Related Experiment Video
Updated: Jan 8, 2026
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Trends in local, regional and contralateral breast tumor recurrence within five years after diagnosis in the
J Meijer1, H J G D van den Bongard2, L B Koppert3
1Department of Research and Development, Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, the Netherlands; Department of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, the Netherlands.
Background:
The objective was to provide an overview of trends in five-year local recurrence (LR), regional recurrence (RR) and contralateral breast cancer (CBC) rates in the Netherlands from 2003 to 2008 and 2012-2016.
Methods:
Women ≥18 years diagnosed with primary early breast cancer between 2003-2008 and 2012-2016 in the Netherlands were included. LR was defined as invasive tumor on the same side as the primary breast cancer. RR was defined as regional lymph node metastasis. CBC was defined as second primary invasive breast tumor in the contralateral breast. Five-year LR, RR and CBC rates were calculated and stratified for age, stage, subtype, and grade.
Results:
Of the 121347 included patients, 5618 were diagnosed with a LR, RR or CBC. Five-year LR, RR and CBC rates decreased from 3.3 %, 1.9 % and 2.2 % in 2003 to 1.5 %, 1.6 % and 1.5 % in 2016, respectively, with fluctuations over the years. Slight increases were observed in RR rates for stage II-III, HR-/HER2+ and HR-/HER2-.
Conclusion:
(s). The observed overall decline in LR, RR and CBC rates could reflect more effective and personalized breast cancer treatment. Our results provide realistic insights in LR, RR and CBC rates and might contribute to further optimization of treatment and surveillance strategies.
More Related Videos
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
06:03Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
Published on: February 6, 2020
