Use of Machine Learning and Lay Care Coaches to Increase Advance Care Planning Conversations for Patients With Metastatic Cancer.

PURPOSE: Patients with metastatic cancer benefit from advance care planning (ACP) conversations. We aimed to improve ACP using a computer model to select high-risk patients, with shorter predicted survival, for conversations with providers and lay care coaches. Outcomes included ACP documentation frequency and end-of-life quality measures. METHODS: In this study of a quality improvement initiative, providers in four medical oncology clinics received Serious Illness Care Program training. Two clinics (thoracic/genitourinary) participated in an intervention, and two (cutaneous/sarcoma) served as controls. ACP conversations were documented in a centralized form in the electronic medical record. In the intervention, providers and care coaches received weekly e-mails highlighting upcoming clinic patients with < 2 year computer-predicted survival and no prior prognosis documentation. Care coaches contacted these patients for an ACP conversation (excluding prognosis). Providers were asked to discuss and document prognosis. RESULTS: In the four clinics, 4,968 clinic visits by 1,251 patients met inclusion criteria (metastatic cancer with no prognosis previously documented). In their first visit, 28% of patients were high-risk (< 2 year predicted survival). Preintervention, 3% of both intervention and control clinic patients had ACP documentation during a visit. By intervention end (February 2021), 35% of intervention clinic patients had ACP documentation compared with 3% of control clinic patients. Providers' prognosis documentation rate also increased in intervention clinics after the intervention (2%-27% in intervention clinics, P < .0001; 0%-1% in control clinics). End-of-life care intensity was similar in intervention versus control clinics, but patients with ≥ 1 provider ACP edit met fewer high-intensity care measures (P = .04). CONCLUSION: Combining a computer prognosis model with care coaches increased ACP documentation.

A survey of patient and public perceptions and awareness of SARS-CoV-2-related risks among participants in India and South Africa

A cross-sectional survey was performed among the adult population of participating countries, India and South Africa. The purpose of this study was to explore perceptions and awareness of SARS-CoV-2-related risks in the relevant countries. The main outcome measures were the proportion of participants aware of SARS-CoV-2, and their perception of infection risks. Self-administered questionnaires were used to collect data via a web- and paper-based survey over three months. For data capturing, Microsoft Excel was employed, and descriptive statistics used for presenting data. Pearsons Chi-squared test was used to assess relationships between variables, and a p-value less than 0.05 was considered significant. There were 844 respondents (India: n=660, South Africa: n=184; response rate 87.6%), with a 61.1% vs 38.3% female to male ratio. Post-high-school or university education was the lowest qualification reported by most respondents in India (77.3%) and South Africa (79.3%). Sources of information about the pandemic were usually media and journal publications (73.2%), social media (64.6%), family and friends (47.7%) and government websites (46.2%). Most respondents correctly identified infection prevention measures (such as physical distancing, mask use), with 90.0% reporting improved hand hygiene practices since the pandemic. Hesitancy or refusal to accept the SARS-CoV-2 vaccine was reported among 17.9% and 50.9% of respondents in India and South Africa, respectively. Reasons cited included rushed vaccine development and the futility of vaccines for what respondents considered a self-limiting flu-like illness. Respondents identified public health promotion measures for SARS-CoV-2. Reported hesitancy to the up-take of SARS-CoV-2 vaccines was much higher in South Africa. Vaccination campaigns should consider robust public engagement and contextually fit communication strategies with multimodal, participatory online and offline initiatives to address public concerns, specifically towards vaccines developed for this pandemic and general vaccine hesitancy.

Characterization of ERBB2 (HER2) Alterations in Metastatic Non-small Cell Lung Cancer and Comparison of Outcomes of Different Trastuzumab-based Regimens.

INTRODUCTION: About 3%-5% of mNSCLC have ERBB2 (HER2) alterations, but currently, there are no FDA-approved targeted therapies for this indication. We compared treatment response between trastuzumab-based and non-targeted regimens in ERBB2-mutant mNSCLC. METHODS: This retrospective, single-institution study included patients with mNSCLC with ERBB2 alterations identified by next-generation sequencing. Best overall response was determined using Response Evaluation Criteria in Solid Tumors 1.1. RESULTS: We identified 3 groups of patients: ERBB2-mutant/EGFR-wildtype mNSCLC (n = 33), ERBB2-amplified/EGFR-wildtype mNSCLC without concurrent ERBB2 mutations (n = 6), and ERBB2-altered/EGFR-mutant mNSCLC (n = 8). Observed mutations included A775_G776insYVMA (n = 23), Gly778_Pro780dup (n = 4), Ser310Phe (n = 3), and others (n = 5). Among the 33 with ERBB2-mutant/EGFR-wildtype mNSCLC, those with and without A775_G776insYVMA had significantly different median overall survival (OS) of 17.7 and 52.9 months, respectively (Cox regression multivariable HR: 5.03, 95% CI: 1.37-18.51, P = .02). In those with mNSCLC with A775_G776insYVMA, trastuzumab-based therapies were associated with greater OS (20.3 vs. 9.8 months; multivariable HR: 0.19, 95% CI: 0.04-0.87, P = .032). Objective response and disease control rates (median tumor size change) in the 33 patients with ERBB2-mutant/EGFR-wildtype mNSCLC were 40.0% and 80.0% (-35.8%), respectively, for patients treated with trastuzumab deruxtecan; 0% and 30.0% (-5.2%) for trastuzumab emtansine; and 7.1% and 50.0% (-13.0%) for trastuzumab/chemotherapy combinations. CONCLUSION: In ERBB2-mutant/EGFR-wildtype mNSCLC, while most trastuzumab-based regimens had modest activity in this real-world analysis, trastuzumab deruxtecan had highest response rates and best tumor size reduction. Receipt of any trastuzumab-based regimen was associated with greater OS with A775_G776insYVMA. There remains an unmet need for approved targeted therapies for ERBB2-mutant/EGFR-wildtype NSCLC.

How acceptable is rapid whole genome sequencing for infectious disease management in hospitals? Perspectives of those involved in managing nosocomial SARS-CoV-2

Structured summaryO_ST_ABSBackgroundC_ST_ABSWhole genome sequencing (WGS) for managing healthcare associated infections (HCAIs) has developed considerably through experiences with SARS-CoV-2. We interviewed various healthcare professionals (HCPs) with direct experience of using WGS in hospitals (within the COG-UK Hospital Onset COVID-19 Infection (HOCI) study) to explore its acceptability and future use. MethodAn exploratory, cross-sectional, qualitative design employed semi-structured interviews with 39 diverse HCPs between December 2020 and June 2021. Participants were recruited from five sites within the larger clinical study of a novel genome sequencing reporting tool for SARS-CoV-2 (the HOCI study). All had experience, in their diverse roles, of using sequencing data to manage nosocomial SARS-CoV-2 infection. Deductive and inductive thematic analysis identified themes exploring aspects of the acceptability of sequencing. FindingsThe analysis highlighted the overall acceptability of rapid WGS for infectious disease using SARS-CoV-2 as a case study. Diverse professionals were largely very positive about its future use and believed that it could become a valuable and routine tool for managing HCAIs. We identified three key themes 1) Proof of concept achieved; 2) Novel insights and implications; and 3) Challenges and demands. ConclusionOur qualitative analysis, drawn from five diverse hospitals, shows the broad acceptability of rapid sequencing and its potential. Participants believed it could and should become an everyday technology capable of being embedded within typical hospital processes and systems. However, its future integration into existing healthcare systems will not be without challenges (e.g., resource, multi-level change) warranting further mixed methods research.

Evaluating the effectiveness of rapid SARS-CoV-2 genome sequencing in supporting infection control teams: the COG-UK hospital-onset COVID-19 infection study

IntroductionViral sequencing of SARS-CoV-2 has been used for outbreak investigation, but there is limited evidence supporting routine use for infection prevention and control (IPC) within hospital settings. MethodsWe conducted a prospective non-randomised trial of sequencing at 14 acute UK hospital trusts. Sites each had a 4-week baseline data-collection period, followed by intervention periods comprising 8 weeks of rapid (<48h) and 4 weeks of longer-turnaround (5-10 day) sequencing using a sequence reporting tool (SRT). Data were collected on all hospital onset COVID-19 infections (HOCIs; detected [≥]48h from admission). The impact of the sequencing intervention on IPC knowledge and actions, and on incidence of probable/definite hospital-acquired infections (HAIs) was evaluated. ResultsA total of 2170 HOCI cases were recorded from October 2020-April 2021, with sequence reports returned for 650/1320 (49.2%) during intervention phases. We did not detect a statistically significant change in weekly incidence of HAIs in longer-turnaround (IRR 1.60, 95%CI 0.85-3.01; P=0.14) or rapid (0.85, 0.48-1.50; P=0.54) intervention phases compared to baseline phase. However, IPC practice was changed in 7.8% and 7.4% of all HOCI cases in rapid and longer-turnaround phases, respectively, and 17.2% and 11.6% of cases where the report was returned. In a per-protocol sensitivity analysis there was an impact on IPC actions in 20.7% of HOCI cases when the SRT report was returned within 5 days. ConclusionWhile we did not demonstrate a direct impact of sequencing on the incidence of nosocomial transmission, our results suggest that sequencing can inform IPC response to HOCIs, particularly when returned within 5 days.

Impact of the COVID-19 pandemic on community antibiotic prescribing and stewardship: a qualitative interview study with general practitioners in England

The COVID-19 pandemic has had a profound impact on the delivery of primary care services. We aimed to identify general practitioners (GPs) perceptions and experiences of how the COVID-19 pandemic influenced antibiotic prescribing and antimicrobial stewardship (AMS) in general practice in England. Twenty-four semi-structured interviews were conducted with 18 GPs at two time-points: autumn 2020 (14 interviews) and spring 2021 (10 interviews). Interviews were audio-recorded, transcribed and analysed thematically, taking a longitudinal approach. Participants reported a lower threshold for antibiotic prescribing (and fewer consultations) for respiratory infections and COVID-19 symptoms early in the pandemic, then returning to more usual (pre-pandemic) prescribing. They perceived less impact on antibiotic prescribing for urinary and skin infections. Participants perceived the changing ways of working and consulting (e.g., proportions of remote and in-person consultations), and the changing patient presentations and GP workload as influencing the fluctuations in antibiotic prescribing. This was compounded by decreased engagement with, and priority of, AMS due to COVID-19-related urgent priorities. Re-engagement with AMS is needed, e.g., through reviving antibiotic prescribing feedback and targets/incentives. While the pandemic disrupted the usual ways of working, it also produced opportunities, e.g., for re-organising ways of managing infections and AMS in the future.

Predicting hospital-onset COVID-19 infections using dynamic networks of patient contacts: an observational study

BackgroundReal-time prediction is key to prevention and control of healthcare-associated infections. Contacts between individuals drive infections, yet most prediction frameworks fail to capture the dynamics of contact. We develop a real-time machine learning framework that incorporates dynamic patient contact networks to predict patient-level hospital-onset COVID-19 infections (HOCIs), which we test and validate on international multi-site datasets spanning epidemic and endemic periods. MethodsOur framework extracts dynamic contact networks from routinely collected hospital data and combines them with patient clinical attributes and background contextual hospital data to forecast the infection status of individual patients. We train and test the HOCI prediction framework using 51,157 hospital patients admitted to a UK (London) National Health Service (NHS) Trust from 01 April 2020 to 01 April 2021, spanning UK COVID-19 surges 1 and 2. We then validate the framework by applying it to data from a non-UK (Geneva) hospital site during an epidemic surge (40,057 total inpatients) and to data from the same London Trust from a subsequent period post surge 2, when COVID-19 had become endemic (43,375 total inpatients). FindingsBased on the training data (London data spanning surges 1 and 2), the framework achieved high predictive performance using all variables (AUC-ROC 0{middle dot}89 [0{middle dot}88-0{middle dot}90]) but was almost as predictive using only contact network variables (AUC-ROC 0{middle dot}88 [0{middle dot}86-0{middle dot}90]), and more so than using only hospital contextual (AUC-ROC 0{middle dot}82 [0{middle dot}80-0{middle dot}84]) or patient clinical (AUC-ROC 0{middle dot}64 [0{middle dot}62-0{middle dot}66]) variables. The top three risk factors we identified consisted of one hospital contextual variable (background hospital COVID-19 prevalence) and two contact network variables (network closeness, and number of direct contacts to infectious patients), and together achieved AUC-ROC 0{middle dot}85 [0{middle dot}82-0{middle dot}88]. Furthermore, the addition of contact network variables improved performance relative to hospital contextual variables on both the non-UK (AUC-ROC increased from 0{middle dot}84 [0{middle dot}82-0{middle dot}86] to 0{middle dot}88 [0{middle dot}86-0{middle dot}90]) and the UK validation datasets (AUC-ROC increased from 0{middle dot}52 [0{middle dot}49-0{middle dot}53] to 0{middle dot}68 [0{middle dot}64-0{middle dot}70]). InterpretationOur results suggest that dynamic patient contact networks can be a robust predictor of respiratory viral infections spreading in hospitals. Their integration in clinical care has the potential to enhance individualised infection prevention and early diagnosis. FundingMedical Research Foundation, World Health Organisation, Engineering and Physical Sciences Research Council, National Institute for Health Research, Swiss National Science Foundation, German Research Foundation.

SARS-CoV-2 lineage B.1.1.7 is associated with greater disease severity among hospitalised women but not men

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.1.7 has been associated with an increased rate of transmission and disease severity among subjects testing positive in the community. Its impact on hospitalised patients is less well documented. MethodsWe collected viral sequences and clinical data of patients admitted with SARS-CoV-2 and hospital-onset COVID-19 infections (HOCIs), sampled 16/11/2020 - 10/01/2021, from eight hospitals participating in the COG-UK-HOCI study. Associations between the variant and the outcomes of all-cause mortality and intensive therapy unit (ITU) admission were evaluated using mixed effects Cox models adjusted by age, sex, comorbidities, care home residence, pregnancy and ethnicity. ResultsSequences were obtained from 2341 inpatients (HOCI cases = 786) and analysis of clinical outcomes was carried out in 2147 inpatients with all data available. The hazard ratio (HR) for mortality of B.1.1.7 compared to other lineages was 1.01 (95% CI 0.79-1.28, P=0.94) and for ITU admission was 1.01 (95% CI 0.75-1.37, P=0.96). Analysis of sex-specific effects of B.1.1.7 identified increased risk of mortality (HR 1.30, 95% CI 0.95-1.78) and ITU admission (HR 1.82, 95% CI 1.15-2.90) in females infected with the variant but not males (mortality HR 0.82, 95% CI 0.61-1.10; ITU HR 0.74, 95% CI 0.52-1.04). ConclusionsIn common with smaller studies of patients hospitalised with SARS-CoV-2 we did not find an overall increase in mortality or ITU admission associated with B.1.1.7 compared to other lineages. However, women with B.1.1.7 may be at an increased risk of admission to intensive care and at modestly increased risk of mortality.

Characterising contact in disease outbreaks via a network model of spatial-temporal proximity

Contact tracing is a key tool in epidemiology to identify and control outbreaks of infectious diseases. Existing contact tracing methodologies produce contact maps of individuals based on a binary definition of contact which can be hampered by missing data and indirect contacts. Here, we present a Spatial-temporal Epidemiological Proximity (StEP) model to recover contact maps in disease outbreaks based on movement data. The StEP model accounts for imperfect data by considering probabilistic contacts between individuals based on spatial-temporal proximity of their movement trajectories, creating a robust movement network despite possible missing data and unseen transmission routes. Using real-world data we showcase the potential of StEP for contact tracing with outbreaks of multidrug-resistant bacteria and COVID-19 in a large hospital group in London, UK. In addition to the core structure of contacts that can be recovered using traditional methods of contact tracing, the StEP model reveals missing contacts that connect seemingly separate outbreaks. Comparison with genomic data further confirmed that these recovered contacts indeed improve characterisation of disease transmission and so highlights how the StEP framework can inform effective strategies of infection control and prevention.

A handheld point-of-care system for rapid detection of SARS-CoV-2 in under 20 minutes

The COVID-19 pandemic is a global health emergency characterized by the high rate of transmission and ongoing increase of cases globally. Rapid point-of-care (PoC) diagnostics to detect the causative virus, SARS-CoV-2, are urgently needed to identify and isolate patients, contain its spread and guide clinical management. In this work, we report the development of a rapid PoC diagnostic test (< 20 min) based on reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) and semiconductor technology for the detection of SARS-CoV-2 from extracted RNA samples. The developed LAMP assay was tested on a real-time benchtop instrument (RT-qLAMP) showing a lower limit of detection of 10 RNA copies per reaction. It was validated against 183 clinical samples including 127 positive samples (screened by the CDC RT-qPCR assay). Results showed 90.55% sensitivity and 100% specificity when compared to RT-qPCR and average positive detection times of 15.45 {+/-} 4.43 min. For validating the incorporation of the RT-LAMP assay onto our PoC platform (RT-eLAMP), a subset of samples was tested (n=40), showing average detection times of 12.89 {+/-} 2.59 min for positive samples (n=34), demonstrating a comparable performance to a benchtop commercial instrument. Paired with a smartphone for results visualization and geo-localization, this portable diagnostic platform with secure cloud connectivity will enable real-time case identification and epidemiological surveillance. One Sentence SummaryWe demonstrate isothermal detection of SARS-CoV-2 in under 20 minutes from extracted RNA samples with a handheld Lab-on-Chip platform.

Hepatitis C virus leaves an epigenetic signature post cure of infection by direct-acting antivirals.

The increasing worldwide prevalence of Hepatocellular carcinoma (HCC), characterized by resistance to conventional chemotherapy, poor prognosis and eventually mortality, place it as a prime target for new modes of prevention and treatment. Hepatitis C Virus (HCV) is the predominant risk factor for HCC in the US and Europe. Multiple epidemiological studies showed that sustained virological responses (SVR) following treatment with the powerful direct acting antivirals (DAAs), which have replaced interferon-based regimes, do not eliminate tumor development. We aimed to identify an HCV-specific pathogenic mechanism that persists post SVR following DAAs treatment. We demonstrate that HCV infection induces genome-wide epigenetic changes by performing chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) for histone post-translational modifications that are epigenetic markers for active and repressed chromatin. The changes in histone modifications correlate with reprogramed host gene expression and alter signaling pathways known to be associated with HCV life cycle and HCC. These epigenetic alterations require the presence of HCV RNA or/and expression of the viral proteins in the cells. Importantly, the epigenetic changes induced following infection persist as an "epigenetic signature" after virus eradication by DAAs treatment, as detected using in vitro HCV infection models. These observations led to the identification of an 8 gene signature that is associated with HCC development and demonstrate persistent epigenetic alterations in HCV infected and post SVR liver biopsy samples. The epigenetic signature was reverted in vitro by drugs that inhibit epigenetic modifying enzyme and by the EGFR inhibitor, Erlotinib. This epigenetic "scarring" of the genome, persisting following HCV eradication, suggest a novel mechanism for the persistent pathogenesis of HCV after its eradication by DAAs. Our study offers new avenues for prevention of the persistent oncogenic effects of chronic hepatitis infections using specific drugs to revert the epigenetic changes to the genome.

Diagnosis and Treatment of Adenocarcinomas and Squamous Cell Carcinomas of the Lung.

Following years in which there were only modest gains in treatment options for non-small cell lung cancer, recognition of targetable mutations and immunogenicity of lung cancer now impact treatment decisions.