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Background Cyanazine is a common pesticide used frequently in the United States during the 1980s and 1990s. Animal and human studies have suggested that triazines may be carcinogenic, but results have been mixed. We evaluated cancer incidence in cyanazine-exposed pesticide applicators among the 57,311 licensed pesticide applicators in the Agricultural Health Study (AHS). Methods We obtained detailed pesticide exposure information from a self-administered questionnaire completed at enrollment (1993–1997). Cancer incidence was followed through January 2002. Over half of cyanazine-exposed applicators had ≥ 6 years of exposure at enrollment, and approximately 85% had begun using cyanazine before the 1990s. We used adjusted Poisson regression to calculate rate ratios (RRs) and 95% confidence intervals (CIs) of multiple cancer sites among cyanazine-exposed applicators. We calculated ptrend values, and all statistical tests were two-sided. Two exposure metrics were used: tertiles of lifetime days of exposure (LD) and intensity-weighted LD. Results A total of 20,824 cancer-free AHS applicators reported ever using cyanazine at enrollment. Cancer incidence comparisons between applicators with the lowest cyanazine exposure and those with the highest exposure yielded the following for the LD metric: all cancers, RR = 0.99 (95% CI, 0.80–1.24); prostate cancer, RR = 1.23 (95% CI, 0.87–1.70); all lymphohematopoietic cancers, RR = 0.92 (95% CI, 0.50–1.72); non-Hodgkin lymphoma, RR = 1.25 (95% CI, 0.47–3.35); lung cancer, RR = 0.52 (95% CI, 0.22–1.25). Conclusions We did not find any clear, consistent associations between cyanazine exposure and any cancer analyzed. The number of sites was small for certain cancers, limiting any conclusion with regard to ovarian, breast, and some other cancers.

Glyphosate is a broad-spectrum herbicide that is one of the most frequently applied pesticides in the world. Although there has been little consistent evidence of genotoxicity or carcinogenicity from in vitro and animal studies, a few epidemiologic reports have indicated potential health effects of glyphosate. We evaluated associations between glyphosate exposure and cancer incidence in the Agricultural Health Study (AHS), a prospective cohort study of 57,311 licensed pesticide applicators in Iowa and North Carolina. Detailed information on pesticide use and other factors was obtained from a self-administered questionnaire completed at time of enrollment (1993-1997). Among private and commercial applicators, 75.5% reported having ever used glyphosate, of which97% were men. In this analysis, glyphosate exposure was defined as a) ever personally mixed or applied products containing glyphosate; b) cumulative lifetime days of use, or "cumulative exposure days" (years of use times days/year); and c) intensity-weighted cumulative exposure days (years of use times days/year times estimated intensity level). Poisson regression was used to estimate exposure-response relations between glyphosate and incidence of all cancers combined and 12 relatively common cancer subtypes. Glyphosate exposure was not associated with cancer incidence overall or with most of the cancer subtypes we studied. There was a suggested association with multiple myeloma incidence that should be followed up as more cases occur in the AHS. Given the widespread use of glyphosate, future analyses of the AHS will allow further examination of long-term health effects, including less common cancers.

A large cohort of 74,828 benzene-exposed and 35,805 nonexposed workers employed between 1972 and 1987 in 12 cities in China was followed to determine mortality from all causes. Benzene-exposed study subjects were employed in a variety of occupations including coating applications, and rubber, chemical, and shoe production. Mortality was slightly increased among workers with greater cumulative exposure to benzene (ptrend < 0.05), but this excess was largely due to cancer deaths (ptrend < 0.01). Deaths due to lymphatic and hematopoietic malignancies (ptrend = 0.01) and lung cancer (ptrend = 0.01) increased with increasing cumulative exposure to benzene. Investigations continue to relate benzene exposure to specific lymphatic and hematopoietic malignancies and other causes of death.

An expanded cohort study of 74,828 benzene-exposed and 35,805 unexposed workers were followed during 1972 to 1987, based on a previous study in 12 cities in China. A small increase was observed in total cancer mortality among benzene-exposed compared with unexposed workers (relative risk [RR] = 1.2). Statistically significant excesses were noted for leukemia (RR = 2.3), malignant lymphoma (RR = 4.5), and lung cancer (RR = 1.4). When risks were evaluated by leukemia subtype, only acute myelogenous leukemia was significantly elevated (RR = 3.1), although nonsignificant excesses were also noted for chronic myelogenous leukemia (RR = 2.6) and acute lymphocytic leukemia (RR = 2.3). A significant excess was also found for aplastic anemia.

The reaction of Farmer et al. regarding our article on glyphosate exposure and cancer incidence in the Agricultural Health Study (AHS) (De Roos et al. 2005) is difficult to understand given the tentative nature of our conclusions. For the most part, we found no associations with the cancers we studied, and to quote from our abstract, Glyphosate exposure was not associated with cancer incidence overall or with most of the cancer subtypes we studied. There was a suggested association with multiple myeloma incidence that should be followed up as more cases occur in the AHS. Despite the fact that we believe our presentation of the data was quite fair and included a lengthy discussion of possible biases affecting our results, several comments by Farmer et al. necessitate a response. Farmer et al. had several criticisms of our review of the genotoxicity literature (De Roos et al. 2005). Although the discussion of the toxicity studies is interesting, these studies only serve as background information in our article; the epidemiologic associations between glyphosate exposure and cancer incidence we observed are the empirical result of our investigation. Criticisms of our reference to the genotoxicity literature do not, of course, alter the human data we presented. We stated in our article the conclusion of the U.S. Environmental Protection Agency (U.S. EPA 1993) and the World Health Organization (1994) that glyphosate is not mutagenic, but because that conclusion focused on the active ingredient, glyphosate, and not formulated products such as Roundup (Monsanto Company, St. Louis, MO), we also cited several studies which show potentially greater toxic effects of Roundup than glyphosate. Our article (De Roos et al. 2005) does not purport to be a comprehensive review of the toxicology literature, and because of space limitations imposed by the journal, we did not discuss several studies showing potentially toxic effects of several glyphosate-based pesticide products through disruption of cell-cycle control mechanisms, which may be relevant for cancer as well as noncancer health outcomes (Marc et al. 2002, 2004). The fact the some of the studies we cited did not use Good Laboratory Practices is irrelevant, because this system is used primarily in analytical chemistry and contract laboratories for routine support of pesticide regulation, and is not required by any of the principal funding agencies for research studies. Studies that are submitted to the U.S. EPA to support applications for licensing pesticides are required to meet specified guidelines for record keeping, data reporting, and protocol development. These Good Laboratory Practices provide some assurance that regulators can rely on the data they review and give them the ability to perform audits as needed. Investigators who perform studies for research purposes are not required to follow these structured practices, but many may do so. Furthermore, it does not follow that work done in labs that do not strictly adhere to the U.S. EPA’s testing and reporting requirements follow “bad” laboratory practices. Quality assurance for research studies is provided by the peer-review process and by replication. This is analogous to the distinction between clinical laboratory tests performed in the context of human research and tests performed for diagnostic purposes. In order for these tests to be covered by insurers, they must be performed in laboratories approved by the Clinical Laboratory Improvement Amendments (CLIA 2005). CLIA approval assures that the test results are valid but does not address the underlying science that led to the development of the test. In their letter, Farmer et al. used exposure information from a study by Acquavella et al. (2004) in which biomonitoring of farmers who applied glyphosate was used to determine a maximum dose calculation. The dose thresholds Farmer et al. cite as relevant for carcinogenicity are from mouse and rat models in which the active ingredient, glyphosate, was tested in feeding studies (Williams et al. 2000). Lower relevant doses may apply for Roundup and other formulated products containing glyphosate, or for glyphosate products used in combination with other active ingredients. In addition, epidemiology can provide direct information on the question of what happens in humans from more relevant routes of exposure. Some questions were raised about the possible associations we observed between glyphosate and multiple myeloma concerning the discrepancy between the age-adjusted relative risk of 1.1 [95% confidence interval (CI), 0.5–2.4] and the relative risk adjusted for selected demographic and lifestyle variables of 2.6 (95% CI, 0.7–9.4) (De Roos et al. 2005). Farmer et al. question whether the discrepancy may be due to confounding or the selection of subjects into the more restricted analysis. This is plausible, and we discussed these issues at length in our article. The association only appeared within the subgroup with complete data on all the covariates; even without any adjustment, there was a 2-fold increased risk of multiple myeloma associated with glyphosate use among the smaller subgroup with covariate data. We acknowledged that this could be due to selection bias, effect modification, or confounding within this subgroup. We would point out, however, that confounding can be both positive and negative. The type of analysis suggested by Farmer et al., in which the data are stratified by each covariate individually in order to identify covariates for which missing data and/or adjustment made the biggest impact on the estimated relative risk, would be unreliable for such a small number of cases. Each estimate would be subject to small sample bias (Greenland 2000), which was cited by Farmer et al. as an issue with our overall estimate for myeloma. The most reliable approach will be to reanalyze the data after more cases accumulate, both to assess whether the association with myeloma persists and to further evaluate confounding and selection bias using a larger case group to support analyses. Following up initial observations with more comprehensive epidemiologic data from the AHS has been our plan since the inception of the study.