Scottish COVID CAncer iMmunity Prevalence (SCCAMP) - a longitudinal study of patients with cancer receiving active anti-cancer treatment during the COVID-19 pandemic

BackgroundCancer and systemic anti-cancer treatment (SACT) have been identified as possible risk factors for infection and related severe illness associated with SARS-CoV-2 virus as a consequence of immune suppression. The Scottish COVID CAncer iMmunity Prevalence (SCCAMP) study aims to characterise the incidence and outcomes of SARS-Cov-2 infection in patients undergoing active anti-cancer treatment during the COVID-19 pandemic and their antibody response following vaccination. Patients and MethodsEligible patients were those attending secondary care for active anti-cancer treatment for a solid tumour. Blood samples were taken for total SARS-CoV-2 antibody assay (Siemens) at baseline and after 1.5, 3, 6 and 12 months. Data on COVID-19 infection, vaccination, cancer type, treatment and outcome was obtained from routine electronic health records. ResultsThe study recruited 766 eligible participants between 28th May 2020 and 31st October 2021. The median age was 62.7 years, and 66.5% were female. Most received cytotoxic chemotherapy (79%), with the remaining 14% receiving immunotherapy and 7% receiving another form of anti-cancer therapy (radiotherapy, other systemic anti-cancer treatment). 48 (6.3%) tested positive for SARS-CoV-2 by PCR during the study period. The overall infection rate matched that of the age-matched local general population until May 2021, after which population levels appeared higher. Antibody testing detected additional evidence of infection prior to vaccination, taking the total number to 58 (7.6%). There was no significant difference in SARS-CoV-2 PCR positive test rates based on type of anti-cancer treatment. Mortality proportion was similar between those who died within 90 days of a positive SARS-CoV-2 PCR and those with no positive PCR (10.4% vs 10.6%). Death from all causes was lowest among vaccinated patients, and of the patients who had a positive SARS-CoV-2 PCR at any time, all of those who died during the study period were unvaccinated. Multivariate analysis correcting for age, gender, socioeconomic status, comorbidities and number of previous medications revealed that vaccination was associated with a significantly lower infection rate regardless of treatment with chemotherapy or immunotherapy with hazard ratios of 0.307 (95% CI 0.144-0.6548) or 0.314 (95% CI 0.041-2.367) in vaccinated patients respectively. Where antibody data was available, 96.3% of patients successfully raised SARS-CoV-2 antibodies at a time point after vaccination. This was unaffected by treatment type. ConclusionSCCAMP provides real-world evidence that patients with cancer undergoing SACT have a high antibody response and protection from SARS-CoV-2 infection following COVID-19 vaccination. Highlights- The SCCAMP dataset represents the largest longitudinal study of patients with cancer undergoing anti-cancer treatment during the COVID-19 pandemic - Rates of infection in the cancer cohort mirrored those of the local age adjusted population - Vaccination was effective in patients with cancer undergoing active treatment in terms of antibody response and SARS-CoV-2 PCR rates - Treatment type did not impact the rate of SARS-CoV-2 antibody response

Modelling the Long-Term Effects of Covid-19 Cancer Services Disruption on Patient Outcome in Scotland

BackgroundModelling the long-term effects of disruption of cancer services and minimising any excess cancer mortality due to the Covid-19 pandemic is of great importance. Here we adapted a stage-shift model to inform service planning decisions within NHS Scotland for the Detect Cancer Early tumours, breast, colorectal and lung cancer which represent 46% of all cancers diagnosed in Scotland. Methods & DataLung, colorectal and breast cancer incidence data for years 2017-18 were obtained from Public Health Scotland Cancer Quality Performance Indicators (QPI), to define a baseline scenario. The most current stage-specific 5-year survival data came from 2009-2014 national cancer registry and South East Scotland Cancer Network (SCAN) QPI audit datasets. The Degeling et al., inverse stage-shift model was adapted to estimate changes in stage at diagnosis, excess mortality and life-years lost from delays to diagnosis and treatment due to Covid-19-related health services disruption. Three and 6-month periods of disruption were simulated to demonstrate the model predictions. ResultsApproximately, 1-9% reductions in stage I/II presentations leading up to 2-10% increases in stage III/IV presentations are estimated across the three cancer types. A 6-month period of service disruption is predicted to lead to excess deaths at 5 years of 32.5 (31.1, 33.9) per 1000 cases for lung cancer, 16.5 (7.9, 24.3) for colorectal cancer and 31.6 (28.5, 34.4) for breast cancer. ConclusionsDisruption of cancer diagnostic services can lead to significant excess deaths in following years. Increasing diagnostic and capacity for cancer services to deal with the backlog of care are needed. Real time monitoring of incidence and referral patterns over the disruption and post-disruption period to reduce excess deaths including more rapid incidence data by stage and other key tumour/clinical characteristics at presentation for key cancer cases (on a quarterly basis). Real time monitoring in cancer care and referral patterns should help inform what type of interventions are needed to reduce excess mortality and whether different population subgroups require public health messaging campaigns. Specific mitigation measures can be the subject of additional modelling analysis to assess the benefits and inform service planning decision making.

The 4C Initiative (Clinical Care for Cardiovascular disease in the COVID-19 pandemic): monitoring the indirect impact of the coronavirus pandemic on services for cardiovascular diseases in the UK

BackgroundThe coronavirus (COVID-19) pandemic affects cardiovascular diseases (CVDs) directly through infection and indirectly through health service reorganisation and public health policy. Real-time data are needed to quantify direct and indirect effects. We aimed to monitor hospital activity for presentation, diagnosis and treatment of CVDs during the pandemic to inform on indirect effects. MethodsWe analysed aggregate data on presentations, diagnoses and treatments or procedures for selected CVDs (acute coronary syndromes, heart failure, stroke and transient ischaemic attack, venous thromboembolism, peripheral arterial disease and aortic aneurysm) in UK hospitals before and during the COVID-19 epidemic. We produced an online visualisation tool to enable near real-time monitoring of trends. FindingsNine hospitals across England and Scotland contributed hospital activity data from 28 Oct 2019 (pre-COVID-19) to 10 May 2020 (pre-easing of lockdown), and for the same weeks during 2018-2019. Across all hospitals, total admissions and emergency department (ED) attendances decreased after lockdown (23 March 2020) by 57.9% (57.1-58.6%) and 52.9% (52.2-53.5%) respectively compared with the previous year. Activity for cardiac, cerebrovascular and other vascular conditions started to decline 1-2 weeks before lockdown, and fell by 31-88% after lockdown, with the greatest reductions observed for coronary artery bypass grafts, carotid endarterectomy, aortic aneurysm repair and peripheral arterial disease procedures. Compared with before the first UK COVID-19 (31 January 2020), activity declined across diseases and specialties between the first case and lockdown (total ED attendances RR 0.94, 0.93-0.95; total hospital admissions RR 0.96, 0.95-0.97) and after lockdown (attendances RR 0.63, 0.62-0.64; admissions RR 0.59, 0.57-0.60). There was limited recovery towards usual levels of some activities from mid-April 2020. InterpretationSubstantial reductions in total and cardiovascular activities are likely to contribute to a major burden of indirect effects of the pandemic, suggesting they should be monitored and mitigated urgently. FundingBritish Heart Foundation, Health Data Research UK

TRACKing Excess Deaths (TRACKED): an interactive online tool to monitor excess deaths associated with COVID-19 pandemic in the United Kingdom

BackgroundWe aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality. MethodsPopulation statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly data on deaths. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. Crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated. Excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years. ResultsThere were 56,961 excess deaths and 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends (http://trackingexcessdeaths.com). ConclusionsContinuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.

Trends in excess cancer and cardiovascular deaths in Scotland during the COVID-19 pandemic 30 December 2019 to 20 April 2020

Understanding the trends in causes of death for different diseases during the current COVID-19 pandemic is important to determine whether there are excess deaths beyond what is normally expected. Using the most recent report from National Records Scotland (NRS) on 29 April 2020, we examined the percentage difference in crude numbers of deaths in 2020 compared to the average for 2015-2019 by week of death within calendar year. To determine if trends were similar, suggesting underreporting/underdiagnosed COVID-19 related deaths, we also looked at the trends in % differences for cardiovascular disease deaths. From the first 17 weeks of data, we found a peak in excess deaths at week 14 of 2020, about four weeks after the first case in Scotland was detected on 1 March 2020-- but by week 17 these excesses had returned to normal levels, 4 weeks after lockdown in the UK began. Similar observations were seen for cardiovascular disease-related deaths. These observations suggest that the short-term increase in excess cancer and cardiovascular deaths might be associated with undetected/unconfirmed deaths related to COVID-19. Both of these conditions make patients more susceptible to infection and lack of widespread access to testing for COVID-19 are likely to have resulted in under-estimation of COVID-19 mortality. These data further suggest that the cumulative toll of COVID-19 on mortality is likely undercounted. More detailed analysis is needed to determine if these excesses were directly or indirectly related to COVID-19. Disease specific mortality will need constant monitoring for the foreseeable future as changes occur in increasing capacity and access to testing, reporting criteria, changes to health services and different measures are implemented to control the spread of the COVID-19. Multidisciplinary, multi-institutional, national and international collaborations for complementary and population specific data analysis is required to respond and mitigate adverse effects of the COVID-19 pandemic and to inform planning for future pandemics.