An official American Thoracic Society statement: diagnosis and management of beryllium sensitivity and chronic beryllium disease.

RATIONALE: Beryllium continues to have a wide range of industrial applications. Exposure to beryllium can lead to sensitization (BeS) and chronic beryllium disease (CBD). OBJECTIVES: The purpose of this statement is to increase awareness and knowledge about beryllium exposure, BeS, and CBD. METHODS: Evidence was identified by a search of MEDLINE. The committee then summarized the evidence, drew conclusions, and described their approach to diagnosis and management. MAIN RESULTS: The beryllium lymphocyte proliferation test is the cornerstone of both medical surveillance and the diagnosis of BeS and CBD. A confirmed abnormal beryllium lymphocyte proliferation test without evidence of lung disease is diagnostic of BeS. BeS with evidence of a granulomatous inflammatory response in the lung is diagnostic of CBD. The determinants of progression from BeS to CBD are uncertain, but higher exposures and the presence of a genetic variant in the HLA-DP ß chain appear to increase the risk. Periodic evaluation of affected individuals can detect disease progression (from BeS to CBD, or from mild CBD to more severe CBD). Corticosteroid therapy is typically administered when a patient with CBD exhibits evidence of significant lung function abnormality or decline. CONCLUSIONS: Medical surveillance in workplaces that use beryllium-containing materials can identify individuals with BeS and at-risk groups of workers, which can help prioritize efforts to reduce inhalational and dermal exposures.

"Quasi nonparametric" upper tolerance limits for occupational exposure evaluations.

Upper tolerance limits (UTLs) are often used in comparing exposure data sets with an occupational exposure limit (OEL) or other regulatory criterion (RC): if the 95%-95% UTL does not exceed the OEL, one is 95% confident that at most 5% of exposures exceed the OEL, and the comparison "passes." The largest of 59 observations is a nonparametric (distribution-free) 95%-95% UTL (NPUTL); the chance that this largest value equals or exceeds the actual 95th percentile is at least 95%, regardless of the underlying data distribution. That many observations may seem excessive in clean environments or small studies, though, and one would like to "pass" using UTLs based on fewer observations sufficiently far below the OEL or RC. "Quasi-nonparametric" UTLs (QNP UTLs) accomplish this. QNP UTLs assign a "pass" so long as one has "59 [values] less than the RC" (the NPUTL itself), "30 less than 1/2 [of the RC]," "21 less than 1/3," and on down to "8 less than 1/10," the last matching a rule-of-thumb given in 2006 American Industrial Hygiene Association (AIHA) guidance. They are derived using the conservative, experience-based assumption that the data distribution is lognormal with log-scale standard deviation σ at most 2.0 (geometric standard deviation at most 7.39). Although based on this assumption, their statistical performance is reasonably unaffected or conservative when data come from other distributions often assumed for contaminant concentrations; moreover, their performance is insensitive to analytical variation. This conservative robustness merits the description "quasi-nonparametric." QNP UTLs are very easy to use. Reporting Limit (RL) issues do not arise. QNP UTLs reduce the numbers of observations needed to support conservative risk management decisions when sampling from compliant working conditions.

Identification of an abnormal beryllium lymphocyte proliferation test.

The potential hazards from exposure to beryllium or beryllium compounds in the workplace were first reported in the 1930s. The tritiated thymidine beryllium lymphocyte proliferation test (BeLPT) is an in vitro blood test that is widely used to screen beryllium exposed workers in the nuclear industry for sensitivity to beryllium. The clinical significance of the BeLPT was described and a standard protocol was developed in the late 1980s. Cell proliferation is measured by the incorporation of tritiated thymidine into dividing cells on two culture dates and using three concentrations of beryllium sulfate. Results are expressed as a 'stimulation index' (SI) which is the ratio of the amount of tritiated thymidine (measured by beta counts) in the simulated cells divided by the counts for the unstimulated cells on the same culture day. Several statistical methods for use in the routine analysis of the BeLPT were proposed in the early 1990s. The least absolute values (LAV) method was recommended for routine analysis of the BeLPT. This report further evaluates the LAV method using new data, and proposes a new method for identification of an abnormal or borderline test. This new statistical-biological positive (SBP) method reflects the clinical judgment that: (i) at least two SIs show a 'positive' response to beryllium; and (ii) that the maximum of the six SIs must exceed a cut-point that is determined from a reference data set of normal individuals whose blood has been tested by the same method in the same serum. The new data is from the Y-12 National Security Complex in Oak Ridge (Y-12) and consists of 1080 workers and 33 non-exposed control BeLPTs (all tested in the same serum). Graphical results are presented to explain the statistical method, and the new SBP method is applied to the Y-12 group. The true positive rate and specificity of the new method were estimated to be 86% and 97%, respectively. An electronic notebook that is accessible via the Internet was used in this work and contains background information and details not included in the paper.

Variation in exposure levels for high hazard frequently monitored agents.

Assumptions about the underlying distribution of occupational exposures are important to the practice of industrial hygiene. They affect decisions on exposure monitoring strategies, the interpretation of monitoring results, and the degree of protection provided by occupational exposure limits and action levels. However, there is little published data validating these assumptions. Strict exposure limits for three highly hazardous agents, asbestos, beryllium, and ionizing radiation, led to frequent monitoring of occupational exposure levels. Consequently, sets of hundreds to thousands of exposure measurements are available for analysis. Statistical analysis of these data sets indicates that within-worker variation, as measured by geometric standard deviation (GSD), tend to be higher than is generally assumed for occupational exposures. The success of health protection programs in identifying and controlling predictable sources of exposure through frequent monitoring is offered as a possible explanation for the relatively high variation observed in these data sets. Despite the high exposure variation, arithmetic mean levels and the percentage of measurements exceeding exposure limits were low, indicating that a large GSD does not imply that working conditions are unacceptable. However, more frequent monitoring is required to assure exposures are acceptable. This article also presents an adaptation of graphical methods, using probability plotting and linear regression, to estimate the distribution parameters of a data set that contains a high percentage of nondetected results.