Derivation of an occupational exposure limit for benzene using epidemiological study quality assessment tools.

This paper derives an occupational exposure limit for benzene using quality assessed data. Seventy-seven genotoxicity and 36 haematotoxicity studies in workers were scored for study quality with an adapted tool based on that of Vlaanderen et al., 2008 (Environ Health. Perspect. 116 1700-5). These endpoints were selected as they are the most sensitive and relevant to the proposed mode of action (MOA) and protecting against these will protect against benzene carcinogenicity. Lowest and No- Adverse Effect Concentrations (LOAECs and NOAECs) were derived from the highest quality studies (i.e. those ranked in the top tertile or top half) and further assessed as being "more certain" or "less certain". Several sensitivity analyses were conducted to assess whether alternative "high quality" constructs affected conclusions. The lowest haematotoxicity LOAECs showed effects near 2 ppm (8 h TWA), and no effects at 0.59 ppm. For genotoxicity, studies also showed effects near 2 ppm and showed no effects at about 0.69 ppm. Several sensitivity analyses supported these observations. These data define a benzene LOAEC of 2 ppm (8 h TWA) and a NOAEC of 0.5 ppm (8 h TWA). Allowing for possible subclinical effects in bone marrow not apparent in studies of peripheral blood endpoints, an OEL of 0.25 ppm (8 h TWA) is proposed.

Benzene risk assessment: does new evidence on myelodysplastic syndrome justify a new approach?

Epidemiologic findings play an important role in benzene risk assessment, which is utilized to guide the selection of recommended benzene exposure levels to prevent adverse health effects. For decades, excess leukemia risk, especially that in the Pliofilm® cohort, has been the focus of benzene risk assessment. While more stringent benzene standards, often ≤1 ppm, have been promulgated to protect workers from developing leukemia, recent epidemiologic studies have reported elevated risk of myelodysplastic syndrome (MDS). This report aims to examine whether the use of new data on MDS is scientifically warranted in future benzene risk assessments. First, we reviewed current benzene guidelines, regulations, and underlying risk assessments in developed countries. Second, we examined current epidemiologic literature on benzene and MDS, which identified seven studies with simultaneous measures of MDS risk and benzene exposure and 17 studies on MDS in populations potentially exposed to benzene. Next, we examined the potential of the MDS data to serve as the basis of future benzene risk assessments, by comparing its quality and risk estimates with those used in current benzene standards. We conclude from the current literature that there is strong evidence that MDS can be caused by benzene, and the MDS data from the pooled petroleum study should be further examined in future benzene risk assessments. We recommend that future MDS-based benzene risk assessment use total MDS as the endpoint, take into consideration the full exposure period, and examine a range of benzene exposure metrics, including the role of peak, intermittent benzene exposures.

Effects of non-differential exposure misclassification on false conclusions in hypothesis-generating studies.

Despite the theoretical success of obviating the need for hypothesis-generating studies, they live on in epidemiological practice. Cole asserted that "… there is boundless number of hypotheses that could be generated, nearly all of them wrong" and urged us to focus on evaluating "credibility of hypothesis". Adopting a Bayesian approach, we put this elegant logic into quantitative terms at the study planning stage for studies where the prior belief in the null hypothesis is high (i.e., "hypothesis-generating" studies). We consider not only type I and II errors (as is customary) but also the probabilities of false positive and negative results, taking into account typical imperfections in the data. We concentrate on a common source of imperfection in the data: non-differential misclassification of binary exposure classifier. In context of an unmatched case-control study, we demonstrate-both theoretically and via simulations-that although non-differential exposure misclassification is expected to attenuate real effect estimates, leading to the loss of ability to detect true effects, there is also a concurrent increase in false positives. Unfortunately, most investigators interpret their findings from such work as being biased towards the null rather than considering that they are no less likely to be false signals. The likelihood of false positives dwarfed the false negative rate under a wide range of studied settings. We suggest that instead of investing energy into understanding credibility of dubious hypotheses, applied disciplines such as epidemiology, should instead focus attention on understanding consequences of pursuing specific hypotheses, while accounting for the probability that the observed "statistically significant" association may be qualitatively spurious.

The use of biomonitoring data in exposure and human health risk assessment: benzene case study.

Abstract A framework of "Common Criteria" (i.e. a series of questions) has been developed to inform the use and evaluation of biomonitoring data in the context of human exposure and risk assessment. The data-rich chemical benzene was selected for use in a case study to assess whether refinement of the Common Criteria framework was necessary, and to gain additional perspective on approaches for integrating biomonitoring data into a risk-based context. The available data for benzene satisfied most of the Common Criteria and allowed for a risk-based evaluation of the benzene biomonitoring data. In general, biomarker (blood benzene, urinary benzene and urinary S-phenylmercapturic acid) central tendency (i.e. mean, median and geometric mean) concentrations for non-smokers are at or below the predicted blood or urine concentrations that would correspond to exposure at the US Environmental Protection Agency reference concentration (30 µg/m(3)), but greater than blood or urine concentrations relating to the air concentration at the 1 × 10(-5) excess cancer risk (2.9 µg/m(3)). Smokers clearly have higher levels of benzene exposure, and biomarker levels of benzene for non-smokers are generally consistent with ambient air monitoring results. While some biomarkers of benzene are specific indicators of exposure, the interpretation of benzene biomonitoring levels in a health-risk context are complicated by issues associated with short half-lives and gaps in knowledge regarding the relationship between the biomarkers and subsequent toxic effects.

Retrospective occupational exposure assessment for case-control and case-series epidemiology studies based in Shanghai China.

To provide exposure information for epidemiology studies conducted in Shanghai from 2001 to 2008, we completed retrospective exposure assessments (EA) of benzene and other hazards. Interviewers administered questionnaires to subjects from Shanghai area hospitals. An initial exposure screening by EA staff members, blinded as to case-control status, stratified jobs into exposed, unexposed, or uncertain categories prior to review by a separate expert panel (EP). Resources for the EA included job/industry-specific questionnaire responses by subjects, short-term benzene area concentration measurements from a Shanghai regulatory agency database, Chinese literature for qualitative and short-term quantitative measurements, on-site investigations, summaries of technology changes, and selected task simulations with concurrent benzene concentration measurements. An EP in Shanghai completed semi-quantitative benzene exposure assignments, with categories of 0 to 4 corresponding to intensity ranges of none, <1, 1 to 10, >10 to 100, and >100 mg/m(3). For other hazards, sources included the EP's knowledge of the industries and Chinese and Western literature. For benzene, 20% of the EAs selected by a stratified random process were evaluated by two alternate methods. The study database of potential cases and controls included 18,857 jobs from the subjects' work histories. From 818 individuals initially screened as probably benzene exposed, 964 jobs underwent further review. From subjects with final diagnoses, 755 jobs qualified for inclusion in the final database for any study. For other exposures, the EA considered 17,893 jobs from 7654 subjects for possible exposures and were in the final study database. Of these, 2565 individuals had exposures of study interest from their 4909 exposed jobs. The prevalent exposures included agricultural chemicals, petroleum products, and metals. The EA involved extensive information assembly and exposure assignment by an EP and periodic reviews. The methods described went beyond those typically applied in past general population studies and may have provided improved information for the epidemiologic analyses. However, sufficient, reliable measured historical data are lacking to evaluate this conclusion.

Exposure assessment methods for a study of mortality and cancer morbidity in relation to specific petroleum industry exposures.

In 1987 a Canadian company implemented an exposure tracking and health information system. The exposure tracking method aligned closely with published concepts for describing workplace exposure, with over 1800 similar exposure groups being used to describe occupational exposures. The database has been actively maintained and is subject to a number of quality checks. Recently, the company initiated a cancer morbidity study, with one objective being to examine whether the exposure tracking data could be used to reconstruct exposure estimates for the cohort. Five agents--hydrogen sulfide, petroleum coke/spent catalyst, hydrocarbon solvents and fuels, hydrocarbon lubricants, and an index for exposure to operations derived from noise exposure--were selected for development of occupational exposure estimates for each cohort member. The cohort consisted of workers first employed between January 1964 and December 1994 and who were employed for at least 1 year. Work history records were associated with a similar exposure group, using human resources data and knowledge of local industrial hygienists. Only employees with >90% duration of their work history assigned were kept in the cohort (25,292 people out of a possible 25,617). For each similar exposure group inventory, the substances were identified that contributed to each of the five agents being studied. Exposure estimates before 1987 were modified using historic occupational exposure limits. Rules were created to sum the exposure from multiple substances found in any one similar exposure group. The validity of exposure estimates was tested via comparison with results documented in industrial hygiene survey reports. Industrial hygienists who were unaware of the derived exposure estimates evaluated several hundred industrial hygiene surveys and prepared benchmark information. The two lists were then evaluated for concordance, which was found to be significantly different from that occurring by chance. We conclude that the process described can create valid exposure estimates for use in epidemiology studies.