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OBJECTIVES: Following the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and the subsequent global spread of the 2019 novel coronavirus disease (COVID-19), health systems and the populations who use them have faced unprecedented challenges. We aimed to measure the impact of COVID-19 on the uptake of hospital-based care at a national level. DESIGN: The study period (weeks ending 5 January to 28 June 2020) encompassed the pandemic announcement by the World Health Organization and the initiation of the UK lockdown. We undertook an interrupted time-series analysis to evaluate the impact of these events on hospital services at a national level and across demographics, clinical specialties and National Health Service Health Boards. SETTING: Scotland, UK. PARTICIPANTS: Patients receiving hospital care from National Health Service Scotland. MAIN OUTCOME MEASURES: Accident and emergency (A&E) attendances, and emergency and planned hospital admissions measured using the relative change of weekly counts in 2020 to the averaged counts for equivalent weeks in 2018 and 2019. RESULTS: Before the pandemic announcement, the uptake of hospital care was largely consistent with historical levels. This was followed by sharp drops in all outcomes until UK lockdown, where activity began to steadily increase. This time-period saw an average reduction of −40.7% (95% confidence interval [CI]: −47.7 to −33.7) in A&E attendances, −25.8% (95% CI: −31.1 to −20.4) in emergency hospital admissions and −60.9% (95% CI: −66.1 to −55.7) in planned hospital admissions, in comparison to the 2018–2019 averages. All subgroup trends were broadly consistent within outcomes, but with notable variations across age groups, specialties and geography. CONCLUSIONS: COVID-19 has had a profoundly disruptive impact on hospital-based care across National Health Service Scotland. This has likely led to an adverse effect on non-COVID-19-related illnesses, increasing the possibility of potentially avoidable morbidity and mortality. Further research is required to elucidate these impacts.

ObjectivesTo quantify the effect of the COVID-19 pandemic on the timeliness of, and geographical and sociodemographic inequalities in, receipt of first measles, mumps and rubella (MMR) vaccination.DesignLongitudinal study using primary care electronic health records.Setting285 general practices in North East London.ParticipantsChildren born between 23 August 2017 and 22 September 2018 (pre-pandemic cohort) or between 23 March 2019 and 1 May 2020 (pandemic cohort).Main outcome measureReceipt of timely MMR vaccination between 12 and 18 months of age.MethodsWe used logistic regression to estimate the ORs (95% CIs) of receipt of a timely vaccination adjusting for sex, deprivation, ethnic background and Clinical Commissioning Group. We plotted choropleth maps of the proportion receiving timely vaccinations.ResultsTimely MMR receipt fell by 4.0% (95% CI: 3.4% to 4.6%) from 79.2% (78.8% to 79.6%) to 75.2% (74.7% to 75.7%) in the pre-pandemic (n=33 226; 51.3% boys) and pandemic (n=32 446; 51.4%) cohorts, respectively. After adjustment, timely vaccination was less likely in the pandemic cohort (0.79; 0.76 to 0.82), children from black (0.70; 0.65 to 0.76), mixed/other (0.77; 0.72 to 0.82) or with missing (0.77; 0.74 to 0.81) ethnic background, and more likely in girls (1.07; 1.03 to 1.11) and those from South Asian backgrounds (1.39; 1.30 to 1.48). Children living in the least deprived areas were more likely to receive a timely MMR (2.09; 1.78 to 2.46) but there was no interaction between cohorts and deprivation (Wald statistic: 3.44; p=0.49). The proportion of neighbourhoods where less than 60% of children received timely vaccination increased from 7.5% to 12.7% during the pandemic.ConclusionsThe COVID-19 pandemic was associated with a significant fall in timely MMR receipt and increased geographical clustering of measles susceptibility in an area of historically low and inequitable MMR coverage. Immediate action is needed to avert measles outbreaks and support primary care to deliver timely and equitable vaccinations.

Background: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of patients with deficient DNA mismatch repair (d-MMR) metastatic colorectal cancer (CRC), yet less than half of patients receive clinical benefit. We hypothesized that immune contexture including spatial distribution of cells expressing immune molecules in the tumor microenvironment may predict immunotherapy outcome. Methods: Primary CRC tissues from consecutive patients with d-MMR metastatic CRC (N=33) were treated with anti-PD-1 antibodies at Mayo Clinic Comprehensive Cancer Center (2015-2018). Tumors were stained for PD-L1, PD-1, CD8, CD3, CD68, LAG3, TGFβR2, MHC-I, CD14, B2M, DAPI and pan-cytokeratin in 5 compartments (overall tumor, tumor epithelia, tumor stroma, peritumor inside vs outside) by multiplex immunofluorescence with digital image analysis. Features computed within each image analysis region included positive cell density, fraction of positive cell types, intensity of positive cells, and spatial distribution between distinct cell types (distances measured using image analysis software). Prior to model fitting, feature selection was performed using regularized Cox regression with LASSO. Regularization parameter was chosen based on 5-fold cross validation. A Cox proportional hazards model was fitted to predict patient progression-free survival (PFS). Results: Among patients with d-MMR CRCs, 16/33 (48.4%) were female, 10 received first-line ICI therapy, and 23 had received > 1 prior chemotherapy regimen. Median age was 61.6 years (IQR of 49.4, 73.7). Eight patients (24.2%) harbored BRAFV600E, 9 (27.2%) had mutant KRAS, and median PFS was 22.2 months (95% CI: 11.8, NR) with 20 events. PD-L1 was expressed in tumor cells, CD68+ macrophages, and CD3+ T lymphocytes. PD-1 expression on CD8+ T lymphocytes was also observed. By univariate analysis, only cell-cell distance readouts achieved statistical significance. Multivariable feature selection identified the mean number of PD-1+ cells within 10 microns of a PD-L1+ cell in the overall tumor as the strongest predictor of anti-PD-1 efficacy, and was significantly associated with PFS (HR=0.87, 95% CI: 0.79-0.95, p< 0.001). In contrast, the ratio of PD-1+/PD-L1+ cells was not predictive of treatment efficacy (p= 0.47), thereby underscoring the importance of spatial distribution for PFS prediction. Conclusion: The mean number of PD-1+ cells in proximity to PD-L1+ cells in tumors was a predictive biomarker of anti-PD-1 efficacy. Confirmatory studies are warranted. Citation Format: Bahar Saberzadeh-Ardestani, Rondell P. Graham, Qian Shi, Eze Ahanonu, Sara McMahon, Crystal Williams, Antony Hubbard, Wenjun Zhang, Andrea Muranyi, Dongyao Yan, Kandavel Shanmugam, Frank A. Sinicrope. Prediction of anti-PD-1 efficacy based on immune marker densities and their spatial distribution in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6648.