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

Journal Article · · International Journal of Radiation Oncology, Biology and Physics
 [1];  [2];  [3];  [4];  [5]; ;  [6];  [7]
  1. Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan (United States)
  2. Department of Radiation Oncology, Summa Health System, Akron, Ohio (United States)
  3. Department of Therapeutic Radiology, Yale School of Medicine, Norwich, Connecticut (United States)
  4. Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas (United States)
  5. Department of Radiation Oncology, Michigan Healthcare Professionals/21st Century Oncology, Farmington, Michigan (United States)
  6. Biostat International Inc, Tampa, Florida (United States)
  7. Department of Surgery, Dallas Breast Center, Dallas, Texas (United States)

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.

OSTI ID:
22458597
Journal Information:
International Journal of Radiation Oncology, Biology and Physics, Vol. 91, Issue 2; Other Information: Copyright (c) 2015 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0360-3016
Country of Publication:
United States
Language:
English