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The third presentation for a workshop in Singapore and AIOH2013

The third presentation for a workshop in Singapore and AIOH2013

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  • Studies could be:population or industry basedsingle or pooled study meta-analysisSelected studies with comparable exposures to GB:Large sample sizeClear case definitionAppropriate comparison populationControlled for confounders where possibleAdequate exposure assessmentNational data sources used to get the numbers ever exposed. CAREX – CARcinogen Exposure database – gives the estimated numbers exposed by country, carcinogen and industry. Included 139 agents evaluated by IARC as Groups 1,2A and some 2B across 55 industrial classes of the UN system ISIC. However, the prevalences were largely based on US and Finnish (FINJEM) rates and applied to numbers employed in the industry of other countries. LFS series of 2% household based samples from 1973Census of employment etc employer based surveys from 1971 – gives numbers by sex/ full and part time/ 4 digit SIC code.Numbers ever worked from UK population of numbers of working age over the REP – gave denominator for the proportion.Adjusted for turnover, new workers and people retiring and dying + change in broad trends in employment patterns e.g. Service industries going up, manufacturing going downThree international workshops held during the project to discuss and develop the methodology. Helped to focus the assumptions we had to make to take account of inherent limitations in available data. These included:Pragmatic decision about REP and cancer latencyDecision to assign industry sectors to ‘higher’ and ‘lower’ i.e. had proportions exposed over the REP at these two levels and then used published literature to select appropriate risk estimates for these levelsDecision to use IARC group 1 and 2A. NB study carried out using classifications in place at end of 2008. In 2009 IARC reviewed all class 1 carcinogens so if we estimated burden now more cancer sites would be included e.g. asbestos and cervical cancer, colorectal cancer
  • Example using silica.We know from exposure data that currently compliance to the current limit of 0.1mg/m3 is only about 33%. Table shows the impact of improving compliance compared with lowering a standard.Could vary both of these and the timing of introducing the standard. Can also express this in terms of DALYs which can be fed into economic analysesDecisions can be made on the scenarios, the AFs, ANs, DALYs etc
  • Right hand graph shows the AFs for each scenario.No difference between them until after 2030Left hand graph shows the same scenarios for each forecast yearShows no difference in attributable cancers between the scenarios up to 2030.Also because the total nos of lung cancers will rise anyway due to the rise population and rising proportion of the elderly the numbers of attributable cancers rises until after 2020.General conclusion is that whatever the intervention there is no impact until after 2030 because of the legacy of past exposures.
  • This example assumes we have halved the current limit and then tests how effective improving compliance is by workplace size. The most effective interventions are the last 2 when a) compliance improves in those companies employing less than 50 employees (200 more saved compared with previous intervention when compliance is improved in only those companies employing more than 50 employees)b) All workplaces have improved compliance including the self-employed (another 200).This is because silica exposure now occurs largely in the construction industry which is largely small companies and the self-employed.
  • Will rise to nearly 13,000 by 2060 given current trends in employment and exposure levels (>12,300 if current levels maintained). Aging population is a factor.No impact seen until 2030 because of general increase in cancers due to aging populationWith modest intervention (e.g. scenario 3) over 2,000 cancers can be avoided (including 376 lung, 928 breast cancers, 432 NMSC)With stronger interventions (e.g. scenario 6) nearly 8,500 can be avoided (including 1,732 lung, 3,062 breast and 3,287 NMSC)Effective interventionsSilica - improve complianceDEE - need for v. low exposure limit indicatedShift work – If increasing risk with duration of exposure is valid then limiting years of night work reduces burdenIntervention scenariosETS: Compliance (3) 98% services 90% other (4) 95%/80%Radon: Reduce exposed numbers by 10% in (3) 2010, (4) 2020, (5) 2030, (6) 50% in 2010Solar radiation: Move (3) 1/3, (4) 2/3, (5) all to next lower exposure category resp., (6) move all to lowest exposure categoryShift Work: Restrictions on length of employment result in (3) 20% 30% 50%, (4) 10% 20% 70%, (5) 0% 10% 90%, at 15+ years, 5-14 years and 100.Intervention (6) for the chemical agents represents 99% compliance to an existing (RCS) or possible standard, e.g. our estimated H/L boundary exposure levels for arsenic, strong acids and tetrachloroethylene (L/B for TCDD). For asbestos and DEE where it represents 90% compliance to a stringent 1/100th of the current exposure standard. For the other agents it represents a 50% reduction in RR for the occupations and for coal tars and a limit on night shift work to 100.
  • The method should be used for comparing the effect of alternative interventions, or comparing avoidable numbers of attributable cancers between exposures. NB don’t apply achieved AF to real 2030 cancer numbers as these will have increased because of the increasing proportions of the elderly. Note: there will probably have been many changes in the contribution of other environment and lifestyle risk factors.

3. Occupational cancer burden identifying the main culprits Presentation Transcript

  • 1. Occupational cancer : identifying the culprits John Cherrie INSTITUTE OF OCCUPATIONAL MEDICINE . Edinburgh . UK www.iom-world.org
  • 2. Summary… • • • • • Current occupational cancer burden in Great Britain What are the main causes identified in this work and how many people are affected? What substances can we reasonably ignore as part of this initiative? What about the cancer burden in the future? Do these data apply elsewhere? Rushton L, Hutchings SJ, Fortunato L, et al. Occupational cancer burden in Great Britain. Br J Cancer 2012;107:S3–S7.
  • 3. Background… • • Over 1 million cancer deaths in Europe each year and about 5% may be due to work The commonest cancers are: • • • • breast cancer (13.5% of all cancer cases and 29% of cancer cases in women) colorectal cancers (12.9%) and lung cancer (12.1%) Important differences incidence between countries • e.g. about a two fold difference for men between the highest (Hungary) and the lowest (Bulgaria) 3
  • 4. The British study… • Current Burden of Occupational Cancer: • • • • to develop and apply methodology to estimate current attributable risk, cancer numbers and DALYs caused by work to identify important cancer sites to identify industries and occupations for targeting for reduction measures Prediction of Future Burden of Occupational Cancer: • • • Estimate size of future burden based on current and past exposures Identify cancer sites, carcinogens and industry sectors where the burden is greatest Demonstrate effects of measures to reduce exposure
  • 5. Current Burden Methodology… • Attributable fraction (AF): the proportion of cases due to occupation Requires: • Risk of Disease (Relative Risk estimates from published literature) • Proportion of Population Exposed (derived from national data sources, accounting for employment turnover and life expectancy; adjusted for employment trends) • Define period of relevant exposure: Risk Exposure Period (REP) based on cancer latency • Dose-response risk estimates and proportions ever exposed over the REP at different exposure levels not generally available; data therefore obtained for ‘higher’ and ‘lower’ levels • AFs used to calculate attributable numbers (ANs) • Estimation for IARC groups 1 (definite) and 2A (probable) carcinogens and occupational circumstances
  • 6. Cancer Site AF (%) M F Deaths (2005) Total M F Registrations (2004) Total M F Total Mesothelioma 97.0 82.5 94.9 1699 238 1937 1699 238 1937 Sinonasal 43.3 19.8 32.7 27 10 38 195 31 126 Lung 21.1 5.3 14.5 4020 725 4745 4627 815 5442 Nasopharynx 10.8 2.4 8.0 7 1 8 14 1 15 Bladder 7.1 1.9 5.3 215 30 245 496 54 550 Breast NMSC 6.9 4.6 1.1 4.6 4.5 20 555 2 555 23 2513 1969 349 1969 2862 Larynx 2.9 1.6 2.6 17 3 20 50 6 56 Oesophagus 3.3 1.1 2.5 156 28 184 159 29 188 STS Stomach 3.4 3.0 1.1 0.3 2.4 1.9 11 101 3 6 13 108 22 149 4 9 27 157 NHL Melanoma (eye) 2.1 2.9 1.1 0.4 1.7 1.6 43 1 14 0 57 1 102 6 39 1 140 6 9988 (6938, 14794) 3611 (2370, 5412) 13598 (9308, 20206) Total 8.2 (7.2, 9.9) 2.3 5.3 (1.7, (4.6, 3.2) 6.6) 6355 1655 8010 (5640, (1249, (6888, 7690) 2287) 9977)
  • 7. Carcinogen or Occupation Total Registrations (% of total burden) Cancer Sites Asbestos 4216 (30.8%) Larynx, Lung, Mesothelioma, Stomach Shift work (+ Flight Personnel) 1957 (14.3%) Breast Mineral oils 1730 Bladder, Lung, NMSC, Sinonasal Solar radiation 1541 (11.3%) NMSC Silica 907 (6.6%) Lung Diesel engine exhaust 801 (5.9%) Bladder,Lung PAHs - Coal tars and pitches 545 (4.0%) NMSC Painters 359 (3.2%) Bladder, Lung, Stomach Dioxins 316 (2.3%) Lung, NHL, STS Environmental Tobacco Smoke (non-smokers) 284 (2.1%) Radon 209 (1.5%) Lung Welders 175 (1.3%) Lung, Melanoma (eye) Tetrachloroethylene 164 (1.2%) Cervix, NHL, Oesophagus Arsenic 129 (0.9%) Lung Strong inorganic-acid mists 122 (0.9%) Larynx, Lung Lung Chromium 89 Lung, Sinonasal Non-arsenical insecticides 73 Brain, Leukaemia, Multiple myeloma, NHL
  • 8. Industry Sector Attributable Registrations Male Female Total Exposures Construction 4573 64 4637 14 Painter + decorators 331 3 334 1 Roadmen + roofers 471 0 471 1 5375 68 5442 16 0 1969 1969 1 1083 169 1252 1 Personal + household services 256 403 659 17 Land Transport 454 42 497 9 Mining 283 12 296 10 Printing, publishing and allied trades 232 50 282 10 Public administration and defence 229 34 263 6 51 136 187 11 Farming 180 39 220 5 Welders 165 16 181 2 Manufacture of instruments, etc 204 2 206 6 Manufacture of transport equipment 164 18 182 16 Non-ferrous metal basic industries 122 34 156 18 Total construction Shift work (including flight personnel) Metal workers Wholesale + retail trades
  • 9. Predicting Future Burden in Britain… • • • • • • AFs estimated for forecast years, e.g. 2010, 2020 … 2060 Define the risk exposure period (REP) for each year e.g. for 2030, 1981 – 2020 (10-50 years latency assumed for solid tumours e.g. lung cancer, 0-20 years for leukaemia) Some past and some future exposure until 2060 Workers at the beginning (2010) assumed to be of all working ages Workers recruited through employment turnover are assumed to be only aged 15-24 Factors stay the same as 2004/5
  • 10. Predicting Future Burden in Britain… • • • • • Use 4 levels of exposure High/Medium/Low/Background Method effectively shifts the proportion of workers exposed in different exposure level categories (H/M/L/B) across time as exposures gradually decrease Forecasted numbers take into account employment turnover and employment trends Methods applied to top 14 carcinogens/occupations identified as accounting for 85.7% of total current (2004) cancer registrations Forecast GB total cancers (deaths and registrations) based ONLY on demographic projections (ONS) and assuming all non-occupational risk
  • 11. Forecast Risk Exposure Periods – 10-50 year latency REPs ‘Known’ exposure 1961-70 1971-80 FTYs Forecast exposure 1981-90 1991-00 2010 2001-10 2020 2011-20 2030 2021-30 2040 2031-40 2050 2041-50 10 year estimation intervals REP Risk exposure period FTY Forecast target year 2060
  • 12. Change in future exposure: Scenarios Estimates made for alternative scenarios of changes in exposure levels and/or numbers exposed • • • (1) Baseline scenario - based on pattern of past exposure, but no future change in exposed numbers or exposure levels (2) Baseline trend scenario - based on pattern of past and current exposure, and on linear projections up to 20 years into the future, after which levels assumed constant due to prediction uncertainty. (3) ‘Intervention scenarios’ also based on past and current exposures, and suitably chosen target exposure levels in the future
  • 13. Change in future exposure: Interventions Can test: Introduction of a range of possible OELsor reduction of a current limit • Improved compliance to an existing exposure standard • Planned intervention such as engineering controls or introduction of personal protective equipment • Industry closure Also can vary: • Timing of introduction (2010, 2020 etc) • Compliance levels e.g. according to workplace size (self-employed, 1-49, 50-249, 250+ employees) •
  • 14. Forecast lung cancers for Respirable Crystalline Silica 2010 Attributable Fraction 3.3 Attributable registrations Avoided registrations 803 2060 Base-line: exposure limit 0.1mg/m3, compliance 33% 1.08 794 Exposure limit 0.05 mg/m3, compliance 33% 0.80 592 202 Exposure limit 0.025 mg/m3, compliance 33% 0.56 409 385 Exposure limit 0.1 mg/m3, compliance 90% 0.14 102 693 Exposure limit 0.05 mg/m3, compliance 90% 0.07 49 745 Exposure limit 0.025 mg/m3, compliance 90% 0.03 21 773
  • 15. Attributable registrations A) B) 1,000 3.0 Attributable Fraction, % Attributable Registrations 900 800 700 600 500 400 300 200 AFs 2.5 2.0 1.5 1.0 0.5 100 0.0 0 2010 2020 2030 2040 2050 2060 2070 2080 2010 2020 2030 2040 2050 2060 2070 2080 Forecast Year (1) Baseline: exposure limit 0.1mg/m3 maintained, compliance 33% (2) Exposure limit 0.05mg/m3 from 2010, compliance 33% (10) Exposure limit 0.025mg/m3 from 2010, compliance 33% (11) Exposure limit 0.1mg/m3 maintained, compliance 90% (12) Exposure limit 0.05mg/m3 from 2010, compliance 90% (13) Exposure limit 0.025mg/m3 from 2010, compliance 90% Forecast Year
  • 16. Improvement in compliance by workplace size for Silica 2010 Attributable Fraction % 3.3 Attributable registrations Avoided registrations 803 2060 Base-line: exposure limit 0.1mg/m3, compliance 33% 1.08 794 Exposure limit 0.05mg/m3, compliance 33% 0.80 592 202 Exposure limit 0.05mg/m3, % compliance changes by employed workplace size and self employed 33% < 250, self employed; 90% 250+ 0.68 499 295 33% < 50, self employed; 90% 50+ 0.61 451 344 33% self employed; 90% all sizes employed 0.35 261 533 90% all workplaces 0.07 49 745
  • 17. Attributable Numbers of Cancer Registrations Scenarios All Base (1) Exposure Cancer Site 2010 Exposure defined by agent; no appropriate exposure measurements ETS Lung 1465 0 Coal tars Radon Solar radiation NMSC Lung NMSC Trend (2) (3) (4) (5) (6) 2060 0 67 156 489 220 1749 Occupational circumstances, no specified carcinogen Painters Bladder, Lung, 461 Stomach 800 379 3069 877 411 3279 602 341 2552 475 317 2030 433 309 1503 402 190 163 640 639 481 383 347 321 Shift work Welders 3062 140 3848 63 2134 105 1178 83 194 76 0 70 92 47 92 88 87 87 2759 2864 2785 2689 2626 2307 380 837 122 406 794 39 399 442 7 451 102 19 412 49 12 374 21 10 34 10 12 286 123 30 22 8 5 6 139 135 119 123 118 117 119 12050 12327 12938 9812 7944 6064 3705 Breast Lung 1649 189 Carcinogens for which exposure standards can be set Arsenic Lung 128 Asbestos Larynx, Lung Mesothelioma, 4281 Stomach Diesel Silica Strong acids TCDD (Dioxins) Bladder, Lung Lung Larynx, Lung Lung, NHL, STS Tetrachloroethylene Cervix, NHL, Oesophagus Total
  • 18. Monitoring success… • The only practicable approach is to monitor exposure levels • No reduction in cancer levels until 2030 at earliest (for solid tumours) After 2030… • • • • Use achieved exposed numbers/proportions exposed at new exposure levels in same (target setting) forecast model to get achieved AF Apply achieved AF to same (2005 based) cancer projections to get achieved attributable numbers Do not apply achieved AF to real 2030 cancer numbers
  • 19. Uncertainties and the impact on the burden estimation Source of Uncertainty Potential impact on burden estimate Exclusion of IARC group 2B and unknown carcinogens e.g. for electrical workers and leukaemia ↓ Inappropriate choice of source study for risk estimate Imprecision in source risk estimate ↑↓ Source risk estimate from study of highly exposed workers applied to lower exposed target population ↑ Risk estimate biased down by healthy worker effect, exposure misclassification in both study and reference population ↓ Inaccurate latency/risk exposure period, e.g. most recent 20 years used for leukaemia, up to 50 years solid tumours ↓ Effect of unmeasured confounders Unknown proportion exposed at different levels ↑↓ ↑↓ ↑↓
  • 20. Cancer burden elsewhere… • China Li P, Deng S-S, Wang J-B, et al. Occupational and environmental cancer incidence and mortality in China. Occup Med (Lond) Published Online First: 12 March 2012. doi:10.1093/occmed/kqs016
  • 21. Mesothelioma mortality rate Delgermaa V, Takahashi K, Park E-K, et al. Global mesothelioma deaths reported to the World Health Organization between 1994 and 2008. Bull World Health Organ 2011;89:716–724C.
  • 22. Summary… • • • • • • • Currently about 8,000 deaths and 14,000 cancer cases due to past work in Britain Most deaths from lung cancer, mesothelioma and breast cancer Most deaths associated with the construction industry Future burden could be much lower with appropriate interventions Respirable crystalline silica – we need better compliance (and a lower limit) Best interventions differ by agent Monitoring exposure is the best way to track progress