Association of meat, vegetarian, pescatarian and fish-poultry diets with risk of 19 cancer sites and all cancer: findings from the UK Biobank prospective cohort study and meta-analysis

The associations of cancer with types of diets, including vegetarian, fish, and poultry-containing diets, remain unclear. The aim of this study was, therefore, to investigate the association of type of diet with all cancers and 19 site-specific incident cancers in a prospective cohort study and then in a meta-analysis of published prospective cohort studies. A total of 409,110 participants from the UK Biobank study, recruited between 2006 and 2010, were included. The outcomes were incidence of all cancers combined and 19 cancer sites. Associations between the types of diets and cancer were investigated using Cox proportional hazards models. Previously published prospective cohort studies were identified from four databases, and a meta-analysis was conducted using random-effects models. The mean follow-up period was 10.6 years (IQR 10.0; 11.3). Compared with meat-eaters, vegetarians (hazard ratio (HR) 0.87 [95% CI: 0.79 to 0.96]) and pescatarians (HR 0.93 [95% CI: 0.87 to 1.00]) had lower overall cancer risk. Vegetarians also had a lower risk of colorectal and prostate cancers compared with meat-eaters. In the meta-analysis, vegetarians (Risk Ratio (RR): 0.90 [0.86 to 0.94]) and pescatarians (RR 0.91 [0.86; 0.96]) had lower risk of overall and colorectal cancer. No associations between the types of diets and prostate, breast, or lung cancers were found. Compared with meat-eaters, vegetarians and pescatarians had a lower risk of overall, colorectal, and prostate cancer. When results were pooled in a meta-analysis, the associations with overall and colorectal cancer persisted, but the results relating to other specific cancer sites were inconclusive. [Abstract copyright: © 2022. The Author(s).

A blended knowledge translation initiative to improve colorectal cancer staging [ISRCTN56824239]

BACKGROUND: A significant gap has been documented between best practice and the actual practice of surgery. Our group identified that colorectal cancer staging in Ontario was suboptimal and subsequently developed a knowledge translation strategy using the principles of social marketing and the influence of expert and local opinion leaders for colorectal cancer. METHODS/DESIGN: Opinion leaders were identified using the Hiss methodology. Hospitals in Ontario were cluster-randomized to one of two intervention arms. Both groups were exposed to a formal continuing medical education session given by the expert opinion leader for colorectal cancer. In the treatment group the local Opinion Leader for colorectal cancer was detailed by the expert opinion leader for colorectal cancer and received a toolkit. Forty-two centres agreed to have the expert opinion leader for colorectal cancer come and give a formal continuing medical education session that lasted between 50 minutes and 4 hours. No centres refused the intervention. These sessions were generally well attended by most surgeons, pathologists and other health care professionals at each centre. In addition all but one of the local opinion leaders for colorectal cancer met with the expert opinion leader for colorectal cancer for the academic detailing session that lasted between 15 and 30 minutes. DISCUSSION: We have enacted a unique study that has attempted to induce practice change among surgeons and pathologists using an adapted social marketing model that utilized the influence of both expert and local opinion leaders for colorectal cancer in a large geographic area with diverse practice settings

A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial

Background: Despite the availability of continuous conventional electroencephalography (cEEG), accurate diagnosis of neonatal seizures is challenging in clinical practice. Algorithms for decision support in the recognition of neonatal seizures could improve detection. We aimed to assess the diagnostic accuracy of an automated seizure detection algorithm called Algorithm for Neonatal Seizure Recognition (ANSeR).Methods: This multicentre, randomised, two-arm, parallel, controlled trial was done in eight neonatal centres across Ireland, the Netherlands, Sweden, and the UK. Neonates with a corrected gestational age between 36 and 44 weeks with, or at significant risk of, seizures requiring EEG monitoring, received cEEG plus ANSeR linked to the EEG monitor displaying a seizure probability trend in real time (algorithm group) or cEEG monitoring alone (non algorithm group). The primary outcome was diagnostic accuracy (sensitivity, specificity, and false detection rate) of health-care professionals to identify neonates with electrographic seizures and seizure hours with and without the support of the ANSeR algorithm. Neonates with data on the outcome of interest were included in the analysis. This study is registered with ClinicalTrials.gov, NCT02431780.Findings: Between Feb 13, 2015, and Feb 7, 2017, 132 neonates were randomly assigned to the algorithm group and 132 to the non-algorithm group. Six neonates were excluded (four from the algorithm group and two from the non-algorithm group). Electrographic seizures were present in 32 (25.0%) of 128 neonates in the algorithm group and 38 (29.2%) of 130 neonates in the non-algorithm group. For recognition of neonates with electrographic seizures, sensitivity was 81.3% (95% CI 66.7-93.3) in the algorithm group and 89.5% (78.4-97.5) in the non-algorithm group; specificity was 84.4% (95% CI 76.9-91.0) in the algorithm group and 89.1% (82.5-94.7) in the non-algorithm group; and the false detection rate was 36.6% (95% CI 22.7-52.1) in the algorithm group and 22.7% (11.6-35.9) in the non-algorithm group. We identified 659 h in which seizures occurred (seizure hours): 268 h in the algorithm versus 391 h in the non algorithm group. The percentage of seizure hours correctly identified was higher in the algorithm group than in the non-algorithm group (177 [66.0%; 95% CI 53.8-77.3] of 268 h vs 177 [45.3%; 34.5-58.3] of 391 h; difference 20.8% [3.6-37.1]). No significant differences were seen in the percentage of neonates with seizures given at least one inappropriate antiseizure medication (37.5% [95% CI 25.0 to 56.3] vs 31.6% [21.1 to 47.4]; difference 5.9% [-14.0 to 26.3]).Interpretation ANSeR, a machine-learning algorithm, is safe and able to accurately detect neonatal seizures. Although the algorithm did not enhance identification of individual neonates with seizures beyond conventional EEG, recognition of seizure hours was improved with use of ANSeR. The benefit might be greater in less experienced centres, but further study is required

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe

Rapid and highly variable warming of lake surface waters around the globe

In this first worldwide synthesis of in situ and satellite-derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade-1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors - from seasonally ice-covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade-1) to ice-free lakes experiencing increases in air temperature and solar radiation (0.53°C decade-1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts