Cancer Loyalty Card Study (CLOCS): protocol for an observational case-control study focusing on the patient interval in ovarian cancer diagnosis

Introduction: Ovarian cancer is the eighth most common cancer in women worldwide, and about 1 in 5 women with ovarian cancer do not receive treatment, because they are too unwell by the time they are diagnosed. Symptoms of ovarian cancer are non-specific or can be associated with other common conditions, and women experiencing these symptoms have been shown to self-manage them using over-the-counter medication. Results from a recent proof-of-concept study suggest there may be an increase in the purchases of painkillers and indigestion medication 10–12 months before ovarian cancer diagnosis. We propose a case–control study, as part of a larger project called the Cancer Loyalty Card Study (CLOCS), to investigate whether a significant change in medication purchases could be an indication for early signs of ovarian cancer, using data already collected through store loyalty cards. Methods and analysis: Using a retrospective case–control design, we aim to recruit 500 women diagnosed with ovarian cancer (cases) and 500 women without ovarian cancer (controls) in the UK who hold a loyalty card with at least one participating high street retailer. We will use pre-existing loyalty card data to compare past purchase patterns of cases with those of controls. In order to assess ovarian cancer risk in participants and their purchase patterns, we will collect information from participants on ovarian cancer risk factors and clinical data including symptoms experienced before diagnosis from recruited women with ovarian cancer. Ethics and dissemination: CLOCS was reviewed and approved by the North West-Greater Manchester South Research Ethics Committee (19/NW/0427). Study outcomes will be disseminated through academic publications, the study website, social media and a report to the research sites that support the study once results are published

Automated calibration of consensus weighted distance-based clustering approaches using sharp

In consensus clustering, a clustering algorithm is used in combination with a subsampling procedure to detect stable clusters. Previous studies on both simulated and real data suggest that consensus clustering outperforms native algorithms. We extend here consensus clustering to allow for attribute weighting in the calculation of pairwise distances using existing regularised approaches. We propose a procedure for the calibration of the number of clusters (and regularisation parameter) by maximising a novel consensus score calculated directly from consensus clustering outputs, making it extremely computationally competitive. Our simulation study shows better clustering performances of (i) models calibrated by maximising our consensus score compared to existing calibration scores, and (ii) weighted compared to unweighted approaches in the presence of features that do not contribute to cluster definition. Application on real gene expression data measured in lung tissue reveals clear clusters corresponding to different lung cancer subtypes. The R package sharp (version 1.4.0) is available on CRAN

Association between purchase of over-the-counter medications and ovarian cancer diagnosis in the Cancer Loyalty Card Study (CLOCS):observational case-control study

BACKGROUND: Over-the-counter (OTC) medications are frequently used to self-care for nonspecific ovarian cancer symptoms prior to diagnosis. Monitoring such purchases may provide an opportunity for earlier diagnosis. OBJECTIVE: The aim of the Cancer Loyalty Card Study (CLOCS) was to investigate purchases of OTC pain and indigestion medications prior to ovarian cancer diagnosis in women with and without ovarian cancer in the United Kingdom using loyalty card data. METHODS: An observational case-control study was performed comparing purchases of OTC pain and indigestion medications prior to diagnosis in women with (n=153) and without (n=120) ovarian cancer using loyalty card data from two UK-based high street retailers. Monthly purchases of pain and indigestion medications for cases and controls were compared using the Fisher exact test, conditional logistic regression, and receiver operating characteristic (ROC) curve analysis. RESULTS: Pain and indigestion medication purchases were increased among cases 8 months before diagnosis, with maximum discrimination between cases and controls 8 months before diagnosis (Fisher exact odds ratio [OR] 2.9, 95% CI 2.1-4.1). An increase in indigestion medication purchases was detected up to 9 months before diagnosis (adjusted conditional logistic regression OR 1.38, 95% CI 1.04-1.83). The ROC analysis for indigestion medication purchases showed a maximum area under the curve (AUC) at 13 months before diagnosis (AUC=0.65, 95% CI 0.57-0.73), which further improved when stratified to late-stage ovarian cancer (AUC=0.68, 95% CI 0.59-0.78). CONCLUSIONS: There is a difference in purchases of pain and indigestion medications among women with and without ovarian cancer up to 8 months before diagnosis. Facilitating earlier presentation among those who self-care for symptoms using this novel data source could improve ovarian cancer patients' options for treatment and improve survival. TRIAL REGISTRATION: ClinicalTrials.gov NCT03994653; https://clinicaltrials.gov/ct2/show/NCT03994653

Международная трудовая миграция и нелегальная миграция в России

Огляд монографії: Метелев С.Е. Международная трудовая миграция и нелегальная миграция в России. Монография. – М.: Юнити. – 2006. – 175 с

Characterising a mobile reference station (MoRS) to quantify personal exposure to air quality

There is increasing clinical, epidemiological, and toxicological evidence linking exposure to air pollution with multiple health outcomes that lead to increased mortality and morbidity. Traditionally, fixed air quality monitors have been used to provide ambient air pollution measurements, but they have spatial and temporal limitations. Rapid advances in instrument miniaturisation have made novel sensing technologies more accessible but these are prone to high sensitivity and inaccuracies. To bridge the gap between fixed monitors and small sensors we have developed a Mobile Reference Station (MoRS) – a portable platform delivering high quality measurements of air pollutants using smaller, low power reference grade instruments at high time resolutions. MoRS enables the simultaneous measurement of a broad aerosol size distribution (10 nm–35 μm), gaseous pollutant concentrations (nitrogen dioxide (NO2) and ozone (O3)), environmental parameters (noise, relatively humidity (RH) and temperature) as well as collecting filter samples for laboratory analysis. The MoRS instrumentation is described and the major challenges in ensuring that high data quality standards are maintained are discussed. Laboratory and field tests were used to derive scaling factors for all the MoRSinstrumentation. Field testing of MoRS showed excellent intercomparability against reference instrumentation (R2 > 0.98) and good agreement with reference instruments in the ultrafine aerosol range, although there was an overestimation of fine particle aerosols. Measurements taken during example mainline train and London Underground (LU) journeys are displayed showing the value of the high-quality data derived from MoRS and how this can help to disentangle multiple confounding environmental pollutants and enrich epidemiological studies

Anthropometry, body fat composition and reproductive factors and risk of oesophageal and gastric cancer by subtype and subsite in the UK Biobank cohort

Background Obesity has been positively associated with upper gastrointestinal cancers, but prospective data by subtype/subsite are limited. Obesity influences hormonal factors, which may play a role in these cancers. We examined anthropometry, body fat and reproductive factors in relation to oesophageal and gastric cancer by subtype/subsite in the UK Biobank cohort. Methods Among 458,713 UK Biobank participants, 339 oesophageal adenocarcinomas, 124 oesophageal squamous cell carcinomas, 137 gastric cardia and 92 gastric non-cardia cancers were diagnosed during a mean of 6.5 years follow-up. Cox models estimated multivariable hazard ratios (HRs) and 95% confidence intervals (CIs). Results Body mass index (BMI), hip circumference, waist circumference, waist-to-hip ratio, waist-to-height ratio, total body fat and trunk fat were positively associated with oesophageal adenocarcinoma (highest vs lowest category: HR = 2.33, 95%-CI:1.65–3.28; HR = 1.56, 95%-CI:1.15–2.13; HR = 2.30, 95%-CI:1.47–3.57; HR = 1.71, 95%-CI:1.01–2.90; HR = 2.87, 95%-CI:1.88–4.38; HR = 1.96, 95%-CI:1.30–2.96; HR = 2.34, 95%-CI:1.70–3.22, respectively). Although there were no statistically significant associations in combined sex analyses, BMI (HR = 1.83, 95%-CI:1.00–3.37), waist circumference (HR = 2.21, 95%-CI:1.27–3.84) and waist-to-hip ratio (HR = 1.92, 95%-CI:1.11–3.29) were associated with gastric cardia cancer in men; however, mutual adjustment attenuated the associations for BMI and waist-to-hip ratio. For oesophageal squamous cell carcinoma, statistically significant inverse associations were observed among women for BMI, hip circumference, waist circumference, waist-to-height ratio, total body fat and trunk fat, although they were based on small numbers. In addition, older age at first (HR = 0.44, 95%-CI:0.22–0.88) and last live birth (HR = 0.44, 95%-CI:0.22–0.87) were inversely associated with oesophageal squamous cell carcinoma and having a stillbirth/miscarriage/termination was positively associated (HR = 1.84, 95%-CI:1.10–3.07). Conclusions Obesity and abdominal obesity specifically may be a risk factor for oesophageal adenocarcinoma and gastric cardia cancer in men. Some reproductive factors may be associated with oesophageal squamous cell carcinoma in women

Dynamics of the Risk of Smoking-Induced Lung Cancer A Compartmental Hidden Markov Model for Longitudinal Analysis

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