Seminário Nacional do Benzeno (5 e 6 de dez/12) - Derivação de Limites de Exposição Ocupacional para Substâncias Carcinogênicas e Mutagênicas - Experiências Internacionais e Nacional

2. Standard setting in the Netherlands:
approaches and examples
Prof Dick Heederik, PhD
Institute for Risk Assessment Sciences, Division of
Environmental Epidemiology
Utrecht University, The Netherlands
d.heederik@uu.nl

3. Standard setting in the Netherlands
1. Health Council, independent, protected by law: proposal
for a standard
2. Socio Economic Council (tri-partite): feasibility of the
standard
3. Ministry of Social Affairs and Employment: sets the
standard
4. Procedures described in guidelines of health council
Standard may be lower than an European Limit (Scientific
Committee Occupational Exposure Limits (SCOEL)

4. Standard setting in the Netherlands
1. Committee consists of toxicologists, epidemiologists,
hygienists
1. General trend is that epidemiological information (human
studies) is becoming more and more important
2. Regular collaboration with other organizations (Nordic
Expert Group)
1. Literature evaluation by a combined subgroup
2. Hazard evaluation per country

5. Standard setting in the Netherlands: carcinogens
1. Non-genotoxic carcinogens (threshold)
2. Genotoxic carcinogens with a non-stochastic mechanism (threshold)
HEALTH BASED RECOMMENDED OCCUPATIONAL EXPOSURE LIMIT
3. Genotoxic carcinogens with a stochastic mechanism (no threshold)
4. Genetoxic carcinogens with an unknown mechanism (assume no
threshold)
Often linear E-R, more often data driven
RISK CALCULATIONS exposure at on average 10-4 and 10-6 extra risk per
year (4.10-3 and 4.10-5 per 40 years exposure)

6. Differences with other organizations
1. EU REACH regulatory framework:
1. DMEL comparable with a risk calculation on the
basis of a linear model
2. Large assessment approach (based on margin of
exposure principle as applied by European Food
Safety Agency), not relevant for occupational
standards
2. SCOEL linear models, no guidance document

7. Steps in the risk assessment proces
- Selection of information useful to derive an HBROEL or risk
figures (complete review)
- Selection of critical study/studies: Quality review/pooled-
analysis/meta-analysis
- Estimation of carcinogenic activity of an agent (exposure-
response)
- Calculation of risk in relation to exposure/derivation of a
NOAEL or nowadays a BMD(L)
- Obtaining exposure level at which a certain absolute risk is
realized or Health Based Occupational Exposure Limit
(HBROEL)

8. Exposure assessment and evidence based
medicine
✽Recent Dutch Health Council
report 2009
✽App. 200 papers identified
✽50% major quality problems,
exposure assessment component,
underpowered, measurement
endpoint, design
✽These studies were not considered
in the evaluation

9. Stepwise exclusion of studies with quality
issues (Lenters et al., EHP 2011, AOH 2012)

10. Benzene
- carcinogenicity is a complex mechanism including genotoxic
damage, inhibition of DNA repair and altered oncogenic
signalling
- leukaemia develops from genotoxic effects in the
progenitor cells in the bone marrow, a primary target in
benzene-toxicity.
- Do effects on bone marrow cells have a threshold?
- Is this an initial and required step to neoplastic disease?

11. Deriving occupational exposure limits:
comparison of approaches
1. NOAEL analysis
2. BMDL analysis
3. Calculation of risks based on exposure response relations

12. Decreased WBC, Granulocyte and Lymphocyte
Counts and Benzene Exposure in Previous Month
(Lan Q et al., Science 2004)
Factory B (k=213, n=2667)
B e n z e n e e xp o s u re F a c to ry B
100
9000
2000 2001 Controls (140)
8000
<1 ppm (109)
7000 1-10 ppm (110)
Peripheral blood cell count
>10 ppm (31)
B e n z e n e (P P M )
6000
10
5000
4000
3000
2000
1
1000
0
White Blood Cells Granulocytes Lymphocytes
N= 214 172 209 20 209 194 210 209 207 171 248 138 450 16
0 .1
A l
A l
N t
M r
M r
ar
ar
ay
ay
ov
ec
n
n
n
ug
ep
ug
eb
eb
Ju
Ju
c
p
p
Ju
Ja
Ju
O
A
A
M
M
D
F
F
S
Monthly Personal Benzene Exposure Distributions by Factory (Vermeulen et
al., 2004)
12

13. exposure limits: NOAEL analysis
1. Lan et al., (2004) study high quality study with a balanced
design. Data obtained from a representative working
population, exposed up to 16 months.
2. mean concentration of 0.57 ppm (1.8 mg/m3) a reduction
of neutrophils was reported in the main study.
3. subgroup of 30 workers, not directly exposed to other
solvents, with the lowest benzene exposure level
measured of 0.29 ± 0.15 ppm (mean ± SD) and a
significant reduction in blood cells.

14. exposure limits: NOAEL analysis
3. uncertainty factor of 3 to take into account the use of a
minimal effect level instead of a no-effect level.
4. A LOAEL of 0.3 ppm, results in an HBROEL of 0.3/3 = 0.1
ppm

15. exposure limits: BMDL analysis
1. Lan et al. (2004) biomarker study was used to estimate
exposure levels that are expected to result in a drop of 5%
or more in white blood cell populations.
2. Generalized Additive Model (GAM), and was adjusted for
age, body mass index (BMI), sex, smoking, alcohol
consumption, and presence of infections

16. Spline Regression Analyses of WBC Count and Benzene Exposure
✽ Modeling of data from
247 exposed and 139
control subjects
✽ No apparent threshold
✽ Evidence of supralinear
response
Stavanger 2007 16

17. exposure limits: BMDL analysis
3. Using the BMDL10 based on the best fitting model (lin-
log) for the most sensitive endpoint would result in an
estimate of 0.1 ppm as well

18. Issues in the interpretation of the results
- Other studies that made use of routine benzene exposure
and haematological response data (Swaen et al., Chem Biol
Interactions, 2010; Tsai et al., Reg Tox Pharmacol, 2004)
- when is a negative an informative negative study?
(Ahlbohm et al., 1990)
- study quality issues?
- genetic differences?

19. What if benzene is considered a no threshold
carcinogen?
B enzene D ose -R esponse R elationships
✽Benzene example
✽Low dose risk 1 0 0 0
n= 1 0 2 3
identification P liofilm
1 0 0
✽Low dose response
1 0
R isk for
AML
1
modeling 0 .1
✽Identification of
< 4 0 4 0 -2 0 0 2 0 0 -4 0 0 > 4 0 0
ppm -yrs
susceptible groups n=4 7 7 14
W ong, 1995
100
C hina 10
R isk for
A N LL/M D S 1
0.1
none <40 40-99 100 +
H ayes et al., 1997
ppm -yrs
19

20. Use of evidence from occupational studies in
benzene dose-response assessment
• Currently most dose-response assessments for benzene
are based on one study conducted among rubber
hydrochloride workers (PLIOFILM)
• Linear extrapolation of findings to exposure levels
relevant to the general public
• Problems:
1. Is linear extrapolation justified?
2. Discussion on the quality of the exposure
assessment in the PLIOFILM study

21. Quality of the exposure assessment in the
PLIOFILM study
✽ Few exposure measurements
✽ Data gaps filled with ‘expert judgment’
✽ Large potential for exposure misclassification:
✽ Assigned exposure levels were either to high or too low
✽ Assigned exposure levels not very accurate
✽ Difficult to decide what the actual value of this study is for
dose-response assessment

22. Studies included in the meta-regression
(Vlaanderen et al., 2010)
Study Country Study design Risk estimates Year
Nested OR 2003
Australian Health Watch Australia
case- control
CAPM-NCI China Cohort, RR 1997
Nested OR 1996
Canada petrol Canada
case-control
Costantini Italy Cohort SMR 2003
DOW USA Cohort SMR 2004
Wong USA Cohort SMR 1987
Nested OR 1997
UK-Petrol U.K.
case-control
Pliofilm USA Cohort SMR 2002
Swaen Netherlands Cohort SMR 2005

23. Distribution of the risk estimates (n=30)

24. Resulting Regression models
Deviance linear model (1): 29.3 (28 df)
Deviance natural spline (2): 25.8 (27 df)
3
Flexible model is not linear 1
2
ln R R
2
1
Both models predicted an intercept
0 Linear intercept: RR = 1.65
0 Spline intercept: RR = 0 0
100 200 3 1.33 400 500 600
C u m u la tive e xp o su re (p p m -ye a rs)

25. Supralinear shape
✽ observed low-dose supralinearity biologically relevant?
• Saturation of benzene-metabolite enzymatic pathways
might have induced a supralinear shape
2000
BO-Alb, pmol/g
1500
1000
500
0
0 10 20 30 40 50
Benzene, ppm
✽ Attenuation of the ERC at higher exposure levels might
also have played a role:
• Depletion of susceptible individuals at high exposures
• Exposure measurement error
• Healthy worker survivor effect
• High disease background rates

26. Sensitivity analysis: Effect of leaving one study out
3 .0
Without CAPM-NCI
2 .5
2 .0
ln R R
1 .5
1 .0
Without Pliofilm
0 .5
0 .0
0 100 200 300 400 500 600
C u m u la tive e xp o su re (p p m -ye a rs)
Study quality is associated with a n.s. increase in slope of the ERR
(Vlaanderen et al., 2012)

27. Impact of substituting benzene with a measure of
benzene metabolism (Vlaanderen Am J Epid 2011)
Exposure metric Health Watch AIC Pliofilm AIC Fold
(*10-3) (*10-3) difference
Benzene 98.9 103.7 5.35 207.0 18
p = 0.0007 p < 0.0001
Sum 2.09 104.4 0.13 207.5 16
of metabolites p = 0.0007 p <0.0001
PBPK model
Sum 1.22 103.9 0.12 207.6 10
of metabolites p = 0.0006 p < 0.0001
MML model
Sum 1.32 103.3 0.11 207.2 12
of metabolites p = 0.0005 p < 0.0001
Regression
splines model

28. Risk calculations Health Council
- Meta-analysis benzene as described in Vlaanderen et al.
(2010)
- Repeated for leukemia and AML
- Cumulative risks of mortality from leukemia and AML were
compared for simulated (hypothetical) cohorts of exposed
and unexposed subjects in a life-table analysis

29. Use of exposure response to calculate exposure
limit: Life-table analysis
- All-cause and cause-specific (leukemia/AML)
mortality rates identical in the exposed and non-
exposed cohorts
- All-cause mortality rates for males: Statistics
Netherlands (Statline)
- mortality rates for leukemia and AML:
Comprehensive Cancer Centre (IKC).
- Mortality rates modeled using Generalized
Additive Model to obtain smooth estimates of
average mortality rates by age.

30. exposure limits: life table analysis

31. exposure limits: life table analysis

32. exposure limits: life table analysis

33. Exposure limits: life table analysis

34. Benzene exposure levels (ppm) that result in an
excess mortality of 4/100.000 (1/1 000 000 per year)
at age 75 after occupational exposure from 20-65
Meta-regression model Decay function Leukemia AML
Linear, no intercept None 0.011 0.031
Linear 15yrs 0.020 0.057
Exponential 10yrs 0.013 0.038
Exponential 15yrs 0.013 0.038
Linear, intercept None 0.017 0.044
Linear 15yrs 0.032 0.080
Exponential 10yrs 0.021 0.053
Exponential 15yrs 0.021 0.054
Spline, no intercept None 0.003 0.007
Linear 15yrs 0.005 0.013
Exponential 10yrs 0.003 0.008
Exponential 15yrs 0.003 0.008
Spline, intercept None 0.004 0.009
Linear 15yrs 0.007 0.016
Exponential 10yrs 0.004 0.011
Exponential 15yrs 0.004 0.011

35. Issues in the calculation of risks
risk diff.
✽ Complete follow-up versus age 80: 1-6-1.9
✽ Use of average rates versus male rates only 0.8-0.9
✽ continuous risk after age 65 versus trapezium model 1.5-2.0
✽ NHL included versus not included 2.6-3.6
✽ Mortality rates UK, EU, NL: no effect

36. Conclusion
Any approach (NOAEL), BMDL, risk calculations, on the basis of the
present information, results in a clear downword pressure for an
exposure standard
Strong interplay between epidemiological and toxicological
information
Epidemiological information crucial for risk calculations (all
approaches make use of human data)
Toxicological interpretation (mechanisms) drives the choice for one of
the approaches