Objective
To explore different models of clinical–insurer engagement around maternity safety and to understand how state insurers could and should engage with clinical staff to improve outcomes and ...reduce harm.
Design
Semi-structured interviews and focus groups were conducted with senior representatives from state insurers. Transcripts were analysed to identify different models of engagement. Themes were also elicited from the transcripts. A further one-day focus group allowed for clarification and elaboration of these themes.
Participants
Senior representatives from state insurers in England, Scotland, Wales, Republic of Ireland, Sweden and Victoria, Australia.
Results
A variety of clinical engagement activities were undertaken by the insurers. These included training on claims and risk management, hospital site visits, facilitating multi-professional network meetings and working with clinical experts to develop best practice recommendations. Some insurers engaged with frontline clinical staff through collaborative patient safety programmes. The themes (identity and size, data and research, incentivising improvement and system integration) were important for considering the role of state insurers within health systems and how insurers could engage with clinical teams.
Conclusions
This study identified different examples of clinical–insurer engagement. Whilst this was encouraging, the relationships between insurers and clinical teams could be developed further. Insurers and clinical staff could still collaborate more closely and work together in improving patient outcomes. Whilst not specifically their domain, insurers do have a role in patient safety. Closer clinical collaboration may strengthen this contribution.
Heterogeneity in reported outcomes can limit the synthesis of research evidence. A core outcome set informs what outcomes are important and should be measured as a minimum in all future studies. We ...report the development of a core outcome set applicable to observational and interventional studies of pregnant women with multimorbidity.
We developed the core outcome set in four stages: (i) a systematic literature search, (ii) three focus groups with UK stakeholders, (iii) two rounds of Delphi surveys with international stakeholders and (iv) two international virtual consensus meetings. Stakeholders included women with multimorbidity and experience of pregnancy in the last 5 years, or are planning a pregnancy, their partners, health or social care professionals and researchers. Study adverts were shared through stakeholder charities and organisations.
Twenty-six studies were included in the systematic literature search (2017 to 2021) reporting 185 outcomes. Thematic analysis of the focus groups added a further 28 outcomes. Two hundred and nine stakeholders completed the first Delphi survey. One hundred and sixteen stakeholders completed the second Delphi survey where 45 outcomes reached Consensus In (≥70% of all participants rating an outcome as Critically Important). Thirteen stakeholders reviewed 15 Borderline outcomes in the first consensus meeting and included seven additional outcomes. Seventeen stakeholders reviewed these 52 outcomes in a second consensus meeting, the threshold was ≥80% of all participants voting for inclusion. The final core outcome set included 11 outcomes. The five maternal outcomes were as follows: maternal death, severe maternal morbidity, change in existing long-term conditions (physical and mental), quality and experience of care and development of new mental health conditions. The six child outcomes were as follows: survival of baby, gestational age at birth, neurodevelopmental conditions/impairment, quality of life, birth weight and separation of baby from mother for health care needs.
Multimorbidity in pregnancy is a new and complex clinical research area. Following a rigorous process, this complexity was meaningfully reduced to a core outcome set that balances the views of a diverse stakeholder group.
Summary Type 1 diabetes (T1D) results from a complex interplay of genetic predisposition, immunological dysregulation, and environmental triggers, that culminate in the destruction of ...insulin‐secreting pancreatic β cells. This review provides a comprehensive examination of the multiple factors underpinning T1D pathogenesis, to elucidate key mechanisms and potential therapeutic targets. Beginning with an exploration of genetic risk factors, we dissect the roles of human leukocyte antigen (HLA) haplotypes and non‐HLA gene variants associated with T1D susceptibility. Mechanistic insights gleaned from the NOD mouse model provide valuable parallels to the human disease, particularly immunological intricacies underlying β cell–directed autoimmunity. Immunological drivers of T1D pathogenesis are examined, highlighting the pivotal contributions of both effector and regulatory T cells and the multiple functions of B cells and autoantibodies in β‐cell destruction. Furthermore, the impact of environmental risk factors, notably modulation of host immune development by the intestinal microbiome, is examined. Lastly, the review probes human longitudinal studies, unveiling the dynamic interplay between mucosal immunity, systemic antimicrobial antibody responses, and the trajectories of T1D development. Insights garnered from these interconnected factors pave the way for targeted interventions and the identification of biomarkers to enhance T1D management and prevention strategies.
Modeling bifurcations in single-cell transcriptomics data has become an increasingly popular field of research. Several methods have been proposed to infer bifurcation structure from such data, but ...all rely on heuristic non-probabilistic inference. Here we propose the first generative, fully probabilistic model for such inference based on a Bayesian hierarchical mixture of factor analyzers. Our model exhibits competitive performance on large datasets despite implementing full Markov-Chain Monte Carlo sampling, and its unique hierarchical prior structure enables automatic determination of genes driving the bifurcation process. We additionally propose an Empirical-Bayes like extension that deals with the high levels of zero-inflation in single-cell RNA-seq data and quantify when such models are useful. We apply or model to both real and simulated single-cell gene expression data and compare the results to existing pseudotime methods. Finally, we discuss both the merits and weaknesses of such a unified, probabilistic approach in the context practical bioinformatics analyses.
Objectives
Partial or total resistance to preoperative chemoradiotherapy occurs in more than half of locally advanced rectal cancer patients. Several novel or repurposed drugs have been trialled to ...improve cancer cell sensitivity to radiotherapy, with limited success. We aimed to understand the mechanisms of resistance to chemoradiotherapy in rectal cancer using patient derived organoid models.
Design
To understand the mechanisms underlying this resistance, we compared the pre-treatment transcriptomes of patient-derived organoids (PDO) with measured radiotherapy sensitivity to identify biological pathways involved in radiation resistance coupled with single cell sequencing, genome wide CRISPR-Cas9 and targeted drug screens.
Results
RNA sequencing enrichment analysis revealed upregulation of PI3K/AKT/mTOR and epithelial mesenchymal transition pathway genes in radioresistant PDOs. Single-cell sequencing of pre & post-irradiation PDOs showed mTORC1 and PI3K/AKT upregulation, which was confirmed by a genome-wide CRSIPR-Cas9 knockout screen using irradiated colorectal cancer (CRC) cell lines. We then tested the efficiency of dual PI3K/mTOR inhibitors in improving cancer cell sensitivity to radiotherapy. After irradiation, significant AKT phosphorylation was detected (
p
=0.027) which was abrogated with dual PI3K/mTOR inhibitors and lead to significant radiosensitisation of the HCT116 cell line and radiation resistant PDO lines.
Conclusions
The PI3K/AKT/mTOR pathway upregulation contributes to radioresistance and its targeted pharmacological inhibition leads to significant radiosensitisation in CRC organoids, making it a potential target for clinical trials.
IntroductionConsidering the high prevalence of polypharmacy in pregnant women and the knowledge gap in the risk–benefit safety profile of their often-complex treatment plan, more research is needed ...to optimise prescribing. In this study, we aim to detect adverse and protective effect signals of exposure to individual and pairwise combinations of medications during pregnancy.Methods and analysisUsing a range of real-world data sources from the UK, we aim to conduct a pharmacovigilance study to assess the safety of medications prescribed during the preconception period (3 months prior to conception) and first trimester of pregnancy. Women aged between 15 and 49 years with a record of pregnancy within the Clinical Practice Research Datalink (CPRD) Pregnancy Register, the Welsh Secure Anonymised Information Linkage (SAIL), the Scottish Morbidity Record (SMR) data sets and the Northern Ireland Maternity System (NIMATS) will be included. A series of case control studies will be conducted to estimate measures of disproportionality, detecting signals of association between a range of pregnancy outcomes and exposure to individual and combinations of medications. A multidisciplinary expert team will be invited to a signal detection workshop. By employing a structured framework, signals will be transparently assessed by each member of the team using a questionnaire appraising the signals on aspects of temporality, selection, time and measurement-related biases and confounding by underlying disease or comedications. Through group discussion, the expert team will reach consensus on each of the medication exposure–outcome signal, thereby excluding spurious signals, leaving signals suggestive of causal associations for further evaluation.Ethics and disseminationEthical approval has been obtained from the Independent Scientific Advisory Committee, SAIL Information Governance Review Panel, University of St. Andrews Teaching and Research Ethics Committee and Office for Research Ethics Committees Northern Ireland (ORECNI) for access and use of CPRD, SAIL, SMR and NIMATS data, respectively.
IntroductionIncreasingly more pregnant women are living with pre-existing multimorbidity (≥two long-term physical or mental health conditions). This may adversely affect maternal and offspring ...outcomes. This study aims to develop a core outcome set (COS) for maternal and offspring outcomes in pregnant women with pre-existing multimorbidity. It is intended for use in observational and interventional studies in all pregnancy settings.Methods and analysisWe propose a four stage study design: (1) systematic literature search, (2) focus groups, (3) Delphi surveys and (4) consensus group meeting. The study will be conducted from June 2021 to August 2022. First, an initial list of outcomes will be identified through a systematic literature search of reported outcomes in studies of pregnant women with multimorbidity. We will search the Cochrane library, Medline, EMBASE and CINAHL. This will be supplemented with relevant outcomes from published COS for pregnancies and childbirth in general, and multimorbidity. Second, focus groups will be conducted among (1) women with lived experience of managing pre-existing multimorbidity in pregnancy (and/or their partners) and (2) their healthcare/social care professionals to identify outcomes important to them. Third, these initial lists of outcomes will be prioritised through a three-round online Delphi survey using predefined score criteria for consensus. Participants will be invited to suggest additional outcomes that were not included in the initial list. Finally, a consensus meeting using the nominal group technique will be held to agree on the final COS. The stakeholders will include (1) women (and/or their partners) with lived experience of managing multimorbidity in pregnancy, (2) healthcare/social care professionals involved in their care and (3) researchers in this field.Ethics and disseminationThis study has been approved by the University of Birmingham’s ethical review committee. The final COS will be disseminated through peer-reviewed publication and conferences and to all stakeholders.
IntroductionOne in five pregnant women has multiple pre-existing long-term conditions in the UK. Studies have shown that maternal multiple long-term conditions are associated with adverse outcomes. ...This observational study aims to compare maternal and child outcomes for pregnant women with multiple long-term conditions to those without multiple long-term conditions (0 or 1 long-term conditions).Methods and analysisPregnant women aged 15–49 years old with a conception date between 2000 and 2019 in the UK will be included with follow-up till 2019. The data source will be routine health records from all four UK nations (Clinical Practice Research Datalink (England), Secure Anonymised Information Linkage (Wales), Scotland routine health records and Northern Ireland Maternity System) and the Born in Bradford birth cohort. The exposure of two or more pre-existing, long-term physical or mental health conditions will be defined from a list of health conditions predetermined by women and clinicians. The association of maternal multiple long-term conditions with (a) antenatal, (b) peripartum, (c) postnatal and long-term and (d) mental health outcomes, for both women and their children will be examined. Outcomes of interest will be guided by a core outcome set. Comparisons will be made between pregnant women with and without multiple long-term conditions using modified Poisson and Cox regression. Generalised estimating equation will account for the clustering effect of women who had more than one pregnancy episode. Where appropriate, multiple imputation with chained equation will be used for missing data. Federated analysis will be conducted for each dataset and results will be pooled using random-effects meta-analyses.Ethics and disseminationApproval has been obtained from the respective data sources in each UK nation. Study findings will be submitted for publications in peer-reviewed journals and presented at key conferences.
Bulk whole genome sequencing (WGS) enables the analysis of tumor evolution but, because of depth limitations, can only identify old mutational events. The discovery of current mutational processes ...for predicting the tumor's evolutionary trajectory requires dense sequencing of individual clones or single cells. Such studies, however, are inherently problematic because of the discovery of excessive false positive (FP) mutations when sequencing picogram quantities of DNA. Data pooling to increase the confidence in the discovered mutations, moves the discovery back in the past to a common ancestor. Here we report a robust WGS and analysis pipeline (DigiPico/MutLX) that virtually eliminates all F results while retaining an excellent proportion of true positives. Using our method, we identified, for the first time, a hyper-mutation (kataegis) event in a group of ∼30 cancer cells from a recurrent ovarian carcinoma. This was unidentifiable from the bulk WGS data. Overall, we propose DigiPico/MutLX method as a powerful framework for the identification of clone-specific variants at an unprecedented accuracy.
Prevalence of colorectal cancer (CRC) in the British Bangladeshi population (BAN) is low compared to British Caucasians (CAU). Genetic background may influence mutations and disease features.
We ...characterized the clinicopathological features of BAN CRCs and interrogated their genomes using mutation profiling and high-density single nucleotide polymorphism (SNP) arrays and compared findings to CAU CRCs.
Age of onset of BAN CRC was significantly lower than for CAU patients (p=3.0 x 10-5) and this difference was not due to Lynch syndrome or the polyposis syndromes. KRAS mutations in BAN microsatellite stable (MSS) CRCs were comparatively rare (5.4%) compared to CAU MSS CRCs (25%; p=0.04), which correlates with the high percentage of mucinous histotype observed (31%) in the BAN samples. No BRAF mutations was seen in our BAN MSS CRCs (CAU CRCs, 12%; p=0.08). Array data revealed similar patterns of gains (chromosome 7 and 8q), losses (8p, 17p and 18q) and LOH (4q, 17p and 18q) in BAN and CAU CRCs. A small deletion on chromosome 16p13.2 involving the alternative splicing factor RBFOX1 only was found in significantly more BAN (50%) than CAU CRCs (15%) cases (p=0.04). Focal deletions targeting the 5' end of the gene were also identified. Novel RBFOX1 mutations were found in CRC cell lines and tumours; mRNA and protein expression was reduced in tumours.
KRAS mutations were rare in BAN MSS CRC and a mucinous histotype common. Loss of RBFOX1 may explain the anomalous splicing activity associated with CRC.
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