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Do pesticides cause cancer ?

Michael Alavanja, Dr.P.H. Captain, USPHS Senior Investigator, Division of Cancer Epidemiology and Genetics, NCI 2007 North American Pesticide Applicator Certification & Safety Education Workshop August 20-23, 2007 Portland, Maine.

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Do pesticides cause cancer ?

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  1. Michael Alavanja, Dr.P.H.Captain, USPHSSenior Investigator, Division of Cancer Epidemiology and Genetics, NCI2007 North American Pesticide ApplicatorCertification &Safety Education WorkshopAugust 20-23, 2007Portland, Maine

  2. Agricultural Health Study on Cancer Findings. Session I: General StrategyTuesday, August 21Breakout Session #1

  3. Do pesticides cause cancer ? • Few strong and consistent associations linking a single chemical to a single cancer. • Animal/laboratory studies show most pesticides in current use to be non-genotoxic. • Exposure assessment in previous epidemiologic studies was general weak, they were based on interviews and could suffer from case recall bias. • Studies of pesticide manufactures are generally too small to give meaningful results for cancer • Exposures among the general population in developed countries are relative low and effect hard to measure. • In summary: Neither animal studies nor human studies give a compelling case for an association.

  4. Background World-wide occupational exposures to pesticides exceed 1.8 billion people (World Bank estimate). • Everyone in the USA has some indirect exposure to pesticides (NHANES). • Agricultural Insecticides as a group labeled as probable (group 2A) human carcinogens by IARC. • Only arsenic and dioxin are listed as human carcinogens by IARC. • Vital public health need to identify human carcinogens on the market!

  5. Background • The Occupational & Environmental Epidemiology Branch, NCI has a history of ecological and case-control of farmers starting in the 1970’s. • A common critique- exposure assessment was weak. • I proposed the idea for a prospective cohort study of pesticide applicators in 1989- 1990. • In 1991 an extramural advisory group recommended the OES conduct the AHS. • The Agricultural Heath Study entered the field in December 12, 1993. • Other federal partners joined the team in 1994 (EPA), 1995 (NIEHS) and NIOSH (1997).

  6. Design AHS(www.aghealth.org) • Prospective cohort study of 89,658 pesticide applicators & spouses (IA and NC). • 82% of target population enrolled 1993-1997. • Little loss to follow-up (<2%). • Cancer incidence and mortality updated annually. • Comprehensive exposure assessment information on 82 pesticides collected at three points in time. • Questionnaire exposure assessment evaluated with field measurements of pesticides. • Buccal cells collected on >35,000 study subjects.

  7. Disease Etiology In the AHS Central Research Objectives: 1. Characterize exposures to the highest degree ever achieved in large cohort study. 2. Identify pesticides and other agricultural exposures that increase the risk of cancer . 3. Identify the mode of action of agents causing disease.

  8. Types of Pesticide Exposure • Acute exposure events. High exposure dose, short time period (minutes or hours). • Chronic exposure. Low exposure dose, long time period (hundreds or thousands of days in a lifetime).

  9. Agricultural Health StudyPesticide Exposure Estimates Calculating Cumulative Exposure Index: Cumulative Exposure = Intensity * Duration Where: Intensity = Exposure scores obtained from algorithms Duration = Days/years * Years/life-time = days/life-time From: Dosemeci et al. Ann Occup Hyg 46:245-260, 2002.

  10. Questionnaire Evaluation: Monitoring Visits

  11. Questionnaire Evaluated with Field Measurements of 2,4-D and Other Pesticides Technician observations MLA Questionnaire } Day 1 Day 2 Day 3&4 • Mix Load Apply (MLA). • Hand wipes after MLA • Dermal patches • Air measurements Collect full first morning void 3. Collect each void from MLA through next morning void. Collect full first morning void

  12. Comparison of Questionnaire Based Intensity Scores and Field Measurements 2,4-D(Thomas et al., in review)

  13. Conclusions: From Exposure Algorithm Assessment • For 2,4-D applicators we observed a significant correlation between the questionnaire-based algorithm (intensity-factor) and post-application urine concentrations. • Important additional determinants of exposure have been identified to refine the exposure algorithm.

  14. Evaluating the association between estimated exposures with health effects. (Cancer Etiology Studies in the AHS)

  15. Effect • End point of a causal mechanism. • Amount of change in a population’s disease frequency caused by a specific factor. • Incident rate: Number of new cases of disease in a specified period of time. • Absolute effect: I1 – I0 • Relative Effect: I1 / I0

  16. Confounding factors • A confounding factor must be a risk factor for the disease. • A confounding factor must be associated with the exposure under study in the source population (the population from which the cases are derived). • A confounding factor must not be effected by the exposure or the disease. In particular, it cannot be an intermediate step in the causal path between the exposure and the disease. • How do we control confounding? Collect quantitative information on the exposure to the confounder and add the term to the multivariate model: y=b0 + b1x1 + b2 x2

  17. Statistical Interaction-Effect Modification • An effect-modifier is an exposure or host factor that modulates the extent of the effect of the study variable on the disease under investigation. • If a cohort is divided into two or more distinct categories defined by the level of an effect modifier the stratum-specific effect measures may or may not be equal. If they are equal there is no effect modification. If they are significantly different there is effect modification. • How do measure effect modification? Collect quantitative information on the exposure thought to be an effect modifier and add the product term to the multivariate model: y=b0 + b1x1 + b2 x2 + b 3 x1 x2

  18. Typical Sequence of Cancer Etiology Studies in AHS [2003-2007] • SIR analysis (generates general hypothesis) [n=1] • Nested case-control study of specific cancers (generate specific hypotheses [n=6]) • 1 ST COHORT ANALYSIS of specific pesticide (generates or refines specific hypotheses [n=21]) • 2ND COHORT ANALYSIS: (Test Specific Hypotheses [n=1 in progress]) • Molecular epidemiology studies of cancer (Evaluates biological plausibility and mode of action [n=3 in progress])

  19. AHS Research Strategy:Mitigate False Positive Results Biological Initial Replication Evidence in Findings later in time Humans Iowa North Carolina License Type Exposure- Response Exposure- Response Exposure- Response Exposure- Response Exposure- Response Exposure- Response YES YES YES

  20. Mitigate False-Positive Associations and Study Rare Diseases Agricultural Health Cohort Consortium. (NCI organized)

  21. Regulatory Implications of AHS Findings • International Agency for Research on Cancer. • International recommendations • United States Environmental Protection Agency • Educating pesticide applicators • Label instructions • Limitations of use • Banning use

  22. Thank you for listening: AHS Research Team

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