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The prior distribution is the usual starting point for Bayesian uncertainty. In this paper, we present a different perspective that focuses on missing observations as the source of statistical uncertainty, with the parameter of interest being known precisely given the entire population. We argue that the foundation of Bayesian inference is to assign a distribution on missing observations conditional on what has been observed. In the i.i.d. setting with an observed sample of size n, the Bayesian would thus assign a predictive distribution on the missing Yn+1:\u221e conditional on Y1:n, which then induces a distribution on the parameter. We utilize Doob\u2019s theorem, which relies on martingales, to show that choosing the Bayesian predictive distribution returns the conventional posterior as the distribution of the parameter. Taking this as our cue, we relax the predictive machine, avoiding the need for the predictive to be derived solely from the usual prior to posterior to predictive density formula. We introduce the martingale posterior distribution, which returns Bayesian uncertainty on any statistic via the direct specification of the joint predictive. To that end, we introduce new predictive methodologies for multivariate density estimation, regression and classification that build upon recent work on bivariate copulas.
\n \n\n \n \nRecent work has reported that respiratory audio-trained AI classifiers can accurately predict SARS-CoV-2 infection status. However, it has not yet been determined whether such model performance is driven by latent audio biomarkers with true causal links to SARS-CoV-2 infection or by confounding effects, such as recruitment bias, present in observational studies. Here we undertake a large-scale study of audio-based AI classifiers as part of the UK government\u2019s pandemic response. We collect a dataset of audio recordings from 67,842 individuals, with linked metadata, of whom 23,514 had positive polymerase chain reaction tests for SARS-CoV-2. In an unadjusted analysis, similar to that in previous works, AI classifiers predict SARS-CoV-2 infection status with high accuracy (ROC\u2013AUC = 0.846 [0.838\u20130.854]). However, after matching on measured confounders, such as self-reported symptoms, performance is much weaker (ROC\u2013AUC = 0.619 [0.594\u20130.644]). Upon quantifying the utility of audio-based classifiers in practical settings, we find them to be outperformed by predictions on the basis of user-reported symptoms. We make best-practice recommendations for handling recruitment bias, and for assessing audio-based classifiers by their utility in relevant practical settings. Our work provides insights into the value of AI audio analysis and the importance of study design and treatment of confounders in AI-enabled diagnostics.
\n \n\n \n \nRecent development of new immune checkpoint inhibitors has been particularly successfully in cancer treatment, but still the majority patients fail to benefit. Converting resistant tumors to immunotherapy sensitive will provide a significant improvement in patient outcome. Here we identify Mi-2\u03b2 as a key melanoma-intrinsic effector regulating the adaptive anti-tumor immune response. Studies in genetically engineered mouse melanoma models indicate that loss of Mi-2\u03b2 rescues the immune response to immunotherapy in vivo. Mechanistically, ATAC-seq analysis shows that Mi-2\u03b2 controls the accessibility of IFN-\u03b3-stimulated genes (ISGs). Mi-2\u03b2 binds to EZH2 and promotes K510 methylation of EZH2, subsequently activating the trimethylation of H3K27 to inhibit the transcription of ISGs. Finally, we develop an Mi-2\u03b2-targeted inhibitor, Z36-MP5, which reduces Mi-2\u03b2 ATPase activity and reactivates ISG transcription. Consequently, Z36-MP5 induces a response to immune checkpoint inhibitors in otherwise resistant melanoma models. Our work provides a potential therapeutic strategy to convert immunotherapy resistant melanomas to sensitive ones.
\n \n\n \n \nPancreatic ductal adenocarcinoma (PDAC) is especially hypoxic and composed of heterogeneous cell populations containing hypoxia-adapted cells. Hypoxia as a microenvironment of PDAC is known to cause epithelial-mesenchymal transition (EMT) and resistance to therapy. Therefore, cells adapted to hypoxia possess malignant traits that should be targeted for therapy. However, current 3D organoid culture systems are usually cultured under normoxia, losing hypoxia-adapted cells due to selectivity bias at the time of organoid establishment. To overcome any potential selection bias, we focused on oxygen concentration during the establishment of 3D organoids. We subjected identical PDAC surgical samples to normoxia (O2 20%) or hypoxia (O2 1%), yielding glandular and solid organoid morphology, respectively. Pancreatic cancer organoids established under hypoxia displayed higher expression of EMT-related proteins, a Moffitt basal-like subtype transcriptome, and higher 5-FU resistance in contrast to organoids established under normoxia. We suggest that hypoxia during organoid establishment efficiently selects for hypoxia-adapted cells possibly responsible for PDAC malignant traits, facilitating a fundamental source for elucidating and developing new treatment strategies against PDAC.
\n \n\n \n \nChronic hepatitis B infection (CHB) is a significant problem worldwide with around 300 million people infected. Ambitious goals have been set towards its elimination as a public health threat by 2030. However, accurate seroprevalence estimates in many countries are lacking or fail to provide representative population estimates, particularly in the WHO African Region (AFRO). This means the full extent of HBV infection is not well described, leading to a lack of investment in diagnostics, treatment and disease prevention. Clinical trials in the WHO AFRO region have been increasing over time and many test for infectious diseases including hepatitis B virus (HBV) to determine baseline eligibility for participants, however these screening data are not reported. Here we review data from six clinical trials completed at the KEMRI-Wellcome Trust Research Programme between 2016 and 2023 that screened for HBV using hepatitis B surface antigen (HBsAg) as part of the trial exclusion criteria. 1727 people had HBsAg results available, of which 60 tested positive. We generated a crude period HBV prevalence estimate of 3.5% (95% CI 2.6-4.5%), and after standardisation for sex and age to account for the population structure of the Kilifi Health Demographics Surveillance System (KHDSS), the prevalence estimate increased to 5.0% (95% CI 3.4-6.6%). The underrepresentation of women in these trials was striking with 1263/1641 (77%) of participants being male. Alanine aminotransferase (ALT) was significantly higher in the HBsAg positive group but was not outside the normal range. We argue that routine collation and publishing of data from clinical trials could increase precision and geographical representation of global HBV prevalence estimates, enabling evidence-based provision of clinical care pathways and public health interventions to support progress towards global elimination targets. We do acknowledge when using clinical trials data for seroprevalence estimates, that local population structure data is necessary to allow standardisation of results, and the point of care tests used here are limited in sensitivity and specificity.
\n \n\n \n \nSummaryAllogeneic haematopoietic stem cell transplant (HSCT) recipients remain at high risk of adverse outcomes from coronavirus disease 2019 (COVID\u201019) and emerging variants. The optimal prophylactic vaccine strategy for this cohort is not defined. T cell\u2010mediated immunity is a critical component of graft\u2010versus\u2010tumour effect and in determining vaccine immunogenicity. Using validated anti\u2010spike (S) immunoglobulin G (IgG) and S\u2010specific interferon\u2010gamma enzyme\u2010linked immunospot (IFN\u03b3\u2010ELIspot)\u00a0assays we analysed response to a two\u2010dose vaccination schedule (either BNT162b2 or ChAdOx1) in 33 HSCT recipients at \u22642\u2009years from transplant, alongside vaccine\u2010matched healthy controls (HCs). After two vaccines, infection\u2010na\u00efve HSCT recipients had a significantly lower rate of seroconversion compared to infection\u2010na\u00efve HCs (25/32 HSCT vs. 39/39 HCs no responders) and had lower S\u2010specific T\u2010cell responses. The HSCT recipients who received BNT162b2 had a higher rate of seroconversion compared to ChAdOx1 (89% vs. 74%) and significantly higher anti\u2010S IgG titres (p\u00a0=\u00a00.022). S\u2010specific T\u2010cell responses were seen after one vaccine in HCs and HSCT recipients. However, two vaccines enhanced S\u2010specific T\u2010cell responses in HCs but not in the majority of HSCT recipients. These data demonstrate limited immunogenicity of two\u2010dose vaccination strategies in HSCT recipients, bolstering evidence of the need for additional boosters and/or alternative prophylactic measures in this group.
\n \n\n \n \nBackgroundLiver cancer has one of the fastest rising incidence and mortality rates among all cancers in the UK, but it receives little attention. This study aims to understand the disparities in epidemiology and clinical pathways of primary liver cancer and identify the gaps for early detection and diagnosis of liver cancer in England.MethodsThis study used a dynamic English primary care cohort of 8.52 million individuals aged \u226525 years in the QResearch database during 2008-2018, followed up to June 2021. The crude and age-standardised incidence rates, and the observed survival duration were calculated by sex and three liver cancer subtypes, including hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (CCA), and other specified/unspecified primary liver cancer. Regression models were used to investigate factors associated with an incident diagnosis of liver cancer, emergency presentation, late stage at diagnosis, receiving treatments, and survival duration after diagnosis by subtype.Findings7331 patients were diagnosed with primary liver cancer during follow-up. The age-standardised incidence rates increased over the study period, particularly for HCC in men (increased by 60%). Age, sex, socioeconomic deprivation, ethnicity, and geographical regions were all significantly associated with liver cancer incidence in the English primary care population. People aged \u226580 years were more likely to be diagnosed through emergency presentation and in late stages, less likely to receive treatments and had poorer survival than those aged <60 years. Men had a higher risk of being diagnosed with liver cancer than women, with a hazard ratio (HR) of 3.9 (95% confidence interval 3.6-4.2) for HCC, 1.2 (1.1-1.3) for CCA, and 1.7 (1.5-2.0) for other specified/unspecified liver cancer. Compared with white British, Asians and Black Africans were more likely to be diagnosed with HCC. Patients with higher socioeconomic deprivation were more likely to be diagnosed through the emergency route. Survival rates were poor overall. Patients diagnosed with HCC had better survival rates (14.5% at 10-year survival, 13.1%-16.0%) compared to CCA (4.4%, 3.4%-5.6%) and other specified/unspecified liver cancer (12.5%, 10.1%-15.2%). For 62.7% of patients with missing/unknown stage in liver cancer, their survival outcomes were between those diagnosed in Stages III and IV.InterpretationThis study provides an overview of the current epidemiology and the disparities in clinical pathways of primary liver cancer in England between 2008 and 2018. A complex public health approach is needed to tackle the rapid increase in incidence and the poor survival of liver cancer. Further studies are urgently needed to address the gaps in early detection and diagnosis of liver cancer in England.FundingThe Early Detection of Hepatocellular Liver Cancer (DeLIVER) project is funded by Cancer Research UK (Early Detection Programme Award, grant reference: C30358/A29725).
\n \n\n \n \nAbstract\nBackground and research aim\nThe incidence and mortality of liver cancer have been increasing in the UK in recent years. However, liver cancer is still under-studied. The Early Detection of Hepatocellular Liver Cancer (DeLIVER-QResearch) project aims to address the research gap and generate new knowledge to improve early detection and diagnosis of primary liver cancer from general practice and at the population level. There are three research objectives: (1) to understand the current epidemiology of primary liver cancer in England, (2) to identify and quantify the symptoms and comorbidities associated with liver cancer, and (3) to develop and validate prediction models for early detection of liver cancer suitable for implementation in clinical settings.\n\nMethods\nThis population-based study uses the QResearch\u00ae database (version 46) and includes adult patients aged 25\u201384\u00a0years old and without a diagnosis of liver cancer at the cohort entry (study period: 1 January 2008\u201330 June 2021). The team conducted a literature review (with additional clinical input) to inform the inclusion of variables for data extraction from the QResearch database. A wide range of statistical techniques will be used for the three research objectives, including descriptive statistics, multiple imputation for missing data, conditional logistic regression to investigate the association between the clinical features (symptoms and comorbidities) and the outcome, fractional polynomial terms to explore the non-linear relationship between continuous variables and the outcome, and Cox/competing risk regression for the prediction model. We have a specific focus on the 1-year, 5-year, and 10-year absolute risks of developing liver cancer, as risks at different time points have different clinical implications. The internal\u2013external cross-validation approach will be used, and the discrimination and calibration of the prediction model will be evaluated.\n\nDiscussion\nThe DeLIVER-QResearch project uses large-scale representative population-based data to address the most relevant research questions for early detection and diagnosis of primary liver cancer in England. This project has great potential to inform the national cancer strategic plan and yield substantial public and societal benefits.\n
\n \n\n \n \nThe aim of this systematic review and meta-analysis is to evaluate available prevalence and viral sequencing data representing chronic hepatitis B (CHB) infection in Kenya. More than 20% of the global disease burden from CHB is in Africa, however there is minimal high quality seroprevalence data from individual countries and little viral sequencing data available to represent the continent. We undertook a systematic review of the prevalence and genetic data available for hepatitis B virus (HBV) in Kenya using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) 2020 checklist. We identified 23 studies reporting HBV prevalence and 8 studies that included HBV genetic data published in English between January 2000 and December 2021. We assessed study quality using the Joanna Briggs Institute critical appraisal checklist. Due to study heterogeneity, we divided the studies to represent low, moderate, high and very high-risk for HBV infection, identifying 8, 7, 5 and 3 studies in these groups, respectively. We calculated pooled HBV prevalence within each group and evaluated available sequencing data. Pooled HBV prevalence was 3.4% (95% CI 2.7\u20134.2%), 6.1% (95% CI 5.1\u20137.4%), 6.2% (95% CI 4.64\u20138.2) and 29.2% (95% CI 12.2\u201355.1), respectively. Study quality was overall low; only three studies detailed sample size calculation and 17/23 studies were cross sectional. Eight studies included genetic information on HBV, with two undertaking whole genome sequencing. Genotype A accounted for 92% of infections. Other genotypes included genotype D (6%), D/E recombinants (1%) or mixed populations (1%). Drug resistance mutations were reported by two studies. There is an urgent need for more high quality seroprevalence and genetic data to represent HBV in Kenya to underpin improved HBV screening, treatment and prevention in order to support progress towards elimination targets.
\n \n\n \n \nThe new edition of this handbook continues to provide an accessible and comprehensive, signs-and-symptoms based source of information on medical problems commonly seen in the tropics.
\n \n\n \n \nBackgroundListeria monocytogenes is a food-borne pathogen that is a rare cause of bacteraemia and meningitis in immunosuppressed patients, and carries a high mortality rate. Cutaneous manifestations of listeriosis are rare, and are usually associated with direct inoculation of the skin.CaseA 41-year-old woman who initially presented to a hospital in Laos with appendicitis was diagnosed with disseminated cutaneous listeriosis without recognised risk factors. Intra-abdominal pathology probably contributed to bacterial bloodstream invasion. Initial treatment with meropenem was switched to ampicillin based on best practice, however our patient died 5 days after diagnosis.ConclusionsThis case highlights listeriosis as an important cause of mortality in low- and middle-income countries, exacerbated by poor availability of laboratory diagnostics and ineffective empiric antibiotic regimens. Improvements in food hygiene, surveillance, and increased laboratory capacity are important strategies to reduce rates of infection and clinical outcomes.
\n \n\n \n \nPurposeImmunoscore (IS) is prognostic in stage III colorectal cancer (CRC) and may predict benefit of duration (6 v 3 months) of adjuvant infusional fluorouracil, leucovorin, and oxaliplatin (FOLFOX) chemotherapy. We sought to determine IS prognostic and predictive value in stage-III CRC treated with adjuvant FOLFOX or oral capecitabine and infusional oxaliplatin (CAPOX) in the SCOT and IDEA-HORG trials.MethodsThree thousand sixty-one cases had tumor samples, of which 2,643 (1,792 CAPOX) were eligible for IS testing. Predefined cutoffs (IS-Low and IS-High) were used to classify cases into two groups for analysis of disease-free survival (3-year DFS) and multivariable-adjusted hazard ratios (mvHRs) by Cox regression.ResultsIS was determined in 2,608 (99.5%) eligible cases, with 877 (33.7%) samples classified as IS-Low. IS-Low tumors were more commonly high-risk (T4 and/or N2; 52.9% IS-Low v 42.2% IS-High; P < .001) and in younger patients (P = .024). Patients with IS-Low tumors had significantly shorter DFS in the CAPOX, FOLFOX, and combined cohorts (mvHR, 1.52 [95% CI, 1.28 to 1.82]; mvHR, 1.58 [95% CI, 1.22 to 2.04]; and mvHR, 1.55 [95% CI, 1.34 to 1.79], respectively; P < .001 all comparisons), regardless of sex, BMI, clinical risk group, tumor location, treatment duration, or chemotherapy regimen. IS prognostic value was greater in younger (\u226465 years) than older (>65 years) patients in the CAPOX cohort (mvHR, 1.92 [95% CI, 1.50 to 2.46] v 1.28 [95% CI, 1.01 to 1.63], PINTERACTION = .026), and in DNA mismatch repair proficient than deficient mismatch repair disease (mvHR, 1.68 [95% CI, 1.41 to 2.00] v 0.67 [95% CI, 0.30 to 1.49], PINTERACTION = .03), although these exploratory analyses were uncorrected for multiple testing. Adding IS to a model containing all clinical variables significantly improved prediction of DFS (likelihood ratio test, P < .001) regardless of MMR status.ConclusionIS is prognostic in stage III CRC treated with FOLFOX or CAPOX, including within clinically relevant tumor subgroups. Possible variation in IS prognostic value by age and MMR status, and prediction of benefit from extended adjuvant therapy merit validation.
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