MICHAEL ALAVANJA, DR.P.H.DIVISION OF CANCER EPIDEMIOLOGY & GENETICS,

NATIONAL CANCER INSTITUTE

2010 MIDWEST RURAL AGRICULTURAL SAFETY & HEALTH FORUM: CULTIVATING CHANGE

NOVEMBER 17-18, 2010 HOTEL VERO/SHERATON, IOWA CITY, IA

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dyAn Excess Risk of Multiple Myeloma (MM)

and a Premalignant MM Disorder in the Agricultural Health Study Cohort Provides

Preliminary Evidence of a Link to Pesticides

Collaborating Federal Agencies

National Cancer Institute

National Institute of Environmental Health Science

U.S. Environmental Protection Agency

National Institute for Occupational Safety and Health

Agenda

1) Why study Multiple Myeloma and why talk about it here?

2) Background: Purpose & Scope of the AHS.

3) Background: Epidemiologic Design of the AHS.

4) Background: Exposure Assessment in the AHS.

5) Multiple Myeloma and Farming

6) Monoclonal Gammopathy of Undetermined Significance (MGUS)

7) MGUS in the AHS

8) Biomarkers of Exposure & Effects of Agriculture (BEEA) Study

Why study Multiple Myeloma and why talk about it here?

Multiple Myeloma is a malignancy of the plasma cell.

The cause (etiology) of multiple myeloma is uncertain but farmers and farming have been associated with this malignancy in many studies conducted in North America, Europe and New Zealand.

Five year survival is only 28% (i.e., 72% die within 5 years).

Background, Purpose & Scope of the AHS

Background

World-wide occupational exposure to pesticides exceeds 1 billion.

Previous health studies characterized as having inadequate exposure assessment.

Exposure misclassification can result from inadequate exposure assessment.

Exposure misclassification reduces our ability to identify agents responsible for disease (Zahm et al., 1997, Kromhout and Heedrick 2005).

Case-control studies.

Exposure information collected after disease onset-case-recall bias possible.

Background

The International Agency for Research on Cancer (IARC) classifies only 1 pesticide (arsenical insecticides) and one pesticide contaminant (dioxin) as human carcinogens. [1991, IARC monograph volume 53].

Over 800 active ingredients in thousands of pesticide formulations are on the market world-wide.

Some of these widely used pesticides are suspected to be human carcinogens, but a final determination has not been made because of limited evidence.

Purpose of the Agricultural Health Study (AHS) (www.aghealth.org)

o To study a wide range of health effects of agricultural exposures in farmers and their families and commercial pesticide applicators.

o Generate research generalizable to a much wider population world-wide.

Scope of the Agricultural Health Study (AHS) (www.aghealth.org)

o Major Exposures under study:

o Pesticides

o Animals

o Engine exhaust

o Solvents

o Organic and inorganic dust

o Health Effects under study:

o Cancer

o Respiratory Health

o Reproductive Health

o Neurologic Disease

o Work Place Injuries

Family Exposure Opportunities

Epidemiology Research: potential contributions of the AHS

o Characteristics:o No extrapolation of results from lab animal to human.

o No extrapolation from high exposures in animal testing to lower exposure in the human experience.

o Results generalizable for the chemical evaluated in adults (within the range of exposures of the study).

o Comprehensive exposure assessment to minimize misclassification—accurately rank order exposures.

o Prospective study to minimize information bias.

o Control for confounders to obtain valid risk estimates.

o Generate biological results to assess biological plausibility and modes of action and identify susceptible sub-populations.

Cancer Epidemiology Design

AHS Design Prospective design (exposure assessed prior to

cancer onset) 52,000 private applicators (i.e., farmers and nursery

operators)

32,000 spouses of farmers

>4,000 commercial applicators (i.e., pesticide application for hire)

Two important agricultural states (Iowa & North Carolina)

Corn , soybean and hog production in both states

Distinctive agriculture in North Carolina: fruits, vegetables, tobacco, cotton

AHS Design

Target population--licensed pesticide applicators (private & commercial applicators) :

Knowledgeable about their chemical use,

Regularly exposed but not exposed every day,

Farmers tend not to move residence (easier to follow-up).

AHS Design Comprehensive exposure assessment

Initial questionnaires –self administered (1993-1997)

Enrollment questionnaire administered at pesticide licensing examination/class—82% participation of target population.

Repeated questionnaires- Telephone interviews (1999-2003 & 2005-2010)-updated exposure & other information

Field measurements of pesticides (sample of study subjects)

EPA [n=69 2,4-D & n=17 chlorpyrifos on field crops]

NIOSH [n=74 captan users in orchards].

AHS Design Questionnaire content

Lifetime pesticide use for >50 pesticides (days/year; years)

Exposure determinants(e.g., pesticide application methods, equipment repair, mixed and/or applied, PPE)

Other Farm activities and non-farm occupational exposures

Lifestyle factors (e.g., smoking, diet, alcohol consumption)

Medical history

Family cancer history

AHS Design

Little loss to cancer incidence follow-up (<2 per cent)

Population-based cancer registries in both states

Monitor date study subjects move from state

National Death Index (NDI)

Over one-million person-years of follow-up in the AHS

Buccal cells collected as a source of DNA 35,000 study subjects, 1999 through present

Control of Confounding Factors in the AHS cohort (A variable will only confound if it is correlated with exposure and effect)

Concurrent pesticide exposures (e.g., information about >50 other pesticides and total pesticide use)

Pesticide exposures and other occupational exposures (e.g., Non-farming occupational history, farm exposures other than pesticide use).

Life-style (e.g., tobacco use, alcohol, diet, physical activity)

AHS Research Strategy for Cancer Studies

BiologicalInitial Reevaluation Evidence inFindings later in time Humans

Iowa

NorthCarolina

LicenseType

Exposure-Response

Exposure- Response

Exposure- Response

Exposure-Response

Exposure- Response

Exposure- Response

YES

YES

YES

Exposure Assessment in the AHS

Exposure Assessment in the AHS Duration of use (yrs of use of >50 pesticides).

Frequency of use (days per year of use >50 pesticides) .

Intensity weighting factors Application method Mix Repair pesticide application equipment Personal protective equipment

Reliability (repeatability) and Duration Validity.

Comparison of questionnaire data to field measurements of pesticides

Exposure Metric in AHS

Cumulative Exposure = Duration X Intensity

Questionnaire Exposure Assessment

Farmers in the AHS provide reproducible reports of pesticide use information (Blair et al, 2002)

Specific chemicals and application methods Agreement 80-95% for ever vs. never use

questionnaire data collected1 year apart

Accurate information on duration of use (Hoppin et al., 2002)

Compared to pesticide registration data Most applicators provided complete information on

lifetime use of pesticides

Questionnaire Exposure Assessment

Reliability of Pesticide Reporting in AHS Questionnaires (n=2,921 Iowa farmers one year apart).

Factor(ever used)

% Exact Agreement Kappa

atrazine 86 0.62

glyphosate 82 0.52

2,4-D 87 0.71

terbufos 83 0.66

fonofos 84 0.63

chlorpyrifos 81 0.61

permethrin 88 0.59

From: Blair et al., Epidemiology; 13; 94-99

Exposure Assessment AlgorithmDosemeci M, et al. (2002) Ann Occup Hyg. Vol 46 (2), 245-260.

Intensity level=(Mix + Application Method + Repair)* PPE

Information from questionnaires administered to all applicators.

Information from monitoring studies from the published literature and the Pesticide Handlers Exposure Data Base (PHED –EPA data base).

Assessment of algorithm made with field measurements of pesticides.

Assessment of algorithm made by comparing results to Canadian exposure assessment study.

Comparison of AHS algorithm exposure score with urine concentration of 2,4-D in sample from AHS cohort.

GM

ug/L

Algorithm Exposure Score (mean score: 5.5, 9.4, 15.2 )

(n=69, 2,4-D applicators in the Agricultural Health Study )Thomas K. et al. (2009) J of Exposure Science and Environmental Epidemiology 1-11.

0

10

20

30

40

50

60

Category 1 Category 2 Category 3

Comparison of AHS algorithm exposure score with urine concentration of 2,4-D in sample from Canadian study.

GM

(Ug/L

in urine)

Algorithm Exposure Score (1-<5, 5-10, >10-15)

(n=39, 2,4-D applicators Pesticide Exposure Assessment Study)

Coble J. et al. (2005) J of Occupational and Environmental Hygiene. 2: 194-201.

0

5

10

15

20

25

30

35

Category 1 Category 2 Category 3

Comparison of AHS algorithm exposure score with urine concentration of MCPA in sample from Canadian study.

GM

ug/L

in urine

Algorithm Exposure Score (1-<5, 5-10, >10-15)

(n=42, MCPA applicators Pesticide Exposure Assessment Study)Coble J. et al. (2005) J of Occupational and Environmental Hygiene.2: 194-201.

0

5

10

15

20

25

Category 1 Category 2 Category 3

Exposure Assessment Summary

AHS exposure algorithm scores consistent with pesticide exposure measurements (Thomas et al & Coble et al)

Algorithm for the AHS were more closely related to measured urinary levels than any individual exposure determinant (e.g., acres, lbs active ingredient), consequently the algorithm should reduce misclassification (Blair A et al and Thomas et al.).

Continued refinement of algorithm weights will be necessary as more exposure data is collected (Hines et al. & Thomas et al.)

__________________________________ Thomas K. et al. (2009) J of Exposure Science and Environmental Epidemiology e-pub . Coble J. et al, (2005) J Occup and Environ Hyg 2: 194-201. Blair A et al., submitted Hines CJ. et al., (2008) Ann Occup Hyg 52(3):153-166.

Summary: Modified Bradford Hill Criteriain the Mode of Action Framework

Dose-response (exposure-response) Total life-times days of exposure to specific pesticide Intensity-weighted lifetime days. Verify exposures (i.e., compare questionnaire to field measures

of pesticides) Temporal concordance

Prospective exposure assessment Biological plausibility

Biomarker studies of exposure and effect (toxicity pathways) Genetic susceptibility (GXE)

Coherence and consistency Iowa vs. North Carolina Private vs. Commercial

Multiple Myeloma, MGUS and Pesticides in the Agricultural Health

Study Cohort

Ola Landgren1,2, Robert Kyle3,, Jane A. Hoppin4, Laura E. Beane Freeman1, Gabriella Andreottti1, Jon Hofmann1, Neil

Caporaso1, Sharon Savage1 , James R. Cerhan3, Jerry A. Katzmann3, S. Vincent Rajkumar3, Michael C. Alavanja1

1Division of Cancer Epidemiology and Genetics, NCI, Bethesda, MD; 2Medical Oncology Branch, NCI, Bethesda, MD;

3College of Medicine, Mayo Clinic , Rochester, MN; 4Epidemiology Branch, NIEHS, NIH, Research Triangle Park, NC.

Epidemiology 101

Relative risk= incidence of disease in the exposed population/ incidence

of disease in the unexposed population. [null RR=1]

Odds ratio is a good approximation for rare diseases

Multiple Myeloma: Background

• Multiple Myeloma is a malignancy of plasma cells (differentiated B cells).

• Characterized by the presents of elevated number of plasma cells in the bone marrow.

• Very often, also characterized by monoclonal proteins in serum and urine (IgA, IgD, IgE, IgG or light chains).

• Five year survival is only 28%.

Multiple Myeloma: Background

• The cause (etiology) of multiple myeloma is uncertain but farmers and farming have been associated with this malignancy in many studies conducted in North America, Europe and New Zealand.

• Other associations: age, obesity, personal use of permanent hair dyes (>20 years), certain medications, autoimmune disorders, male gender, African-American greater than European-Americans greater than Asians-Americans, some other factors suspected.

Multiple Myeloma: Background

MGUS ----> Multiple Myeloma (MM)

MGUS=Monoclonal gammopathy of undetermined significance

MM always preceded by a premalignant disorder MGUS (Landgren O, et al., Blood 2009;113:5412-5417)

Multiple Myeloma: Background

• Over 1 billion people are occupationally exposed to pesticides world-wide.

• SIR of multiple myeloma in Agricultural Health Study (AHS) = 1.34 (0.97-1.98).

Causal Logic to Establish Human Carcinogenicity

HumanCarcinogen

Epidemiology

Biological Plausibility

Exposure Assessment

Methods

• The prevalence of MGUS in a sample (n=555) of men > 50 years from the AHS cohort was compared to the prevalence of MGUS in a population-based sample (n=9,469) of men from Olmsted County, MN > 50 years.

Table 1. MGUS prevalence (%) among 678 men in the Agricultural Health Study and 9,469 men in Olmsted, MN

Age Agricultural Health Study

Olmsted County, MN

MGUS, n/Total , n

Prevalence (95% CI)

MGUS, n /Total, n

Prevalence (95% CI)

<50 0/123

0 0/0

NA

50-59 5/214

2.3 (1.0-5.4) 82/4038

2.0 (1.6-2.5)

60-69 10/182

5.5 (3.0-9.9) 105/2864

3.7 (3.0-4.4)

70-79 18/129

14.0 (9.0-21.1) 104/1858

5.6 (4.6-6.7)

>80 5/30

16.7(7.1=34.3) 59/709

8.3 (6.5-10.6)

Total > 50 years 38/555

6.8 (5.0-9.3) 350/9468

3.7 (3.3-4.1)

Logistic regression adjusted for age yields an odds ratio=1.9 (95% CI, 1.3-2.7)-------------p for trend<0.001

Table 2. Specific pesticide use at enrollment and the risk of

MGUS

Pesticide Exposed Total, n MGUS, n Odds ratio (95% CI)

Dieldrin Never 649 31 1.0 (reference)

Ever 20 6 5.6 (1.9-16.6)

2,4-D Never 139 5 1.0 (reference)

Ever 537 33 1.8 (0.7-3.1)

Carbon-tetra- chloride/carbon-disulfide mix

Never 632 31 1.0 (reference)

Ever 41 7 3.9 (1.5-10.0)

Chlorothalonil Never 561 28 1.0 (reference)

Ever 115 10 2.4 (1.1-5.3)

Diazinon Never 435 19 1.0 (reference)

Ever 242 19 1.8 (0.9-3.6)

Summary: Observation from AHS(follow-up evaluations scheduled)

1) Multiple Myeloma in excess in AHS SIR=1.34 (0.97-1.81) (Alavanja MCR, et al. Scand J Work Environ Health 2005:31 suppl 1:39-45).

2) Monoclonal gammopathy of undetermined significance (MGUS) – 2-fold significant excess in AHS (Landgren O. et al., Blood (2009), 113(25);6386-6391).

3) Several widely used pesticides are associated with elevated MGUS levels (Landgren O. et al., Blood (2009), 113(25);6386-6391).

4) Odds ration for multiple myeloma = 5.7 (2.1-7.2) for heaviest users of permethrin (Rusiecki J, et al., Environ. Health Perspectives (2009), 117;581-586).

SIGNIFICANCE

• Several million Americans use pesticides for which we found an association with MGUS in the AHS.

• Causes of MGUS risk might be an underlying explanation of the previously observed excess of multiple myeloma risk among persons exposed to pesticides, including those in the AHS.

STRENGTHS

• Comprehensive pesticide exposure assessment for AHS cohort.

• Minimal misclassification of MGUS since both the AHS cohort and Olmsted County samples analyzed by the Mayo Clinic Laboratory.

• Any minimal misclassification of pesticide use would be non-differential

LIMITATIONS

• Unable to evaluate certain pesticides due to limited number of exposed cases.

• Results generalizable mostly to white males.

Future Research

• To further explore the associations between pesticides and MGUS and multiple myeloma, a follow-up study of 1,600 AHS study subjects was initiated in June 2010 (approx. 3X size of the previous study).

• Will examine additional pesticides with additional exposure assessment from 1998-2009.

• Will examine other biomarkers of relevance to pesticide exposure and/or multiple myeloma

Bibliography

>110 peer reviewed manuscripts have been published from the Agricultural Health Study they are listed at: papers have been published from the Agricultural Health Study , the complete current bibliography can be found at

>http://aghealth.nci.nih.gov/publications.html.

Under the major topic headings:1. 1. Methods2. 2. Exposure Assessment3. 3. Health Outcomes4. 4. Diet5. 5. Injury

Under the major topic headings

Intramural Research Team

National Cancer Institute: Michael Alavanja Laura Beane Freeman Jay Lubin Stella Koutros Gabriella Andreotti Jonathan Hofmann Neil Caporaso Ola Lundgren Sharon Savage Rashmi Sinha Aaron Blair Shelia Zahm Kathryn Hughes

NIOSH Cynthia Hines Brian Curwin Paul Henneberger Greg Kullman

NIEHS

• Jane Hoppin Dale Sandler Freya Kamel Donna Baird Olga Basso Stephanie London Beth Regan David Umbach Clarice Weinberg Martha Montgomery Sharon Myers Tina Saldana Martin Valcin Jenna Waggoner

USEPA Kent Thomas Carol Christensen

Thank you for the invitation!

Please support our research effort , we are making tremendous progress.

Thank you for your excellent work in promoting the health of farmers and their families.

Appendix

Illustrative Algorithm Score (weight) for Exposure Determinants

Dosemeci M, et al. (2002) Ann Occup Hyg. Vol 46 (2), 245-260.

Factor Score

Mix No=0 Yes=9

Apply Banded=2 Broadcast spray=3

Hand spray=9

Repair No=0 Yes=2

PPE See next table

Algorithm score factor for PPE

Dosemeci M, et al. (2002) Ann Occup Hyg. Vol 46 (2), 245-260.

PPE Categories Overall PPE

ScorePPE-3 PPE-2 PPE-1 PPE-0

Yes Yes Yes No 0.1

Yes Yes No No 0.3

Yes No Yes No 0.4

No Yes Yes No 0.5

Yes No No No 0.6

No Yes No No 0.7

No No Yes No 0.8

No No No Yes 1.0

PPE-3=chem. resistant gloves; PPE-2=cartridge respirator or gas mask, disposable outer clothing; PPE-1=face shields or goggles, fabric/leather gloves, other PPE such as boots; PPE-0=no PPE

Exposure Assessment Algorithm

Intensity Score= (Mix + Application Method + Repair) * PPE

1. Mixed (yes) = 9

2. Application method (Hand spray)= 9

3. Repair (yes) = 2

4. PPE (chem. resistant gloves & boots) = 0.4

Intensity Score=(9+8+2)* 0.4 = 7.6

Dosemeci M, et al. (2002) Ann Occup Hyg. Vol 46 (2), 245-260.

Exposure Metric in AHS

Cumulative Exposure = Duration (days) X Intensity

(mgs*/day)

AHS Design Comprehensive exposure assessment

Initial questionnaires –self administered (1993-1997) Enrollment questionnaire administered at pesticide licensing

examination/class—82% participation of target population.

Take-home questionnaire (applicators), Spouse enrollment questionnaire

Repeated questionnaires- Telephone interviews (1999-2003 & 2005-2010)-updated exposure & other information

Field measurements of pesticides (sample of study subjects)

EPA [n=69 2,4-D & n=17 chlorpyrifos on field crops]

NIOSH [n=74 captan users in orchards].

Exposure Metrics In the AHS

1. Life time Exposure Days (specific pesticide) = Yrs Application (specific pesticide) * Days of application/Yr (specific pesticide)

2. Intensity Weighted Lifetime Exposure Days (specific pesticide) = Life time Exposure Days (to specific pesticide) * Intensity of exposure

3. Life time Exposure Days (all pesticides) = Yrs Application * Days of application/Yr

4. High Pesticide Exposure Events = acute events involving unusually high exposures because of spills, immersions, etc.