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Background: All forms of asbestos are now banned in 52 countries. Safer products have replaced many materials that once were made with it. Nonetheless, many countries still use, import, and export asbestos and asbestos-containing products, and in those that have banned other forms of asbestos, the so-called \"controlled use\" of chrysotile asbestos is often exempted from the ban. In fact, chrysotile has accounted for > 95% of all the asbestos used globally. Objective: We examined and evaluated the literature used to support the exemption of chrysotile asbestos from the ban and how its exemption reflects the political and economic influence of the asbestos mining and manufacturing industry. Discussion: All forms of asbestos, including chrysotile, are proven human carcinogens. All forms cause malignant mesothelioma and lung and laryngeal cancers, and may cause ovarian, gastrointestinal, and other cancers. No exposure to asbestos is without risk. Illnesses and deaths from asbestos exposure are entirely preventable. Conclusions: All countries of the world have an obligation to their citizens to join in the international endeavor to ban the mining, manufacture, and use of all forms of asbestos. An international ban is urgently needed. There is no medical or scientific basis to exempt chrysotile from the worldwide ban of asbestos.

Background There exist several predictive risk models for cardiovascular disease (CVD), including some developed specifically for patients with type 2 diabetes mellitus (T2DM). However, the models developed for a diabetic population are based on information derived from medical records or laboratory results, which are not typically available to entities like payers or quality of care organizations. The objective of this study is to develop and validate models predicting the risk of cardiovascular events in patients with T2DM based on medical insurance claims data. Methods Patients with T2DM aged 50 years or older were identified from the Optum™ Integrated Real World Evidence Electronic Health Records and Claims de-identified database (10/01/2006–09/30/2016). Risk factors were assessed over a 12-month baseline period and cardiovascular events were monitored from the end of the baseline period until end of data availability, continuous enrollment, or death. Risk models were developed using logistic regressions separately for patients with and without prior CVD, and for each outcome: (1) major adverse cardiovascular events (MACE; i.e., non-fatal myocardial infarction, non-fatal stroke, CVD-related death); (2) any MACE, hospitalization for unstable angina, or hospitalization for congestive heart failure; (3) CVD-related death. Models were developed and validated on 70% and 30% of the sample, respectively. Model performance was assessed using C-statistics. Results A total of 181,619 patients were identified, including 136,544 (75.2%) without prior CVD and 45,075 (24.8%) with a history of CVD. Age, diabetes-related hospitalizations, prior CVD diagnoses and chronic pulmonary disease were the most important predictors across all models. C-statistics ranged from 0.70 to 0.81, indicating that the models performed well. The additional inclusion of risk factors derived from pharmacy claims (e.g., use of antihypertensive, and use of antihyperglycemic) or from medical records and laboratory measures (e.g., hemoglobin A1c, urine albumin to creatinine ratio) only marginally improved the performance of the models. Conclusion The claims-based models developed could reliably predict the risk of cardiovascular events in T2DM patients, without requiring pharmacy claims or laboratory measures. These models could be relevant for providers and payers and help implement approaches to prevent cardiovascular events in high-risk diabetic patients.

With advancements in and increased access to next-generation sequencing technology, hospitals (such as Duke Medical Center) have started to track the microbiomes of at-risk patients over time, but at inconsistently measured points across patients. Modeling the trajectories of high-throughput microbiome data proves difficult, due to inconsistent data collection, as well as a collection of analytical obstacles such as compositional data, sparsity, high dimensionality, and phylogenetic covariance structure. As a result, few methods allow us to capture uncertainty in the microbiome over time using increasingly standard data collection and processing methods.Here, we develop a novel hierarchical model to measure dynamics of the microbiome across cohorts of patients measured inconsistently, which we call logistic-tree Gaussian processes for the microbiome (LoTGaP). LoTGaP adds to the existing microbiome literature through (1) using Gaussian processes to flexibly estimate the evolution of the microbiome over a finite set of days to handle missing/inconsistently measured data, (2) transforming operational taxonomic units (OTUs) to their internal nodes on the phylogenetic tree to accelerate computation and preserve biological relationships, and (3) building functionality to estimate the influence of covariates on microbiome dynamics across patients, which can allow for hospitals to link treatment regimens to microbiome dynamics, or make direct connections between microbiome data and other measurements, such as demographic information.We demonstrate that LoTGaP produces uncertainty bands that reflect both within-person variation over time and across-person variation while comparing favorably in computation time to existing methods that are narrower in scope.

Claims for there being honest intellectual doubt about the need to operate a worldwide ban were being made by the CMA as late as 2001 when its Journal debated: 'Should Canadian health care professionals call for a worldwide ban on asbestos?' Despite the authoritative opinions of the UN and the EU, the CMA expressed the need for a panel of experts with no \"significant experience or interest in asbestos research\" [sic] to review the public health implications of asbestos and the efficacy and the hazards of alternative materials.

Objectives: Canadian chrysotile (white asbestos) could be a paradigm for those agents that are successfully exploited commercially long after they have been found to be lethal. Mining started in the late 1870s, and reports of disability and death followed in Britain (1898), in France (1906), and Italy (1908), but it was not until 1955 that Canada acknowledged asbestosis in its asbestos miners and millers. Even when shortly after asbestos was shown to be carcinogenic, Canadian Public Relations experts assisted by their scientists exculpated chrysotile by deeming other agents to have been causal Results: The PR techniques that have been successfully used in the defense of chrysotile are reviewed to forewarn scientists involved in formulating public health policy for similar agents, as to the tricks that will be played on them.

Objectives: Canadian chrysotile (white asbestos) could be a paradigm for those agents that are successfully exploited commercially long after they have been found to be lethal. Mining started in the late 1870s, and reports of disability and death followed in Britain (1898), in France (1906), and Italy (1908), but it was not until 1955 that Canada acknowledged asbestosis in its asbestos miners and millers. Even when shortly after asbestos was shown to be carcinogenic, Canadian Public Relations experts assisted by their scientists exculpated chrysotile by deeming other agents to have been causal. Results: The PR techniques that have been successfully used in the defense of chiysotile are reviewed, to forewarn scientists involved in formulating public health policy for similar agents, as to the tricks that will be played on them. [PUBLICATION ABSTRACT]