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Int J Radiat Oncol Biol Phys. 2015 Feb 1;91(2):312-8. doi: 10.1016/j.ijrobp.2014.09.029. Epub 2014 Nov 11.

Nomogram for predicting the risk of locoregional recurrence in patients treated with accelerated partial-breast irradiation.

Author information

1
Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan.
2
Department of Radiation Oncology, Beaumont Health System, Royal Oak, Michigan. Electronic address: PChen@beaumont.edu.
3
Department of Radiation Oncology, Summa Health System, Akron, Ohio.
4
Department of Therapeutic Radiology, Yale School of Medicine, Norwich, Connecticut.
5
Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas.
6
Department of Radiation Oncology, Michigan Healthcare Professionals/21st Century Oncology, Farmington, Michigan.
7
Biostat International Inc, Tampa, Florida.
8
Department of Surgery, Dallas Breast Center, Dallas, Texas.

Abstract

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.

PMID:
25446607
DOI:
10.1016/j.ijrobp.2014.09.029
[Indexed for MEDLINE]

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