Rose M. Ray

Cancer in asbestos-exposed occupational cohorts: a meta-analysis

Objective: To examine existing asbestos-exposed occupational cohorts and apply a meta-analytic technique to determine the magnitude of association between exposure and lung cancer and to investigate other cancer sites that may be related to such an exposure.Methods: We summarized the data from 69 asbestos-exposed occupational cohorts reporting on cancer morbidity and mortality. Data were extracted regarding numbers of deaths for each cancer, numbers of mesotheliomas, occupations and latency for respiratory, gastrointestinal, urinary and lymphohematopoietic cancers. For each cancer, we calculated a meta-SMR and examined heterogeneity of results using a chi-square test and by calculating a Z-statistic for each study. To examine the dose–response effect, we divided the studies into tertiles according to the percentage of mesothelioma deaths that served as a proxy estimation of asbestos exposure.Results: Lung cancer data demonstrated meta-SMRs of 163 and 148 with and without latency, respectively, with significant heterogeneity of results even after stratification according to occupational groups. Stratification of lung cancer studies according to percentage of mesothelioma deaths showed a dose–response effect. Z-scores ranged from − 12.21 to + 29.49. Analysis for laryngeal cancer yielded meta-SMRs of 157 and 133 with and without latency, respectively, demonstrating homogeneous results across studies but accompanied by no evidence of a dose–response effect. Data for gastrointestinal cancers showed no evidence of a significant association and no dose–response effect. Kidney cancer demonstrated statistically non-significant meta-SMRs of 120 (95% CI 88–160) and 111 (95% CI 94–131) with and without latency respectively.Conclusions: This meta-analysis demonstrates a wide variability of the association between occupational asbestos and lung cancer. There was a suggestion of an association between asbestos and laryngeal carcinoma and no clear association with other cancers.

Assessment of the Beryllium Lymphocyte Proliferation Test Using Statistical Process Control

Despite more than 20 years of surveillance and epidemiologic studies using the beryllium blood lymphocyte proliferation test (BeBLPT) as a measure of beryllium sensitization (BeS) and as an aid for diagnosing subclinical chronic beryllium disease (CBD), improvements in specific understanding of the inhalation toxicology of CBD have been limited. Although epidemiologic data suggest that BeS and CBD risks vary by process/work activity, it has proven difficult to reach specific conclusions regarding the dose-response relationship between workplace beryllium exposure and BeS or subclinical CBD. One possible reason for this uncertainty could be misclassification of BeS resulting from variation in BeBLPT testing performance. The reliability of the BeBLPT, a biological assay that measures beryllium sensitization, is unknown. To assess the performance of four laboratories that conducted this test, we used data from a medical surveillance program that offered testing for beryllium sensitization with the BeBLPT. The study population was workers exposed to beryllium at various facilities over a 10-year period (1992–2001). Workers with abnormal results were offered diagnostic workups for CBD. Our analyses used a standard statistical technique, statistical process control (SPC), to evaluate test reliability. The study design involved a repeated measures analysis of BeBLPT results generated from the company-wide, longitudinal testing. Analytical methods included use of (1) statistical process control charts that examined temporal patterns of variation for the stimulation index, a measure of cell reactivity to beryllium; (2) correlation analysis that compared prior perceptions of BeBLPT instability to the statistical measures of test variation; and (3) assessment of the variation in the proportion of missing test results and how time periods with more missing data influenced SPC findings. During the period of this study, all laboratories displayed variation in test results that were beyond what would be expected due to chance alone. Patterns of test results suggested that variations were systematic. We conclude that laboratories performing the BeBLPT or other similar biological assays of immunological response could benefit from a statistical approach such as SPC to improve quality management.

A Survey Methodology for Collecting Fish Consumption Data in Urban and Industrial Water Bodies (Part 1)

The potential human health risks associated with consuming fish containing hazardous substances are related to the frequency, duration, and magnitude of exposure. Because these risk factors are often site specific, they require site-specific data. In anticipation of performing a risk assessment of the lower 6 miles of the Passaic River in New Jersey (Study Area), a year-long creel/angler survey collected such site-specific data. The lower Passaic River is urbanized and industrialized, and its site conditions present unique survey design and sampling challenges. For example, the combined population of the municipalities surrounding the Study Area is nearly 330,000, but because the Study Area is tidal, state law does not require fishing licenses for anglers to fish or crab in the Study Area. The sampling challenges posed by the lack of licensing are exacerbated by the industrialization and lack of public access in the lower half of the Study Area. This article presents a survey methodology designed to overcome these challenges to provide data for accurately estimating the Study Areas angling population and the fish and crabs they catch, keep, and eat. In addition to addressing the challenges posed by an urban and industrial setting, the survey methodology also addresses the issues of coverage, avidity, and deterrence, issues necessary for collecting a representative sample of the Study Areas anglers. This article is a companion to two other articles. The first companion article describes the analytical methodology designed to process the data collected during the survey. The second presents, validates, and interprets the survey results relating to human exposure factors for the lower Passaic River.

A Statistical Method for Analyzing Data Collected by a Creel/Angler Survey (Part 2)

This article describes a unique analytical method employed to characterize angler activities on the lower 6-mile stretch of the Passaic River in New Jersey. The method used data collected by a creel/angler survey that was designed to capture the information necessary to calculate the exposure factors needed to characterize the fish consumption pathway for recreational anglers in a human health risk assessment for the river. The survey used two methods to address the challenges of conducting a creel/angler survey in an urban and industrial setting with limited river access. While unique, the analytical method described in this article is based upon accepted methods of interpreting survey data and basic laws of probability. This article was written as a companion to two other articles, also in this issue and cited here, of which one describes in detail the survey methodology designed for the lower Passaic River creel/angler survey to meet various challenges unique to conducting such a survey in urban and industrialized rivers, and the other presents, validates, and interprets the results of the lower Passaic River work relating to human exposure factors using the methodology described in this article.

An Examination of Motorcycle Antilock Brake Systems (ABS) in Reducing Crash Risk

To prevent wheel lock up (and possible loss of control and capsize) during hard braking motorcycle manufacturers have equipped motorcycles with Antilock Brake Systems (ABS) either as an option or as standard equipment. Several studies utilizing real-world crash data have been published which estimate the effectiveness of motorcycle ABS in reducing the risk of a crash based on varying assumptions. These investigations have reported mixed results.The present investigation relies upon the Fatality Analysis Reporting System (FARS) and the Florida police-reported crash databases to further investigate the effectiveness of motorcycle ABS by expanding upon and refining previous approaches. Notably a case-control approach is used whereby crashes involving ABS- and non-ABS-equipped motorcycles are divided into five groups with a varying likelihood that ABS will affect the risk of crashes in that group. The group of crashes with the least likelihood of being influenced by ABS is considered the control group and used as a measure of exposure to crashes. This methodology attempts to reduce any selection biases that might exist in the two motorcycle classes.The results support the hypothesis that ABS is effective in reducing the crash risk in some crash types. However, it was found that the case-control approach does not incorporate all factors that might influence the overall effectiveness of ABS, for example, motorcycle class and operator age. Accounting for these additional factors would likely require the use of regression analyses and would benefit significantly from additional data.Copyright

An Examination of Motorcycle Antilock Brake Systems in Reducing Crash Risk

To prevent wheel lockup (and possible loss-of-control and capsize) during hard braking, motorcycle manufacturers have equipped motorcycles with antilock brake systems (ABS) either as an option or as standard equipment. Several studies utilizing real-world crash data have been published, which estimate the effectiveness of motorcycle ABS in reducing the risk of a crash based on varying assumptions. These investigations have reported mixed results. The present investigation relies upon the fatality analysis reporting system (FARS) and the Florida police-reported crash databases to further investigate the effectiveness of motorcycle ABS by expanding upon and refining previous approaches. Notably, a case-control approach is used, whereby crashes involving ABS- and non-ABS-equipped motorcycles are divided into five groups with a varying likelihood that ABS will affect the risk of crashes in that group. The group of crashes with the least likelihood of being influenced by ABS is considered the control group and used as a measure of exposure to crashes. This methodology attempts to reduce any selection biases that might exist in the two motorcycle classes. The results support the hypothesis that ABS is effective in reducing the crash risk in some crash types. However, it was found that the case-control approach does not incorporate all factors that might influence the overall effectiveness of ABS, e.g., motorcycle class and operator age. Accounting for these additional factors would likely require the use of regression analyses and would benefit significantly from additional data.

Diffuse electrical injury: Questioning the scientific basis

Published reports postulate the existence of an electrical injury syndrome or pattern whereby clinical and physical manifestations of a shock injury occur remote to the actual current pathway, and may present in the absence of related acute findings. It is suggested that the extent of such injury is unrelated to the magnitude of shock current and that the timing of the ldquodiffuse electrical injuryrdquo may be indefinitely delayed with respect to the time of the sustained shock. Other reports refer to possible shock injury mechanisms that manifest solely with neuropsychological symptoms. A critical examination of this literature reveals no mechanistic basis for the association of the proposed physical symptoms of diffuse electrical injury with remote injury. Additionally, serious errors in the stated methodology of the publications citing the existence of diffuse electrical injury cast doubt upon the scientific basis for the stated conclusions.

Using Weibull Analysis for Cases With an Unknown Susceptible Population

Weibull analysis is a powerful predictive tool for studying failure trends of engineering systems. [1] One noted shortcoming is that traditional techniques require the size of the susceptible population to be known. The method described in this paper allows for estimation of the size of the susceptible population using only failure data and no assumptions about total population size or susceptible portion. In the analysis of failures of mass-produced products, a large amount of failure data may be available, but all the conditions that define the susceptible population may never be known. For example, units with a particular usage condition may be expected to fail over time following a Weibull model, but the number of units subjected to that usage condition may never be known. To assume that the entire population is susceptible to the failure mode would greatly over-predict future failures, and the model could not be used to guide decision-making. By doing a least squares fit to the trend of failures versus time, a Weibull model can be fit to the data and then used to estimate the total number of susceptible units expected in the population. The ability to accurately estimate the size of the susceptible sub-population from failure data will be explored as a function of the size of the data set used, for known sets of failure data. For example, for a failure distribution that has increased, peaked, and then decreased to zero, almost the entire population has failed, so an estimate of the size of the susceptible population from this data is likely to be accurate. On the contrary, for only a few data points that show an increasing failure rate over time, little can be determined. Monte Carlo simulations will be used in order to estimate the error associated with this technique. Our analysis will show that predictions of total susceptible populations become similar to the actual susceptible populations when the predicted mean time to failure (MTTF) from the observed data is shorter than the observation time. In effect, predictions become accurate when it is clear to the observer that the number of failures per unit time has peaked.Copyright