Bayesian joint modeling of longitudinal and survival data

The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

Systematic literature review on internet-based interventions to prevent HIV transmission

Objective. To perform a systematic review of the internet based HIV prevention interventions.^ Data Source. Data resources including Ovid Medline, CINAHL (EBSCOhost and Psycinfo) were searched for the relevant articles. Study Selection: Studies were selected if the entire article was in English, Randomized control trial performed after 1998 till current, internet based aimed towards HIV/AIDS prevention. ^ Data Extraction. Each relevant article was coded using a code sheet which consisted of background information, study characteristics, study population information, program details, intervention and results. Data Synthesis: Total of seven relevant articles were coded and the information obtained was incorporated into the evidence tables for comparison.^ Conclusion. Overall the internet based HIV prevention studies have been very successful in recruiting large number of people but has not been able to show effective results due to high attrition. More research needs to be done in the area.^