Identification of potential mediators of the relationship between body mass index and colorectal cancer: a Mendelian randomization analysis.

BACKGROUND: Colorectal cancer (CRC) is the third-most-common cancer worldwide and its rates are increasing. Elevated body mass index (BMI) is an established risk factor for CRC, although the molecular mechanisms behind this association remain unclear. Using the Mendelian randomization (MR) framework, we aimed to investigate the mediating effects of putative biomarkers and other CRC risk factors in the association between BMI and CRC. METHODS: We selected as mediators biomarkers of established cancer-related mechanisms and other CRC risk factors for which a plausible association with obesity exists, such as inflammatory biomarkers, glucose homeostasis traits, lipids, adipokines, insulin-like growth factor 1 (IGF1), sex hormones, 25-hydroxy-vitamin D, smoking, physical activity (PA) and alcohol consumption. We used inverse-variance weighted MR in the main univariable analyses and performed sensitivity analyses (weighted-median, MR-Egger, Contamination Mixture). We used multivariable MR for the mediation analyses. RESULTS: Genetically predicted BMI was positively associated with CRC risk [odds ratio per SD (5 kg/m2) = 1.17, 95% CI: 1.08-1.24, P-value = 1.4 × 10-5] and robustly associated with nearly all potential mediators. Genetically predicted IGF1, fasting insulin, low-density lipoprotein cholesterol, smoking, PA and alcohol were associated with CRC risk. Evidence for attenuation was found for IGF1 [explained 7% (95% CI: 2-13%) of the association], smoking (31%, 4-57%) and PA (7%, 2-11%). There was little evidence for pleiotropy, although smoking was bidirectionally associated with BMI and instruments were weak for PA. CONCLUSIONS: The effect of BMI on CRC risk is possibly partly mediated through plasma IGF1, whereas the attenuation of the BMI-CRC association by smoking and PA may reflect confounding and shared underlying mechanisms rather than mediation.

Post-diagnosis adiposity, physical activity, sedentary behaviour, dietary factors, supplement use and colorectal cancer prognosis: Global Cancer Update Programme (CUP Global) summary of evidence grading.

Based on the World Cancer Research Fund Global Cancer Update Programme, we performed systematic reviews and meta-analyses to investigate the association of post-diagnosis adiposity, physical activity, sedentary behaviour, and dietary factors with colorectal cancer prognosis. We searched PubMed and Embase until 28th February, 2022. An independent expert committee and expert panel graded the quality of evidence. A total of 167 unique publications were reviewed, and all but five were observational studies. The quality of the evidence was graded conservatively due to the high risk of several biases. There was evidence of non-linearity in the associations between body mass index and colorectal cancer prognosis. The associations appeared reverse J-shaped, and the quality of this evidence was graded as limited (likelihood of causality: limited-no conclusion). The evidence on recreational physical activity and lower risk of all-cause mortality (relative risk [RR] highest vs. lowest: 0.69, 95% confidence interval [CI]: 0.62-0.77) and recurrence/disease-free survival (RR: 0.80, 95% CI: 0.70-0.92) was graded as limited-suggestive. There was limited-suggestive evidence for the associations between healthy dietary and/or lifestyle patterns (including diets that comprised plant-based foods), intake of whole grains and coffee with lower risk of all-cause mortality, and between unhealthy dietary patterns and intake of sugary drinks with higher risk of all-cause mortality. The evidence for other exposures on colorectal cancer outcomes was sparse and graded as limited-no conclusion. Analyses were conducted excluding cancer patients with metastases without substantial changes in the findings. Well-designed intervention and cohort studies are needed to support the development of lifestyle recommendations for colorectal cancer patients.

Post-diagnosis dietary factors, supplement use and colorectal cancer prognosis: A Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis.

The role of diet in colorectal cancer prognosis is not well understood and specific lifestyle recommendations are lacking. We searched for randomised controlled trials (RCTs) and longitudinal observational studies on post-diagnosis dietary factors, supplement use and colorectal cancer survival outcomes in PubMed and Embase from inception until 28th February 2022. Random-effects dose-response meta-analyses were conducted when at least three studies had sufficient information. The evidence was interpreted and graded by the CUP Global independent Expert Committee on Cancer Survivorship and Expert Panel. Five RCTs and 35 observational studies were included (30,242 cases, over 8700 all-cause and 2100 colorectal cancer deaths, 3700 progression, recurrence, or disease-free events). Meta-analyses, including 3-10 observational studies each, were conducted for: whole grains, nuts/peanuts, red and processed meat, dairy products, sugary drinks, artificially sweetened beverages, coffee, alcohol, dietary glycaemic load/index, insulin load/index, marine omega-3 polyunsaturated fatty acids, supplemental calcium, circulating 25-hydroxyvitamin D (25[OH]D) and all-cause mortality; for alcohol, supplemental calcium, circulating 25(OH)D and colorectal cancer-specific mortality; and for circulating 25(OH)D and recurrence/disease-free survival. The overall evidence was graded as 'limited'. The inverse associations between healthy dietary and/or lifestyle patterns (including diets that comprised plant-based foods), whole grains, total, caffeinated, or decaffeinated coffee and all-cause mortality and the positive associations between unhealthy dietary patterns, sugary drinks and all-cause mortality provided 'limited-suggestive' evidence. All other exposure-outcome associations provided 'limited-no conclusion' evidence. Additional, well-conducted cohort studies and carefully designed RCTs are needed to develop specific lifestyle recommendations for colorectal cancer survivors.

Familiarity, confidence and preference of artificial intelligence feedback and prompts by Australian breast cancer screening readers.

ObjectivesThis study explored the familiarity, perceptions and confidence of Australian radiology clinicians involved in reading screening mammograms, regarding artificial intelligence (AI) applications in breast cancer detection.MethodsSixty-five radiologists, breast physicians and radiology trainees participated in an online survey that consisted of 23 multiple choice questions asking about their experience and familiarity with AI products. Furthermore, the survey asked about their confidence in using AI outputs and their preference for AI modes applied in a breast screening context. Participants' responses to questions were compared using Pearson's χ2 test. Bonferroni-adjusted significance tests were used for pairwise comparisons.ResultsFifty-five percent of respondents had experience with AI in their workplaces, with automatic density measurement powered by machine learning being the most familiar AI product (69.4%). The top AI outputs with the highest ranks of perceived confidence were 'Displaying suspicious areas on mammograms with the percentage of cancer possibility' (67.8%) and 'Automatic mammogram classification (normal, benign, cancer, uncertain)' (64.6%). Radiology and breast physicians preferred using AI as second-reader mode (75.4% saying 'somewhat happy' to 'extremely happy') over triage (47.7%), pre-screening and first-reader modes (both with 26.2%) (P < 0.001).ConclusionThe majority of screen readers expressed increased confidence in utilising AI for highlighting suspicious areas on mammograms and for automatically classifying mammograms. They considered AI as an optimal second-reader mode being the most ideal use in a screening program. The findings provide valuable insights into the familiarities and expectations of radiologists and breast clinicians for the AI products that can enhance the effectiveness of the breast cancer screening programs, benefitting both healthcare professionals and patients alike.

Post-diagnosis physical activity and sedentary behaviour and colorectal cancer prognosis: A Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis.

Low physical activity and high sedentary behaviour have been clearly linked with colorectal cancer development, yet data on their potential role in colorectal cancer survival is limited. Better characterisation of these relationships is needed for the development of post-diagnosis physical activity and sedentary behaviour guidance for colorectal cancer survivors. We searched PubMed and Embase through 28 February 2022 for studies assessing post-diagnosis physical activity, and/or sedentary behaviour in relation to all-cause and cause-specific mortality and recurrence after colorectal cancer diagnosis. Total and recreational physical activity were assessed overall and by frequency, duration, intensity, and volume using categorical, linear, and non-linear dose-response random-effects meta-analyses. The Global Cancer Update Programme (CUP Global) independent Expert Committee on Cancer Survivorship and Expert Panel interpreted and graded the likelihood of causality. We identified 16 observational studies on 82,220 non-overlapping patients from six countries. Physical activity was consistently inversely associated with colorectal cancer morbidity and mortality outcomes, with 13%-60% estimated reductions in risk. Sedentary behaviour was positively associated with all-cause mortality. The evidence had methodological limitations including potential confounding, selection bias and reverse causation, coupled with a limited number of studies for most associations. The CUP Global Expert panel concluded limited-suggestive evidence for recreational physical activity with all-cause mortality and cancer recurrence. Total physical activity and its specific domains and dimensions, and sedentary behaviour were all graded as limited-no conclusion for all outcomes. Future research should focus on randomised trials, while observational studies should obtain objective and repeated physical activity measures and better adjustment for confounders.

Post-diagnosis adiposity and colorectal cancer prognosis: A Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis.

The adiposity influence on colorectal cancer prognosis remains poorly characterised. We performed a systematic review and meta-analysis on post-diagnosis adiposity measures (body mass index [BMI], waist circumference, waist-to-hip ratio, weight) or their changes and colorectal cancer outcomes. PubMed and Embase were searched through 28 February 2022. Random-effects meta-analyses were conducted when at least three studies had sufficient information. The quality of evidence was interpreted and graded by the Global Cancer Update Programme (CUP Global) independent Expert Committee on Cancer Survivorship and Expert Panel. We reviewed 124 observational studies (85 publications). Meta-analyses were possible for BMI and all-cause mortality, colorectal cancer-specific mortality, and cancer recurrence/disease-free survival. Non-linear meta-analysis indicated a reverse J-shaped association between BMI and colorectal cancer outcomes (nadir at BMI 28 kg/m2). The highest risk, relative to the nadir, was observed at both ends of the BMI distribution (18 and 38 kg/m2), namely 60% and 23% higher risk for all-cause mortality; 95% and 26% for colorectal cancer-specific mortality; and 37% and 24% for cancer recurrence/disease-free survival, respectively. The higher risk with low BMI was attenuated in secondary analyses of RCTs (compared to cohort studies), among studies with longer follow-up, and in women suggesting potential methodological limitations and/or altered physiological state. Descriptively synthesised studies on other adiposity-outcome associations of interest were limited in number and methodological quality. All the associations were graded as limited (likelihood of causality: no conclusion) due to potential methodological limitations (reverse causation, confounding, selection bias). Additional well-designed observational studies and interventional trials are needed to provide further clarification.

Environmental and genetic predictors of whole blood mercury and selenium concentrations in pregnant women in a UK birth cohort.

There is evidence that tissue concentrations of mercury (Hg) and selenium (Se) are predicted by numerous dietary, sociodemographic, environmental, and genetic factors. This study aimed to estimate the relative importance of predictors of Hg and Se concentrations in blood samples taken from pregnant women. The Avon Longitudinal Study of Parents and Children (ALSPAC) in the UK measured whole blood Hg and Se concentrations in 3,972 pregnant women. We identified 30 potential predictors of Hg and 24 of Se, which were evaluated using cross-validated random forests to identify the optimal models for predictive power. The relative importance of individual variables was estimated by averaging the added-R2 per predictor. Linkage disequilibrium score regression was used to estimate the variance explained by genotype. A multivariable model of 14 predictors explained 22.4% of Hg variance (95% CI: 13.0 to 37.1), including 6.9% from blood Se and 3.2% from white fish consumption. There were 11 predictors which explained 15.3% of Se variance (CI: 8.9 to 25.9), including 6.4% from blood Hg, 1.3% from blood lead, and 1.3% from oily fish. Measured genetic variation explained 30% of Hg variance (CI: 8.4 to 51.5) and 37.5% of Se (CI: 10.4 to 64.5). A high proportion of Hg and Se variance could be explained from dietary, sociodemographic, metabolic, and genetic factors. Seafood consumption was less predictive of Hg than may be expected and other factors should be considered when determining risk of exposure. There was tentative evidence that genotype is a major contributor to Hg and Se variation, possibly by modifying the efficacy of internal metabolism.

Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis.

BACKGROUND: Tumour-promoting inflammation is a "hallmark" of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear. METHODS: We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combined cis-Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,294 cancer cases and up to 1,238,345 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant (P < 5.0 × 10-8) cis-acting SNPs (i.e., in or ±250 kb from the gene encoding the relevant protein) in weak linkage disequilibrium (LD, r2 < 0.10). Effect estimates were generated using inverse-variance weighted random-effects models and standard errors were inflated to account for weak LD between variants with reference to the 1000 Genomes Phase 3 CEU panel. A false discovery rate (FDR)-corrected P-value ("q-value") <0.05 was used as a threshold to define "strong evidence" to support associations and 0.05 ≤ q-value < 0.20 to define "suggestive evidence". A colocalisation posterior probability (PPH4) >70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes. Findings were replicated in the FinnGen study and then pooled using meta-analysis. FINDINGS: We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR: 1.19, 95% CI: 1.10-1.29, q-value = 0.033, PPH4 = 84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR: 1.42, 95% CI: 1.20-1.69, q-value = 0.055, PPH4 = 73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR: 0.66, 95% CI: 0.53-0.81, q-value = 0.067, PPH4 = 81.8%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR: 0.92, 95% CI: 0.88-0.97, q-value = 0.15, PPH4 = 85.6%). These findings were replicated in pooled analyses with the FinnGen study. Though suggestive evidence was found to support an association of macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR: 2.46, 95% CI: 1.48-4.10, q-value = 0.072, PPH4 = 76.1%), this finding was not replicated when pooled with the FinnGen study. For 22 of 30 cancer outcomes examined, there was little evidence (q-value ≥0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk. INTERPRETATION: Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 4 circulating inflammatory markers in risk of 4 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated. FUNDING: Cancer Research UK (C68933/A28534, C18281/A29019, PPRCPJT∖100005), World Cancer Research Fund (IIG_FULL_2020_022), National Institute for Health Research (NIHR202411, BRC-1215-20011), Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4), Academy of Finland Project 326291, European Union's Horizon 2020 grant agreement no. 848158 (EarlyCause), French National Cancer Institute (INCa SHSESP20, 2020-076), Versus Arthritis (21173, 21754, 21755), National Institutes of Health (U19 CA203654), National Cancer Institute (U19CA203654).

Computer-extracted global radiomic features can predict the radiologists' first impression about the abnormality of a screening mammogram.

OBJECTIVE: Radiologists can detect the gist of abnormal based on their rapid initial impression on a mammogram (ie, global gist signal [GGS]). This study explores (1) whether global radiomic (ie, computer-extracted) features can predict the GGS; and if so, (ii) what features are the most important drivers of the signals. METHODS: The GGS of cases in two extreme conditions was considered: when observers detect a very strong gist (high-gist) and when the gist of abnormal was not/poorly perceived (low-gist). Gist signals/scores from 13 observers reading 4191 craniocaudal mammograms were collected. As gist is a noisy signal, the gist scores from all observers were averaged and assigned to each image. The high-gist and low-gist categories contained all images in the fourth and first quartiles, respectively. One hundred thirty handcrafted global radiomic features (GRFs) per mammogram were extracted and utilized to construct eight separate machine learning random forest classifiers (All, Normal, Cancer, Prior-1, Prior-2, Missed, Prior-Visible, and Prior-Invisible) for characterizing high-gist from low-gist images. The models were trained and validated using the 10-fold cross-validation approach. The models' performances were evaluated by the area under receiver operating characteristic curve (AUC). Important features for each model were identified through a scree test. RESULTS: The Prior-Visible model achieved the highest AUC of 0.84 followed by the Prior-Invisible (0.83), Normal (0.82), Prior-1 (0.81), All (0.79), Prior-2 (0.77), Missed (0.75), and Cancer model (0.69). Cluster shade, standard deviation, skewness, kurtosis, and range were identified to be the most important features. CONCLUSIONS: Our findings suggest that GRFs can accurately classify high- from low-gist images. ADVANCES IN KNOWLEDGE: Global mammographic radiomic features can accurately predict high- from low-gist images with five features identified to be valuable in describing high-gist images. These are critical in providing better understanding of the mammographic image characteristics that drive the strength of the GGSs which could be exploited to advance breast cancer (BC) screening and risk prediction, enabling early detection and treatment of BC thereby further reducing BC-related deaths.

Evaluating Recalibrating AI Models for Breast Cancer Diagnosis in a New Context: Insights from Transfer Learning, Image Enhancement and High-Quality Training Data Integration.

This paper investigates the adaptability of four state-of-the-art artificial intelligence (AI) models to the Australian mammographic context through transfer learning, explores the impact of image enhancement on model performance and analyses the relationship between AI outputs and histopathological features for clinical relevance and accuracy assessment. A total of 1712 screening mammograms (n = 856 cancer cases and n = 856 matched normal cases) were used in this study. The 856 cases with cancer lesions were annotated by two expert radiologists and the level of concordance between their annotations was used to establish two sets: a 'high-concordances subset' with 99% agreement of cancer location and an 'entire dataset' with all cases included. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of Globally aware Multiple Instance Classifier (GMIC), Global-Local Activation Maps (GLAM), I&H and End2End AI models, both in the pretrained and transfer learning modes, with and without applying the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm. The four AI models with and without transfer learning in the high-concordance subset outperformed those in the entire dataset. Applying the CLAHE algorithm to mammograms improved the performance of the AI models. In the high-concordance subset with the transfer learning and CLAHE algorithm applied, the AUC of the GMIC model was highest (0.912), followed by the GLAM model (0.909), I&H (0.893) and End2End (0.875). There were significant differences (p < 0.05) in the performances of the four AI models between the high-concordance subset and the entire dataset. The AI models demonstrated significant differences in malignancy probability concerning different tumour size categories in mammograms. The performance of AI models was affected by several factors such as concordance classification, image enhancement and transfer learning. Mammograms with a strong concordance with radiologists' annotations, applying image enhancement and transfer learning could enhance the accuracy of AI models.

Infection prevention and control in computed tomography: creating a national survey.

BACKGROUND: Infection prevention and control (IPC) is essential for quality healthcare, with healthcare associated infections (HAI) a known risk to patients requiring medical imaging (MI). To date, few papers have adopted a national approach to understanding or benchmarking the knowledge of, attitudes toward, and practice (KAP) of IPC in the context of MI and no validated surveys or scales are identified in the literature. The Computed Tomography (CT) suite is a unique MI environment where radiographers deliver prescription medicines to patients via intravenous (IV) means through an injector system. This paper describes the development of a survey that informs the use of IPC processes in the CT suite. METHODS: Standard Precautions via current national guidelines formed the benchmark of the survey, with a KAP survey used as the framework to explore IPC. The questions and associated responses are developed based on the National Health and Medical Research Council (NHMRC) guidelines, industry/professional protocols and adapted to the equipment and practices commonly used in the CT suite of MI departments by radiographers and nurses. RESULTS: Key survey development steps are described to include the justification of the benchmarking source, the survey framework and design. Detailed information is given to show the evolution of truth statements and sources, KAP question variations, and rationales for the methodology of question responses. National guidelines are mapped to survey questions and responses and pilot testing reflections are included. CONCLUSION: This paper reports on the construction of a standardised KAP survey for IPC specific to the CT suite in the Australian healthcare setting. The survey is ready for dissemination amongst MI departments. Documented use will aid validation and reliability as a survey tool to measure and map IPC specifically in relation to IV contrast administration.

Prevalence and Factors Associated with Behavioral Problems in 5-Year-Old Children Born with Cleft Lip and/or Palate from the Cleft Collective.

OBJECTIVES: To determine the UK prevalence of behavioral problems in 5-year-old children born with isolated or syndromic cleft lip and/or palate (CL/P) compared to the general population and identify potentially associated factors. DESIGN: Observational study using questionnaire data from the Cleft Collective 5-Year-Old Cohort study and three general population samples. MAIN OUTCOME MEASURE: The Strengths and Difficulties Questionnaire (SDQ). PARTICIPANTS: Mothers of children (age: 4.9-6.8 years) born with CL/P (n = 325). UK general population cohorts for SDQ scores were: Millennium Cohort Study (MCS) (n = 12 511), Office of National Statistics (ONS) normative school-age SDQ data (n = 5855), and Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 9386). RESULTS: By maternal report, 14.2% of children born with CL/P were above clinical cut-off for behavioral problems, which was more likely than in general population samples: 7.5% of MCS (OR = 2.05 [1.49-2.82], P < 0.001), 9.8% of ONS (OR = 1.52 [1.10-2.09], P = 0.008), and 6.6% of ALSPAC (OR = 2.34 [1.70-3.24], P < 0.001). Children in the Cleft Collective had higher odds for hyperactivity, emotional and peer problems, and less prosocial behaviors. Maternal stress, lower maternal health-related quality of life and family functioning, receiving government income support, and maternal smoking showed evidence of association (OR range: 4.41-10.13) with behavioral problems, along with maternal relationship status, younger age, and lower education (OR range: 2.34-3.73). CONCLUSIONS: Findings suggest elevated levels of behavioral problems in children born with CL/P compared to the general population with several associated maternal factors similar to the general population.

Genome-Wide Association Study of Blood Mercury in European Pregnant Women and Children.

Mercury has high industrial utility and is present in many products, and environmental contamination and occupational exposure are widespread. There are numerous biological systems involved in the absorption, metabolism, and excretion of Hg, and it is possible that some systems may be impacted by genetic variation. If so, genotype may affect tissue concentrations of Hg and subsequent toxic effects. Genome-wide association testing was performed on blood Hg samples from pregnant women of the Avon Longitudinal Study of Parents and Children (n = 2893) and children of the Human Early Life Exposome (n = 1042). Directly-genotyped single-nucleotide polymorphisms (SNPs) were imputed to the Haplotype Reference Consortium r1.1 panel of whole genotypes and modelled againstlog-transformed Hg. Heritability was estimated using linkage disequilibrium score regression. The heritability of Hg was estimated as 24.0% (95% CI: 16.9% to 46.4%) in pregnant women, but could not be determined in children. There were 16 SNPs associated with Hg in pregnant women above a suggestive p-value threshold (p < 1 × 10-5), and 21 for children. However, no SNP passed this threshold in both studies, and none were genome-wide significant (p < 5 × 10-8). SNP-Hg associations were highly discordant between women and children, and this may reflect differences in metabolism, a gene-age interaction, or dose-response effects. Several suggestive variants had plausible links to Hg metabolism, such as rs146099921 in metal transporter SLC39A14, and two variants (rs28618224, rs7154700) in potassium voltage-gated channel genes. The findings would benefit from external validation, as suggestive results may contain both true associations and false positives.

Leisure time television watching, computer use and risks of breast, colorectal and prostate cancer: A Mendelian randomisation analysis.

BACKGROUND: Sedentary behaviours have been associated with increased risks of some common cancers in epidemiological studies; however, it is unclear if these associations are causal. METHODS: We used univariable and multivariable two-sample Mendelian randomisation (MR) to examine potential causal relationships between sedentary behaviours and risks of breast, colorectal and prostate cancer. Genetic variants associated with self-reported leisure television watching and computer use were identified from a recent genome-wide association study (GWAS). Data related to cancer risk were obtained from cancer GWAS consortia. A series of sensitivity analyses were applied to examine the robustness of the results to the presence of confounding. RESULTS: A 1-standard deviation (SD: 1.5 h/day) increment in hours of television watching increased risk of breast cancer (OR per 1-SD: 1.15, 95% confidence interval [CI]: 1.05-1.26) and colorectal cancer (OR per 1-SD: 1.32, 95% CI: 1.16-1.49) while there was little evidence of an association for prostate cancer risk (OR per 1-SD: 0.94, 95% CI: 0.84-1.06). After adjusting for years of education, the effect estimates for television watching were attenuated (breast cancer, OR per 1-SD: 1.08, 95% CI: 0.92-1.27; colorectal cancer, OR per 1-SD: 1.08, 95% CI: 0.90-1.31). Post hoc analyses showed that years of education might have a possible confounding and mediating role in the association between television watching with breast and colorectal cancer. Consistent results were observed for each cancer site according to sex (colorectal cancer), anatomical subsites and cancer subtypes. There was little evidence of associations between genetically predicted computer use and cancer risk. CONCLUSIONS: Our univariable analysis identified some positive associations between hours of television watching and risks of breast and colorectal cancer. However, further adjustment for additional lifestyle factors especially years of education attenuated these results. Future studies using objective measures of exposure can provide new insights into the possible role of sedentary behaviour in cancer development.

Infection prevention and control in the medical imaging environment: a scoping review.

Infection prevention and control (IPC) practices are key to preventing and controlling the spread of pathogens in medical imaging departments (MIDs). The objective of this scoping review was to synthesise information about current research in MID regarding IPC and to use the Systems Engineering Initiative for Patient Safety (SEIPS) model to identify the work system factors ('persons', 'organisation', 'tools and technology', 'tasks' and 'environment') influencing the practice of IPC, in order to better understand challenges and facilitators that affect IPC in MID. Predefined search terms and medical subject headings relating to IPC in the medical imaging setting were used to search 3 databases. A total of 46 publications met the inclusion criteria, which combined, encompassed all five SEIPS domains influencing IPC. The literature supports the interrelated nature of the five SEIPS domains, and influence to one another. Hand hygiene was a major focus of publications. Mechanisms of infection in contrast-enhanced computed tomography were most reported, with human error, lack of education, and issues associated with devices and processes mechanisms found to influence IPC breaches. A systems approach, such as the SEIPS model, is useful for understanding barriers and hence opportunities for improvement of IPC in the medical imaging setting. Future studies should address individuals' decision-making processes in the medical imaging setting, and a greater focus should be placed into the procedural steps, education and tools used for contrast media administration. CRITICAL RELEVANCE STATEMENT: A systems approach, such as the Systems Engineering Initiative for Patient Safety model, is useful for understanding barriers and hence opportunities for improvement of IPC in the medical imaging setting. KEY POINTS: 1. IPC in the medical imaging setting would benefit from a systems approach. 2. The role of education and monitoring of IPC compliance requires further research. 3. Geographical location is a key variable in IPC research in medical imaging.

Atopic dermatitis and risk of 14 site-specific cancers: A Mendelian randomization study.

BACKGROUND: Atopic dermatitis (AD) accounts for a large proportion of the burden of skin disease, with a prevalence of around 10% among adults worldwide. In addition, systematic reviews and meta-analyses have found that AD is associated with cancer risk at several sites; if found to be causal this could highlight potential treatment targets to reduce cancer risk. OBJECTIVES: To assess the potential causative link between AD and 14 site-specific cancers in a two-sample randomization study. METHODS: From the largest genome-wide association study (GWAS) of AD (10,788 cases and 30,047 non-cases), genetic variants highly associated (p < 5 × 10-8 ) with AD in the European population were selected as instrumental variables (IVs). Data from large cancer consortia, as well as the UK Biobank study (n = 442,239) and the FinnGen study (n = 218,792), were employed to assess genetic associations with 14 site-specific cancers and overall cancer. A set of complementary approaches and sensitivity analyses were carried out to examine the robustness of our results. In addition, associations for the same cancer site from different data sources were combined using meta-analyses. RESULTS: We discovered no strong causal evidence of AD on the risk of overall cancer, with effect estimates close to zero. After the Benjamini-Hochberg correction, the inverse-variance weighted method indicated no association between AD and overall cancer risk in both the UK Biobank (OR, 1.00; 95% CI, 0.94-1.06; FDR, 0.98) and FinnGen studies (OR, 0.96; 95% CI, 0.92-1.02; FDR, 0.68). No strong evidence of an association was found between genetically predicted AD and the risk of any site-specific cancers. CONCLUSIONS: Our MR investigation does not support a causal effect of AD on cancer risk. This finding has important implications for the prevention and management of both AD and cancer, as it reduces the concern of potential adverse effects of AD on cancer outcomes.

Blood pressure, calcium channel blockers, and the risk of prostate cancer: a Mendelian randomization study.

BACKGROUND: Observational studies have found some evidence of an association between elevated blood pressure and prostate cancer risk; however, the results are inconclusive. We tested whether systolic blood pressure (SBP) influences prostate cancer risk and evaluated the effect of calcium channel blockers (CCB) on the disease using Mendelian randomization (MR) approach. METHODS: We used 278 genetic variants associated with SBP and 16 genetic variants in CCB genes as instrumental variables. Effect estimates were obtained from the UK Biobank sample of 142,995 males and from PRACTICAL consortium (79,148 cases and 61,106 controls). RESULTS: For each 10 mm Hg increase in SBP the estimated effect was OR 0.96 (0.90-1.01) for overall prostate cancer; and OR 0.92 (0.85-0.99) for aggressive prostate cancer. The MR-estimated effect of a 10 mm Hg- SBP lowering through CCB genetic variants was OR 1.22 (1.06-1.42) for all prostate cancers and OR 1.49 (1.18-1.89) for aggressive prostate cancer. CONCLUSION: The results of our study did not support a causal relationship between SBP and prostate cancer; however, we found weak evidence of a protective effect of high SBP on aggressive prostate cancer and we found that blocking calcium channel receptors may increase prostate cancer risk.

Genetically proxied glucose-lowering drug target perturbation and risk of cancer: a Mendelian randomisation analysis.

AIMS/HYPOTHESIS: Epidemiological studies have generated conflicting findings on the relationship between glucose-lowering medication use and cancer risk. Naturally occurring variation in genes encoding glucose-lowering drug targets can be used to investigate the effect of their pharmacological perturbation on cancer risk. METHODS: We developed genetic instruments for three glucose-lowering drug targets (peroxisome proliferator activated receptor γ [PPARG]; sulfonylurea receptor 1 [ATP binding cassette subfamily C member 8 (ABCC8)]; glucagon-like peptide 1 receptor [GLP1R]) using summary genetic association data from a genome-wide association study of type 2 diabetes in 148,726 cases and 965,732 controls in the Million Veteran Program. Genetic instruments were constructed using cis-acting genome-wide significant (p<5×10-8) SNPs permitted to be in weak linkage disequilibrium (r2<0.20). Summary genetic association estimates for these SNPs were obtained from genome-wide association study (GWAS) consortia for the following cancers: breast (122,977 cases, 105,974 controls); colorectal (58,221 cases, 67,694 controls); prostate (79,148 cases, 61,106 controls); and overall (i.e. site-combined) cancer (27,483 cases, 372,016 controls). Inverse-variance weighted random-effects models adjusting for linkage disequilibrium were employed to estimate causal associations between genetically proxied drug target perturbation and cancer risk. Co-localisation analysis was employed to examine robustness of findings to violations of Mendelian randomisation (MR) assumptions. A Bonferroni correction was employed as a heuristic to define associations from MR analyses as 'strong' and 'weak' evidence. RESULTS: In MR analysis, genetically proxied PPARG perturbation was weakly associated with higher risk of prostate cancer (for PPARG perturbation equivalent to a 1 unit decrease in inverse rank normal transformed HbA1c: OR 1.75 [95% CI 1.07, 2.85], p=0.02). In histological subtype-stratified analyses, genetically proxied PPARG perturbation was weakly associated with lower risk of oestrogen receptor-positive breast cancer (OR 0.57 [95% CI 0.38, 0.85], p=6.45×10-3). In co-localisation analysis, however, there was little evidence of shared causal variants for type 2 diabetes liability and cancer endpoints in the PPARG locus, although these analyses were likely underpowered. There was little evidence to support associations between genetically proxied PPARG perturbation and colorectal or overall cancer risk or between genetically proxied ABCC8 or GLP1R perturbation with risk across cancer endpoints. CONCLUSIONS/INTERPRETATION: Our drug target MR analyses did not find consistent evidence to support an association of genetically proxied PPARG, ABCC8 or GLP1R perturbation with breast, colorectal, prostate or overall cancer risk. Further evaluation of these drug targets using alternative molecular epidemiological approaches may help to further corroborate the findings presented in this analysis. DATA AVAILABILITY: Summary genetic association data for select cancer endpoints were obtained from the public domain: breast cancer ( https://bcac.ccge.medschl.cam.ac.uk/bcacdata/ ); and overall prostate cancer ( http://practical.icr.ac.uk/blog/ ). Summary genetic association data for colorectal cancer can be accessed by contacting GECCO (kafdem at fredhutch.org). Summary genetic association data on advanced prostate cancer can be accessed by contacting PRACTICAL (practical at icr.ac.uk). Summary genetic association data on type 2 diabetes from Vujkovic et al (Nat Genet, 2020) can be accessed through dbGAP under accession number phs001672.v3.p1 (pha004945.1 refers to the European-specific summary statistics). UK Biobank data can be accessed by registering with UK Biobank and completing the registration form in the Access Management System (AMS) ( https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access ).

Global Radiomic Features from Mammography for Predicting Difficult-To-Interpret Normal Cases.

This work aimed to investigate whether global radiomic features (GRFs) from mammograms can predict difficult-to-interpret normal cases (NCs). Assessments from 537 readers interpreting 239 normal mammograms were used to categorise cases as 120 difficult-to-interpret and 119 easy-to-interpret based on cases having the highest and lowest difficulty scores, respectively. Using lattice- and squared-based approaches, 34 handcrafted GRFs per image were extracted and normalised. Three classifiers were constructed: (i) CC and (ii) MLO using the GRFs from corresponding craniocaudal and mediolateral oblique images only, based on the random forest technique for distinguishing difficult- from easy-to-interpret NCs, and (iii) CC + MLO using the median predictive scores from both CC and MLO models. Useful GRFs for the CC and MLO models were recognised using a scree test. The CC and MLO models were trained and validated using the leave-one-out-cross-validation. The models' performances were assessed by the AUC and compared using the DeLong test. A Kruskal-Wallis test was used to examine if the 34 GRFs differed between difficult- and easy-to-interpret NCs and if difficulty level based on the traditional breast density (BD) categories differed among 115 low-BD and 124 high-BD NCs. The CC + MLO model achieved higher performance (0.71 AUC) than the individual CC and MLO model alone (0.66 each), but statistically non-significant difference was found (all p > 0.05). Six GRFs were identified to be valuable in describing difficult-to-interpret NCs. Twenty features, when compared between difficult- and easy-to-interpret NCs, differed significantly (p < 0.05). No statistically significant difference was observed in difficulty between low- and high-BD NCs (p = 0.709). GRF mammographic analysis can predict difficult-to-interpret NCs.

Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis.

Background: Tumour-promoting inflammation is a "hallmark" of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear. Methods: We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combined cis-Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,162 cancer cases and up to 824,556 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant (P < 5.0 x 10-8) cis-acting SNPs (i.e. in or ±250 kb from the gene encoding the relevant protein) in weak linkage disequilibrium (LD, r2 < 0.10). Effect estimates were generated using inverse-variance weighted random-effects models and standard errors were inflated to account for weak LD between variants with reference to the 1000 Genomes Phase 3 CEU panel. A false discovery rate (FDR)-corrected P-value ("q-value") < 0.05 was used as a threshold to define "strong evidence" to support associations and 0.05 ≤ q-value < 0.20 to define "suggestive evidence". A colocalisation posterior probability (PPH4) > 70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes. Results: We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR 1.19, 95% CI 1.10-1.29, q-value=0.033, PPH4=84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR 1.42, 95% CI 1.20-1.69, q-value=0.055, PPH4=73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR 0.66, 95% CI 0.53-0.81, q-value=0.067, PPH4=81.8%), macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR 1.14, 95% CI 1.05-1.23, q-value=0.072, PPH4=76.1%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR 0.92, 95% CI 0.88-0.97, q-value=0.15), PPH4=85.6%). For 22 of 30 cancer outcomes examined, there was little evidence (q-value ≥ 0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk. Conclusion: Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 5 circulating inflammatory markers in risk of 5 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated.