Trial (n=1449). Techniques included multiplanar interstitial catheters (n=98), balloon-based brachytherapy (n=1689), and 3-dimensional conformal radiation therapy (n=213). Clinicopathologic variables were gathered prospectively. A nomogram was formulated utilizing the Cox proportional hazards regression model to predict for LRR. This was validated by generating a bias-corrected index and cross-validated with a concordance index. Results Median follow-up was 5.5 years (range, 0.9-18.3 years). Of the 2000 cases, 435 were excluded because of missing data. Univariate analysis found that age <50 years, pre-/perimenopausal status, close/positive margins, estrogen receptor negativity, and high grade were associated with a higher frequency of LRR. These 5 independent covariates were used to create adjusted estimates, weighting each on a scale of 0-100. The total score is identified on a points scale to obtain the probability of an LRR over the study period. The model demonstrated good concordance for predicting LRR, with a concordance index of 0.641. Conclusions The formulation of a practical, easy-to-use nomogram for calculating the risk of LRR in patients undergoing APBI will help guide the appropriate selection of patients for off-protocol utilization of APBI.
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ISSN:0360-3016
1879-355X
DOI:10.1016/j.ijrobp.2014.09.029