High BMI, delayed wound healing and axillary surgery are risk factors for lower patient satisfaction. This first publication reporting the whole dataset for the BREAST-Q BCT will serve as a benchmark for future studies of patient satisfaction following BCT.
Background
The B-MaP-C study aimed to determine alterations to breast cancer (BC) management during the peak transmission period of the UK COVID-19 pandemic and the potential impact of these treatment decisions.
Methods
This was a national cohort study of patients with early BC undergoing multidisciplinary team (MDT)-guided treatment recommendations during the pandemic, designated ‘standard’ or ‘COVID-altered’, in the preoperative, operative and post-operative setting.
Findings
Of 3776 patients (from 64 UK units) in the study, 2246 (59%) had ‘COVID-altered’ management. ‘Bridging’ endocrine therapy was used (n = 951) where theatre capacity was reduced. There was increasing access to COVID-19 low-risk theatres during the study period (59%). In line with national guidance, immediate breast reconstruction was avoided (n = 299). Where adjuvant chemotherapy was omitted (n = 81), the median benefit was only 3% (IQR 2–9%) using ‘NHS Predict’. There was the rapid adoption of new evidence-based hypofractionated radiotherapy (n = 781, from 46 units). Only 14 patients (1%) tested positive for SARS-CoV-2 during their treatment journey.
Conclusions
The majority of ‘COVID-altered’ management decisions were largely in line with pre-COVID evidence-based guidelines, implying that breast cancer survival outcomes are unlikely to be negatively impacted by the pandemic. However, in this study, the potential impact of delays to BC presentation or diagnosis remains unknown.
Breast density is a significant predictor in the risk of developing breast cancer. Several methods are available for assessing breast density, but most are subject to intra-observer variability and are unable to assess the breast as a three-dimensional structure. Using Quantra(™) to quantify breast density, we have correlated this with risk factors to determine what impact these variables have on breast density. Women attending for full field digital mammography at the South West London Breast Screening Unit between December 2008 and March 2009 were invited to participate in the study by questionnaire. Consenting women returned the questionnaire allowing further data collection including demographics, menopausal status and hormone replacement therapy (HRT) use. Data were correlated against breast density measurements to determine the degree of association. Mammograms were assessed on a Hologic(™) workstation and breast density calculated using Quantra(™). Quantra(™) is an automated algorithm for volumetric assessment of breast tissue composition from digital mammograms. Six-hundred and eighty-three women were invited to participate. Those with implants or mastectomy were excluded. Three-hundred and twenty questionnaires were fully completed and able to be assessed. The mean age of participants was 59 years (range 49-81). Mean density was 19.7% (range 8.5-48.5%). There was a decrease in density with age (Pearson product-moment correlation coefficient -0.17). Correlation between density and HRT use showed a significant positive result (correlation coefficient 0.07). Quantra(™) has shown to be an accurate, reproducible tool for quantifying breast density, demonstrated by its correlation with lifestyle and demographic data. Given its ease of acquisition this may be the future of breast density quantification in the digital age.
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