Latent Class Analysis for Estimating an Unknown Population Size – with Application to Censuses

Abstract Estimation of the unknown population size using capture-recapture techniques relies on the key assumption that the capture probabilities are homogeneous across individuals in the population. This is usually accomplished via post-stratification by some key covariates believed to influence individual catchability. Another issue that arises in population estimation from data collected from multiple sources is list dependence, where an individual’s catchability on one list is related to that of another list. The earlier models for population estimation heavily relied upon list independence. However, there are methods available that can adjust the population estimates to account for dependence among lists. In this article, we propose the use of latent class analysis through log-linear modelling to estimate the population size in the presence of both heterogeneity and list dependence. The proposed approach is illustrated using data from the 1988 US census dress rehearsal.</jats:p

RESTORE: an exploratory trial of an online intervention to enhance self-efficacy to manage problems associated with cancer-related fatigue following primary cancer treatment: study protocol for a randomized controlled trial

Background: There are over 25 million people worldwide living with or beyond cancer and this number is increasing. Cancer survivors face a range of problems following primary treatment. One of the most frequently reported and distressing symptoms experienced by cancer survivors is fatigue. There is growing support for survivors who are experiencing problems after cancer treatment to engage in supported self-management. To date there is some evidence of effective interventions to manage fatigue in this population; however, to our knowledge there are no online resources that draw on this information to support self-management of fatigue. This paper describes the protocol for an exploratory randomized controlled trial of an online intervention to support self-management of cancer-related fatigue after primary cancer treatment.Methods/design: This is a parallel-group two-armed (1:1) exploratory randomized controlled trial including 125 cancer survivors experiencing fatigue (scoring ≥4 on a unidimensional 11-point numeric rating scale for fatigue intensity) within five years of primary treatment completion with curative intent. Participants will be recruited from 13 NHS Trusts across the UK and randomized to either the online intervention (RESTORE), or a leaflet comparator (Macmillan Cancer Backup, Coping with Fatigue). The primary outcome is a change in Perceived Self-Efficacy for Fatigue Self-Management (as measured by the Perceived Self-Efficacy for Fatigue Self-Management Instrument). Secondary outcomes include impact on perception and experience of fatigue (measured by the Brief Fatigue Inventory), and quality of life (measured by the Functional Assessment of Cancer Therapy - General and the Personal Wellbeing Index). Outcome measures will be collected at baseline, 6 weeks (completion of intervention), and 3 months. Process evaluation (including telephone interviews with recruiting staff and participants) will determine acceptability of the intervention and trial processes.Discussion: Data from this trial will be used to refine the intervention and contribute to the design of an effectiveness trial. This intervention will be expanded to address other cancer-related problems important to cancer survivors following primary cancer treatment

A Risk Score for Predicting Multiple Sclerosis

Multiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI.78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals.There was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p<0.0005). Unaffected siblings had a risk score intermediate to people with MS and controls (p<0.0005). The best performing risk score generated an AUC of 0.82 (95%CI 0.75–0.88).The risk score demonstrates an AUC on the threshold for clinical utility. Our score enables the identification of a high-risk sibling group to inform pre-symptomatic longitudinal studies

Established Risk Factors Account for Most of the Racial Differences in Cardiovascular Disease Mortality

BACKGROUND: Cardiovascular disease (CVD) mortality varies across racial and ethnic groups in the U.S., and the extent that known risk factors can explain the differences has not been extensively explored. METHODS: We examined the risk of dying from acute myocardial infarction (AMI) and other heart disease (OHD) among 139,406 African-American (AA), Native Hawaiian (NH), Japanese-American (JA), Latino and White men and women initially free from cardiovascular disease followed prospectively between 1993–1996 and 2003 in the Multiethnic Cohort Study (MEC). During this period, 946 deaths from AMI and 2,323 deaths from OHD were observed. Relative risks of AMI and OHD mortality were calculated accounting for established CVD risk factors: body mass index (BMI), hypertension, diabetes, smoking, alcohol consumption, amount of vigorous physical activity, educational level, diet and, for women, type and age at menopause and hormone replacement therapy (HRT) use. RESULTS: Established CVD risk factors explained much of the observed racial and ethnic differences in risk of AMI and OHD mortality. After adjustment, NH men and women had greater risks of OHD than Whites (69% excess, P<0.001 and 62% excess, P = 0.003, respectively), and AA women had greater risks of AMI (48% excess, P = 0.01) and OHD (35% excess, P = 0.007). JA men had lower risks of AMI (51% deficit, P<0.001) and OHD (27% deficit, P = 0.001), as did JA women (AMI, 37% deficit, P = 0.03; OHD, 40% deficit, P = 0.001). Latinos had underlying lower risk of AMI death (26% deficit in men and 35% in women, P = 0.03). CONCLUSION: Known risk factors explain the majority of racial and ethnic differences in mortality due to AMI and OHD. The unexplained excess in NH and AA and the deficits in JA suggest the presence of unmeasured determinants for cardiovascular mortality that are distributed unequally across these populations

INSIG2 gene rs7566605 polymorphism is associated with severe obesity in Japanese

The single nucleotide polymorphism (SNP) rs7566605 in the upstream region of the insulin-induced gene 2 (INSIG2) is associated with the obesity phenotype in many Caucasian populations. In Japanese, this association with the obesity phenotype is not clear. To investigate the relationship between rs7566605 and obesity in Japanese, we genotyped rs7566605 from severely obese subjects [n = 908, body mass index (BMI) ≥ 30 kg/m2] and normal-weight control subjects (n = 1495, BMI < 25 kg/m2). A case–control association analysis revealed that rs7566605 was significantly associated with obesity in Japanese. The P value in the minor allele recessive mode was 0.00020, and the odds ratio (OR) adjusted for gender and age was 1.61 [95% confidential interval (CI) = 1.24–2.09]. Obesity-associated phenotypes, which included the level of BMI, plasma glucose, hemoglobin A1c, total cholesterol, triglycerides, high-density lipoprotein (HDL) cholesterol, and blood pressure, were not associated with the rs7566605 genotype. Thus, rs7566605 in the upstream region of the INSIG2 gene was found to be associated with obesity, i.e., severe obesity, in Japanese

Modulation of 11β-hydroxysteroid dehydrogenase as a strategy to reduce vascular inflammation

Atherosclerosis is a chronic inflammatory disease in which initial vascular damage leads to extensive macrophage and lymphocyte infiltration. Although acutely glucocorticoids suppress inflammation, chronic glucocorticoid excess worsens atherosclerosis, possibly by exacerbating systemic cardiovascular risk factors. However, glucocorticoid action within the lesion may reduce neointimal proliferation and inflammation. Glucocorticoid levels within cells do not necessarily reflect circulating levels due to pre-receptor metabolism by 11β-hydroxysteroid dehydrogenases (11β-HSDs). 11β-HSD2 converts active glucocorticoids into inert 11-keto forms. 11β-HSD1 catalyses the reverse reaction, regenerating active glucocorticoids. 11β-HSD2-deficiency/ inhibition causes hypertension, whereas deficiency/ inhibition of 11β-HSD1 generates a cardioprotective lipid profile and improves glycemic control. Importantly, 11β-HSD1-deficiency/ inhibition is atheroprotective, whereas 11β-HSD2-deficiency accelerates atherosclerosis. These effects are largely independent of systemic risk factors, reflecting modulation of glucocorticoid action and inflammation within the vasculature. Here, we consider whether evidence linking the 11β-HSDs to vascular inflammation suggests these isozymes are potential therapeutic targets in vascular injury and atherosclerosis

The research on endothelial function in women and men at risk for cardiovascular disease (REWARD) study: methodology

Background Endothelial function has been shown to be a highly sensitive marker for the overall cardiovascular risk of an individual. Furthermore, there is evidence of important sex differences in endothelial function that may underlie the differential presentation of cardiovascular disease (CVD) in women relative to men. As such, measuring endothelial function may have sex-specific prognostic value for the prediction of CVD events, thus improving risk stratification for the overall prediction of CVD in both men and women. The primary objective of this study is to assess the clinical utility of the forearm hyperaemic reactivity (FHR) test (a proxy measure of endothelial function) for the prediction of CVD events in men vs. women using a novel, noninvasive nuclear medicine -based approach. It is hypothesised that: 1) endothelial dysfunction will be a significant predictor of 5-year CVD events independent of baseline stress test results, clinical, demographic, and psychological variables in both men and women; and 2) endothelial dysfunction will be a better predictor of 5-year CVD events in women compared to men. Methods/Design A total of 1972 patients (812 men and 1160 women) undergoing a dipyridamole stress testing were recruited. Medical history, CVD risk factors, health behaviours, psychological status, and gender identity were assessed via structured interview or self-report questionnaires at baseline. In addition, FHR was assessed, as well as levels of sex hormones via blood draw. Patients will be followed for 5 years to assess major CVD events (cardiac mortality, non-fatal MI, revascularization procedures, and cerebrovascular events). Discussion This is the first study to determine the extent and nature of any sex differences in the ability of endothelial function to predict CVD events. We believe the results of this study will provide data that will better inform the choice of diagnostic tests in men and women and bring the quality of risk stratification in women on par with that of men

Selection on Alleles Affecting Human Longevity and Late-Life Disease: The Example of Apolipoprotein E

It is often claimed that genes affecting health in old age, such as cardiovascular and Alzheimer diseases, are beyond the reach of natural selection. We show in a simulation study based on known genetic (apolipoprotein E) and non-genetic risk factors (gender, diet, smoking, alcohol, exercise) that, because there is a statistical distribution of ages at which these genes exert their influence on morbidity and mortality, the effects of selection are in fact non-negligible. A gradual increase with each generation of the ε2 and ε3 alleles of the gene at the expense of the ε4 allele was predicted from the model. The ε2 allele frequency was found to increase slightly more rapidly than that for ε3, although there was no statistically significant difference between the two. Our result may explain the recent evolutionary history of the epsilon 2, 3 and 4 alleles of the apolipoprotein E gene and has wider relevance for genes affecting human longevity

Inferring cellular networks – a review

In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical models and Bayesian networks. The second part discusses probabilistic and graph-based methods for data from experimental interventions and perturbations

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta