BENEFITS OF POST-OPERATIVE SPECIALIST GERIATRIC CARE FOR OLDER PATIENTS UNDERGOING ELECTIVE ORTHOPAEDIC SURGERY

Background: The Covid-19 pandemic changed work practices across many different healthcare institutions. The difficulties with cross-site transfers created an opportunity in our institution to provide on-site post-operative rehabilitation for older patients undergoing elective orthopaedic surgery. The aim of this study is to assess the impact of post-operative specialist geriatric care on older patients. Methods: This is a single-centre, retrospective study that received approval from the local hospital ethics committee. Data were collected on all patients admitted to the on-site specialist rehabilitation unit post-elective orthopaedic surgery between 1st May 2020 and 31st December 2021. Two patients in this group were excluded as they had not attended a pre-operative assessment clinic. Data were collected from hospital Information Technology platform, Bluespiers. Results: 76 patients, 18 males and 58 females, were included in this study. The median age was 80 years. In the specialist rehabilitation unit, evidence of cognitive impairment was established in 40.79% of cases, there were 3 cases of newly diagnosed dementia, a history of falls was identified in 32.89% of patients and 13.16% of patients were found to have sarcopaenia. The median length of stay in the rehabilitation unit was 25 days. 51.32% of patients were discharged home independently, 23.68% of patients went home with a new Home-Care Package (HCP), 15.79% of patients were discharged home with an existing HCP, 6.58% of patients were transferred for further treatment and 2.63% patients were discharged to residential care units. Conclusion: This data demonstrates a clear role for specialist geriatric care in elective rehabilitation, with a significant proportion of patients being discharged home independently. The benefits of a comprehensive geriatric assessment in the peri-operative setting include increased identification of cognitive impairment allowing appropriate implementation of brain health as well as identification of a history of falls, enabling falls risk assessment and management including bone health assessment.

Long-term survival in advanced melanoma for patients treated with nivolumab plus ipilimumab in CheckMate 067

Background: Durable clinical benefit has been achieved with nivolumab (NIVO) + ipilimumab (IPI), including an overall survival (OS) of 49% and a melanoma-specific survival (MSS) of 56%, with median MSS not reached (NR) at 6.5-y minimum follow-up. Here we report sustained efficacy outcomes at 7.5 y. Methods: Patients (pts) with previously untreated, unresectable stage III/IV melanoma were randomly assigned 1:1:1 and stratified by PD-L1 status, BRAF mutation status, and metastasis stage to receive NIVO 1 mg/kg + IPI 3 mg/kg for 4 doses Q3W, followed by NIVO 3 mg/kg Q2W (n = 314);NIVO 3 mg/kg Q2W + placebo (n = 316);or IPI 3 mg/kg Q3W for 4 doses + placebo (n = 315) until progression or unacceptable toxicity. Co-primary endpoints were progression-free survival (PFS) and OS with NIVO + IPI or NIVO alone versus IPI. Results: With a minimum follow-up of 7.5 y, median OS remained stable at 72.1 mo (NIVO + IPI), 36.9 mo (NIVO), and 19.9 mo (IPI);median MSS was NR, 49.4 mo, and 21.9 mo, respectively (Table). While the objective response rate remained stable at 58% (NIVO + IPI), 45% (NIVO), and 19% (IPI), median duration of response had now been reached for NIVO at 90.8 mo and remains NR and 19.2 mo for NIVO + IPI and IPI, respectively. Subsequent systemic therapy was received by 36%, 49%, and 66% of NIVO + IPI-, NIVO-, and IPI-treated patients, respectively, and median time to that therapy was NR (95% CI, 45.9-NR), 24.7 mo (16.0-38.7), and 8.0 mo (6.5-8.7). Of patients alive at 7.5 y, 106/138 (77%, NIVO + IPI), 80/115 (70%, NIVO), and 27/60 (45%, IPI) were off treatment and had never received subsequent systemic therapy. No change to the safety summary was observed with additional follow-up;updated health-related quality of life data will be reported. Of the 10 new deaths since the 6.5-y follow-up (ie, 5 NIVO + IPI;3 NIVO;2 IPI), none were treatment-related;4 were due to melanoma progression;1 was due to an unknown cause;and 5 were due to other causes, but not associated with a COVID diagnosis. Conclusions: The 7.5-y follow-up continues to demonstrate the durability of responses with NIVO + IPI and an ongoing survival plateau. A substantial difference in median OS and MSS between patients treated with NIVO + IPI or NIVO was observed in descriptive analyses.

EFFECTIVENESS OF COVID-19 VACCINES IN A LARGE EUROPEAN HAEMODIALYSIS COHORT

BACKGROUND AND AIMS: To date, no large-scale study has evaluated the effectiveness of COVID-19 vaccines in hemodialysis patients. We sought to evaluate the effectiveness of vaccines against SARS-CoV-2 infections and death in haemodialysis patients registered in the Fresenius Medical Care (FMC) Nephrocare network. METHOD: In this historical, 1:1 matched cohort study, we analysed electronic health records (EHR) of individuals receiving in-center haemodialysis therapy in FMC European dialysis clinics from 1 December 2020, to 31 May 2021 (study period). For each vaccinated patient, an unvaccinated patient was selected among patients registered in the same country and attending a dialysis session within +/-3 days from the vaccination date. Matching without replacement was based on demographics, clinical characteristics, past COVID-19 infections and a risk score representing the local (dialysis centre) background risk of infection at each vaccination date. The infection risk score was calculated from an artificial Intelligence model predicting the risk of COVID-19 outbreak in each clinic over a 2-week prediction horizon. The infection risk score was based on trends in regional COVID-19 epidemic metrics, FMC COVID-19 reporting system and clinical practice patterns. The index date was the date of the first vaccination for the vaccinated and the matching treatment date for the unvaccinated controls. To overcome violation of the proportional hazard assumption, we estimated the effectiveness of the COVID-19 vaccines in preventing infection and mortality rates as 1-hazard ratio estimated from a time-dependent extended Cox regression stratified by country and vaccine type. RESULTS: We included 44 458 patients, 22 229 vaccinated and matched 22 229 unvaccinated. Distribution of covariates was balanced across study arms after matching (Figure 1A). In the effectiveness analysis on mRNA vaccines, we observed 850 SARS-CoV-2 infections and 201 COVID19-related deaths among the 28 110 patients (14 055 vaccinated and 14 055 unvaccinated) during a mean follow up time of 44 ± 40 days. In the effectiveness analysis of viral-vector vaccines, we observed 297 SARS-CoV-2 infections and 64 COVID19-related deaths among 12 888 patients (6444 vaccinated and 6444 unvaccinated) during a mean a follow-up time of 48 ± 32 days (Figure 1B). We observed 18.5/100 patient-year and 8.5/100 patient-year fewer infections and 5.4/100 patient-year and 5.2/100 patient-year fewer COVID-19-related deaths among patients vaccinated with mRNA and viral-vector vaccines respectively, as compared to matched unvaccinated controls. The effectiveness of COVID-19 vaccines concerning both symptomatic infections and COVID-related death along the follow up period is shown in Figure 2. CONCLUSION: In this matched, historical cohort study, we observed a strong reduction in both SARS-CoV-2 symptomatic infection and COVID-19-related death among dialysis patients receiving an mRNA vaccine. Despite seemingly less protective against symptomatic infections, we observed similar reduction in COVID-19 mortality rate among patients receiving a viral-carrier vaccine. (Figure Presented).

MODIFIABLE AND NON-MODIFIABLE FACTORS ASSOCIATED WITH INCREASED COVID-19 RELATED MORTALITY AMONG DIALYSIS PATIENTS

BACKGROUND AND AIMS: Patients with end-stage kidney disease (ESKD) face higher risk for severe outcomes from COVID-19 infection. Moreover, it is not well known to which extent potentially modifiable risk factors contribute to mortality risk. In this study, we investigated the incidence and risk factors for 30-day case-fatality of COVID-19 in haemodialysis patients treated in the European Fresenius Medical Care (FMC) Nephrocare network. METHOD: In this historical cohort study, we included unvaccinated adult dialysis patients with a first documented SARS-CoV-2 infection between 1 February 2020 and 31 March 2021 (study period) registered in the European Clinical Database (EuCliD ® ). The first SARS-CoV-2 suspicion date for all documented infections was considered the index date for the analysis. Patients were followed for up to 30 days. Follow-up time was defined from the index date until the date of death, end of follow-up period or lost to follow-up, whichever occurred first. We ascertained patients' characteristics in the 6-month period prior to index date. We used logistic regression and XGBoost to assess risk factors for 30-day mortality. RESULTS: We included 9211 patients meeting the inclusion criteria for the study (Table 1). Age was 65.4 ± 13.7 years, dialysis vintage was 4.2 ± 3.7 years. In the follow up period, 1912 patients died within 30 days (20.8%, 95% confidence interval: 19.9%- 21.6%). Correlates of COVID-19 related mortality are summarized in Table 2. Several potentially modifiable factors were associated with increased risk of death: patients on HD compared with online haemodiafiltration had shorter survival after presentation with COVID-19 as well as those who did not achieve the therapeutic targets for serum albumin, erythropoietin resistance index, protein catabolic rate, haemodynamic status, C-reactive protein, single-pool Kt/V, hydration status and serum sodium in the months before infection. The discrimination accuracy of prediction models developed with XGBoost was similar to that observed for main-effect logistic regression (AUC 0.69 and 0.71, respectively) suggesting that no major cross-interaction and non-linear effect could improve prediction accuracy. CONCLUSION: We observed high 30-day COVID-19 related mortality among unvaccinated dialysis patients. Older patients, men and those with greater.

Adaptive immunity to SARS-CoV-2 in cancer patients: The CAPTURE study

There is a pressing need to characterise the nature, extent and duration of immune response to SARS-CoV-2 in cancer patients, to inform risk-reduction strategies and preserve cancer outcomes. CAPTURE is a prospective, longitudinal cohort study of cancer patients and healthcare workers (HCWs) integrating immune profiles and clinical annotation. We evaluated 529 blood samples and 1051 oronasopharyngeal swabs from 144 cancer patients and 73 HCWs and correlated with >200 clinical variables. In patients with solid cancers and HCWs, S1-reactive and neutralising antibodies to SARS-CoV-2 were detectable five months post-infection. In these participants, SARS-CoV-2-specific T-cell responses were detected. CD4+ T-cell response correlated with S1 antibody levels. Patients with haematological malignancies had impaired but partially compensated immune responses, depending on malignancy and therapy. Overall, cancer stage, disease status, and therapies did not correlate with immune responses. These findings have implications for understanding individual risks and potential effectiveness of SARS-CoV-2 vaccination in this population.

Denali, a phase 3B multicenter, open-label single-arm study of roxadustat: Operational learnings within us dialysis organizations

Background: Roxadustat is an oral hypoxia-inducible factor prolyl hydroxylase (HIF-PH) inhibitor that promotes erythropoiesis and improves iron availability in patients with anemia of chronic kidney disease (CKD). This trial aims to provide practical data on roxadustat use in dialysis patients with anemia via a semi-pragmatic evaluation of introduction into providers' practices (Fresenius Medical Care). Methods: This open-label, single-arm study assesses the efficacy and safety of roxadustat in correcting/maintaining hemoglobin (Hb) in patients with CKD-related anemia receiving in-center/home dialysis at nine US sites (NCT04410198). Initial roxadustat dose is weight-based (erythropoiesis-stimulating agent [ESA]-naïve patients) or guided by an ESA dose-conversion algorithm (ESA patients), in this trial targeting Hb=11±1 g/dL. Roxadustat dose is titrated every 4 weeks based on Hb level or rate of change, with 24-week treatment duration and up to 1-year extension. Efficacy is assessed by change from baseline in Hb and proportion of patients achieving mean Hb ≥10 g/dL averaged over weeks 16-24. Exploratory endpoints include time to first red blood cell transfusion, proportion of patients achieving mean Hb ≥10 g/dL in first 8 weeks, intravenous iron use, and dosing adherence. Safety endpoints include treatment-emergent adverse events (AE), with COVID-19 positivity an AE of special interest. Results: This ongoing trial was successfully initiated and enrolled (n=203) during the COVID-19 pandemic, with modifications for home dialysis. Baseline characteristics appear representative of the US dialysis population (Table). Conclusions: This trial adds to phase 3 studies of roxadustat by evaluating its use in treating anemia of CKD in home/in-center dialysis patients during the COVID-19 pandemic, while providing a view into operationalization and ease of real-world use. Full study results will be presented. (Table Presented) .

Adaptive immunity to SARS-CoV-2 infection and vaccination in cancer patients: The CAPTURE study

Background: Patients with cancer are at increased risk of severe outcomes from COVID-19. Understanding the impact of SARS-CoV-2 infection and vaccination induced-immunity is an area of unmet need. Methods: CAPTURE (NCT03226886) is a prospective longitudinal cohort study of COVID-19 vaccine or SARS-CoV-2 infection-induced immunity. SARS-CoV-2 infections were confirmed by RT-PCR and ELISA. Neutralising antibody titres (NAbT) against wild-type (WT) SARS-CoV-2 and variants of concern (VOC;Alpha, Beta, Delta) and SARS-CoV-2 specific T-cells (SsT-cells) were quantified. Results: 118 patients (89% solid malignancy, [SM]) were SARS-CoV-2-positive (median follow-up: 154 days). 85% patients were symptomatic;2 died of COVID-19. 82% had S1-reactive antibodies, of whom 89% had neutralising antibodies (NAbs);NAbT were lower against all VOCs. While S1-reactive antibody levels declined over time, NAbT remained stable up to 329 days. Most patients had detectable SsT-cells (76% CD4+, 52% CD8+). Haematological malignancy (HM) patients had impaired immune responses that were disease and treatment-specific (anti-CD20), but with evidence suggestive of compensation from T-cells. 585 patients were evaluated following 2 doses of BNT162b2 or AZD1222 vaccines, administered 12 weeks apart. Seroconversion rates after 2 doses were 85% and 54% in patients with SM and HM, respectively. A lower proportion of patients had detectable NAbs against SARS-CoV-2 VOC (Alpha 62%, Beta 54%, Delta 49%) vs WT (84%), with corresponding significantly lower NAbT. Patients with HM were more likely to have an undetectable NAb and had lower NAbT vs solid malignancies to both WT and VOCs. Seroconversion showed poor concordance with NAbTs against VOCs. Prior SARS-CoV-2 infection boosted NAbT including against VOCs. Anti-CD20 treatment was associated with severely diminished NAbTs. Vaccine-induced T-cell responses were detected in 80% of patients, with no differences between vaccines or cancer types. Conclusions: Patients with HM had blunted humoural responses to infection and vaccination, particularly against VOCs, but preserved cellular responses might contribute to protection. Our results lend support to prioritisation of all cancer patients for further booster vaccination. Clinical trial identification: NCT03226886. Legal entity responsible for the study: The Royal Marsden NHS Foundation Trust. Funding: The Royal Marsden Charity;The National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at the Royal Marsden Hospital and Institute for Cancer Research (ICR). Disclosure: All authors have declared no conflicts of interest.

Immunotherapy use outside clinical trial populations: never say never?

BACKGROUND: Based on favourable outcomes in clinical trials, immune checkpoint inhibitors (ICIs), most notably programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors, are now widely used across multiple cancer types. However, due to their strict inclusion and exclusion criteria, clinical studies often do not address challenges presented by non-trial populations. DESIGN: This review summarises available data on the efficacy and safety of ICIs in trial-ineligible patients, including those with autoimmune disease, chronic viral infections, organ transplants, organ dysfunction, poor performance status, and brain metastases, as well as the elderly, children, and those who are pregnant. In addition, we review data concerning other real-world challenges with ICIs, including timing of therapy switch, relationships to radiotherapy or surgery, re-treatment after an immune-related toxicity, vaccinations in patients on ICIs, and current experience around ICI and coronavirus disease-19. Where possible, we provide recommendations to aid the often-difficult decision-making process in those settings. CONCLUSIONS: Data suggest that ICIs are often active and have an acceptable safety profile in the populations described above, with the exception of PD-1 inhibitors in solid organ transplant recipients. Decisions about whether to treat with ICIs should be personalised and require multidisciplinary input and careful counselling of patients with respect to potential risks and benefits. Clinical judgements need to be carefully weighed, considering factors such as underlying cancer type, feasibility of alternative treatment options, or activity in trial-eligible patients.

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19.

We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

CAPTURE: Cancer and COVID-19antiviral immune monitoring study

Introduction: Certain retrospective and registry-based studies have indicated a higher risk of COVID-19 adverseoutcomes in cancer, but a detailed understanding of the immune response in cancer patients and the impact ofcancer therapy is needed. CAPTURE is a pan-cancer, prospective longitudinal study established in response to theunique challenges of SARS-CoV-2 pandemic for the care of cancer patients. Experimental Procedures: CAPTURE is a multicenter, UK-based longitudinal cohort study that commencedrecruitment in May 2020. Study participants are recruited from a broad range of cancer types and cancerinterventions and irrespective of their SARS-CoV-2 status, in order to capture both the nominator and thedenominator. In addition to cancer patients, the study participants also include health care workers (HCW) for thepurpose of studying transmission dynamics. Detailed clinical, epidemiologic, and demographic data are collectedfrom all participants alongside a range of biologic samples that underpin case definitions and will facilitate immunemonitoring. All participants will be followed up longitudinally for up to five years. Results: The overarching aim is to establish a prospective and unbiased understanding of the susceptibility andmorbidity of COVID-19 in cancer patients and the patterns of viral nosocomial transmission. We will follow uppatients long-term to understand the extent and duration of immunity and how immunity is impacted by cancer type, stage, and therapy. Our comprehensive sampling will help to draw a detailed picture of immune response to SARS-CoV-2 in cancer patients by monitoring active infection, antibody response, and T-cell activation, supplemented bydetailed immunophenotyping, transcriptome, TCR/BCR sequencing, and germline profiling for HLA typing andidentification of disease-associated polymorphisms. Finally, while there is a well-established correlation of circulatingcytokine levels and Covid-19 severity, CAPTURE will identify early indicators of a maladapted inflammatoryresponse in cancer patients by cytokine and chemokine profiling to establish early biomarkers of disease severity.Within the first month, we have recruited 95 participants (54% cancer patients, 46% HCWs) with matching swabs, plasma, PBMC, and whole blood for RNA sequencing. Two longitudinal samples were collected on average. Resultsfrom antigen and antibody profiling within this cohort will be presented at the meeting. Conclusion: CAPTURE will provide a detailed understanding of the interaction between immune response toSARS-CoV-2, cancer, and cancer treatments. Results will be informative in a wider health care context in order tominimize harm and maximize cancer outcomes in a sustainable manner. Furthermore, given inherent and iatrogenicdefects in discreet immune cell subsets, this is a key patient cohort to inform a wider understanding of the immuneresponse to SARS-CoV-2.

Trajectories of clinical and laboratory characteristics before COVID-19 diagnosis in hemodialysis patients

Background: The frequency of evaluations in hemodialysis (HD) care affords opportunities to assess profiles that may characterize onset of the 2019 coronavirus disease (COVID-19). We aimed to characterize the trajectories of clinical/laboratory assessments before COVID-19 diagnosis in HD patients. Methods: We assessed data from HD patients with known COVID-19 dialyzed at Fresenius Kidney Care in the United States between 02 Mar and 09 Apr 2020. We computed mean daily values for 40 variables 90 days before a positive rRT-PCR test (COVID-19+). Nonparametric smoothing splines were used to fit data of individual trajectories and estimate the mean change over time. Results: There were 1294 HD patients with COVID-19 (mean age 64±14 years, 60% male, 47% white race, 69% had diabetes, and 24% had coronary artery disease). Mean pre- HD body temperature (primarily oral) increased by about 1° Fahrenheit (F) over 10 days before COVID-19+ test and approached 99° F at diagnosis (Fig 1A). Mean interdialytic weight gain decreased by about 0.75 kg (Fig 1B) over 14 days before COVID-19+ test;concurrent decreases of about 20 minutes were seen in HD treatment time. Mean neutrophil-to-lymphocyte ratio had mild increases (Fig 1C), while mean platelet counts decreased by about 40×109/L over 14 days before COVID-19+ test (Fig 1D). Trajectories of many variables (vitals, heparin, hematology, nutrition, bone, anemia) were observed to change before COVID-19+ test, yet alternations were generally minor. Conclusions: The trajectories of several clinical/laboratory parameters appeared to change before COVID-19 diagnosis in HD patients. Many changes were small and may not be independently useful in identifying onset of COVID-19. Mean pre-HD body temperature before SARS-CoV-2 infection was 97.4° F and should be considered in screening. Findings may have utility in prediction model development. Further comparisons to patients without COVID-19 are needed.

Trends in fever and respiratory illness in hemodialysis patients during the COVID-19 pandemic

Background: Hemodialysis (HD) patients are vulnerable to the 2019 coronavirus disease (COVID-19) due to older age and common coexistence of comorbidities. Fever and respiratory illness (RI) are common symptoms of COVID-19. In order to create a disease surveillance tool and anticipate areas of COVID-19 outbreak, we aimed to assess the trends in fever and RI symptoms in HD patients treated at a national dialysis provider network in the United States during the pandemic. Methods: We used data from HD patients actively treated between Jan 1 2018 ad May 16 2020 at a national dialysis provider network of large integrated health care company. If the body temperature of the patient either before or after the treatment was greater than 100 degrees Fahrenheit, then the patient was identified as exhibiting the symptom of fever. If the patient complained of shortness of breath, wheezing, runny nose, bloody cough, dry cough or purulent cough, then in this analysis the patient was identified as exhibiting the symptom of RI. Results: The total patients count ranged from 196,774 to 209,475 per week while the total count of HD treatments ranged from 413,477 to 454,215. For the year 2020, a clear increase in trend for number of patients was observed after week 11 (03/08-03/14/2020) for RI symptoms (Figure 1A) and week 12 (3/15-3/21/2020) for fever symptom (Figure 1B). Both increasing trends spike at the week 15 (04/05-04/11/2020) and decline thereafter. Conclusions: HD patients appear to exhibit a different trend in RI and fever symptoms during the year 2020 compared to concurrent periods in 2018 and 2019. which coincides with COVID-19 outbreak. Routine surveillance of dialysis patients may allow for early identification of COVID-19 outbreaks.

Enhanced sentinel surveillance system for COVID-19 outbreak prediction in a European dialysis clinics network

Background: Accurate predictions of epidemic dynamics may enable timely organizational interventions in high risk regions. We exploited the interconnection of the EMEA Fresenius Medical Care (FMC) dialysis clinic network to establish a sentinel surveillance system where the occurrence of new cases in a clinic propagates distanceweighted risk estimates to proximal dialysis units. The surveillance system is embedded in an artificial intelligence model which predicts COVID-19 outbreak occurrence in HD clinics from trends in clinical practice patterns and regional COVID-19 epidemic metrics. The system stratifies clinics by their risk of new local outbreak. Methods: The risk prediction model is computed considering a cohort of 640 clinics belonging to the FMC network. We trained a model to predict outbreak in each clinic in a 2-week prediction horizon (i.e. two or more COVID-19 cases). In addition to sentinel distance-weighted risk estimates, the model included 73 variables (i.e. regional-level epidemic data from open source datasets and clinical practice data from the EuCliD® database). We generated the training set on data available on 04/01/2020 and tested prediction accuracy at 4/15/2020 and 4/20/2020. Results: In the training set there were 58 (9.1%) clinics with two or more patients with COVID-19 infection in the two-week prediction window. In the validation samples there were 27 (4.2%) and 12 (1.9%) clinics with two or more patients with COVID-19 infection during the two-week prediction window. The performance of the model was suitable in both testing windows (AUC=0.86 and 0.80 respectively). The model is used to construct risk maps highlighting geographical clusters of clinics at risk (figure). Conclusions: A sentinel surveillance system together with the wealth of information collected in EuCliD® and state of the art modeling strategies allows prompt risk assessment and timely response to COVID-19 epidemic challenges throughout networked European clinics.

Collateral damage: the impact on outcomes from cancer surgery of the COVID-19 pandemic.

BACKGROUND: Cancer diagnostics and surgery have been disrupted by the response of health care services to the coronavirus disease 2019 (COVID-19) pandemic. Progression of cancers during delay will impact on patients' long-term survival. PATIENTS AND METHODS: We generated per-day hazard ratios of cancer progression from observational studies and applied these to age-specific, stage-specific cancer survival for England 2013-2017. We modelled per-patient delay of 3 and 6 months and periods of disruption of 1 and 2 years. Using health care resource costing, we contextualise attributable lives saved and life-years gained (LYGs) from cancer surgery to equivalent volumes of COVID-19 hospitalisations. RESULTS: Per year, 94 912 resections for major cancers result in 80 406 long-term survivors and 1 717 051 LYGs. Per-patient delay of 3/6 months would cause attributable death of 4755/10 760 of these individuals with loss of 92 214/208 275 life-years, respectively. For cancer surgery, average LYGs per patient are 18.1 under standard conditions and 17.1/15.9 with a delay of 3/6 months (an average loss of 0.97/2.19 LYGs per patient), respectively. Taking into account health care resource units (HCRUs), surgery results on average per patient in 2.25 resource-adjusted life-years gained (RALYGs) under standard conditions and 2.12/1.97 RALYGs following delay of 3/6 months. For 94 912 hospital COVID-19 admissions, there are 482 022 LYGs requiring 1 052 949 HCRUs. Hospitalisation of community-acquired COVID-19 patients yields on average per patient 5.08 LYG and 0.46 RALYGs. CONCLUSIONS: Modest delays in surgery for cancer incur significant impact on survival. Delay of 3/6 months in surgery for incident cancers would mitigate 19%/43% of LYGs, respectively, by hospitalisation of an equivalent volume of admissions for community-acquired COVID-19. This rises to 26%/59%, respectively, when considering RALYGs. To avoid a downstream public health crisis of avoidable cancer deaths, cancer diagnostic and surgical pathways must be maintained at normal throughput, with rapid attention to any backlog already accrued.