Assessing Mode of Recurrence in Breast Cancer to Identify an Optimised Follow-Up Pathway: 10-Year Institutional Review.

BACKGROUND: Breast cancer surveillance programmes ensure early identification of recurrence which maximises overall survival. Programmes include annual clinical examination and radiological assessment. There remains debate around the value of annual clinical exam in diagnosing recurrent disease/second primaries. The aim was to assess diagnostic modalities for recurrent breast cancer with a focus on evaluating the role of annual clinical examination. PATIENTS AND METHODS: A prospectively maintained database from a symptomatic breast cancer service between 2010-2020 was reviewed. Patients with biopsy-proven recurrence/second breast primary were included. The primary outcome was the diagnostic modality by which recurrences/secondary breast cancers were observed. Diagnostic modalities included (i) self-detection by the patient, (ii) clinical examination by a breast surgeon or (iii) radiological assessment. RESULTS: A total of 233 patients were identified and, following application of exclusion criteria, a total of 140 patients were included. A total of 65/140 (46%) patients were diagnosed clinically, either by self-detection or clinical examination, while 75/140 (54%) were diagnosed radiologically. A total of 59/65 (91%) of patients clinically diagnosed with recurrence presented to the breast clinic after self-detection of an abnormality. Four (6%) patients had cognitive impairment and recurrence was diagnosed by a carer. Two (3%) patients were diagnosed with recurrence by a breast surgeon at clinical examination. The median time to recurrence in all patients was 48 months (range 2-263 months). CONCLUSION: Clinical examination provides little value in diagnosing recurrence (< 5%) and surveillance programmes may benefit from reduced focus on such a modality. Regular radiological assessment and ensuring patients have urgent/easy access to a breast clinic if they develop new symptoms/signs should be the focus of surveillance programmes.

Interspecific variation in the spatially-explicit risks of trace metals to songbirds.

Many wild animals can be adversely affected by trace metals around point sources but little is known about the risks to birds across their ranges. Trace metals in the soil are ubiquitously, if heterogeneously distributed, across the world due to natural and anthropogenic sources. Here, we built, parameterized and applied a spatially explicit modelling framework to determine the risks of soil-associated metals to 30 invertebrate-consuming passerine species across their spatial distribution in England and Wales. The model uses a risk characterization approach to assess the risks of soil-associated metals. Various monitoring datasets were used as input parameters: soil metal concentrations in England and Wales, bird spatial distribution; bird diet, bioaccumulation and toxicity data were extracted from the literature. Our model highlights significant differences in toxicity risks from Cd, Cu, Pb and Zn across the UK distributions of different species; Pb and Zn posed risks to all species across most of species' distributions, with more localised risks to some species of conservation concern from Cd and Cu. No single taxa of invertebrate prey drove avian exposure to metal toxicity. Adults were found to be at higher risk from Pb and Zn toxicity across their distributions than nestlings. This risk was partially driven by diet, with age differences in diets identified. Our spatially explicit model allowed us to identify areas of each species' national distribution in which the population was at risk. Overall, we determined that for all species studied an average of 32.7 ±â€¯0.2%, 8.0 ±â€¯0.1%, 86.1 ±â€¯0.1% and 93.2 ±â€¯0.1% of the songbird spatial distributions in the UK were characterized at risk of Cd, Cu, Pb and Zn, respectively. Despite some limitations, our spatially explicit model helps in understanding the risks of metals to wildlife and provides an efficient method of prioritising areas, contaminants and species for environmental risk assessments. The model could be further evaluated using a targeted monitoring dataset of metal concentration in bird tissues. Our model can assess and communicate to stakeholders the potential risks of environmental contaminants to wildlife species at a national and potentially international scale.