SS
Sabine Siesling
9 records found
1
Background: In the Netherlands, the COVID-19 pandemic resulted in a temporary halt of population screening for cancer and limited hospital capacity for non-COVID care. We aimed to investigate the impact of the pandemic on the in-hospital diagnostic pathway of breast cancer (BC) a
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Background: Individualized treatment in older patients with breast cancer can be improved by including comorbidity and other-cause mortality in prediction tools, as the other-cause mortality risk strongly increases with age. However, no optimal comorbidity score is established fo
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Impact of Older Age and Comorbidity on Locoregional and Distant Breast Cancer Recurrence
A Large Population-Based Study
Background: Studies have demonstrated worse breast cancer-specific mortality with older age, despite an increasing risk of dying from other causes due to comorbidity (competing mortality). However, findings on the association between older age and recurrence risk are inconsistent
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Delayed time to chemotherapy (TTC) is associated with decreased outcomes of breast cancer patients. Recently, studies suggested that the association might be subtype-dependent and that TTC within 30 days should be warranted in patients with triple-negative breast cancer (TNBC). T
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Background: Surgery is increasingly being omitted in older patients with operable breast cancer in the Netherlands. Although omission of surgery can be considered in frail older patients, it may lead to inferior outcomes in non-frail patients. Therefore, the aim of this study was
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Hospital transfer after a breast cancer diagnosis
A population-based study in the Netherlands of the extent, predictive characteristics and its impact on time to treatment
Purpose: Patients may transfer of hospital for clinical reasons but this may delay time to treatment. The purpose of this study is to provide insight in the extent of hospital transfer in breast cancer care; which type of patients transfer and what is the impact on time to treatm
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Purpose: In the Netherlands, radiotherapy after breast-conserving surgery (BCS) is omitted in up to 30% of patients aged ≥ 75 years. Although omission of radiotherapy is considered an option for older women treated with endocrine treatment, the majority of these patients do not r
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Purpose. For individualized follow-up, accurate prediction of locoregional recurrence (LRR) and second primary (SP) breast cancer risk is required. Current prediction models employ regression, but with large data sets, machine-learning techniques such as Bayesian Networks (BNs) m
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