Breast cancer management pathways during the COVID-19 pandemic: outcomes from the UK ‘Alert Level 4’ phase of the B-MaP-C study

Abstract: 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

An LP Planning Model for a Mental Health Community Support System

In this paper we develop a resource planning and allocation model for a mental-health community-support system. The intent of the model is to provide a tool to system managers and planners to support resource planning and allocation decision-making. More and more, mental health care is being delivered by a variety of community-based service agencies instead of single, comprehensive institutions. The service needs of a client population are continually changing, and depend upon the relative functioning of the population, which depends upon the efficacy of the services provided. The availability of resources is becoming scarcer, and is more closely scrutinized. Consequently, the system manager must attempt to apply the available resources as effectively as possible. We develop a conceptual framework for planning that includes aggregating patients according to their functional level and service needs, and defining "service package options" for each aggregate patient group. We also estimate the effect of giving a particular service package to a patient group, in terms of functional improvement or regression. The planning problem is then to assign service packages to aggregate groups over a multi-period planning horizon to maximize some measure of system welfare within the available resources. This planning problem is a linear programming problem that we illustrate using representative data.health care: treatment, linear programming: applications, mental health resource planning