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Vaccine effectiveness against COVID-19 breakthrough infections in patients with cancer (UKCCEP): a population-based test-negative case-control study.
No full textBACKGROUND
People with cancer are at increased risk of hospitalisation and death following infection with SARS-CoV-2. Therefore, we aimed to conduct one of the first evaluations of vaccine effectiveness against breakthrough SARS-CoV-2 infections in patients with cancer at a population level.
METHODS
In this population-based test-negative case-control study of the UK Coronavirus Cancer Evaluation Project (UKCCEP), we extracted data from the UKCCEP registry on all SARS-CoV-2 PCR test results (from the Second Generation Surveillance System), vaccination records (from the National Immunisation Management Service), patient demographics, and cancer records from England, UK, from Dec 8, 2020, to Oct 15, 2021. Adults (aged ≥18 years) with cancer in the UKCCEP registry were identified via Public Health England's Rapid Cancer Registration Dataset between Jan 1, 2018, and April 30, 2021, and comprised the cancer cohort. We constructed a control population cohort from adults with PCR tests in the UKCCEP registry who were not contained within the Rapid Cancer Registration Dataset. The coprimary endpoints were overall vaccine effectiveness against breakthrough infections after the second dose (positive PCR COVID-19 test) and vaccine effectiveness against breakthrough infections at 3-6 months after the second dose in the cancer cohort and control population.
FINDINGS
The cancer cohort comprised 377 194 individuals, of whom 42 882 had breakthrough SARS-CoV-2 infections. The control population consisted of 28 010 955 individuals, of whom 5 748 708 had SARS-CoV-2 breakthrough infections. Overall vaccine effectiveness was 69·8% (95% CI 69·8-69·9) in the control population and 65·5% (65·1-65·9) in the cancer cohort. Vaccine effectiveness at 3-6 months was lower in the cancer cohort (47·0%, 46·3-47·6) than in the control population (61·4%, 61·4-61·5).
INTERPRETATION
COVID-19 vaccination is effective for individuals with cancer, conferring varying levels of protection against breakthrough infections. However, vaccine effectiveness is lower in patients with cancer than in the general population. COVID-19 vaccination for patients with cancer should be used in conjunction with non-pharmacological strategies and community-based antiviral treatment programmes to reduce the risk that COVID-19 poses to patients with cancer.
FUNDING
University of Oxford, University of Southampton, University of Birmingham, Department of Health and Social Care, and Blood Cancer UK
A guideline for the haematological management of major haemorrhage: a British Society for Haematology Guideline.
No full textInflammatory bowel disease-related colorectal cancer: Past, present and future perspectives.
No full textInflammatory bowel disease-related colorectal cancer (IBD-CRC) is one of the most serious complications of IBD contributing to significant mortality in this cohort of patients. IBD is often associated with diet and lifestyle-related gut microbial dysbiosis, the interaction of genetic and environmental factors, leading to chronic gut inflammation. According to the "common ground hypothesis", microbial dysbiosis and intestinal barrier impairment are at the core of the chronic inflammatory process associated with IBD-CRC. Among the many underlying factors known to increase the risk of IBD-CRC, perhaps the most important factor is chronic persistent inflammation. The persistent inflammation in the colon results in increased proliferation of cells necessary for repair but this also increases the risk of dysplastic changes due to chromosomal and microsatellite instability. Multiple pathways have been identified, regulated by many positive and negative factors involved in the development of cancer, which in this case follows the 'inflammation-dysplasia-carcinoma' sequence. Strategies to lower this risk are extremely important to reduce morbidity and mortality due to IBD-CRC, among which colonoscopic surveillance is the most widely accepted and implemented modality, forming part of many national and international guidelines. However, the effectiveness of surveillance in IBD has been a topic of much debate in recent years for multiple reasons - cost-benefit to health systems, resource requirements, and also because of studies showing conflicting long-term data. Our review provides a comprehensive overview of past, present, and future perspectives of IBD-CRC. We explore and analyse evidence from studies over decades and current best practices followed globally. In the future directions section, we cover emerging novel endoscopic techniques and artificial intelligence that could play an important role in managing the risk of IBD-CRC
Reproducibility of the electronic chromoendoscopy PICaSSO score (Paddington International Virtual ChromoendoScopy ScOre) in ulcerative colitis using multiple endoscopic platforms: a prospective multicenter international study (with video).
No full textBACKGROUND AND AIMS
Endoscopic and histologic remission (HR) are key therapeutic targets in the management of ulcerative colitis (UC). The aim of this study was to evaluate the reproducibility of the Paddington International virtual ChromoendoScopy ScOre (PICaSSO), a virtual chromoendoscopy score originally validated by use of the iSCAN platform, with the narrow-band imaging (NBI), linked-color imaging (LCI), and blue-laser imaging (BLI) platforms.
METHODS
We evaluated endoscopic activity using the Mayo Endoscopic Score (MES), the Ulcerative Colitis Endoscopic Index of Severity (UCEIS), and PICaSSO in 159 UC patients (78 NBI and 81 BLI/LCI) who underwent colonoscopy in 2 tertiary referral centers. HR was defined by the Robarts Histopathology Index (RHI) and the Nancy Histologic Index (NHI). Receiver operating characteristic curves were plotted to evaluate endoscopic scores for the prediction of HR. Intraclass correlation coefficients (ICC) between endoscopists were evaluated.
RESULTS
PICaSSO had an ICC of 0.825 when the NBI and BLI/LCI cohorts were combined, higher than MES and UCEIS. The correlation between PICaSSO and RHI and NHI was 0.83 and 0.79 in the NBI cohort and between 0.63 and 0.65 in LCI/BLI. In the NBI cohort, the accuracy of MES, UCEIS, and PICaSSO was 0.936, 0.897, and 0.808 for HR measured by RHI and 0.897, 0.885, and 0.821 by NHI, respectively. In the BLI/LCI cohort, the accuracy of MES, UCEIS, LCI PICaSSO and BLI PICaSSO was 0.765, 0.778, 0.827, and 0.79 to predict HR with RHI and NHI, respectively.
CONCLUSIONS
The PICaSSO score can be consistently and accurately reproduced with NBI and LCI/BLI and therefore can be applied to all virtual electronic chromoendoscopy platforms
Positive approaches to safety: learning from what we do well.
No full textHistorical and current methodologies in patient safety are based on a deficit-based model, defining safety as the absence of harm. This model is aligned with the human innate negativity bias and the general philosophy of healthcare: to diagnose and cure illness, and to relieve suffering. Whilst this approach has underpinned measurable progress in healthcare outcomes, a common narrative in the healthcare literature indicates that this progress is stalling or slowing. It is important to learn from and improve poor outcomes, but the deficit-based approach has some theoretical limitations. In this article, we discuss some of the theoretical limitations of the prevailing approach to patient safety, and introduce emerging, complementary approaches in this field of practice. Safety-II and resilience engineering represent a new paradigm of safety, characterised by focusing on the entirety of work, with a systems-wide lens, rather than single incidents of failure. More overtly positive approaches are available, specifically focusing on success - both outstanding success and everyday success - including exnovation, appreciative inquiry, learning from excellence and positive deviance. These approaches are not mutually exclusive. The new methods described in this article are not intended as replacements of the current methods, rather they are presented as complementary tools, designed to allow the reader to take a balanced and holistic view of patient safety
Associating transcriptomics data with inflammatory markers to understand tumour microenvironment in hepatocellular carcinoma.
No full textBACKGROUND
Liver cancer is the fourth leading cause of cancer-related death globally which is estimated to reach more than 1 million deaths a year by 2030. Among liver cancer types, hepatocellular carcinoma (HCC) accounts for approximately 90% of the cases and is known to have a tumour promoting inflammation regardless of its underlying aetiology. However, current promising treatment approaches, such as immunotherapy, are partially effective for most of the patients due to the immunosuppressive nature of the tumour microenvironment (TME). Therefore, there is an urgent need to fully understand TME in HCC and discover new immune markers to eliminate resistance to immunotherapy.
METHODS
We analyse three microarray datasets, using unsupervised and supervised methods, in an effort to discover signature genes. First, univariate, and multivariate, feature selection methods, such as the Boruta algorithm, are applied. Subsequently, an optimisation procedure, which utilises random forest algorithm with three dataset pairs combinations, is performed. The resulting optimal gene sets are then combined and further subjected to network analysis and pathway enrichment analysis so as to obtain information related to their biological relevance. The microarray datasets were analysed via the MCP-counter, CIBERSORT, TIMER, EPIC, and quanTIseq deconvolution methods and an estimation of cell type abundances for each dataset sample were identified. The differences in the cell type abundances, between the adjacent and tumour sample groups, were then assessed using a Wilcoxon Rank Sum test (p-value < 0.05).
RESULTS
The optimal gene signature sets, derived from each of the data pairs combination, achieved AUC values ranging from 0.959 to 0.988 in external validation sets using Random Forest model. CLEC1B and PTTG1 genes are retrieved across each optimal set. Among the signature genes, PTTG1, AURKA, and UBE2C genes are found to be involved in the regulation of mitotic sister chromatid separation and anaphase-promoting complex (APC) dependent catabolic process (adjusted p-value < 0.001). Additionally, the application of deconvolution algorithms revealed significant changes in cell type abundances of Regulatory T (Treg) cells, M0 and M1 macrophages, and T CD8 cells between adjacent and tumour samples.
CONCLUSION
We identified ECM1 gene as a potential immune-related marker acting through immune cell migration and macrophage polarisation. Our results indicate that macrophages, such as M0 macrophage and M1 macrophage cells, undergo significant changes in HCC TME. Moreover, our immune deconvolution approach revealed significant infiltration of Treg cells and M0 macrophages, and a significant decrease in T CD8 cells and M1 macrophages in tumour samples
Acceptability of donor funding for clinical trials in the UK: a qualitative empirical ethics study using focus groups to elicit the views of research patient public involvement group members, research ethics committee chairs and clinical researchers.
No full textOBJECTIVES
The Plutocratic Proposal is a novel method of funding early phase clinical trials where a single donor funds the entire trial and in so doing secures a place on it. The aim of this study was to identify and explore concerns that may be raised by UK research ethics committees (RECs) when reviewing clinical trials funded in this way.
DESIGN
Empirical ethics combining ethical analysis and qualitative data from three focus groups held online using Frith's symbiotic approach. Data were analysed using inductive thematic approach informed by the study aims and ethical analysis.
PARTICIPANTS
22 participants were recruited: 8 research patient public involvement group members, 7 REC chairs and 7 clinical researchers. All were based in the UK.
RESULTS
With one exception, participants thought the Plutocratic Proposal may be 'all things considered' acceptable, providing their concerns were met, primary of which was upholding scientific integrity. Other concerns discussed related to the acceptability of the donor securing a place on the trial including: whether this was an unfair distribution of benefits, disclosing the identity of the donor as the funder, protecting the donor from exploitation and funding a single study with multiple donors on the same terms. Some misgivings fell outside the usual REC purview: detrimental impact of donors of bad character, establishing the trustworthiness of the matching agency and its processes and optimising research funding and resources. Despite their concerns, participants recognised that because the donor funds the whole trial, others would also potentially benefit from participating.
CONCLUSIONS
We identified concerns about the Plutocratic Proposal. UK RECs may be open to approving studies if these can be addressed. Existing governance processes will do some of this work, but additional REC guidance, particularly in relation to donors securing a place on the trial, may be necessary to help RECs navigate ethical concerns consistently
Why are some ReSPECT conversations left incomplete? A qualitative case study analysis.
No full textBackground
As an emergency care and treatment planning process (ECTP), a key feature of the Recommended Summary Plan for Emergency Care and Treatment (ReSPECT) is the engagement of patients and/or their representatives in conversations about treatment options including, but not limited to, cardiopulmonary resuscitation (CPR). However, qualitative research suggests that some ReSPECT conversations lead to partial or no decision-making about treatment recommendations. This paper explores why some ReSPECT conversations are left incomplete.
Methods
Drawing on observation and interview data collected in four National Health Service (NHS) hospital sites in England, this paper offers an in-depth exploration of six case studies in which ReSPECT conversations were incomplete. Using thematic analysis, we triangulate fieldnote data documenting these conversations with interview data in which the doctors who conducted these conversations shared their perceptions and reflected on their decision-making processes.
Results
We identified two themes, both focused on 'mismatch': (1) Mismatch between the doctor's clinical priorities and the patient's/family's immediate needs; and (2) mismatch between the doctor's conversation scripts, which included patient autonomy, the feasibility of CPR, and what medicine can and should do to prolong a patient's life, and the patient's/family's understandings of these concepts.
Conclusions
This case study analysis of six ReSPECT conversations found that mismatch between doctors' priorities and understandings and those of patients and/or their relatives led to incomplete ReSPECT conversations. Future research should explore methods to overcome these mismatches
Metabolite selection for machine learning in childhood brain tumour classification.
No full textMRS can provide high accuracy in the diagnosis of childhood brain tumours when combined with machine learning. A feature selection method such as principal component analysis is commonly used to reduce the dimensionality of metabolite profiles prior to classification. However, an alternative approach of identifying the optimal set of metabolites has not been fully evaluated, possibly due to the challenges of defining this for a multi-class problem. This study aims to investigate metabolite selection from in vivo MRS for childhood brain tumour classification. Multi-site 1.5 T and 3 T cohorts of patients with a brain tumour and histological diagnosis of ependymoma, medulloblastoma and pilocytic astrocytoma were retrospectively evaluated. Dimensionality reduction was undertaken by selecting metabolite concentrations through multi-class receiver operating characteristics and compared with principal component analysis. Classification accuracy was determined through leave-one-out and k-fold cross-validation. Metabolites identified as crucial in tumour classification include myo-inositol (P < 0.05, ), total lipids and macromolecules at 0.9 ppm (P < 0.05, ) and total creatine (P < 0.05, ) for the 1.5 T cohort, and glycine (P < 0.05, ), total N-acetylaspartate (P < 0.05, ) and total choline (P < 0.05, ) for the 3 T cohort. Compared with the principal components, the selected metabolites were able to provide significantly improved discrimination between the tumours through most classifiers (P < 0.05). The highest balanced classification accuracy determined through leave-one-out cross-validation was 85% for 1.5 T H-MRS through support vector machine and 75% for 3 T H-MRS through linear discriminant analysis after oversampling the minority. The study suggests that a group of crucial metabolites helps to achieve better discrimination between childhood brain tumours