Seminário Nacional do Benzeno (5 e 6 de dez/12) - ESTUDOS EPIDEMIOLÓGICOS E EXPOSIÇÃO AO BENZENO

1. THE HEALTH WATCH STUDY
Australian petroleum industry cohort
A/Prof Deborah Glass and Prof Malcolm Sim
Monash Centre Occupational Environmental Health,
Department of Epidemiology and Preventive Medicine
www.monash.edu.au

2. Health Watch
• Set up 1980
• Prospective cohort study of mortality and
cancer incidence
• Australian petroleum industry workers
– Upstream sites
– Refineries
– Terminals
– Airports
• Funded Australian Institute of Petroleum (AIP)
– Large companies not small independents
www.monash.edu.au
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3. Health Watch Cohort
• 95% of blue collar employees interviewed
– except those at sites with <10 employees
• >5 years in industry
• Actively followed & re-interviewed every 5 years
until 2000
• Surveys inc. job histories, smoking and drinking
www.monash.edu.au
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4. Cohort is ageing
• Over 30 years
• 16,623 men and 1,375 women
• 2004: 1,473 men and 34 women died
– 289,275 person-years of observation in men
– 19,347 person-years in women
www.monash.edu.au
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5. Update to mortality and cancer incidence
• Matched to national death data
– end 2004
• Matched to Cancer Registry data
– end 2002
www.monash.edu.au
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6. Strong healthy worker effect
Overall SMR Cancer SMR Cancer SIR
Sex (95% C.I.) (95% C.I.) (95% C.I.)
Male 0.72 0.81 0.99
(0.68-0.76) (0.75-0.88) (0.94-1.04)
Female 0.65 0.88 0.89
(0.45-0.91) (0.54-1.34) (0.68-1.15)
All major causes of death are low
www.monash.edu.au
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7. Women in Health Watch
Too few women to do many analyses
• 21/34 deaths were from cancer
– SMR for cancer as expected
• 58 cancers
– SIR for cancer as expected
www.monash.edu.au
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8. Mortality among men in Health Watch
Cause SMR (95% C.I.)
Cancer (Malignant) 0.81 (0.75-0.88)
Ischaemic heart disease 0.77 (0.69-0.85)
Stroke 0.60 (0.46-0.77)
Respiratory disease 0.73 (0.59-0.89)
All diseases of the digestive system 0.57 (0.42-0.77)
External Causes (accidents, violence, suicide) 0.64 (0.53-0.77)
All other causes 0.55 (0.47-0.64)
All causes 0.72 (0.68-0.76)
www.monash.edu.au
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9. For men in Health Watch
There is no evidence of increasing cancer
incidence or increasing cancer mortality with:
• increasing duration of employment;
• increasing time since first employment;
• time period of first employment.
www.monash.edu.au
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10. Cancer among men in Health Watch
• Significantly excess:
– Mesothelioma - 1.29 (1.13 - 1.48)
– Melanoma - 1.76 (1.12 - 2.65)
• Leukaemia, prostate cancer and bladder
cancer are no longer in excess
• Kidney cancer raised but not in significant
excess in cohort or drivers
www.monash.edu.au
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11. Health Watch lymphohaematopoetic (LH)
cancers over time
3.7
3.2
non Hodgkin lymphoma (NHL)
Multiple myeloma (MM)
2.7 Leukaemia
SIR for men
2.2
1.7
1.2
0.7
0.2
1987 1990 1993 1996 1999 2002
Year of analyses
www.monash.edu.au
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12. Nested case-control questions
• Is benzene exposure associated with increases in:
– Leukaemia & sub-types?
– Non-Hodgkin lymphoma (NHL)?
– Multiple myeloma (MM)?
• Is there a latent period?
• Does exposure rate (peaks) matter?
• Are smoking and alcohol risk factors?
www.monash.edu.au
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13. Nested case-control study
Health Watch
Cohort
(~16,000 men)
79 LH Cancer 395 Controls
5:1 age matched
www.monash.edu.au
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14. Quantitative exposure assessment
• Detailed job histories from cohort records
– Interview
– Company records
• Site history
• Contemporary colleague
– Structured case-blind interview
> tasks
> products
> technology
www.monash.edu.au
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15. Exposure model
• Exposure measurements
– Company & supplementary data
→ Base Estimates for tasks (ppm)
• Exposure modifiers
– eg technology factors
• Individual exposure estimates
– work history + algorithm
→ individual exposure estimates (ppm & ppm-years)
www.monash.edu.au
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16. Base estimates
• 54 BEs, 49 used in study
• 36 based on local data
– Based on measured personal exposure to benzene
– Data from Australian petroleum industry
– Data from Australian sites
– More than 3870 data points
– Identified task/job
– Routine exposure
– Used AM of data
www.monash.edu.au
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17. Rail car loading
3
2
1
0
Expected Normal
-1
-2
-6 -4 -2 0 2 4 6
Observed Value www.monash.edu.au
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18. Laboratory worker (lubes, R&D)
3
2
1
0
Expected Normal
-1
-2
-6 -5 -4 -3 -2 -1 0 1
www.monash.edu.au
Observed Value
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19. Exposure metrics
• Duration (years)
• Intensity (average daily ppm)
– Highest or longest job
• Cumulative exposure (ppm-years)
www.monash.edu.au
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20. Drum Filling
Rail Car Loading
Vehicle Maintenance
Drum Laundry & Preparation
Fitting
Road Tanker Loading
Laboratory
Tank Farm
Operations
Wharf & Jetty
Operations
Aircraft Refuelling
Refinery Operations
Road Tanker Driving
Other Terminal
Job group and
Other Refinery exposure
Supervision
Upstream Operations
Office
Other Upstream
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
www.monash.edu.au
Average Intensity of Exposure
20 20

21. Years of employment
mean exposure period of 20 years (range 4-42)
40%
30%
Cases
20%
Controls
10%
0%
<10 10-20 20-30 30-40 >40
www.monash.edu.au
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22. Health Watch case-control study
7
1000
Leukaemia
100 98
Odds ratio (log scale)
6 8 3 6
10
NHL/MM
1.0
0.1
<1 1-2 4-8 8-16 > 16
Cumulative Lifetime Benzene Exposure midpoint (ppm-years)
www.monash.edu.au
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23. Combining two lowest exposure groups
Exposure Case OR (95% CI)
(ppm-years) s
<2 9 1.0
2-4 8 2.9 (1.0 – 8.5)
4-8 3 1.2 (0.3 – 5.0)
8 - 16 6 3.1 (0.9 – 10.6)
> 16 7 51.9 (5.6 – 477)
www.monash.edu.au
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24. Leukaemia < 15 years
1000
100
34.12
10
Odds Ratio (log scale)
1
0.05
Leukaemia Leukaemia > 15 years
latency 1000
100
10 6.18
1
0.05
0 5 10 15
www.monash.edu.au
Cumulative Exposure (ppm-years) 24
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25. Leukaemia exposure groups
100
50
Odds Ratio (log scale)
20
10
5
2
1
0.5
0 20 40 60
Cumulative Exposure (ppm-years)
Horizontal bars indicate the range of exposure in each group
www.monash.edu.au
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26. Leukaemia risk by sub-type
Exposure Odds Ratio
quintile ( 95%CI) Cases
AML 1-3 1.00 4
4 0.00 (0.00) 0
5 8.89 (0.95-82.84) 5
ANLL 1-3 1.00 4
(AML+AUL) 4 1.11 (0.18-6.96) 2
OTHER 5 8.29 (1.31-52.36) 5
2 ALL CML 1-3 1.00 5
1 hairy cell leukaemia
4 0.00 (0.00) 0
2 unspecified lymphocytic
5 0.78 (0.07-9.06) 1
CLL 1-3 1.00 4
4 2.25 (0.34-14.76) 2
5 7.15 (1.29-39.70) 5
www.monash.edu.au
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27. What is a peak?
• Highest job?
• Highest day?
• Highest hour?
• Highest 15 minutes?
www.monash.edu.au
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28. Evidence for effects of peak exposure
1000
500
With CB/BTX cases
Odds Ratio (log scale)
100 98
39
10
Without CB/BTX cases
1
0.5
0 10 20 30 40
Cumulative Exposure (ppm-years) www.monash.edu.au
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29. High exposures
• 12 subjects were exposed to concentrated
benzene or BTX
• 5 developed leukaemia, no NHL or MM
• 5/12 exposed >32 ppm-years
• 4 developed leukaemia
• No cases among office workers
www.monash.edu.au
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30. Adding possible high exposures (PHEs)
16 32 64 128
Cumulative Exposure with PHEs
added log scale (ppm/years)
8
4
2
1
1 2 4 8 16 32 64 128
Cumulative Exposure log scale (ppm/years)
www.monash.edu.au
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31. Odds ratios reduced
Benzene Number of Cumulative exposure
exposure cases and PHEs
(ppm-years) OR (95% CI)
≤2 9 1.0
>2-4 8 3.1 (1.0 - 9.3)
>4-8 3 1.2 (0.3 - 5.2)
>8-16 6 2.7 (0.7 - 10.1)
>16 7 7.8 (2.3 - 25.9)
www.monash.edu.au
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32. Summary of case-control results
• NHL MM - not associated with benzene exposure
• Leukaemia - strongly positive
– ANNL & CLL ~ positive
• Significant excess risk at >16 ppm-years
– Cum exp and intensity too close to separate
• Latency period ≈ 10-15 years
• Effect of “peaks” – some evidence
• No association with smoking or alcohol
www.monash.edu.au
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32

33. THE POOLED PETROLEUM
INDUSTRY CASE-CONTROL STUDY
www.monash.edu.au

34. Pooled study (published online JNCI 30/10/12)
• 3 case-control studies (Canadian, UK, Australian)
nested in petroleum industry cohorts
• Each updated with new cases and pooled
• more power for leukaemia subtypes
• use WHO classification of LH cancers
• Similar design, case and control identification,
exposure assessment and analytical methods
www.monash.edu.au
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35. Aims of the study
To investigate the relationship between
exposure to benzene and risk of leukaemia
– Evaluate dose-response overall
– Evaluate by WHO subtype
– Include leukaemias, MDS and MPD
– Explore influence on dose-response
relationships of study, site type, job,
lag/latency, exposure metrics
www.monash.edu.au
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36. Pooling three nested case control studies
U.K.2
Canada1 Australia3
inconsistent dose
no consistent strong dose response,
response, depending on
Refs: dose response, but
small study
subgroups and different for ANNL & CLL
exposure metrics
1. Schnatter et al. 1996
53:773-781.
based on 31 LH cancers based on 90 leukaemias based on 79 LH cancers
2. Rushton et al. 1997
54: 152-166. before pooling data  update studies
3. Glass et al. 2003
14: 569-577. 60 LH cancers 193 LH cancers 117 LH cancers
Incl. 5 MDS Incl. 11 MDS Incl. 13 MDS
370 LH cancers
www.monash.edu.au
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37. Pooled study steps
• Ethical approvals, identify new cases & controls, obtain
work histories, carry out exposure assessment
• Ensure consistency of disease classification
• Certainty of diagnosis
• Assess consistency of exposure assessments
– Development of common job groups
– Development of peak and skin exposure metrics
– Certainty of exposure
– Comparability of background exposure
– Rationalization of differences across studies
• Statistical Analyses
www.monash.edu.au
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38. Checked lymphohaematopoietic (LH)
cancer classification
Traditional Paradigm: Anatomy
• LEUKAEMIAS (in peripheral blood)
• LYMPHOMAS (in lymph system)
New Paradigm: Cell of Origin
• MYELOID tumours
– Myeloproliferative Disease (MPD)
– Myelodysplastic Syndrome (MDS)
– Acute Myeloid Leukaemias (AML)
• LYMPHOID tumours
– B-cells
– T-cells (leukaemias and lymphomas)
www.monash.edu.au
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39. Quantitative exposure assessment
• Individual job histories
• Site histories
• Exposure of new cases and controls
assessed by original study method
• Exposure intensity (ppm) for each job
• Confidence score for each estimate
– L, M, H
www.monash.edu.au
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40. Pooled study exposure assessment
• Team of study hygienists and external hygienist
• Peak exposure metric
– Prob. >3ppm for 15-60 mins at least weekly
• Skin exposure metric
– 0, L, M, H prob of at least weekly skin exposure
• Prepared common list of job categories
– Allocated each job for each individual
www.monash.edu.au
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41. Exposure assessment rationalisation
• Compared job estimates between studies
• Estimates in each job category by era
– pre 1945, 1945-1960, 1960s & 1970s and 1980+
– AM, GM, n, max & min
• If mean were same (within 10%)- no change
• If different
– Checked job/technology/products/conditions
– If no apparent local explanation, adjust
• Some job cats. had no other study comparison
– Different industry sector or period
www.monash.edu.au
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42. Study exposure estimates
Little change from original estimates
Little difference between original and revised
www.monash.edu.au
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43. Statistical analyses
• Risk as ORs by exposure :
– cumulative benzene (ppm-years)
> ppm-years within relevant window (lag/latency)
– average & maximum intensity (ppm)
– peaks & skin
• Job category, industry sector
• Sensitivity analyses: study, job confidence,
exposure confidence
www.monash.edu.au
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44. www.monash.edu.au
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45. MDS, cumulative benzene exposure and
certainty of diagnosis
100
10 11.6
Odds Ratios
4.33
3.47
1.73
1
All Subjects More Certain Diagnoses
0.1
>0.348 and >2.93 >0.348 and >2.93
<2.93 Cumulative Exposure (ppm-years) <2.93 www.monash.edu.au
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46. Pooled analysis MDS cases and controls
Current
exposure
zone
Suggests MDS cases over-represented at approx 1+ ppm
www.monash.edu.au
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47. CONCAWE study findings
• MDS associated with low benzene exposure
• MDS may be a more sensitive outcome than AML
• AML: several ORs were >1, few statistically sig.
• perhaps higher benzene exp. for sig. risks of AML
• some cases formerly classified as AML were MDS
• CML: several ORs >1, but no clear exposure
response pattern
• CLL and MPD: no strong relationship
www.monash.edu.au
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48. Putting the evidence together
• Epidemiology assesses risk for the group
Can it be applied to other groups?
• Risk estimates from single studies wobbly
• Pooled data or meta-analyses needed for
conclusions about causation
www.monash.edu.au
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49. Population risk vs individual risk
• Attribution at a population level
– Benzene exposure increases the incidence of
leukaemia
• Attribution for an individual
– Benzene exposure caused leukaemia in this person
www.monash.edu.au
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50. Acknowledgements
• Australian Institute of Petroleum
• Institute of Petroleum (UK)
• American Petroleum Institute
• Conservation for Clean Air and Water
Europe (CONCAWE)
• Aromatic Producers Association
• Energy Institute
• Canadian Petroleum Products Institute
www.monash.edu.au
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