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Abstract: The present study investigated whether whole population exposure to radiation introduced by radio broadcasting and cell phone systems might explain recent increases in melanoma trends in Nordic countries or not. Trends were modeled using a single exponential function of the time each age group has been living in the new environment since an environmental change took place. The results clearly show that melanoma incidences started to increase exponentially by the time lived as an adult since 1955 and that a second trend break occurred in 1997. We searched best fit between calculated and reported age-standardized rates by parameter variation, and compared calculated with reported age-specific rates without further parameter adjustments. Local variations of breast cancer, lung cancer and all cancers together significantly correlated with corresponding local melanoma rates in Sweden. Increasing cancer trends since around 1997 seem related to a population covering environmental change effective from early 90’s. We conclude that this exponential trend model can be a useful tool in understanding responses to sudden environmental changes. Keywords: Cancer, Melanoma, Cell phone, Speech time, Incidence, Trends.Download Full Article |
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Abstract: Cancer incidence and mortality trends in the Nordic countries show that most cancer types have been increasing for a long time, while a few show decreasing trends. The object of this study was to investigate melanoma mortality trends to see if there is a specific year for the trend breaks, possibly indicating a common causing factor affecting most of the population from the same time. The results clearly show that melanoma mortality started to increase exponentially by the time lived as an adult since 1955 and that the trends easily can be modeled and used for projection purpose. The findings are in support of earlier studies, suggesting reduced or temporarily disturbed DNA repair capacity due to a population-wide environmental change to be the main cause to increasing cancer rates in general, and increasing melanoma incidence and mortality in particular. Keywords: Melanoma, cancer, mortality, incidence, exponential, model, DNA repair.Download Full Article |
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Abstract: Background:The key feature of Bayesian methods is their lack of dependence on defaults necessary for classical statistics. Because of the high volume of simulation, Bayesian methods have a high degree of accuracy. They are efficient in data mining and analyzing large volumes of data, and can be upgraded by entering new data. Objective: We used Bayesian multidimensional scaling (MDS) to analyze the genetic relationships among 11 Iranian ethnic groups based on HLA class II data. Method: Allele frequencies of three HLA loci from 816 unrelated individuals belonging to 11 Iranian ethnic groups were analyzed by Bayesian MDS using R and WinBUGS software. Results: like the results of correspondence analysis as a prototype of classicalMDS analysis, the results of Bayesian MDS also showed Arabs from Famur, Balochis, Zoroastrians and Jews to be separate from other Iranian ethnic groups. Decreases stress in Bayesian MDS method compared to classicalmethod revealed the accuracy of Bayesian MDS for HLA data analyses. Conclusion:This study reports the first application of Bayesian multidimensional scaling to HLA data analysis with Nei’sDA genetic distances. Stress reduction in Bayesian MDScompared to classical MDS showed that the Bayesian approach can improve the accuracy of genetic data analysis. Keywords: Bayesian methods, Multidimensional scaling, Anthropological study, Immunogenetics, R and WinBUGS software.Download Full Article |
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Abstract: Background: An accurate tool with good discrimination for bleeding would be useful to clinicians for improved management of all their patients. Bleeding risk models have been published but not externally validated in independent clinical dataset. We chose the NCDR PCI score to validate within a large, multi-site community datasets. The aim of the study was to determine the diagnostic utility of this bleeding risk score tool. Methods: This is a large-scale retrospective analysis utilizing American College of Cardiology data from a 37-hospital health system. The central repository of PCI procedures between 6-1-2009 and 6-30-2012 was utilized to validate the NCDR PCI bleeding risk score (BRS) among 4693 patients. The primary endpoint was major bleeding. Discriminant analysis calculating the receiver operating characteristic curve was performed. Results:There were 143 (3.0%) major bleeds. Mean bleeding risk score was 14.7 (range 3 – 42). Incidence of bleeding by risk category: low (0.5%), intermediate (1.7%), and high risk (7.6%). Patients given heparin had 113 (3.7%) major bleeds and those given bivalirudin had 30 (2.1%) major bleeds. Tool accuracy was poor to fair (AUC 0.78 heparin, 0.65 bivalirudin). Overall accuracy was 0.71 (CI: 0.66-0.76). Accuracy did not improve when confined to just the intermediate risk group (AUC 0.58; CI: 0.55-0.67). Conclusion:Bleeding risk tools have low predictive value. Adjustment for anticoagulation use resulted in poor discrimination because bivalirudin differentially biases outcomes toward no bleeding. The current state of bleeding risk tools provides little support for diagnostic utility in regards to major bleeding and therefore have limited clinical applicability. Keywords: Major bleeding, bleeding risk model, anticoagulant, percutaneous coronary intervention, cardiovascular. |
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Abstract: This study looked at how cigarette smoking, alcohol consumption, obesity, and physical activity are associated with the prevalence and severity of arthritis among adults living in Delaware, U.S. through the analysis of survey data. We examined data from the 2009 Delaware Behavioral Risk Factor Surveillance System (BRFSS). Weighted percentages were calculated for the arthritis-related factors above by arthritis status and activity limitation due to arthritis/joint symptoms, and were analyzed using the Rao-Scott χ2 test. A multiple logistic regression analysis was performed to determine an odds ratio (OR) while adjusting for gender, age, race/ethnicity, and education. Adult Delawareans self-reporting arthritis were more likely to be former and current smokers than those without self-reported arthritis (p < 0.001; OR = 1.58 for former smokers vs. non-smokers; OR = 1.52 for current smokers vs. non-smokers). Moderate and heavy alcohol consumption was associated with lower severity of arthritis (p < 0.001; OR = 0.66 for moderate drinking vs. no drinking; OR = 0.50 for heavy drinking vs. no drinking). There was a significant relationship of obesity to both arthritis status (p < 0.001; OR = 2.13 for obesity vs. not overweight/obesity) and severity (p < 0.008; OR = 1.67 for obesity vs. not overweight/obesity). Furthermore, people having arthritis-related activity limitation were more likely to not meet the current physical activity recommendations (p = 0.013; OR = 1.46). It appears that smoking and obesity have a negative impact on the risk and severity of arthritis, whereas alcohol consumption and physical activity may be protective against arthritis. A proper analysis of survey data is essential to truly understand how human behavior impacts people’s health. Keywords: Rao-Scott χ2 test, logistic regression, Behavioral Risk Factor Surveillance System, cigarette smoking, alcohol consumption, obesity, physical activity, odds ratio.Download Full Article |