Bayesian analysis of silica exposure and lung cancer, incorporating prior information from animal studies and a model for measurement error

2016 ◽  
Vol 2016 (1) ◽  
Author(s):  
Scott Bartell* ◽  
Ghassan Hamra ◽  
Kyle Steenland
Keyword(s):  
Lung Cancer ◽  
Measurement Error ◽  
Bayesian Analysis ◽  
Animal Studies ◽  
Prior Information ◽  
Silica Exposure

Bayesian Analysis of Silica Exposure and Lung Cancer Using Human and Animal Studies

Epidemiology ◽  
2017 ◽  
Vol 28 (2) ◽  
pp. 281-287 ◽  
Author(s):  
Scott M. Bartell ◽  
Ghassan Badri Hamra ◽  
Kyle Steenland
Keyword(s):  
Lung Cancer ◽  
Bayesian Analysis ◽  
Animal Studies ◽  
Silica Exposure

scholarly journals Silica exposure and risk of lung cancer.

Thorax ◽  
1996 ◽  
Vol 51 (7) ◽  
pp. 772-772
Author(s):  
W. K. Morgan ◽  
R. B. Reger
Keyword(s):  
Lung Cancer ◽  
Silica Exposure

scholarly journals A Probabilistic Approach for Economic Evaluation of Occupational Health and Safety Interventions: A Case Study of Silica Exposure Reduction Interventions in the Construction Sector

2020 ◽  
Author(s):  
Amirabbas Mofidi ◽  
Emile Tompa ◽  
SeyedBagher Mortazavi ◽  
Akbar Esfahanipour ◽  
Paul A. Demers
Keyword(s):  
Lung Cancer ◽  
Economic Evaluation ◽  
Probabilistic Modeling ◽  
Hazardous Substances ◽  
Construction Sector ◽  
Net Benefit ◽  
Expected Cost ◽  
Silica Exposure ◽  
Exposure Reduction ◽  
Modeling Approach

Abstract Background: Construction workers are at a high risk of exposure to various types of hazardous substances such as crystalline silica. Though multiple studies indicate the evidence regarding the effectiveness of different silica exposure reduction interventions in the construction sector, the decisions for selecting a specific silica exposure reduction intervention are best informed by an economic evaluation. Economic evaluation of interventions is subjected to uncertainties in practice, mostly due to the lack of precise data on important variables. In this study, we aim to identify the most cost-beneficial silica exposure reduction intervention for the construction sector under uncertain situation. Methods: We apply a probabilistic modeling approach that covers a large number of variables relevant to the cost of lung cancer, as well as the costs of silica exposure reduction interventions. To estimate the societal lifetime cost of lung cancer, we use an incidence cost approach. To estimate the net benefit of each intervention, we compare the expected cost of lung cancer cases averted, with expected cost of implementation of the intervention in one calendar year. Sensitivity analysis is used to quantify how different variables effects interventions net benefit.Results: A positive net benefit is expected for all considered interventions. The highest number of lung cancer cases are averted by combined use of wet method, local exhaust ventilation and personal protective equipment, about 107 cases, with expected net benefit of $45.9 million. Results also suggest that the level of exposure is an important determinant for the selection of the most cost-beneficial intervention.Conclusions: This study provides important insights for decision makers about silica exposure reduction interventions in the construction sector. It also provides an overview of the potential advantages of using probabilistic modeling approach to undertake economic evaluations, particularly when researchers are confronted with a large number of uncertain variables.

scholarly journals On the Nature of Evidence and ‘Proving’ Causality: Smoking and Lung Cancer vs. Sun Exposure, Vitamin D and Multiple Sclerosis

2018 ◽  
Vol 15 (8) ◽  
pp. 1726 ◽  
Author(s):  
Robyn Lucas ◽  
Rachael Rodney Harris
Keyword(s):  
Risk Factors ◽  
Multiple Sclerosis ◽  
Lung Cancer ◽  
Vitamin D ◽  
Observational Studies ◽  
Animal Studies ◽  
Disease Risk ◽  
Sun Exposure ◽  
Sufficient Evidence

If environmental exposures are shown to cause an adverse health outcome, reducing exposure should reduce the disease risk. Links between exposures and outcomes are typically based on ‘associations’ derived from observational studies, and causality may not be clear. Randomized controlled trials to ‘prove’ causality are often not feasible or ethical. Here the history of evidence that tobacco smoking causes lung cancer—from observational studies—is compared to that of low sun exposure and/or low vitamin D status as causal risk factors for the autoimmune disease, multiple sclerosis (MS). Evidence derives from in vitro and animal studies, as well as ecological, case-control and cohort studies, in order of increasing strength. For smoking and lung cancer, the associations are strong, consistent, and biologically plausible—the evidence is coherent or ‘in harmony’. For low sun exposure/vitamin D as risk factors for MS, the evidence is weaker, with smaller effect sizes, but coherent across a range of sources of evidence, and biologically plausible. The association is less direct—smoking is directly toxic and carcinogenic to the lung, but sun exposure/vitamin D modulate the immune system, which in turn may reduce the risk of immune attack on self-proteins in the central nervous system. Opinion about whether there is sufficient evidence to conclude that low sun exposure/vitamin D increase the risk of multiple sclerosis, is divided. General public health advice to receive sufficient sun exposure to avoid vitamin D deficiency (<50 nmol/L) should also ensure any benefits for multiple sclerosis, but must be tempered against the risk of skin cancers.

scholarly journals Projections in Breast and Lung Cancer Mortality among Women: A Bayesian Analysis of 52 Countries Worldwide

2018 ◽  
Vol 78 (15) ◽  
pp. 4436-4442 ◽  
Author(s):  
Juan Carlos Martín-Sánchez ◽  
Nuno Lunet ◽  
Adrián González-Marrón ◽  
Cristina Lidón-Moyano ◽  
Nuria Matilla-Santander ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Bayesian Analysis ◽  
Cancer Mortality ◽  
Lung Cancer Mortality
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