scholarly journals Patterns of Locoregional Recurrence in Breast Cancer After Optimal Multimodality Treatment

2016 ◽  
Vol 96 (2) ◽  
pp. E25
Author(s):  
R.A. Vadgonkar ◽  
T. Wadasadawala ◽  
S. Chakraborty ◽  
A. Budrukkar ◽  
R. Jalali ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Locoregional Recurrence ◽  
Multimodality Treatment

scholarly journals Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model

2021 ◽  
Author(s):  
Vinzenz Völkel ◽  
Tom A. Hueting ◽  
Teresa Draeger ◽  
Marissa C. van Maaren ◽  
Linda de Munck ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Locoregional Recurrence ◽  
Clinical Decision Making ◽  
Metastatic Breast ◽  
Distant Metastases ◽  
Time Dependent ◽  
Individual Risk ◽  
Primary Tumors ◽  
Statistical Approaches

Abstract Purpose To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches. Methods Data on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples. Results Age, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74–0.76) and SP (0.67, 95%CI: 0.65–0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77–0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created. Conclusions INFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients.

scholarly journals About locoregional recurrence risk after lipofilling in breast cancer patients

2012 ◽  
Vol 23 (3) ◽  
pp. 802-803 ◽  
Author(s):  
G. Semprini ◽  
F. Cattin ◽  
L. Lazzaro ◽  
C. Cedolini ◽  
P.C. Parodi
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Locoregional Recurrence ◽  
Recurrence Risk ◽  
Breast Cancer Patients

scholarly journals Treatment results of breast cancer patients with locoregional recurrence after mastectomy

2013 ◽  
Vol 31 (3) ◽  
pp. 138 ◽  
Author(s):  
Yuri Jeong ◽  
Su Ssan Kim ◽  
Gyungyub Gong ◽  
Hee Jin Lee ◽  
Sei Hyun Ahn ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Locoregional Recurrence ◽  
Breast Cancer Patients ◽  
Treatment Results
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