The lifetime risk of occupational lung cancer in Australia

The lifetime risk of occupational lung cancer
in Australia
Renee N Carey1 and the AWES-Cancer team1-4
1.
2.
3.
4.
School of Public Health, Curtin University
School of Public Health, University of Sydney
Department of Epidemiology and Preventive Medicine, Monash University
School of Population Health, University of Western Australia
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Lung Cancer
 Malignant tumour in tissue of one or both
lungs
 Fifth most common cancer in Australia
• 10,511 new cases diagnosed in 2011 (9% of all cancers)
• Risk of diagnosis by age 85 is 1 in 16 (6%)
 Leading cause of cancer death, accounting for 19% of all
cancer deaths
• 8,137 deaths from lung cancer in 2012
• 5-year survival rate 14%
 More common in men (61% cases) than women (39%)
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Lung Carcinogens
 Number of carcinogens associated with lung cancer,
including:
• Tobacco smoke (including passive)
• Air pollution
• Asbestos
• Diesel engine exhaust
• Ionising radiation
• Metals including arsenic, beryllium,
cadmium, hexavalent chromium, nickel
• Silica
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Occupational Lung Carcinogens
 Recent Australian study (AWES) investigated current
prevalence of exposure to 13 occupational lung
carcinogens
 Overall 31% sample exposed to at least one lung
carcinogen (45% males, 13% females)
• Diesel engine exhaust: 19%
• Environmental tobacco smoke: 14%
• Silica: 7%
• Other polycyclic aromatic hydrocarbons: 6%
 Extrapolated to approximately 2.9 million workers
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Exposure by Occupation
 Most commonly exposed occupational groups:
• Miners: 100%
• Heavy vehicle drivers: 99%
• Farmers: 98%
• Vehicle tradespeople (e.g. mechanics): 95%
• Automobile drivers (e.g. couriers): 93%
• Construction workers: 90%
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Link between Exposure and Cancer
 AWES provides detailed information on:
• what lung carcinogens workers are exposed to;
• who is exposed; and
• how prevalent those exposures are.
 However, contribution of these exposures to future burden
of lung cancer not known
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Our Research Question
What proportion of future lung cancers will occur in those
people who were occupationally exposed to lung
carcinogens in 2012, as a result of their exposure?
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An Illustration
Cohort of
Australian
working
population
Baseline
lung
cancers
Exposed
population
Excess lung
cancers in
exposed
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Lifetime Risk Approach
 Used to estimate proportion of future lung cancers due to
exposure occurring in the proportion of the population who
were exposed in 2012
Working age population
in 2012 (including exposed
cohort)
1950
2094
Start
cancer
count
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End
cancer
count
Lifetime Risk Approach – Required Input
 4 required inputs:
• Estimate of proportion of population currently
exposed to carcinogens of interest (obtained
from AWES)
• Relative risk estimate for each exposure
(obtained from literature)
• Estimate of future lung cancer rates
(projected from current rates using
Canproj)
• Estimate of future person years at risk
(estimated using life table mortality rates and
lung cancer incidence rates)
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Lifetime Risk of Lung Cancer in the 2012
Working Age Population (LRWP)
 First step to calculate lifetime risk of lung cancer
in our cohort (LRWP; regardless of exposure)
𝐿𝑅𝑊𝑃 =
𝑅 ∗𝑃𝑌
𝑁
=
𝐷
𝑁
 Calculated separately for men and women
 We estimated LRWP as 5.6% for men and 4.4% for women
• Translates to 408,650 future lung cancers in men and 319,700 in
women
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Excess Lifetime Risk
 Then calculate excess lifetime risk (LRe) for each exposure
• Excess risk of lung cancer in exposed resulting from exposure
• Calculated separately for each exposure
𝐿𝑅𝑊𝑃 ∗ 𝑁 𝑅𝑅𝑒 − 1
𝐿𝑅𝑒 =
𝑁𝑢 + 𝑁𝑒 ∗ 𝑅𝑅𝑒
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Future Excess Number (FEN) and Future
Excess Fraction (FEF)
 Future Excess Number (FEN) is number of excess cancers
in exposed population
𝐹𝐸𝑁 = 𝐿𝑅𝑒 ∗
𝑁𝑒
 Future Excess Fraction (FEF) is proportion of future
cancers in exposed population due to exposure
𝐹𝐸𝑁
𝐹𝐸𝐹 =
𝐿𝑅𝑊𝑃 ∗ 𝑁𝑊𝑃
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Combining Exposures
 Combine FEFs across all exposures using complement of
the product of complements
• Adjusts for possibility of simultaneous exposures
𝐹𝐸𝐹𝑜𝑣𝑒𝑟𝑎𝑙𝑙 = 1 −
𝑘
(1 − 𝐹𝐸𝐹𝑘 )
𝐹𝐸𝑁𝑜𝑣𝑒𝑟𝑎𝑙𝑙 = 𝐹𝐸𝐹𝑜𝑣𝑒𝑟𝑎𝑙𝑙 ∗ (𝐿𝑅𝑊𝑃 ∗ 𝑁𝑊𝑃 )
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Results - Overall
Male
Female
Total
Total lung cancers
in cohort
408,650
319,700
728,350
Excess lung
cancers due to
exposure
25,100
1420
26,530
Overall Future
Excess Fraction
6.1%
0.4%
3.6%
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Results by Exposure – FENs (>50 cancers)
Future Excess Number (n)
Exposure
M
F
Total
Asbestos
3515
20
3535
Cadmium
191
16
207
Chromium VI
1322
40
1362
Diesel Engine
Exhaust
4242
92
4334
ETS
3238
636
3874
Nickel
4937
248
5184
Other PAHs
2697
219
2916
Silica
5641
117
5758
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Results by Exposure – FEFs (>50 cancers)
Future Excess Fraction (%)
Exposure
M
F
Total
Asbestos
0.9
0.01
0.5
Cadmium
0.05
0.01
0.03
Chromium VI
0.3
0.01
0.2
Diesel Engine
Exhaust
1.0
0.03
0.6
ETS
0.8
0.2
0.5
Nickel
1.2
0.1
0.7
Other PAHs
0.7
0.1
0.4
Silica
1.4
0.04
0.8
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Implications
 Results can show us where greatest burden is coming
from (what exposures are leading to the most cancers)
Future Excess Number (n)
Exposure
M
F
Total
Asbestos
3515
20
3535
Cadmium
191
16
207
Chromium VI
1322
40
1362
Diesel Engine
Exhaust
4242
92
4334
ETS
3238
636
3874
Nickel
4937
248
5185
Other PAHs
2697
219
2916
Silica
5641
117
5758
 Also possible to look at this by occupation and/or industry
(results not presented)
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Implications and Future Research
 Can also see potential effect of various interventions to
reduce exposure – e.g.
• Banning particular carcinogens
• Reducing exposure to particular carcinogens
• Closing high risk industries
• Changing tasks which may lead to high levels of exposure
• Increasing use of protective equipment
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Assumptions of Lifetime Risk Model
 Use of current prevalence of exposure – assume a normal
distribution around this prevalence
2012
 No latent period
• Because some people have been exposed for long time in past,
may be getting their cancers now so no need for latent period
 Use of modelled future cancer incidence rates rather than
present rates
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Conclusions
 Used lifetime risk to estimate contribution of current
exposure to future risk of lung cancer
• Estimated that 26,530 future cancers will occur in 2012 exposed
population as result of exposure
 Results can be used to show where greatest burden
coming from (in terms of exposure, occupation, and/or
industry)
 Can also model potential effect of preventive interventions
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Acknowledgements
 AWES Cancer team
Lin Fritschi
Tim Driscoll
Deborah Glass
Susan Peters
Alison Reid
Geza Benke
Ellie Darcey
Si Si
Sally Hutchings
Lesley Rushton
Jayzii Chan
 National Health and Medical Research Council; Cancer
Council of Western Australia
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Email: [email protected]
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