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Abstract: Background: Significantly high concentration of secondary bile acids and low concentration of primary acids are reported by the surgeons in patients with gallbladder carcinoma (GBC) compared to control and cholelithiasis groups. Aim: To examine the effect of primary and secondary bile acids on the development of cholelithiasis and GBC and to investigate the association, if any, among the two groups of bile acids. Methods: The study uses two groups of patients at a time selected in accordance with some pre-fixed inclusion and exclusion criteria. Informed consent was obtained from all patients. The demographic characteristics such as mean age, sex ratio and body mass index, etc. are obtained for the selected groups of patients. The study defines dichotomous responses and the four bile acid constituents, namely cholic acid (CA), chenodeoxycholic acid (CDCA), deoxycholic acid (DCA) and lithocholic acid (LCA), as the predictors. It then assumes logistic regression model to associate the binary responses with the predictors by using probability scores. Bayes analysis is developed using Markov chain Monte Carlo (MCMC) pack in R software for the posterior simulation. Results:Twenty one cholelithiasis patients and twenty patients in each of control and GBC groups are studied. It is seen that a unit decrement in the level of CA (CDCA) increases the log (odds ratio) for cholelithiasis by an amount of 0.49 (0.14) and odds ratio by almost 1.5 (1.12). Similarly, a unit increment in the level of DCA (LCA) provides the log (odds ratio) for cholelithiasis as 0.18 (1.3) and odds ratio as 1.16 (2.95). Comparing GBC with control population, it is noted that a unit decrease in the level of CA (CDCA) in the control population increases the log (odds ratio) for GBC by an amount of 1.16(0.26) and odds ratio by almost 2.63 (1.24) times. Similarly, the log(odds ratio) for GBC increases by 0.77(1.94) and the odds ratio increases by 1.9 (5.0) for the unit increment in the level of DCA(LCA). Conclusions: The study observes relatively high variations in the primary and secondary bile acids in the cholelithiasis and GBC groups as compared with the control group. It, in turn, reflects strong association among the two categories of bile acids in gallbladder diseases. Keywords: Bile acid constituents, Cholelithiasis, Gallbladder carcinoma, Logistic regression model, Vague prior, Odds ratio, Posterior simulation.Download Full Article |
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Abstract: The research on biomarkers has been limited in its effectiveness because biomarker levels can only be measured within the thresholds of assays and laboratory instruments, a challenge referred to as a detection limit (DL) problem. In this paper, we propose a Bayesian approach to the Cox proportional hazards model with explanatory variables subject to lower, upper, or interval DLs. We demonstrate that by formulating the time-to-event outcome using the Poisson density with counting process notation, implementing the proposed approach in the OpenBUGS and JAGS is straightforward. We have conducted extensive simulations to compare the proposed Bayesian approach to the other four commonly used methods and to evaluate its robustness with respect to the distribution assumption of the biomarkers. The proposed Bayesian approach and other methods were applied to an acute lung injury study, in which a panel of cytokine biomarkers was studied for the biomarkers’ association with ventilation-free survival. Keywords: Bayesian, Biomarker, Detection limit, Lung Injury, Proportional hazards models.Download Full Article |
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Abstract: Summary: Esophageal cancer is one of the main health issues in Mizoram. The risk factors of the disease are related to consumption of alcohol. There have not been any epidemiological studies on this subject in the state. The aim of the study is to assess the relationship between esophageal cancer and consumption of alcohol. Materials and Methods: A hospital based matched case-control study was conducted comprising of 138 cases with histologically confirmed diagnosis of esophageal cancer and 276 controls that were cancer and esophageal cancer disease free. Cases and controls matched by gender and age (± 5 years). Ratio of cases and controls were 1:2. A questionnaire was used to collect information on possible risk factors of esophageal cancer. The odds ratios (OR) and 95% confidence intervals (CI) for gastric cancer were calculated by a conditional logistic regression. Results: Cases had significantly lower education level. Most of the cases are from middle income class. After adjustment for consumption of betel quid, tobacco, smoking, body mass index (BMI), family history of cancer, education level and income level, higher risk of esophageal cancer was found for those who have the habit of consuming alcohol in the morning. After controlling for consumption of betel quid, tobacco, smoking, body mass index (BMI), family history of cancer, education level, income level, dietary habits, physical activity, consumption of Zu(locally brewed alcohol) and both Zu(locally brewed alcohol) and commercial alcohol(rum, whisky, vodka and beer, etc) are also associated with higher risk of esophageal cancer (O.R = 9.820, 95% CI = 2.029-47.523). Keywords: Alcohol consumption, betel quid consumption, tobacco consumption, smoking, esophageal cancer, Mizoram.Download Full Article |
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Abstract: When the nature of a data set comes from a skew distribution, the use of usual Gaussian mixed effect model can be unreliable. In recent years, skew-normal mixed effect models have been used frequently for longitudinal data modeling in many biomedical studies. These models are flexible for considering skewness of the longitudinal data. In this paper, a shared parameter model is considered for simultaneously analysing nonignorable missingness and skew longitudinal outcomes. A Bayesian approach using Markov Chain Monte Carlo is adopted for parameter estimation. Some simulation studies are performed to investigate the performance of the proposed methods. The proposed methods are applied for analyzing an AIDS data set, where CD4 count measurements are gathered as longitudinal outcomes. In these data CD4 counts measurements are severely skew. In application section, different structures of skew-normal distribution assumptions for random effects and errors are considered where deviance informationcriterion is used for model comparison. Keywords: Bayesian approach, Longitudinal data, Markov Chain Monte Carlo, Missingness mechanism, Nonignorable missing data, Random effects model. |
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Abstract:Objective: We evaluate pertussis and measles immunization strategies and compare the consequences in terms of health effects and economic costs. Methods: Based on epidemiological data for pertussis and measles in England and Wales from 1970 to 2012, we use ARIMA approach to model the relation between notification cases and vaccination coverage for each disease. We then perform an economic evaluation of vaccination programs at 95% and discuss the benefits for the society to achieve this level when compared with lower vaccination rates currently observed. The advantages for the society of increasing vaccination coverage up to 98% are considered respectively for pertussis and measles. Results: The programs at a 95% vaccination rate, which is able to significantly reduce the mortality and the morbidity due to pertussis and measles, are confirmed to be the best cost saving immunization strategy. The total social net benefits are systematically maximized when the programs are compared to strategies with lower vaccination coverage. The decision to exceed the herd immunity level and reach the rate at 98% is economically justified for measles, while for pertussis the programs at 98% are less cost effective than the programs at 95%. Conclusion: Additional efforts must be carried out to promote measles vaccination since immunization strategies at 95% and at higher rates are recommended on epidemiological and economic grounds. Keywords: Pertussis and measles immunization, cost analysis of vaccination program, epidemiology of pertussis and measles in England and Wales, ARIMA transfer function model.Download Full Article |