how response is modeled as a function of exposure.  Therefore these
descriptions are incomplete and do not necessarily refer to separate
models.  The entire report needs to be carefully read for errors such as
this, and particularly to insure that “log-linear” and
“log-transformed exposure”  are not used incorrectly (e.g.,
interchangeably).

A “log-linear model” based on cumulative exposure is a fundamentally
different model from a “log-linear model” based on the log-transform
of cumulative exposure.  For clarity the document should use different
terminology in referring to these different models (e.g., “cumulative
exposure log-linear” and “log-transformed cumulative exposure
log-linear”).

Page 17

“Log quadratic: RR = (β1E + β2E2)”

This equation should read RR = EXP(β1E + β2E2).

 Page 19

Define REL the first time it is used.

Page 28

“For the model based on the pooled analysis, OSHA used the exposure
coefficient (β=0.060) that reflected corrections made by Steenland and
Bartell to the original data (see Table VI-1) and assumed 250 working
days per year.”

This section should state the exposure metric in every case.  E.g., the
coefficient of 0.060 is in what units and for which model?

Page 31-32

“It is also possible that the lung cancer response was diminished in
this group due to an exposure-related increase in competing causes of
death; in particular, tuberculosis, pneumoconiosis, and non-malignant
respiratory disease mortality rates were all 2- or 3-fold higher than
those for the remaining exposure groups.”

Is this really a problem, since the analysis controlled for competing
causes of death?

Page 35 and 36 and other places

Mannetje et al. (2002a) should often be Mannetje et al. (2002b).

Pages 40-41

Another difference between methods of risk estimation by Mannetje et al.
(2002b) and Park et al. (2002) is that Park et al. apparently adjusted
for competing risks of death whereas Mannetje et al. did not.  This
would tend to make the disparity even greater.

Page 41

“study represent the most conservative estimates”

“Conservative” needs clarification.

Page 48

“Assuming that the errors resulting from the assignment of
job-specific mean exposures to individuals and the exposure metric
conversions affect diseased and nondiseased study participants equally
results in a type of error known as a Berkson error”

This definition is incorrect.  Berkson error has to do with the exposure
variable and is not defined in terms of the response.

Page 56

“Part of the problem appears to have arisen from an erroneous footnote
in the Hnizdo et al. (1997) report in which they indicate they applied
the 30-percent conversion factor to respirable dust which had been
acid-washed (for which the 54% conversion rate would have been more
appropriate), whereas in fact the investigators applied the 30-percent
factor to untreated dust.”

This is taken from the Toxichemica Inc. report where it is stated
without any reference.  A reference is needed for this claim.

Page 57

“According to Toxichemica, Inc., (2004) the use of the
log-transformation (i.e., either the log-linear model with log
cumulative exposure or the spline model using log cumulative exposure)
ensures that any constant multiplicative bias in exposure has virtually
no effect on conditional logistic regression coefficients, and would
have no effect at all using a pure log-transformation (i.e., without
adding 1 to allow for exposures at 0 mg/m3-days).”

This is true, which argues against the biological reasonableness of such
a model.

Page 89

“Miller et al. (1998) study reflect the risk that nodular profusion
will progress such that a chest x-ray would be classified as ILO major
category 2 or higher.  Such estimates would understate the risk of
developing lesser degrees of profusion (i.e., ILO 1/0 or 1/1).”

It could also be noted that some of subjects in this study were still
fairly young (<= age 35) when the last evaluation was conducted, and it
seems likely that additional ones of these will develop opacities over
time.

Page 94

“In addition, the results of this study are made uncertain by a lack
of follow up; for the cohort overall, the latest chest film was taken an
average of 11.5 years after hire, a period too short to ensure that all,
or nearly all, cases of silicosis that will develop could be
detected.”

But I don’t see how this detracts from their findings.  Their finding
was statistically significant with the amount of followup present in
their study.  Is OSHA suggesting that the effect would go away with more
followup?

Page 94

“several-fold above the current OSHA PEL (i.e., above …”

Change to “several-fold above the current OSHA PEL (i.e., several-fold
above …”.

~Page 95

“freshly fractured silica”

Does freshly fractured silica contain more particles per mass?  Could
any different toxicity be due to this factor?

Page 108

“The use of the log-transformed exposure metric in the pooled study
was necessary to reduce significant heterogeneity between the 10 worker
cohorts that was evident with a model based on untransformed cumulative
exposure.”

As pointed out in answers to questions, this is a faulty argument.

Page 108

“or a substantial increase in mortality from competing causes.”

The study controlled for mortality from competing causes, so this should
not be a factor.

Page 114

“OSHA believes that risk estimates based on the Miller et al. (1998)
study are the most reliable overall because of the availability of
high-quality exposure data, but they may understate the risk of
developing early signs of silicosis (i.e., corresponding to ILO x-ray
film classifications of 1/0 and 1/1).”

Also, this study may underestimate risk because it included a sizable
fraction of younger men who are at risk of developing silicosis in the
future.

Page 128, Footnotes to table 12

“Estimated by OSHA based on the Park et al. (2002) linear relative
rate model, RR = 0.5469*E where E is cumulative respirable crystalline
silica exposure in mg/m3-years.”

The model is stated incorrectly.  It should be RR = 0.5469*(1+E).  I
don’t know if this was a typographical error or an error in the
calculation.  If the latter, risk will be underestimated.  More
generally, these footnotes should be reviewed carefully and expanded, if
necessary, to make it clear exactly how these calculations were
conducted.

References not used in the document under review

Akaike, H. (1974). A new look at the statistical model identification.
Automatic Control, IEEE Transactions on, 19(6), 716-723.

Carroll, R. J., Ruppert, D., & Stefanski, L. A. (2006). Measurement
Error in Nonlinear Models (p. 455). Boca Raton: Chapman & Hall/CRC.

Cox, D. R. (1972). Regression models and life tables. Journal of the
Royal Statistical Society, Series B (methodological), 34(2), 187-220.

Figure 1

Illustration of why rejecting a model that shows significant
heterogeneity in favor one that doesn’t is not a good decision rule.

This figure depicts data from two studies, Study 1 (blue points) and
Study 2 (red points).  Exposure to a toxicant is measured on the
horizontal axis and the corresponding biological response is plotted on
the vertical axis.  In both studies, increased exposure is associated
with a decrease in the biological effect being measured.  There is an
apparent study effect as exposure causes a stronger decrease in response
in Study 1 than in Study 2.  Two models are used to analyze these data:
Model 1 (orange lines) and Model 2 (green lines).  The solid lines
indicate the fits of the models to the combined data and the dashed
lines indicate the fit of the models to the data from the individual
studies.  The fit of Model 2 to the combined data (solid green line) is
clearly better (i.e., larger log-likelihood) than the fit of Model 1
(solid orange line).  However, there is a significant improvement in fit
when Model 2 is fit separately to the two studies (dotted green lines).
Thus, this model detects significant heterogeneity.  However, with Model
1 the improvement in fit is not significant (in fact shows practically
no improvement); hence there is no significant heterogeneity detected by
this model.  By the decision logic used in the analysis of the lung
cancer data from the pooled analysis to select the model based on
log-transformed exposure over the model based on untransformed exposure,
Model 2 would be ruled out in favor of Model 1 even though Model 2 is
clearly superior.

Murray Finkelstein	None.

Gary Ginsberg	None.

Brian Miller

Brian Miller	Edits, corrections and suggestions

P12 para 2 ?Make explicit that in each set of odds ratios the first is
set arbitrarily at 1.0 and therefore has a different meaning from the
others.

P13 para 2 The non-spline models…

P16 para 1 e.g. -> i.e.

P18 para 2 It should not be a surprise that results from Cox- type
analyses and Poisson regression are similar, since the underlying model
in both is the same.  Where they may differ is in the extent of grouping
applied.  If the same grouping strategy is applied, the results will be
identical.  So often these are compared as if they were different
models, when they’re not.

Same again on P39

P32 para 1 line10 estimate -> estimates

P78 para 1 Poission -> Poisson

P103 para 2 difference -> differences

P107 para 1 OSHA estimates the risk *up to what age?* to be…

P114 para 2 may -> must

Andrew Salmon

Andrew Salmon

Andrew Salmon	General Comment:  Compared to the more usual kind of
quantitative risk assessment study, this is a very peculiar document.
The usual risk assessment paradigm involves hazard identification,
exposure assessment, dose-response assessment for hazards identified as
being of concern, and finally a risk characterization which seeks to
identify either a slope factor for non-threshold effects, or a
health-protective level where the effect of concern is considered to
show a threshold.  These conclusions are then combined by the risk
manager with any other relevant considerations (including measurement
and feasibility) in setting suitable trigger levels for regulatory
action.  The section on health effects does a thorough job of
identifying and reviewing the information on health hazards.  This
section on the other hand starts with the previously chosen regulatory
levels, and seeks an analysis of various available data to provide
estimates of risk for key endpoints at these exposure levels.

Given this perspective, which is the inverse of the normal approach, the
document makes a very good case that substantial adverse health effects
are anticipated in workers exposed for a working lifetime to these
predefined exposure levels.  The most thoroughly developed analyses are
for lung cancer incidence and mortality from silicosis, which are severe
endpoints, and the principal concern in selection of dose-response
models appears to have been the accuracy with which the data are fitted
in the range of the target exposures of interest.  It is hard not to
conclude from a prediction of a 2% lung cancer incidence in workers
exposed at the lower PEL that these regulatory levels are insufficient
to protect workers’ health.  Yet, because of the studies, models and
endpoints selected this report contributes almost nothing to
consideration of what might be more reasonable levels of exposure that
should be considered at least as goals, even if they prove difficult or
expensive to achieve.  In particular, there is no consideration of
dose-response modeling at the lower end of the observed dose ranges, and
no consideration of the possible existence and location of a threshold
in the dose-response curve for silicosis.  There is a tendency in the
current analysis to concentrate on severe endpoints such as mortality
and severe grades of silicosis (which are observed at the exposure
levels predetermined to be of interest), rather than to evaluate milder,
but still significant endpoints which are observed in some studies at
substantially lower exposure levels.

As in the case of most other non-cancer health effects, our
understanding of the mechanism for silicosis induction by quartz
particles, although far from complete, is certainly consistent with the
possibility of a threshold in the dose response relationship, although
this threshold might be well below the levels commonly encountered in
high-risk occupational settings.  The existence of such a threshold for
silicosis is supported by the fact that, although background exposure to
crystalline silica is not zero, this disease is not usually observed in
the general population (although a few special situations producing
“environmental silicosis” are known).  In more specific terms,
Schenker et al (2009) observed histologically identifiable
pneumoconiosis in agricultural workers from the dusty California Central
Valley, but not in individuals from the same area without the heavier
exposures characteristic of employment in agriculture.  Quantitative
analyses of silicosis dose-response which did consider the lower dose
ranges (e.g. Collins et al., 2005) have generally assumed a model which
does imply a threshold, rather than the linear, logistic or log-linear
relationships used to model the response in the range considered by
OSHA.

On the other hand, a threshold for lung cancer induction is not
necessarily expected on theoretical grounds.  There might nevertheless
be such a threshold, or at least a substantial increase in the dose
response slope at higher exposures, especially if the hypothesized link
between lung cancer and silicosis (or some precursor to that condition)
were to be established. The demonstration of any such thresholds would
have important implications for defining “safe” or at least low-risk
exposures in occupational settings.  Toxichemica (2004), citing
Steenland and Deddens (2002), note that such a threshold may in fact
exist at low levels –around 10 µg/m3, although they were unable to
confirm this from a purely statistical standpoint.  It is a significant
omission both in terms of defining a health protective standard, and in
analyzing possible mechanisms of silica lung carcinogenesis, that the
OSHA document does not further examine this possibility, and the
relationship between possible thresholds for lung carcinogenesis and for
silicosis.

References cited

(other than those appearing the bibliography for the OSHA QRA document)

Beadle DG, Bradley AA. 1970. The composition of airborne dust in South
African gold mines. In: Shapiro HA (ed). Pneumoconiosis. Proceedings of
the International Conference. Johannesburg 1969. Cape Town: Oxford
University Press. pp. 462-6.

Churchyard GJ, Ehrlich R, teWaterNaude JM, Pemba L, Dekker K, Vermeijs
M, White N, Myers J (2004). Silicosis prevalence and exposure-response
relations in South African goldminers. Occup Environ Med. 61(10):811-6.

Collins JF, Salmon AG, Brown JP, Marty MA, Alexeeff GV (2005).
Development of a chronic inhalation reference level for respirable
crystalline silica.  Regul Toxicol Pharmacol.  43:292-300.

OEHHA, 2005. Determination of Noncancer Chronic Reference Exposure
Levels.  Chronic Toxicity Summary for Silica (crystalline, respirable).
  HYPERLINK
"http://www.oehha.ca.gov/air/hot_spots/2008/AppendixD3_final.pdf" \l
"page=486"
http://www.oehha.ca.gov/air/hot_spots/2008/AppendixD3_final.pdf#page=486
.

Page-Shipp RJ, Harris E. 1972. A study of dust exposure of South African
white gold miners. South Afr Inst Mining Metall. 73:10-24.

Schenker MB, Pinkerton KE, Mitchell D, Vallyathan V, Elvine-Kreis B,
Green FHY (2009).  Pneumoconiosis from Agricultural Dust Exposure among
Young California Farmworkers.  Environmental Health Perspectives 117(6):
988–994.

Noah Seixas	One additional comment.

OSHA estimates risk of deaths due to silica exposure at 0.05 mg/m3 using
best estimates, in the range of 19-29 per 1000 workers, or 2-3 deaths
per 100 workers.  This is clearly an unacceptable risk of death.  The
risk analysis on which these estimates are given is very strong given
the underlying data.  There are three large studies based on eight
cohorts, each with a substantial degree of exposure quantification, and
the results are strikingly consistent. Given the strength of the risk
analysis, OSHA should set a standard with an acceptable level of
estimated risk.  Two to three deaths per 100 workers is clearly an
unacceptable level of risk.  A lower standard, consistent with legal and
societal norms of acceptable risk should be considered.

Individual Peer Review Comments

Bruce Allen

Bruce Allen Consulting, Chapel Hill, NCFrom: 	"Bruce Allen"
<EMAIL_ADDRESS>
To:	"'Kate Schalk'"<EMAIL_ADDRESS>
Date: 	12/16/2009 1:52 PM

Subject: 	RE: OSHA SILICA - Final revised comments due to ERG 12/16

I have no additional comments or modifications to my earlier comments.
The only part of the discussion that I contributed to that you hade
marked as perhaps needing input from me related to a comment about the
uncertainty related to exposure intensity measures. My comment was that
I did not think that they would be any more uncertain (and perhaps
slightly less uncertain) than cumulative exposure measures for any of
the cohorts used.  That would allow examination to see if adding
exposure intensity (related to the dose rate question) would
significantly improve the fit of the models to the data.  My comment was
in response to another reviewer who expressed the opinion that intensity
or rate data would be too uncertain to use; my response is that since
they are used now to estimate cumulative exposures, they can add no
other uncertainties than those that are already included.

Bruce

Peer Review of OSHA’s Preliminary Quantitative Risk Assessment for
Silica

Comments from Bruce Allen

The draft report evaluates exposure-response data from several
occupational studies as to their suitability for quantitative assessment
of lung cancer and silicosis risk resulting from airborne exposures to
silica.  Are the strengths and limitations of the selected data sets
adequately discussed and appropriately evaluated?  Are you aware of
other study data that are better suited for quantifying lung cancer or
silicosis risk from occupational exposure to silica?  If yes, inform
OSHA of the other data.

In general, I found the discussion of the strengths and weaknesses of
the selected studies to be adequate.  Because such discussions can be
very discursive, I might suggest that a tabular summary of the strengths
and weaknesses be presented.  In such a summary table, the criteria for
evaluating strengths and weaknesses could be laid out (say in the rows)
and then for each study (one per column), a brief point or two could be
presented.  This would allow the more in-depth discussions of the
strengths and weaknesses in the text to be tied back to this summary and
would allow a clearer appreciation of how the studies compared to one
another with respect to the criteria under consideration.

If anything, the weaknesses of all the studies with respect to
reconstruction of exposure histories (both with respect to the
atmospheric concentrations and the job-specific features that lead to
worker exposures to those concentrations) may not have been presented
with enough emphasis to convey just how limiting and problematic that
process can be.  There is some discussion of the “reasonableness of
the exposure assessment” on p. 10, where silicosis mortality odds
ratios are compared across exposure categories from the pooled cohorts
of Steenland et al.  The values presented do not give me a very strong
sense that exposure misclassification was negligible, since the odds
ratios presented hardly differ (the highest three are almost identical)
and I am not sure that a formal test would reject the hypothesis that
the odds ratios were the same, i.e., would not reject the hypothesis
that would hold if all individuals were randomly allocated to the four
groups regardless of their cumulative exposure level.  I have to wonder
if this is the best evidence that is available to OSHA to make the
desired point about impact of exposure misclassification.

I am not aware of any other data that are better suited for quantifying
the lung cancer and silicosis health risks.

The draft assessment relies on quantitative uncertainty analysis and
sensitivity analysis of exposure measurement error in key studies of
lung cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach?  If so, explain.

In contrast to my comments above about the less-than-convincing
presentation related to exposure misclassification, I did like the
analysis that was presented to examine the quantitative effects of
uncertainties about the exposure reconstruction and the individual
worker exposures within that reconstruction.  The Monte Carlo analysis
approach that was applied is a reasonable way to address this question.
My only comment related to that is that a typical Monte Carlo analysis
usually includes many more than 50 iterations (the maximum number if
simulations run in the uncertainty analyses for lung cancer and
silicosis mortality).

Note also that the analyses were performed by selecting some fixed
values for the variabilities considered.  Although the variability was
based on some observations (see bottom of p. 50 and bottom of p. 52 to
top of p. 53), those observations were themselves limited and may not be
the best reflections of the variability that is needed here.  It would
be informative to determine just how much variability is required to
result in a substantial change in the risk estimates.  If that amount of
variability can be deemed unreasonable, then there is stronger support
for the risk estimates that OSHA presents.  Or, another way of thinking
about it: if, even when there is very large variability (representing
uncertainty in the exposures), the calculated risks are still considered
substantial, then there is very strong support for the conclusion that
workers are at risk at the exposure levels under consideration.

The draft assessment evaluates the use of a physiologically-based
pharmacokinetic model that predicts silica lung burdens in individuals
exposed to particulates through inhalation for estimating risk from lung
cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach? If so, explain.

The use of a kinetic model to estimate lung burdens that would then lead
to inflammation, fibrosis, etc. is a very reasonable approach.  However,
the methods and approaches used by Kuempel et al. for their assessment
are not well explained or presented in the OSHA QRA document.

I am particularly troubled by the description starting in the middle of
p. 25 that says that Kuempel et al. used the dose coefficients that had
been previously derived for the two cohorts they analyzed.  Why would
they use those coefficients that were derived without consideration of
the lung burden metric, i.e., that considered simple cumulative
exposure, to estimate lifetime risks based on the lung burdens
associated with various exposure scenarios?  This is either an error in
their methodology or an incomplete and misleading reporting of their
analysis in the OSHA document.

The discussion on p. 27 (first full paragraph) describes the analysis
using the lung burden metric with the 10-cohort study data.  Although
the conclusion is that the lung burden metric does as good a job as
cumulative exposure, the risk estimates derived from that analysis are
not presented (neither in the text nor in Table VI-2, where the summary
of all the risk estimates is presented).  My impression is that OSHA has
not fully considered the lung burden-based risk estimates and perhaps
does not consider them to be “on a par” with the other estimates.
The discussion of the Kuempel et al. study appears to be the most
cursory of the discussions of the various studies.  If it is the case
that this study is not considered as relevant or it is thought of as
secondary (perhaps because it was not an epidemiology study in and of
itself but relied on the response data of two of the other studies
cited), then there should be some discussion of that and the
inter-relationships between the estimates from that “study” and the
others.

The draft assessment summarizes several published risk assessments that
use a variety of models and statistical methodologies employed by the
various analysts to fit the featured data sets.  Are the models and
approaches used by these investigators adequately explained and
evaluated?  If not, let OSHA know what needs to be added to the
presentation.

I think that a summary table showing the approaches and models used by
the various investigators could improve the presentation somewhat.
Table VI-2 does have some of that information (which model was used for
the risk estimation – although there appears to be an error there in
that the Attfield and Costello analysis appears to have used a linear,
not log-linear, relative risk model).

It is difficult to determine how much information to include in a
summary of the studies.  But seeking consistency in the presentation of
the methods and results across studies (as opposed to just reflecting
the perhaps-idiosyncratic information presented by the original authors)
is a desirable goal.  So, the presentation for each study could include
the same, “standardized” information: models considered, lag times
considered, how fitting was done and evaluated, special concerns about
model fit (e.g., nonmonotonicities in observed response rates or odds
ratios), etc.

Here are a few examples of questions that I had in reading the summaries
and evaluating what had been done.

	a.  p. 20, line 7: it says Attfield and Costello used unlagged
exposure.  But how is that possible if they did not update work
histories beyond the original 1982 follow-up (p. 20, line 4) when they
extended mortality follow-up to 1994?

	b. p. 21, line 6: how did Attfield and Costello evaluate
“best-fitting” among all their dose-response analyses, especially
when some of them were on different data (i.e., some with and some
without the high-exposure category)?

	c. If Graham et al. (2004) “concluded that dust control measures were
shown to be effective in reducing lung disease and mortality” (p. 23,
lines 3-4), how could they conclude that the results “did not support
a causal relationship between exposure to quartz and lung cancer” (p.
23, lines 4-5)?

The draft report identifies and describes several key areas of
uncertainty with regard to the estimates of risk.  Were the major
uncertainties in the risk assessment adequately characterized?  If not,
explain what should be included.

As stated above, although I think the uncertainty associated with
historical exposure reconstruction was under-characterized, I like the
Monte Carlo approach to addressing exposure uncertainties (with some
possible extensions suggested in response to question 2.)  The
discussions of possible selection bias, confounding, and bias in
conversion factors were adequate to dispel major concerns about their
having any negative impact on the findings.

The draft assessment relies on the use of cumulative exposure (or a
transformation of cumulative exposure) as the principal dose metric on
which lung cancer and silicosis risks are evaluated.  The draft also
contains a discussion of studies that are suggestive of a dose-rate
effect.  Given this discussion, is cumulative exposure a reasonable
exposure metric for silica-induced lung cancer and silicosis in exposed
workers?  Is there a more appropriate exposure metric?  If so, explain.

It seems that the dose-rate effect may be related to the lung burden
metric predicted by the kinetic model of Kuempel et al.  If that idea
could be explored then there may be a way to provide further support for
the risk estimates that have been presented, especially those based on
that lung burden metric.  This is important given the fact that,
apparently, the lung burden metric did as well as cumulative exposure
(or log-cumulative exposure) in fitting the data.

On the other hand, I was not bothered by the fact that a dose-rate
effect might be present, given the indications that it may occur at
concentrations clearly above levels that OSHA needs to be concerned
about for reducing workers’ health risks.  Given the information about
where (at what concentrations) significant dose-rate effects appear to
be occurring, I am satisfied with the use of cumulative exposure for the
determination of concentration levels associated with the lower levels
of risk of concern for regulatory decision making.

OSHA’s estimates of lung cancer and silicosis mortality are
represented as a range of estimates with those derived from the
diatomaceous earth and U.S. granite studies considered to be plausible
upper bound risk estimates.  OSHA also acknowledges that the risk may be
lower such as suggested by the results of the IARC multi-centric study,
which relied on pooled data from several epidemiological studies.  Is
this a sound and reasonable estimation of risk from the available data?
Is this decision adequately explained?  Should the risk estimates based
on one data set be preferred over the other?  Is there a more
appropriate representation of the lung cancer risk from silica exposure?
 If so, explain.

I think it is appropriate to present a range of risk estimates and to
consider the differences in the estimates when making decisions about
regulatory limits. As discussed in the document, there are various
differences among the cohorts of individuals exposed to silica,
including the physical properties of the silica itself, that are
potentially important considerations and which may account for the range
of risk estimates. Given those differences, it is important to show the
range as a reflection of what those differences may entail (in addition
to the fact that no two sets of results will be exactly alike or give
exactly the same estimates, even if everything was identical).

The only reason that I can see to prefer one set of estimates to another
would be if that one set was based on a substantially superior study,
say in terms of sample size, relevance of exposure, measurement of
exposure, representativeness of the cohort members in relation to the
workers for whom regulatory limits are being set, etc.  The 10-cohort
study is larger than the other two cohorts alone, and its exposure
contexts clearly cover a wider spectrum.  It might be justified to base
decisions solely on the results of that study, but it is not clear that
those results should be presented to the exclusion of the others.

The cumulative risk of silicosis morbidity is preliminarily considered
to be best represented by a range (approximately 3- to 4-fold) that is
based on results from four published exposure-response assessments.
Does this range reflect a sound and reasonable estimation of risk from
the available data?  Is this decision adequately explained?  Should the
risk estimates based on one data set be preferred over the other?  Is
there a more appropriate representation of the silicosis morbidity risk
from silica exposure?  If so, explain.

The decision to limit quantitative risk estimates to the studies that
included retirees as well as current workers was a good one.
Cross-sectional studies are particularly problematic, and the cumulative
risk studies that excluded retired workers lose a segment of the
population that may have a different (higher) response rate than those
who were able to continue work.

The decision to present estimates from those five studies appears
reasonable.  OSHA has indicated a slight preference for the estimates
derived from Miller et al. based on the quality of the exposure indices.
 That is a reasonable position, but the variations across study are
informative and largely corroborative.  Again, given the differences
that might occur across current and future work places subject to
regulation, it is appropriate to consider as many different reasonable
estimates of risk as possible.

OSHA estimated the risk of lung cancer mortality, silicosis mortality,
and silicosis morbidity for 45-year exposures to 0.25 and 0.5 mg/m3
respirable crystalline silica; these represent a range of exposures
consistent with OSHA’s current standards for construction and maritime
industry sectors, but are above OSHA’s current general industry
standards (approximately 0.1 mg/m3 for respirable quartz).  The
cumulative exposures corresponding to these higher exposure levels are
at or above the cumulative exposures of most of the more highly exposed
workers included in the studies that underlie the risk estimates.  Is
OSHA’s approach for extrapolating risk above the

observed range reasonable?  Is it clearly explained?  Is there a more
appropriate approach that should be considered to estimate risk at
cumulative exposures that are generally above the observed range of the
underlying epidemiological studies?

I consider these questions to be moot.  If the analyses show substantial
risk associated with concentrations lower than those in question, ones
that do not require extrapolation above the cumulative exposures
observed in the studies themselves, then it is entirely reasonable to
presume that higher concentrations (i.e., the 0.25 and 0.5 mg/m3 values)
will be associated with even higher risks.  In that sense, there need
not be a detailed explanation of (nor angst about) methods for
extrapolation above the levels where there are observed increased risks.

Kenneth Crump

Louisiana Tech University Foundation, Inc., Ruston, LA

This review is organized around the questions provided to the peer
reviewers.

The draft report evaluates exposure-response data from several
occupational studies as to their suitability for quantitative assessment
of lung cancer and silicosis risk resulting from airborne exposures to
silica.  Are the strengths and limitations of the selected data sets
adequately discussed and appropriately evaluated?  Are you aware of
other study data that are better suited for quantifying lung cancer or
silicosis risk from occupational exposure to silica?  If yes, inform
OSHA of the other data.

Response

The strengths and limitations of the selected data sets appear to be
adequately discussed and evaluated.  Areas that could be improved in
some relatively minor ways are discussed below.  I am not aware of any
other studies that are better suited for quantifying lung cancer or
silicosis risk from occupational exposure to silica.

 The draft assessment relies on quantitative uncertainty analysis and
sensitivity analysis of exposure measurement error in key studies of
lung cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach?  If so, explain.

Response

This question refers to the analysis of exposure measurement error in
Toxichemica, Inc. (2004).  These analyses are well designed, clearly
explained and evaluated.  Evaluating and adjusting for exposure
measurement error is a very difficult issue.  The analysis of error
conducted by Toxichemica, Inc. is a very strong effort.  The assumptions
are clearly described and the data upon with they are based appear to be
appropriate and appropriately applied.  However, there are questions, as
there will always be with such an analysis, regarding the form(s)
assumed for the errors, the assumptions used in modeling the errors, and
in the completeness of the sources of errors modeled.

For the Berkson component of the error, it would seem reasonable to
consider a multiplicative error model, i.e.,

		Exposuretrue = Exposureobserved * ε

where ε has a log-normal distribution.  In this form, both the mean and
the variance of the true exposure increases with the observed exposure,
which seems reasonable.  Also, unlike the additive error model, this
model does not produce negative exposures (to avoid this problem is
presumably why the distribution was truncated in the Toxichemica, Inc.
analysis).  This model might produce significantly different results
from the additive model, including modifying the shape of the dose
response curve (Carroll et al. 2006).

It could also be assumed that silica concentrations differed randomly by
work area rather than by job.  Workers in same area of a facility will
breathe the same air even if they are doing different jobs.  Resampling
randomly by job within work area rather than by work area may tend to
average out variations by work areas and underestimate uncertainty.

The method for evaluating error in converting from dust measurements to
quartz measurements appropriately based on data and well-designed and
implemented.  However, other important sources of error do not appear to
be accounted for.

A major source of error that apparently was not accounted for is in
assuming that the average measure of exposure assigned to a job is the
true average.  But it is not always clear how representative the
underlying measurements were.  E.g., were some measurements taken at
times when it was believed there was a particular problem with high
exposures?  Moreover, some of these averages (particularly, those that
pertain to earlier times and which are likely the more influential since
they probably represent the highest exposures) were not based on direct
measurements, but were projected based on judgments of persons familiar
with the operations.  There is possibly considerable error in such
estimates.  Another source of uncertainty in the averages stems from the
need to convert from one measurement method to another (e.g., from
particle counts to gravimetric measurements).

Based on these considerations, it seems likely that the effects of
exposure errors could have been larger than predicted by the
Toxichemica, Inc. analysis.  It would also be useful to evaluate the
effect of errors in exposure using other exposure metrics than log
cumulative exposure.  Risk models based on other exposure metrics are
likely to be more sensitive to exposure error.  (Also, see response to
Question 4 regarding the use of log cumulative exposure as the exposure
metric.)

The draft assessment evaluates the use of a physiologically-based
pharmacokinetic model that predicts silica lung burdens in individuals
exposed to particulates through inhalation for estimating risk from lung
cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach? If so, explain.

Response

This refers to an analysis in Toxichemica, Inc. (2004).  Exposure
metrics based on lung burdens can provide reasonable alternatives to the
more empirical metrics emphasized in the papers reviewed by OSHA (lagged
or unlagged cumulative exposure or log cumulative exposure).  The lung
cancer and silicosis analyses are adequately explained as far as they
go.  Whereas the silicosis analysis considered several metrics based on
lung burden, the lung cancer analysis only considered one exposure
metric – lung burden lagged 15 years.  However, both the lung cancer
and silicosis analyses stopped short of estimating risks using this
approach.  Even if a fit to data using a metric based on lung burdens is
similar to the fit provided by an empirical metric such as log
cumulative exposure, that doesn’t imply that the estimated risks from
45 years of exposure will be similar.  Without estimating risk using the
metrics based on lung burden, the effect of these metrics upon the
estimated risk will not be known.  If workers in the epidemiological
studies predominately were exposed for only a short time (e.g., a few
months), different exposure metrics could predict significantly
different risks from 45 years of exposure even if they provided
equivalent fits to the epidemiological data.

The draft assessment summarizes several published risk assessments that
use a variety of models and statistical methodologies employed by the
various analysts to fit the featured data sets.  Are the models and
approaches used by these investigators adequately explained and
evaluated?  If not, let OSHA know what needs to be added to the
presentation.

Response

The reasons given for emphasizing analyses of the pooled data on lung
cancer (Steenland et al. 2001a) that use log-transformed cumulative
exposures are faulty.  There are several reasons for preferring analyses
based on untransformed exposures.  Using untransformed exposure with a
15 year lag gave a considerably better fit to the data than
log-transformed exposure with a 15 year lag (log-likelihood of 21.4
versus 18.8—what is referred to as the likelihood in Steenland et al.
(2001a) is presumably the log-likelihood).  The fact that the model
based on log-transformed exposure did not show significant improvement
in fit when the interaction terms were added (i.e., did not show
significant heterogeneity) should be viewed as more of a disadvantage of
this model in comparison to the one based on untransformed exposures
rather than an advantage: The model based on untransformed exposures not
only fit better that the model based on untransformed exposures, but
adding interaction terms significantly improved the fit of the already
better-fitting model, but did not significantly improve the fit of the
poorer-fitting model.

Figure 1 provides a simple illustration of this point.  This figure
depicts data from two studies, Study 1 (blue points) and Study 2 (red
points).  There is an apparent study effect as exposure shows a stronger
effect in Study 1 than in Study 2.  Two models are used to analyze these
data, Model 1 (orange lines) and Model 2 (green lines).  The solid lines
indicate the fits of the models to the combined data and the dashed
lines indicate the fit of the models to the data from the individual
studies.  The fit of Model 2 to the combined data (solid green line) is
clearly better (i.e., larger log-likelihood) than the fit of Model 1
(solid orange line).  However, there is a significant improvement in fit
when Model 2 is fit separately to the two studies (dotted green lines).
Thus, this model detects significant heterogeneity.  However, with Model
1 the improvement in fit is not significant; hence there is no
significant heterogeneity identified by this model.  By the decision
logic described above, Model 2 would be ruled out in favor of Model 1
even though Model 2 is clearly superior.  This example has the same
characteristics as the fits to the lung cancer data in the pooled data,
with Model 2 playing the role of the model using untransformed exposure
and Model 1 playing the role of the model using log-transformed
exposure.

There are several procedures for choosing the best model based on the
value of the likelihood (e.g., AIC (Akaike information criterion, Akaike
1974)).  Each of these procedures would identify the model based on
untransformed exposures as better than the one based on log-transformed
exposures.  The fact that the significant heterogeneity was found for
this model suggests that this model could be improved, but it does not
indicate that the model using log-transformed exposures is better.

Dose responses for the same effect (e.g., lung cancer from silica) would
not be expected to have fundamentally different forms in different
studies (e.g., derived from log-transformed exposure in one study and
untransformed exposure in another).  It would assist in comparing
results across studies to present risk estimates from the three studies
in Table VI-2 using a common exposure metric.  Similarly, it would
assist in comparing the effect of different exposure metrics, by
computing risk from single study using different exposure metrics.  Both
of these goals could be accomplished by adding to Table VI-2 risk
estimates derived from the analysis of the pooled cohorts (Steenland et
al. 2001) based on a linear relative risk model.  If the model is truly
linear in the exposure variable, use of the log-transformed exposures
will tend to underestimate risks at lower exposures and overestimate
risks at higher exposures.

More consideration needs to be given in the document to model selection
and its effect upon risk estimates.  Although log-linear models are
relied upon extensively, such models are generally selected for
convenience (since this is the model generally used in Cox regression
(Cox 1972)) rather than for biological plausibility.  Such models are
supralinear when applied to untransformed exposure (increase at a rate
faster than linear with increasing exposure).  OSHA states that it does
not believe that a supralinear response “is biologically plausible and
believes that it is more reasonable to assume that the exposure-response
relationship remains linear …”  This argues for using a linear model
(like the linear relative rate model used in Rice et al. (2001)) instead
of a log-linear model.  It also argues against using a log-linear model
with log-transformed exposure, since such models are sublinear, as
illustrated by the very slow increase in risk with increasing exposure
exhibited by the lung cancer model implemented by Toxichemica Inc.
(2004) (Table VI-12).  To more fully evaluate the effect of model
selection, it would useful to reanalyze the data from one or more of the
key studies, such as the data from the pooled cohort, using a truly
linear model, and perhaps other models, and compare risk estimates
obtained from these models.

It is claimed that the Attfield and Costello (2004) log linear model
becomes supralinear at cumulative exposures above 4.5 mg/m3-years.  How
OSHA arrived at this conclusion is not explained.  As noted above such a
model is actually supralinear at all values of cumulative exposure.

The draft report identifies and describes several key areas of
uncertainty with regard to the estimates of risk.  Were the major
uncertainties in the risk assessment adequately characterized?  If not,
explain what should be included.

Response

The potential for selection bias and for bias due to confounding are
adequately addressed.  As explained in response to Question 2, some
aspects of uncertainty in risk due to uncertainty in exposures are
addressed but others probably are not.  In addition, the effect upon
risk of the exposure uncertainty that was quantified is possibly
underestimated due to the use of log-transformed exposures, as risk
estimates based upon log-transformed exposures tend to be relative
insensitive to changes in exposures.  As discussed in response to
Question 4, there needs to be additional evaluation of the uncertainty
due to the risk models used.

The draft assessment relies on the use of cumulative exposure (or a
transformation of cumulative exposure) as the principal dose metric on
which lung cancer and silicosis risks are evaluated.  The draft also
contains a discussion of studies that are suggestive of a dose-rate
effect.  Given this discussion, is cumulative exposure a reasonable
exposure metric for silica-induced lung cancer and silicosis in exposed
workers?  Is there a more appropriate exposure metric?  If so, explain.

Response

First it needs to be clear about what is meant by a “dose-rate
effect”.  My interpretation of that concept is that there is a
non-linearity in the exposure-response whereby a given increase in
intensity of exposure will cause a greater than proportional increase in
risk.  An example would be if risk varies as the integral over time of
the square of the exposure level.  Thus, there are dose metrics other
than cumulative exposure that do not incorporate a dose-rate effect.
Since OSHA is relying on cumulative exposure to estimate risk, I
interpret this question as whether cumulative exposure is an appropriate
metric, or is some other metric that incorporates a dose-rate effect
more appropriate.

Estimating risk based on an “incomplete” exposure metric like
average exposure is not recommended.  It is highly implausible that such
a metric could apply over an extended range of exposure patterns that
are likely to exist in a study.  E.g., exposure to a particular air
concentration for one week is unlikely to carry the same risk as
exposure to that concentration for 20 years, although the average
exposures are the same.

Finding a significant relationship between average exposure and risk in
itself is not evidence of a dose-rate effect.  In general, even if risk
is truly a function of cumulative exposure, there with likely also be a
significant relationship between risk and average exposure, since
cumulative exposure and average exposure are likely to be correlated.
For example, if all exposures are for the same duration, average
exposure is totally confounded with cumulative exposure.  On the other
hand, demonstration of a significant relationship with cumulative
exposure does not rule out a dose-rate effect, since cumulative exposure
will possibly be correlated with a metric that incorporates such an
effect.

To demonstrate evidence for a dose-rate effect that is not captured by
cumulative exposure, it would be most convincing to show some effect of
dose rate that is in addition to the effect of cumulative exposure.  To
demonstrate such an effect one would need to model both cumulative
exposure and some effect of dose rate, and show that adding the effect
of dose rate makes a statistically significant improvement to the model
over that provided by cumulative exposure alone.  I am not aware of any
such analysis that has been conducted for lung cancer from silica or for
silicosis mortality.  However, as discussed below, two studies conducted
such analyses for silicosis morbidity.

Most of the analyses of for silicosis morbidity did not examine exposure
metrics other than cumulative exposure.  Of the eight cumulative risk
studies summarized by OSHA (Table VI-11), only Hughes et al. (1998)
specifically tested for a dose-rate effect.  This study found that,
after controlling for cumulative exposure, workers exposed to ≥ 0.5
mg/m3 crystalline silica had a significantly higher risk than workers
exposed to lower levels.  A similar dose-rate effect was found by
Buchanan et al. (2003).  Although Steenland and Brown (1995a) found that
average exposure did not describe the morbidity in their cohort nearly
as well as cumulative exposure, this is not as specific a test for a
dose-rate effect as was conducted by Hughes et al. and Buchanan et al.
The remaining six studies used to summarize risk of silicosis morbidity
(Table VI-11) considered only cumulative exposure as an exposure metric.
 So the two studies that looked carefully for a dose-rate effect found
evidence for such an effect.  In addition, Park et al. (2002) found a
13-fold higher incidence of silicosis during 1942-52 than in subsequent
years after controlling for cumulative exposure.  Although they
attributed this possibly to a change in surveillance, it could also be
due to high exposures during this early period and a dose-rate effect.

The OSHA report states that a dose-rate effect for silicosis is
biologically plausible.  And if such an effect is present for silicosis
morbidity, it would presumably also be present for silicosis mortality.
The report also states that even if there is such an effect it may not
exist at concentrations in the range of the current PEL.  However, even
if this is the case, risks in the range of the current PEL are being
estimated from studies that involved higher air concentrations.  Not
accounting for a dose-rate effect, if one exists, could overestimate
risk at lower concentrations.

Having noted that there is evidence for a dose-rate effect for
silicosis, it may be difficult to account for it quantitatively.  The
data are likely to be limited by uncertainty in exposures at earlier
times, which were likely to be higher.  Perhaps rather than identifying
an alternative dose metric to cumulative exposure, it would be better to
retain cumulative exposure but use data from lower exposures where any
dose-rate effect would be less severe.  One possible approach that might
could be used to adjust existing estimates for a potential dose-rate
effect is to use either the coefficients estimated by Hughes et al.
and/or Buchanan et al. for low exposures (e.g., equation (1) of Hughes
et al 1998 with con = 0, or equation (2) of Buchanan et al. 2005).
Another possibility is to reanalyze data from some of the better studies
using an approach similar to the approaches used by Hughes et al. (1998)
and Buchanan et al. (2003).

The analysis by Toxichemica, Inc. (2004) that investigated several
exposure metrics based on lung burden, although it investigated exposure
metrics different from cumulative exposure, did not address a dose-rate
effect per se.

OSHA’s estimates of lung cancer and silicosis mortality are
represented as a range of estimates with those derived from the
diatomaceous earth and U.S. granite studies considered to be plausible
upper bound risk estimates.  OSHA also acknowledges that the risk may be
lower such as suggested by the results of the IARC multi-centric study,
which relied on pooled data from several epidemiological studies.  Is
this a sound and reasonable estimation of risk from the available data?
Is this decision adequately explained?  Should the risk estimates based
on one data set be preferred over the other?  Is there a more
appropriate representation of the lung cancer risk from silica exposure?
 If so, explain.

Response

Other things being equal I would recommend emphasizing risks estimated
from the multi-centric study, since it incorporates data from many
studies and is less likely to be unduly influenced by exposure errors
from a single study.  However, I would not recommend emphasizing risks
from this study as currently estimated using log-transformed exposures.
The lower risk estimated from the multi-centric study is likely to be an
artifact due to the use of log-normal transformed exposure.  As pointed
out earlier, untransformed exposure provided a better fit to these data
than log-transformed exposure.  The limited increase in risk projected
by this model to result from a 10-fold increase in exposure (0.05 mg/m3
to 0.5 mg/m3) doesn’t seem plausible.  OSHA could consider calculating
risk from the multi-center using untransformed exposures and a linear
model.

	The cumulative risk of silicosis morbidity is preliminarily considered
to be best represented by a range (approximately 3- to 4-fold) that is
based on results from four published exposure-response assessments.
Does this range reflect a sound and reasonable estimation of risk from
the available data?  Is this decision adequately explained?  Should the
risk estimates based on one data set be preferred over the other?  Is
there a more appropriate representation of the silicosis morbidity risk
from silica exposure?  If so, explain.

Response

As discussed above, studies that have tested for a dose-rate effect have
found evidence of such an effect.  Given this, it would be reasonable to
take such an effect into account in the risk estimates.  Some
suggestions are made above about how this might be accomplished.

OSHA estimated the risk of lung cancer mortality, silicosis mortality,
and silicosis morbidity for 45-year exposures to 0.25 and 0.5 mg/m3
respirable crystalline silica; these represent a range of exposures
consistent with OSHA’s current standards for construction and maritime
industry sectors, but are above OSHA’s current general industry
standards (approximately 0.1 mg/m3 for respirable quartz).  The
cumulative exposures corresponding to these higher exposure levels are
at or above the cumulative exposures of most of the more highly exposed
workers included in the studies that underlie the risk estimates.  Is
OSHA’s approach for extrapolating risk above the observed range
reasonable?  Is it clearly explained?  Is there a more appropriate
approach that should be considered to estimate risk at cumulative
exposures that are generally above the observed range of the underlying
epidemiological studies?

Response

OSHA evaluated this issue by comparing cumulative exposures
corresponding to exposure levels of 0.25 and 0.5 mg/m3 to the median
exposures and third quartile exposures in various cohorts.  Such
comparisons are not particularly indicative of whether risks have been
extrapolated beyond the range of the data.  The important issue is
whether there are sufficient numbers of cohort members with exposures in
the range of interest.  Irrespective of the median of third quartile
exposures, there still could be significant numbers of cohort members
with exposures in the range of interest.  For example, adding many
additional cohort members with low exposures would lower both the median
and third quartile exposure, but would not reduce the ability to
quantify risk at higher exposures.  To explore this issue further, OSHA
could evaluate the potential numbers of cohort members in the various
studies with exposures in the range of interest.  My expectation is that
the pooled analysis will contain a significant number of cohort members
with exposures in this range.  (However, the pooled analysis may
underestimate risks in this range due to use of log-transformed
exposures – see response to Question 4.)

Additional comments

Page 6

“OSHA’s current general industry PEL for quartz is the gravimetric
formula 10 mg/m3/(%quartz + 2) expressed as the concentration of
respirable dust.  For quartz concentrations exceeding 5 percent, the PEL
expressed as the concentration of respirable quartz exceeds 0.07 mg/m3
and approaches 0.1 mg/m3 as the quartz content increases.”

An example could perhaps make this clearer.

Page 12

“the log of cumulative exposure”

This should be the log of cumulative exposure plus 1.  This is an
important distinction that should be made throughout the document.  In a
log linear model that uses log-transformed exposure, the relative risk
approaches zero as exposure approaches zero, rather than approaching
1.0.  However, when 1 is added to cumulative exposure, the relative risk
approaches 1.0 as it should.

Page 15

“Steenland et al. (2001a) estimated excess lifetime risk of lung
cancer based on rate ratios from the spline and log-linear models
(15-year lagged log-cumulative exposure for both),”

“Spline” refers to how exposure is modeled.  “Log-linear refers to
how response is modeled as a function of exposure.  Therefore these
descriptions are incomplete and do not necessarily refer to separate
models.  The entire report needs to be carefully read for errors such as
this, and particularly to insure that “log-linear” and
“log-transformed exposure”  are not used incorrectly (e.g.,
interchangeably).

A “log-linear model” based on cumulative exposure is a fundamentally
different model from a “log-linear model” based on the log-transform
of cumulative exposure.  For clarity the document should use different
terminology in referring to these different models (e.g., “cumulative
exposure log-linear” and “log-transformed cumulative exposure
log-linear”).

Page 17

β1E + β2E2)”

This equation should read RR = EXP(β1E + β2E2).

 Page 19

Define REL the first time it is used.

Page 28

“For the model based on the pooled analysis, OSHA used the exposure
coefficient (β=0.060) that reflected corrections made by Steenland and
Bartell to the original data (see Table VI-1) and assumed 250 working
days per year.”

This section should state the exposure metric in every case.  E.g., the
coefficient of 0.060 is in what units and for which model?

Page 31-32

“It is also possible that the lung cancer response was diminished in
this group due to an exposure-related increase in competing causes of
death; in particular, tuberculosis, pneumoconiosis, and non-malignant
respiratory disease mortality rates were all 2- or 3-fold higher than
those for the remaining exposure groups.”

Is this really a problem, since the analysis controlled for competing
causes of death?

Page 35 and 36 and other places

Mannetje et al. (2002a) should often be Mannetje et al. (2002b).

Pages 40-41

Another difference between methods of risk estimation by Mannetje et al.
(2002b) and Park et al. (2002) is that Park et al. apparently adjusted
for competing risks of death whereas Mannetje et al. did not.  This
would tend to make the disparity even greater.

Page 41

“study represent the most conservative estimates”

“Conservative” needs clarification.

Page 48

“Assuming that the errors resulting from the assignment of
job-specific mean exposures to individuals and the exposure metric
conversions affect diseased and nondiseased study participants equally
results in a type of error known as a Berkson error”

This definition is incorrect.  Berkson error has to do with the exposure
variable and is not defined in terms of the response.

Page 56

“Part of the problem appears to have arisen from an erroneous footnote
in the Hnizdo et al. (1997) report in which they indicate they applied
the 30-percent conversion factor to respirable dust which had been
acid-washed (for which the 54% conversion rate would have been more
appropriate), whereas in fact the investigators applied the 30-percent
factor to untreated dust.”

This is taken from the Toxichemica Inc. report where it is stated
without any reference.  A reference is needed for this claim.

Page 57

“According to Toxichemica, Inc., (2004) the use of the
log-transformation (i.e., either the log-linear model with log
cumulative exposure or the spline model using log cumulative exposure)
ensures that any constant multiplicative bias in exposure has virtually
no effect on conditional logistic regression coefficients, and would
have no effect at all using a pure log-transformation (i.e., without
adding 1 to allow for exposures at 0 mg/m3-days).”

This is true, which argues against the biological reasonableness of such
a model.

Page 89

“Miller et al. (1998) study reflect the risk that nodular profusion
will progress such that a chest x-ray would be classified as ILO major
category 2 or higher.  Such estimates would understate the risk of
developing lesser degrees of profusion (i.e., ILO 1/0 or 1/1).”

It could also be noted that some of subjects in this study were still
fairly young (<= age 35) when the last evaluation was conducted, and it
seems likely that additional ones of these will develop opacities over
time.

Page 94

“In addition, the results of this study are made uncertain by a lack
of follow up; for the cohort overall, the latest chest film was taken an
average of 11.5 years after hire, a period too short to ensure that all,
or nearly all, cases of silicosis that will develop could be
detected.”

But I don’t see how this detracts from their findings.  Their finding
was statistically significant with the amount of followup present in
their study.  Is OSHA suggesting that the effect would go away with more
followup?

Page 94

“several-fold above the current OSHA PEL (i.e., above …”

Change to “several-fold above the current OSHA PEL (i.e., several-fold
above …”.

~Page 95

“freshly fractured silica”

Does freshly fractured silica contain more particles per mass?  Could
any different toxicity be due to this factor?

Page 108

“The use of the log-transformed exposure metric in the pooled study
was necessary to reduce significant heterogeneity between the 10 worker
cohorts that was evident with a model based on untransformed cumulative
exposure.”

As pointed out in answers to questions, this is a faulty argument.

Page 108

“or a substantial increase in mortality from competing causes.”

The study controlled for mortality from competing causes, so this should
not be a factor.

Page 114

“OSHA believes that risk estimates based on the Miller et al. (1998)
study are the most reliable overall because of the availability of
high-quality exposure data, but they may understate the risk of
developing early signs of silicosis (i.e., corresponding to ILO x-ray
film classifications of 1/0 and 1/1).”

Also, this study may underestimate risk because it included a sizable
fraction of younger men who are at risk of developing silicosis in the
future.

Page 128, Footnotes to table 12

“Estimated by OSHA based on the Park et al. (2002) linear relative
rate model, RR = 0.5469*E where E is cumulative respirable crystalline
silica exposure in mg/m3-years.”

The model is stated incorrectly.  It should be RR = 0.5469*(1+E).  I
don’t know if this was a typographical error or an error in the
calculation.  If the latter, risk will be underestimated.  More
generally, these footnotes should be reviewed carefully and expanded, if
necessary, to make it clear exactly how these calculations were
conducted.

References not used in the document under review

Akaike, H. (1974). A new look at the statistical model identification.
Automatic Control, IEEE Transactions on, 19(6), 716-723.

Carroll, R. J., Ruppert, D., & Stefanski, L. A. (2006). Measurement
Error in Nonlinear Models (p. 455). Boca Raton: Chapman & Hall/CRC.

Cox, D. R. (1972). Regression models and life tables. Journal of the
Royal Statistical Society, Series B (methodological), 34(2), 187-220.

Figure 1

Illustration of why rejecting a model that shows significant
heterogeneity in favor one that doesn’t is not a good decision rule.

This figure depicts data from two studies, Study 1 (blue points) and
Study 2 (red points).  Exposure to a toxicant is measured on the
horizontal axis and the corresponding biological response is plotted on
the vertical axis.  In both studies, increased exposure is associated
with a decrease in the biological effect being measured.  There is an
apparent study effect as exposure causes a stronger decrease in response
in Study 1 than in Study 2.  Two models are used to analyze these data:
Model 1 (orange lines) and Model 2 (green lines).  The solid lines
indicate the fits of the models to the combined data and the dashed
lines indicate the fit of the models to the data from the individual
studies.  The fit of Model 2 to the combined data (solid green line) is
clearly better (i.e., larger log-likelihood) than the fit of Model 1
(solid orange line).  However, there is a significant improvement in fit
when Model 2 is fit separately to the two studies (dotted green lines).
Thus, this model detects significant heterogeneity.  However, with Model
1 the improvement in fit is not significant (in fact shows practically
no improvement); hence there is no significant heterogeneity detected by
this model.  By the decision logic used in the analysis of the lung
cancer data from the pooled analysis to select the model based on
log-transformed exposure over the model based on untransformed exposure,
Model 2 would be ruled out in favor of Model 1 even though Model 2 is
clearly superior.

Murray Finkelstein

McMaster University, Thornhill, ON Canada

  SEQ CHAPTER \h \r 1 Peer Review of OSHA’s Preliminary Quantitative
Risk Assessment for Silica

	The draft report evaluates exposure-response data from several
occupational studies as to their suitability for quantitative assessment
of lung cancer and silicosis risk resulting from airborne exposures to
silica.  Are the strengths and limitations of the selected data sets
adequately discussed and appropriately evaluated?  Are you aware of
other study data that are better suited for quantifying lung cancer or
silicosis risk from occupational exposure to silica?  If yes, inform
OSHA of the other data.

I think that the strengths and limitations of the selected data sets
were adequately discussed and appropriately evaluated. I am not aware of
other study data that are better suited for quantifying risk.

	 The draft assessment relies on quantitative uncertainty analysis and
sensitivity analysis of exposure measurement error in key studies of
lung cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach?  If so, explain.

The use of uncertainty and sensitivity analysis by the Toxichemica team
is well explained. I think that this is an excellent approach for
evaluating uncertainty.

	The draft assessment evaluates the use of a physiologically-based
pharmacokinetic model that predicts silica lung burdens in individuals
exposed to particulates through inhalation for estimating risk from lung
cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach? If so, explain.

The analyses are clearly explained. I think that this would be a
reasonable approach for evaluating silica-induced risk only in the
absence of human epidemiologic data. I think that the application of
dust doses and inflammatory effects in rats to the prediction of
mortality in humans is too great a leap. I think that the appropriate
approach is risk assessment based upon human epidemiologic data.

	The draft assessment summarizes several published risk assessments that
use a variety of models and statistical methodologies employed by the
various analysts to fit the featured data sets.  Are the models and
approaches used by these investigators adequately explained and
evaluated?  If not, let OSHA know what needs to be added to the
presentation.

These models are adequately explained and evaluated.

	The draft report identifies and describes several key areas of
uncertainty with regard to the estimates of risk.  Were the major
uncertainties in the risk assessment adequately characterized?  If not,
explain what should be included.

I think that the major uncertainties were adequately characterized.

	The draft assessment relies on the use of cumulative exposure (or a
transformation of cumulative exposure) as the principal dose metric on
which lung cancer and silicosis risks are evaluated.  The draft also
contains a discussion of studies that are suggestive of a dose-rate
effect.  Given this discussion, is cumulative exposure a reasonable
exposure metric for silica-induced lung cancer and silicosis in exposed
workers?  Is there a more appropriate exposure metric?  If so, explain.

I am skeptical of the observation of a dose-rate effect because I think
that exposure assessment and assignment to individual workers is too
uncertain. I think that cumulative exposure is reasonable for the risk
assessment of chronic diseases such as silicosis and lung cancer.

	OSHA’s estimates of lung cancer and silicosis mortality are
represented as a range of estimates with those derived from the
diatomaceous earth and U.S. granite studies considered to be plausible
upper bound risk estimates.  OSHA also acknowledges that the risk may be
lower such as suggested by the results of the IARC multi-centric study,
which relied on pooled data from several epidemiological studies.  Is
this a sound and reasonable estimation of risk from the available data?
Is this decision adequately explained?  Should the risk estimates based
on one data set be preferred over the other?  Is there a more
appropriate representation of the lung cancer risk from silica exposure?
 If so, explain.

I believe that the best estimate is that derived from the IARC
multi-centric study because it averages over study uncertainties. In so
doing, it is possible that the heterogeneity and uncertainties blunt the
dose response relationship. Nevertheless, I think that individual study
uncertainties are sufficiently large that pooling is the best approach.
I am particularly impressed by the sensitivity analysis conducted by
Steenland and colleague. I have examined and worked with the raw
exposure data from the US granite study. I think that these data are
much too weak to be used on a stand-alone basis.

	The cumulative risk of silicosis morbidity is preliminarily considered
to be best represented by a range (approximately 3- to 4-fold) that is
based on results from four published exposure-response assessments.
Does this range reflect a sound and reasonable estimation of risk from
the available data?  Is this decision adequately explained?  Should the
risk estimates based on one data set be preferred over the other?  Is
there a more appropriate representation of the silicosis morbidity risk
from silica exposure?  If so, explain.

I agree with OSHA that the relevant cohorts are those that include
extended follow-up, including the experience of retirees. I agree that
it is important to acknowledge a sizeable range in the risk estimates,
due primarily to sampling variability, length of follow-up, and exposure
uncertainties. I think that the range presented reflects a sound and
reasonable estimation of risk from the available data. I think that the
decision is adequately explained. Because of uncertainties, I favor the
use of as many studies as are relevant, rather than relying on single
studies.

	OSHA estimated the risk of lung cancer mortality, silicosis mortality,
and silicosis morbidity for 45-year exposures to 0.25 and 0.5 mg/m3
respirable crystalline silica; these represent a range of exposures
consistent with OSHA’s current standards for construction and maritime
industry sectors, but are above OSHA’s current general industry
standards (approximately 0.1 mg/m3 for respirable quartz).  The
cumulative exposures corresponding to these higher exposure levels are
at or above the cumulative exposures of most of the more highly exposed
workers included in the studies that underlie the risk estimates.  Is
OSHA’s approach for extrapolating risk above the observed range
reasonable?  Is it clearly explained?  Is there a more appropriate
approach that should be considered to estimate risk at cumulative
exposures that are generally above the observed range of the underlying
epidemiological studies?

Extrapolation beyond the observed range depends on the adoption of a
risk model. The selection of the linear or log-linear models is clearly
explained. The approach adopted by OSHA is reasonable. An alternative
approach is simply to say that the risk is greater than X, where X is
the risk observed at the maximum exposure category in the underlying
epidemiologic studies.

Gary Ginsberg

Connecticut Department of Public Health, Hartford, CTResponse to Charge
Questions

OSHA’s Preliminary Quantitative Risk Assessment for Silica

ERG Task # 0<IP_ADDRESS>

Reviewer:  Gary Ginsberg

November 4th 2009

1.  The variety of exposure-response studies are generally well
described in terms of numbers of subjects, exposure characterization,
statistical analysis, potential confounders, and where applicable, dose
response modeling.  The report however is lacking in terms of providing
a critical appraisal of each study and its relative merit, power or
weighting for the purposes of risk assessment.  The risk assessment
section relies upon 4 studies which conducted their own quantitative
dose response assessment, accepting those cohorts as the basis for the
OSHA evaluation. However, there are numerous other studies which might
lend themselves to quantitative assessment by virtue of their exposure
and outcome measurement.  For example, Section V.C. describes many
studies which might be suitable for quantitative assessment (e.g.,
Guenel et al. 1989 of Danish stone cutters) but which are not critically
appraised for this purpose.  Further, the Cassidy 2007 European
multi-center analysis is promoted in Section V.C. as particularly useful
(even “compelling” – numerous positive qualities including
exposure assessment) but yet is not included in the Section VI
quantitative risk assessment.  One wonders whether any bias is
introduced into the assessment by the omission of one or more
potentially useful studies.  The lack of a critical appraisal of the
quantitative utility of such studies or the potential bias introduced by
their omission, weakens the Section VI analysis.

2.   I am not a statistician and don’t normally get involved with
quantitative uncertainty assessment.  Therefore, I cannot comment
directly on the detailed presentation of this work.  It does appear that
the major areas of measurement uncertainty have been identified and
dealt with in some manner by the extra effort to characterize these
uncertainties.   An area of concern however is the treatment of
potential confounding by smoking.  Page 44 assumes that the only issue
with smoking as an uncontrolled variable is the potential for smoking
rate to correlate with silica exposure in such manner to bias the
disease risk high.  The text goes on to assert that this is unlikely
from the available evidence and study design.  However, this rationale
excludes the possibility that when smoking is an uncontrolled variable
it will lead to elevated cancer risk in both the reference and
silica-exposed population leading to a high and variable baseline that
will tend to bias the results towards the null hypothesis and weaken
associations between silica and lung cancer.  I could not find any
explanation or substantiative evidence that such confounding by smoking
may not have occurred given the lack of smoking history and control for
smoking present in the underlying data.   The net result may be an
underestimation of silica-induced cancer risk relative to a non-smoking
population unless there is evidence that smoking potentiates
silica-induced lung cancer.    A similar potential exists for
underestimating cancer risk in diatomaceous earth workers simultaneously
exposed to asbestos and silica (page 46).  Once again, the concern
expressed in this document is the potential for additive risk across
these exposures to inflate the potency factor.  However, the rate of
mesothelioma in the asbestos exposed workers is not discussed.  If this
were a significant intercedent cause of mortality, it would curtail the
silica-induced cancer rate.   In addition, this report would be well
served to view radon and other uncontrolled exposure variables through
this lens of potential weakening of dose response relationships.

3.  The “PBPK” lung burden model is not well explained and pretty
much just mentioned in passing as this line of evidence is not given
substantiative weight.  PBPK usually refers to a mathematical
description of chemical fate within systemic compartments that have
parameters for organ size, blood flow and clearance processes, with QC
check conducted to ensure mass balance.  I haven’t read Kuempel et al
(2001) but it sounds more like an inhalation deposition/dosimetry model
that a PBPK model.  The model description on Pages 24-27 could be
enhanced by showing the model structure, a table of parameter values for
both species (breathing rate, respiratory tract surface areas; clearance
rates in various lung compartments), how is the model affected by
breathing rate and particle size, whether clearance is a static
parameter or allowed to vary (decrease) with increased silica burden,
and how is the threshold for critical quartz lung burden (0.39 mg/g)
set.  Also, the description of the human model at the top of Page 25 is
vague – how many coal workers, are central estimates used or are all
the data used to create a statistical distribution, how was the rat
model adapted for a standard human adult?

The lung burden model has potential utility as it defines a threshold
for lung cancer.  However, it is not explained well and this concept is
not used in the remainder of the report to assess risks from low dose
exposure.

The description of the published risk assessments is generally adequate.
 As described above, more information regarding why certain studies were
excluded from the meta analysis or not quantitatively described would be
helpful.  The issue of threshold is not given proper attention in these
descriptions.  The sense one gets is that these studies and associated
models generally find a dose response in the range of current OSHA
standards (0.05 to 0.1 mg/m3 and higher), with a threshold possibly
existing at lower concentrations:  e.g. $0.036 mg/m3 for 45 yrs based
upon critical lung burden.   The issue of possible thresholds should be
systematically evaluated for each study – was it statistically
investigated by the study authors?  Were the data sufficient to allow
such an analysis?  Do the studies agree regarding where a threshold
might lie for lung cancer and silicosis and how would such a threshold
affect OSHA’s risk assessment?

Also meriting greater description are the physical characteristics of
the silica in each study.  Given that features such as the manner in
which it was mined/produced/fractured, whether it has surface coatings,
its mineral content (quartz, cristobalite, tridymite) and its age all
appear to influence its reactivity, this should be described for each
industry studied.

The 10 cohort study reported by Steenland et al. (2001a) shows general
agreement amongst 9 of the studies but one study (South African gold
miners) showed approximately 10 fold higher potency for lung cancer
(Page 15 and Table VI-1).  OSHA reports that Steenland reports that
exclusion of that dataset was not influential in the overall
meta-analysis (likely because it contained only 77 cases out of a pooled
analysis of over a thousand).  However, that is not the end of the
story.  In toxicology and risk assessment, one should consider whether
the most sensitive study and endpoint is of high enough quality to be
the source of risk calculations or whether the entire risk range should
be presented (e.g. the gold miners representing one end of a reported
potency range) or whether some central tendency potency estimate should
be used.  It may be that the South African gold miner study is more
potent for a good reason (e.g., least confounded by smoking, most potent
form of silica) and should be given serious consideration as a stand
alone data point for potency estimation and risk calculations.  Or
perhaps that study is no better or even inferior or less relevant than
the others.  The combination of Sections V and VI provide no analysis of
this but rather just accepts the Steenland treatment of the data.

OSHA focuses on cancer potency in the range of current standards and
also on higher exposures (pp 28-32).  The rationale for this is unclear.
 Is OSHA contemplating raising the standard to make it less strict?  Why
not focus as well on the dose response at lower levels of exposure just
in case there might be a desire to lower the standards (more strict).
It strikes me that the lower end of the dose response curve may be more
interesting given the potential for thresholds (e.g., the lung burden
model; potential that silicosis is needed for lung cancer to occur) and
the potential that lowering the standard might be desirable given the
high cancer risks associated with the current standards.

As described above, I believe the major uncertainties in the estimate of
risk not adequately dealt with are the potential for confounding by
smoking to decrease the strength of associations, and the uncertainty
regarding the existence of thresholds for cancer and non-cancer
endpoints.

The studies suggesting that silica risk is driven by exposure rate more
so than cumulative exposure are not particularly numerous or compelling
and I agree with the current analysis.  Further, the cumulative exposure
metric ties into the critical lung burden I mention above.  However, one
cannot rule out the potential for dose-rate to have an influence on
disease rate and so it is appropriate to treat this as an uncertainty.
In this regard, more could be done to describe the possible
ramifications of a dose-rate model on silica risk assessment and more
mechanistic information could be brought forth regarding why dose-rate
should (or should not) be considered relevant.  For example, what
non-linearities in the biological response might exist that would be
sensitive to dose rate (e.g., threshold phenomena such as exceedance of
defense mechanisms or damage requirement needed for excitation of
immune/inflammatory processes).

Assuming cumulative exposure is the best metric for silica risk
assessment, it brings up an interesting assessment/intervention
question.  It raises the possibility that the OSHA standard should be
based upon worker cumulative exposure (in mg/m3-yrs) rather than a set
number (e.g. 0.05 ug/m3).  For example, it may be determined that to
reach a particular cancer risk target (e.g., 1 in a thousand), the
cumulative lifetime exposure should be no greater than xx mg/m3-years.
Some workers may get this faster (higher exposure, shorter period) while
for others it may take longer.  Akin to radiological worker protection,
it may be possible to have a running tally of cumulative silica exposure
and to limit further exposure once the “acceptable risk” level has
been superceded.  This approach would seem compatible with the
cumulative exposure assessments in this document and allow the “bright
line” to be a particular risk target (e.g., 1 in a thousand).  From
the current document, it is unclear what OSHA’s target or acceptable
risk level is.  While the cumulative exposure approach would require
more record keeping, affected industries might find it attractive in
that it might allow short –term occupations to have higher exposure
levels while limiting the cumulative exposure for any given worker.

7.  OSHA’s risk range is based upon the limited number of studies
which have received quantitative treatment.  As discussed above, there
may be others which would be suitable for quantitative assessment if
they were formally considered for this application, but this document
does not do so.  For example, as stated above, one study in the
Steenland et al 2001 analysis, South African gold miners, yielded a
potency that was approximately 10 times greater than the remainder of
the studies.  Perhaps that is an appropriate upper bound for lung cancer
risk.  Without further discussion of the merits of that study relative
to the others, one cannot determine how much weight to put on it.

Further, the assumption is made that this risk range applies equally to
quartz and other polymorphs such as cristobalite, and with respect to
non-cancer endpoints, that it refers specifically to silicosis.  In
lumping quartz and cristobalite potency information, OSHA should provide
better support that this is appropriate.  The quartz/cristobalite
distinction is brought up in passing on Page 41 and more detailed
explanations are supposedly provided in Sections VI-B and VI-E.  I
couldn’t find this discussion in VI-B and in a later section of VI
titled “Physical Factors that may Influence ….. (page 97-98, I guess
VI-E but unclear)” two paragraphs are given to this distinction, with
rather unconvincing result.  For example, the statement is made that a
difference between these polymorphs has not been seen in epidemiologic
studies but only a limited dataset is being referred to here, and it
evidently does not include the Park et al. 2002 data which showed 8-9
times higher silica-related mortality in diatomaceous earth workers
(cristobalite) than in the multi-center study.  Clearly some of this
difference is due to the broader case definition in Park et al. 2002,
but that doesn’t seem to account for all of the difference as a large
number (percentage undefined) of the LDOC deaths were likely silicosis.

A review by Bolsaitis and Wallace (1996) is cited as supporting no
difference in terms of hemolysis or fibrosis between cristobalite and
quartz but from the abstract that review appears to focus mostly on
surface properties rather than polymorph.  The OSHA document would be
benefited from further documentation along these lines especially since
there is at least some epidemiology of increased risk in association
with cristobalite.

OSHA may want to evaluate whether the LDOC mortality (lung disease other
than cancer, as defined by Park et al., 2002) is the more appropriate
endpoint for silica-induced non-cancer mortality risk.  Right now the
focus is on silicosis, which as stated in the document, can be an
underreported condition, sometimes called emphysema or other lung
conditions as a cause of death.  Further, as documented in Section V,
silica can induce a wide variety of lung conditions in addition to, and
without the necessary occurrence of, silicosis.  Therefore, an additive
or more inclusive approach to silica-induced non-cancer risk assessment
(as suggested by the Park et al. 2002 approach) may be more appropriate.
 It is useful that Table VI-12 pulls that data point out separately but
its unclear how much weight will be given to this potency value.

8.  OSHA appropriately narrowed the field of potential morbidity studies
to those which employed retirement followup and did a good job of
describing the pros and cons of each study.  Given the wide disparity in
exposures, exposure measures, and diagnostic procedures, it is
surprising that the potency estimates fall into a fairly narrow range.
OSHA’s characterization of this range appears to be appropriate.
However, the statement on Page 82 regarding autopsy results in the 1993
study is troubling, suggesting a high rate of false negatives.  This
implies that autopsy results are more sensitive and that there may be
some systemic under-reporting of silicosis.  While the uncertainty in
this study regarding the possible underestimation of exposure is
mentioned in summary on Page 89, the possibility of underestimation of
disease is not.  The uncertainty created by this possible source of
underestimation should be further described.

9.  The issue of extrapolation to cumulative exposures higher than the
majority of the empirical data is a concrete issue.  The lung cancer
high exposure analysis (pp 28-32) seems to be contradictory in that OSHA
argues that a linear relationship with cumulative dose is likely (page
29) but then prefers the estimates derived from the log cumulative
exposure model which flattens out the dose response at high dose.  OSHA
argues that other forms of mortality or healthy worker effect may be
behind this flattening.  Given that the US granite worker data show an
apparent flattening at cumulative exposures below the range of concern
in this question (Attfield and Costello 2004 study described on page
20), it would appear that a model that reflects a response plateau may
be appropriate.  OSHA focused on the high dose in Attfield and Costello
2004 as a possible outlier.  I agree with this interpretation but
believe that a more appropriate focus would be on the entire
dose-response curve in this study and the others.  Is there evidence
from the other studies of flattening as well?  Are there cases of a
superlinear response at the high end of cumulative dose?  It would
appear that OSHA could make more complete use of the underlying data to
support model choice.

Brian Miller

IOM Consulting Ltd., Scotland, UK

Response to Technical Charge to External Peer Reviewers

ERG Contract No. GS-10F-0125P

BPA No. DOLQ059622303

ERG Task No. 0<IP_ADDRESS>

Review of OSHA’s Preliminary Quantitative Risk Assessment for Silica

Charge Questions

The draft report evaluates exposure-response data from several
occupational studies as to their suitability for quantitative assessment
of lung cancer and silicosis risk resulting from airborne exposures to
silica.  Are the strengths and limitations of the selected data sets
adequately discussed and appropriately evaluated?  Are you aware of
other study data that are better suited for quantifying lung cancer or
silicosis risk from occupational exposure to silica?  If yes, inform
OSHA of the other data.

As far as I am aware, the studies are in the main well described and
evaluated.  It’s worth noting that the choice of radiological
opacities grade 2/1+ for analysis in the Buchanan et al. (2003) paper
was driven by the use of that level being required for compensation in
the UK systems.  The radiographs from the follow-up study were all
classified on the full ILO scale just as the earlier PFR ones had been,
and there are fuller descriptions of the studies and descriptions and
analyses of the distributions at lower levels e.g. 1/0+ in earlier
publications.  The 1998 paper gives logistic regression analyses only
for 2/1+, but the 1995 research report (available to download) also has
detailed analyses of a 1/0+ response.

Miller BG, Kinnear AG.  (1988).  Pneumoconiosis in coalminers and
exposure to dust of variable quartz content.  Edinburgh: Institute of
Occupational Medicine.  (IOM Report TM/88/17).
http://iom-world.org/pubs/IOM_TM8817.pdf

Miller BG, Hagen S, Love RG, Cowie HA, Kidd MW, Lorenzo S, Tielemans
ELJP, Robertson A, Soutar CA.  (1995).  A follow-up study of miners
exposed to unusual concentrations of quartz.  Edinburgh: Institute of
Occupational Medicine.  (IOM Report TM/95/03).

  HYPERLINK "http://iom-world.org/pubs/IOM_TM9503.pdf"
http://iom-world.org/pubs/IOM_TM9503.pdf

Miller BG, Hagen S, Love RG, Soutar CA, Cowie HA, Kidd MW, Robertson A.
(1998).  Risks of silicosis in coalworkers exposed to unusual
concentrations of respirable quartz.  Occupational and Environmental
Medicine;  55: 52-58.

There are some new data on the risk of lung cancer with respect to
respirable silica exposure, from an extended follow-up of the British
PFR mortality study:

Miller BG, MacCalman L. (2009). Cause-specific mortality in British coal
workers and exposure to respirable dust and quartz. Occup. Environ. Med.
(Published Online First: 9 October 2009. doi:10.1136/oem.2009.046151.

The above paper is summarised from:

Miller BG, MacCalman L, Hutchison PA. (2007). Mortality over an extended
follow-up period in coal workers exposed to respirable dust and quartz.
Edinburgh: Institute of Occupational Medicine.  (IOM Report TM/07/06).
 HYPERLINK "http://www.iom-world.org/pubs/IOM_TM0706rev.pdf"
http://www.iom-world.org/pubs/IOM_TM0706rev.pdf

 The draft assessment relies on quantitative uncertainty analysis and
sensitivity analysis of exposure measurement error in key studies of
lung cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach?  If so, explain.

Where there is error in exposure assessment, it is important to assess
the extent to which this may affect the estimation of the
exposure-response coefficient, and to correct for that if necessary and
possible.  Other sources of uncertainty may also be important. The
approach used is a reasonable one for assessing, describing and allowing
for such sources of uncertainty within the approach taken for
quantifying the expected or average risk, which needs to be discussed
separately (see below).

The draft assessment evaluates the use of a physiologically-based
pharmacokinetic model that predicts silica lung burdens in individuals
exposed to particulates through inhalation for estimating risk from lung
cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach? If so, explain.

Where no epidemiology exists, it may be that the only approach that can
be used for predicting risk is extrapolation from an animal model.  In
the present context, much use is made of the concept of lung burden.
This may be the correct target organ dose metric, but epidemiological
data on it is very sparse; hence the normal focus on exposure
experienced as a surrogate for dose.  The extrapolation involved
requires many more assumptions than assessing risk from epidemiological
studies, and it may not be prudent to place the same degree of reliance
on the model-based estimates as on those from epidemiological
observation.  Having said that, one advantage of the animal model is
that the exposure is usually rather better characterized than in humans.

The draft assessment summarizes several published risk assessments that
use a variety of models and statistical methodologies employed by the
various analysts to fit the featured data sets.  Are the models and
approaches used by these investigators adequately explained and
evaluated?  If not, let OSHA know what needs to be added to the
presentation.

The studies from which the risk coefficients are derived are based on
outcomes (mortality, diagnosis of silicosis) at different lengths of
follow-up from the exposures.  In a situation where the effect of an
exposure on the progression of risk may be time-dependent (see 6 below),
these coefficients may not be comparable.  There should be more
discussion of the possible effects of this disparity.

The draft report identifies and describes several key areas of
uncertainty with regard to the estimates of risk.  Were the major
uncertainties in the risk assessment adequately characterized?  If not,
explain what should be included.

I have no other areas of uncertainty to suggest.  (We have quite enough
to deal with already.)

The draft assessment relies on the use of cumulative exposure (or a
transformation of cumulative exposure) as the principal dose metric on
which lung cancer and silicosis risks are evaluated.  The draft also
contains a discussion of studies that are suggestive of a dose-rate
effect.  Given this discussion, is cumulative exposure a reasonable
exposure metric for silica-induced lung cancer and silicosis in exposed
workers?  Is there a more appropriate exposure metric?  If so, explain.

Cumulative exposure has been widely used in studies of occupational
health risks, and it has been shown theoretically that it is an
appropriate metric in circumstances where the exposure acts over a short
period of time after it is experienced.   This is true of e.g. ionizing
radiation exposures, and has been found to be a reasonable fit for
exposure to respirable coal dust (in which the whole dust rather than
the silica component has usually appeared to drive the risk).
Additionally, in most coalworker epidemiology, to a good approximation,
pneumoconiosis does not progress after exposure ceases.

With silica exposure the responses are rather different.  High exposures
can precipitate severe or accelerated reactions, and silicosis, once
well established, is likely to progress even without further exposure.
The data of Miller et al (1998), in the reanalysis of Buchanan et al
(2003), showed higher silicosis risks, mass for mass, from exposures
derived from higher concentrations.  This might be described as a
dose-rate effect, although that would not specifically address the
mechanism by which it derives, which is likely to be due to the
overloading of the human body’s defence and clearance mechanisms.

Thus there is good reason to believe that cumulative exposure, with no
allowance for the rate at which it accumulated, and no consideration of
persistence of its effects over time, may not be the most appropriate
metric, and that a metric that allowed for these aspects would be
preferred.  However, to be useful for risk assessment, such a metric
would require a more complex formula for its calculation, and would need
quantitative estimates of the coefficients for that formula.  Such
estimation would need very good exposure data.  Buchanan et al (2003)
had some success in this area, notably in establishing the relative
increase in risk from exposures at higher concentrations, but were
unable to obtain a reliable coefficient for the effect of persistence.
This was assumed to be because the high silica exposures were
accumulated over a relatively short time period, so the follow-up time
varied little across the study group, and the power to estimate an
effect of elapsed time was accordingly very low.  It may be that other
studies with a wider range of follow-up lengths might be informative on
this aspect through re-analysis.

OSHA’s estimates of lung cancer and silicosis mortality are
represented as a range of estimates with those derived from the
diatomaceous earth and U.S. granite studies considered to be plausible
upper bound risk estimates.  OSHA also acknowledges that the risk may be
lower such as suggested by the results of the IARC multi-centric study,
which relied on pooled data from several epidemiological studies.  Is
this a sound and reasonable estimation of risk from the available data?
Is this decision adequately explained?  Should the risk estimates based
on one data set be preferred over the other?  Is there a more
appropriate representation of the lung cancer risk from silica exposure?
 If so, explain.

The calculation and presentation of risk estimates needs further
elucidation and discussion.

The section on risk assessment for lung cancer mortality displays
several different estimates of what it calls ‘lifetime’ risks of 45
years’ exposure to silica at chosen average concentrations, starting
from age 20.  These risks are based on predicting numbers of deaths,
allowing for intercurrent mortality from other causes, but it is not
clear exactly how this is done.  The commissioned report summarizing
these estimates (ToxaChemica, 2004) does not spell this out, merely
referring to a paper from 1974; the paper references Chiang, a standard
reference on life table methods.  Different estimates for mortality and
morbidity are quoted that predict over different periods, variously up
to and truncated at ages 65, 75 and 85.  None of these can claim to be
‘lifetime’ risks, although that to age 85 comes closest.  Certainly,
if silica exposure has an effect on lung cancer risk, it would be
expected to produce excess cases from the rising background risks way
beyond age 65, particularly since the data suggest no reduction of
excess risk on cessation of exposure.  So summation to 65 must produce a
considerable underestimate of the total impact.  To tabulate these
together as if they are comparable, as in Table VI-9, seems unwise
unless accompanied by carefully-worded warnings.

How large is the underestimation of lifetime risk depends on exactly how
the calculation was done.  If I interpret it correctly, the text
suggests that the risk is for 45 years’ exposure starting at age 20,
so follow-up from the end of exposure to age 65 has zero duration, and
therefore should have zero risk.  However, non-zero risks to age 65 are
shown in e.g. Table VI-9, suggesting that the life-table calculation is
done differently.  It is possible that the calculation proceeds stepwise
through the years, introducing excess risk as exposure cumulates, in
which case excess cases could be predicted to occur from 15 years after
exposure began (to allow for latency), but then those that die before
age 65 do not experience 40 years’ exposure.

The process of predicting excess cases using life-table methods is a
purely arithmetic process, easily done with standard spreadsheets, but
the answers produced depend critically on various assumptions. Whether
to allow time-dependent exposure effects, and for how long to calculate
a follow-up are among these, and need to be described carefully and
accurately.  It is not difficult to produce estimates up to advanced
ages, which might truly be considered ‘lifetime’, so it is not clear
why any estimate so labeled should be truncated at age 65.

	The cumulative risk of silicosis morbidity is preliminarily considered
to be best represented by a range (approximately 3- to 4-fold) that is
based on results from four published exposure-response assessments.
Does this range reflect a sound and reasonable estimation of risk from
the available data?  Is this decision adequately explained?  Should the
risk estimates based on one data set be preferred over the other?  Is
there a more appropriate representation of the silicosis morbidity risk
from silica exposure?  If so, explain.

There is ample evidence that the morbidity risks from silica vary widely
across industries and across exposures that differ in nature and in
composition.  For that reason alone, different studies are likely to
produce a range of estimates.  All other things being equal, for
purposes of regulation one might want to focus on the highest risk
estimates.  However, all other things may not be equal.  For example, it
should be clear that much of the risk of silicosis from the Miller et al
(1998) study was from short exposures at concentrations well above the
target concentrations considered here.

Although the Miller study is highlighted as having the
best-characterised exposures, the most recently published analyses
(Buchanan et al.) were of a response at ILO category 2/1+, and therefore
fewer than if all responses at 1/0+ had been taken.  It would of course
be possible to use from these data the results of analyses with a 1/0+
response, if that were required:  see the publications listed in answer
to Q1.  Whatever response is considered, interpretation needs to bear in
mind that the radiological responses were taken at a particular point in
time, and that it is both possible and likely that the abnormalities in
at least some of the workers studied would have progressed further, even
though no longer exposed.  With a progressive disease process,
quantitative lifetime risk estimates must take into account the rate of
progression over time.

OSHA estimated the risk of lung cancer mortality, silicosis mortality,
and silicosis morbidity for 45-year exposures to 0.25 and 0.5 mg/m3
respirable crystalline silica; these represent a range of exposures
consistent with OSHA’s current standards for construction and maritime
industry sectors, but are above OSHA’s current general industry
standards (approximately 0.1 mg/m3 for respirable quartz).  The
cumulative exposures corresponding to these higher exposure levels are
at or above the cumulative exposures of most of the more highly exposed
workers included in the studies that underlie the risk estimates.  Is
OSHA’s approach for extrapolating risk above the observed range
reasonable?  Is it clearly explained?  Is there a more appropriate
approach that should be considered to estimate risk at cumulative
exposures that are generally above the observed range of the underlying
epidemiological studies?

The mechanism of the approach is clearly explained;  the appropriateness
of the methodology depends on cumulative exposure being the correct
metric, and this is discussed above.  A different metric would
presumably produce a different set of differentials between the average
concentrations.

Edits, corrections and suggestions

P12 para 2 ?Make explicit that in each set of odds ratios the first is
set arbitrarily at 1.0 and therefore has a different meaning from the
others.

P13 para 2 The non-spline models…

P16 para 1 e.g. -> i.e.

P18 para 2 It should not be a surprise that results from Cox- type
analyses and Poisson regression are similar, since the underlying model
in both is the same.  Where they may differ is in the extent of grouping
applied.  If the same grouping strategy is applied, the results will be
identical.  So often these are compared as if they were different
models, when they’re not.

Same again on P39

P32 para 1 line10 estimate -> estimates

P78 para 1 Poission -> Poisson

P103 para 2 difference -> differences

P107 para 1 OSHA estimates the risk *up to what age?* to be…

P114 para 2 may -> must

Andrew Salmon

Private Consultant, Lafayette, CAReview of OSHA’s Preliminary
Quantitative Risk Assessment for Silica

General Comment

Compared to the more usual kind of quantitative risk assessment study,
this is a very peculiar document.  The usual risk assessment paradigm
involves hazard identification, exposure assessment, dose-response
assessment for hazards identified as being of concern, and finally a
risk characterization which seeks to identify either a slope factor for
non-threshold effects, or a health-protective level where the effect of
concern is considered to show a threshold.  These conclusions are then
combined by the risk manager with any other relevant considerations
(including measurement and feasibility) in setting suitable trigger
levels for regulatory action.  The section on health effects does a
thorough job of identifying and reviewing the information on health
hazards.  This section on the other hand starts with the previously
chosen regulatory levels, and seeks an analysis of various available
data to provide estimates of risk for key endpoints at these exposure
levels.

Given this perspective, which is the inverse of the normal approach, the
document makes a very good case that substantial adverse health effects
are anticipated in workers exposed for a working lifetime to these
predefined exposure levels.  The most thoroughly developed analyses are
for lung cancer incidence and mortality from silicosis, which are severe
endpoints, and the principal concern in selection of dose-response
models appears to have been the accuracy with which the data are fitted
in the range of the target exposures of interest.  It is hard not to
conclude from a prediction of a 2% lung cancer incidence in workers
exposed at the lower PEL that these regulatory levels are insufficient
to protect workers’ health.  Yet, because of the studies, models and
endpoints selected this report contributes almost nothing to
consideration of what might be more reasonable levels of exposure that
should be considered at least as goals, even if they prove difficult or
expensive to achieve.  In particular, there is no consideration of
dose-response modeling at the lower end of the observed dose ranges, and
no consideration of the possible existence and location of a threshold
in the dose-response curve for silicosis.  There is a tendency in the
current analysis to concentrate on severe endpoints such as mortality
and severe grades of silicosis (which are observed at the exposure
levels predetermined to be of interest), rather than to evaluate milder,
but still significant endpoints which are observed in some studies at
substantially lower exposure levels.

As in the case of most other non-cancer health effects, our
understanding of the mechanism for silicosis induction by quartz
particles, although far from complete, is certainly consistent with the
possibility of a threshold in the dose response relationship, although
this threshold might be well below the levels commonly encountered in
high-risk occupational settings.  The existence of such a threshold for
silicosis is supported by the fact that, although background exposure to
crystalline silica is not zero, this disease is not usually observed in
the general population (although a few special situations producing
“environmental silicosis” are known).  In more specific terms,
Schenker et al (2009) observed histologically identifiable
pneumoconiosis in agricultural workers from the dusty California Central
Valley, but not in individuals from the same area without the heavier
exposures characteristic of employment in agriculture.  Quantitative
analyses of silicosis dose-response which did consider the lower dose
ranges (e.g. Collins et al., 2005) have generally assumed a model which
does imply a threshold, rather than the linear, logistic or log-linear
relationships used to model the response in the range considered by
OSHA.

On the other hand, a threshold for lung cancer induction is not
necessarily expected on theoretical grounds.  There might nevertheless
be such a threshold, or at least a substantial increase in the dose
response slope at higher exposures, especially if the hypothesized link
between lung cancer and silicosis (or some precursor to that condition)
were to be established. The demonstration of any such thresholds would
have important implications for defining “safe” or at least low-risk
exposures in occupational settings.  Toxichemica (2004), citing
Steenland and Deddens (2002), note that such a threshold may in fact
exist at low levels –around 10 µg/m3, although they were unable to
confirm this from a purely statistical standpoint.  It is a significant
omission both in terms of defining a health protective standard, and in
analyzing possible mechanisms of silica lung carcinogenesis, that the
OSHA document does not further examine this possibility, and the
relationship between possible thresholds for lung carcinogenesis and for
silicosis.

Charge Questions

The draft report evaluates exposure-response data from several
occupational studies as to their suitability for quantitative assessment
of lung cancer and silicosis risk resulting from airborne exposures to
silica.  Are the strengths and limitations of the selected data sets
adequately discussed and appropriately evaluated?  Are you aware of
other study data that are better suited for quantifying lung cancer or
silicosis risk from occupational exposure to silica?  If yes, inform
OSHA of the other data.

Response:

The studies considered are adequately described and evaluated.  In
particular, the U.S. studies and the IARC meta-analysis for lung cancer
are described in sufficient detail and carefully evaluated.  However,
the discussion of silicosis and choice of key studies is somewhat less
convincing.  The consideration of other possible datasets, particularly
the data on South African gold miners, receive somewhat more cursory
treatment.  The recent paper by Churchyard et al. (2004) describing
silicosis morbidity in black gold miners is important both for the high
level of effect seen in these workers and the use of gravimetric
exposure measures.  However, although this paper was briefly noted
elsewhere by OSHA, it is not considered in this section.  The existence
of analyses other than those performed by OSHA and its regular
collaborators is not consistently acknowledged.  This is unfortunate
since some of these analyses do to some extent address the question of
dose-response at lower levels, which is not adequately discussed in this
section (See for instance Collins et al., 2005 and OEHHA, 2005),
analyzing the data of Hnizdo and Sluis-Cremer, 1993; Steenland and
Brown, 1995; Chen et al., 2001 and Churchyard et al., 2004).  The focus
on extreme endpoints is illustrated by the extensive coverage devoted to
analysis of silicosis mortality, which is a good technical analysis but
from a public health standpoint feels like an admission of failure!
Also, the choice of the Scottish mining study (Miller et al., 1998) as a
key study for silicosis dose-response analysis is colored by this
perspective.  This is undoubtedly an excellent study from the technical
standpoint, but its choice of a more severe cut-point (ILO 2/1) for the
radiographic diagnosis sets it apart as being less sensitive than most
of the other studies in the field, in spite of evidence discussed here
and in the section on health effects showing that even an ILO 1/1
radiographic level substantially under-diagnoses silicosis as assessed
by later follow-up or other methods e.g. histology.  There appears to be
no discussion of the complicating fact that these coal miners were also
exposed to other pneumoconiosis-inducing dusts, notably coal dust.
Miller and his co-authors spend some time addressing this point in the
paper, but it is not referenced in OSHA’s narrative.

Evaluation of the dose-response relationships for disease endpoints
related to low-dose silica exposure will require evaluation of different
studies and dose-response models from those used in the existing
assessment, since those presented here (e.g. the study by Miller et al.,
1998 and linear or log-linear models) were selected for their
informative value at the pre-defined levels of interest rather than for
any information on dose-response at lower levels.  The appropriate
models would need to be selected and justified on the basis of the data
available in the lower exposure ranges, including the likelihood of a
threshold at least for non-cancer effects, as discussed above.  This
different approach is necessary to obtain a realistic evaluation of the
responses seen in the lower dose range.

 The draft assessment relies on quantitative uncertainty analysis and
sensitivity analysis of exposure measurement error in key studies of
lung cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach?  If so, explain.

Response:

The approach used is reasonable to address uncertainty in exposure
estimation.  Indeed, given OSHA’s recognized expertise in this area it
is unsurprising that they and their contractor (Toxichemica) have done a
thorough, indeed exhaustive, job on this aspect.  The ultimate
conclusion that there is some uncertainty, but that it does not
undermine the basic conclusions of the quantitative analysis, is
reassuring, although perhaps a little underwhelming given the amount of
effort that was applied to this topic.

The draft assessment evaluates the use of a physiologically-based
pharmacokinetic model that predicts silica lung burdens in individuals
exposed to particulates through inhalation for estimating risk from lung
cancer and silicosis.  Are these analyses clearly explained and
evaluated?  Is this a reasonable approach for evaluating silica-induced
lung cancer and silicosis in exposed workers?  Is there a more
appropriate approach? If so, explain.

Response:

The description of the lung-burden analysis by Kuempel et al. (2001),
and the further analysis by Toxichemica (2004), is quite brief and
limited mainly to describing the overall conclusions of this work.  It
is not sufficiently detailed to allow a reader to determine exactly what
was done, or whether the implicit assumptions are reasonable.  What is
presented sounds reasonable and interesting, but Toxichemica’s
eventual conclusion appears to be that it does not improve the analysis
of Steenland’s pooled cancer data relative to the simpler cumulative
exposure model.  It seems relatively unlikely that the available data on
lung cancer or silicosis are of sufficient precision to directly support
use of this or any other complex dose metric.  Toxichemica (2004) also
note that the effect of the lung burden calculation is to build a lag
time into the dose-response model.  While this is a reasonable
assumption, and there is limited evidence that this is appropriate for
the silicosis data, there are a number of explanations besides
dependence on silica lung burden for this effect.

The draft assessment summarizes several published risk assessments that
use a variety of models and statistical methodologies employed by the
various analysts to fit the featured data sets.  Are the models and
approaches used by these investigators adequately explained and
evaluated?  If not, let OSHA know what needs to be added to the
presentation.

Response:

The description of the models used and statistical methods are in
general adequately described.  OSHA relies on the models used by the
published analysts although these are in most cases very simplistic,
e.g. linear with cumulative dose.  These simple models are adequate to
fit the data in the observed ranges of the specific studies considered
(indeed, many of the studies lack the precision and/or cover an
insufficient range of different exposures to support anything more
complex).  OSHA describes these models well and confirms their validity
for prediction of response at the PELs, but makes no effort to determine
whether more informative models could be developed which would be useful
in critical exposure ranges such as those below these arbitrarily
pre-defined PELs.

The draft report identifies and describes several key areas of
uncertainty with regard to the estimates of risk.  Were the major
uncertainties in the risk assessment adequately characterized?  If not,
explain what should be included.

Response:

Given that so much thoughtful analysis was devoted to uncertainty in the
exposure measurements, it is unfortunate that the same level of
investigation was not directed to determining the uncertainty in
determination of the other half of the dose-response relationship.
There is some useful qualitative discussion of the limitations of death
certificates and the reliability, but low sensitivity, of the ILO
radiographic method of diagnosing silicosis in the health effects
section.  However, there is no quantitative analysis of uncertainty in
determination of health endpoints beyond the usual statistical tests
reported in epidemiological studies.  The overall uncertainties in
determining health endpoints could easily be as great as, or greater
than, the uncertainties in exposure assessment, especially for silicosis
morbidity and mortality.  An initial attempt at quantifying
uncertainties in health endpoints could be obtained by reviewing
confidence limits on measures such as SMRs for specific endpoints, and
the distribution of severity or response at different dose levels. The
latter consideration might be helpful in reviewing the impact of
reliance on measures of higher severity such as mortality, higher-grade
radiographic diagnosis, or eligibility for workers’ compensation, in
some studies.   However, there is an underlying problem in that although
specific quantitative endpoints such as cancer incidences or specific
radiographic grades of silicosis are well defined, the overall disease
process is not well characterized by any established integrative
measures, so estimates of the overall disease burden are subject to
substantial qualitative as well as quantitative uncertainties.

The draft assessment relies on the use of cumulative exposure (or a
transformation of cumulative exposure) as the principal dose metric on
which lung cancer and silicosis risks are evaluated.  The draft also
contains a discussion of studies that are suggestive of a dose-rate
effect.  Given this discussion, is cumulative exposure a reasonable
exposure metric for silica-induced lung cancer and silicosis in exposed
workers?  Is there a more appropriate exposure metric?  If so, explain.

Response:

It appears that cumulative exposure is the most appropriate dose metric,
and that this is adequate to correlate with the observed response data
in all the major studies examined.  It is certainly possible that there
are dose rate effects, especially at extremely high (or low) doses, but
the studies considered do not, it seems, provide clear and unequivocal
evidence to demonstrate or quantify these effects.  Similarly, it is
possible that lung residence time is a factor in the development of
silicosis and other health endpoints, but the study which evaluated this
metric did not show that it materially improved the correlation with
health effects beyond what was obtained with the cumulative exposure
metric.

OSHA’s estimates of lung cancer and silicosis mortality are
represented as a range of estimates with those derived from the
diatomaceous earth and U.S. granite studies considered to be plausible
upper bound risk estimates.  OSHA also acknowledges that the risk may be
lower such as suggested by the results of the IARC multi-centric study,
which relied on pooled data from several epidemiological studies.  Is
this a sound and reasonable estimation of risk from the available data?
Is this decision adequately explained?  Should the risk estimates based
on one data set be preferred over the other?  Is there a more
appropriate representation of the lung cancer risk from silica exposure?
 If so, explain.

Response:

In my opinion the presentation of the lung cancer and silicosis
mortality risk for the exposure range considered is well handled in this
section.  The IARC multi-center study probably represents a reliable
median estimate, but by its nature is likely to underestimate the upper
bound on risk in a situation where individual cohorts show real
variation in risks due to differences in the nature and intensity of the
exposure and the effectiveness in determining health endpoints.  The
description in this section describing and characterizing the range of
available estimates is therefore appropriate.

The cumulative risk of silicosis morbidity is preliminarily considered
to be best represented by a range (approximately 3- to 4-fold) that is
based on results from four published exposure-response assessments.
Does this range reflect a sound and reasonable estimation of risk from
the available data?  Is this decision adequately explained?  Should the
risk estimates based on one data set be preferred over the other?  Is
there a more appropriate representation of the silicosis morbidity risk
from silica exposure?  If so, explain.

Response:

A range of risk estimates is presented for the specific concentrations
previously identified as OSHA PEL values.  This is obviously of interest
in the specific context of this assessment, but it does not provide an
evaluation of the overall relationship between exposure and effect,
especially for an effect such as silicosis where the dose-response
relationship is not necessarily linear at low doses.  The charge
question refers to four studies chosen for principal evaluation, but the
summary description (page 112 and page 114) refers to five studies (Chen
et al., 2001; Chen et al., 2005; Hnizdo and Sluis-Cremer, 1993; Miller
et al., 1998 and Steenland and Brown, 1995b) as useful in estimating
long-term risk of silicosis.  This dichotomy needs to be clarified as to
exactly which sources OSHA is using as the basis of its range of
estimates.

At several points in the discussion OSHA notes concerns with the
exposure measures used in the South African studies (specifically Hnizdo
and Sluis-Cremer, 1993 in this context).  It should be noted that
although obviously there is some uncertainty in any process of
conversion of exposure measures from one basis to another these data
have in this case been thoroughly explored (Beadle and Bradley, 1970;
Page-Shipp and Harris, 1972), providing reasonable confidence in the
results.  The assertion of Gibbs and duToit (2002) that, based on the
assumed silica content of the dust, exposure was underestimated by
Hnizdo and Sluis-Cremer (1993) has been shown to be incorrect (OEHHA,
2005).  Other sources (e.g. Kielblock et al., 1997) suggest that if
anything the uncertainty is in the other direction.  The more recent
report by Churchyard et al. (2004) is also useful to compare with the
earlier South African results, since these authors used gravimetric
exposure measurements in similar situations to the earlier
particle-based data.  This data set is also worth consideration in
providing additional estimates of silicosis morbidity, although the size
of the cohort is not as large as that examined by Hnizdo and
Sluis-Cremer (1993).  The large size and inclusion of job classes with a
substantial range of different exposure levels make the study by Hnizdo
and Sluis-Cremer (1993) important for determining the overall dose
response for silicosis.  Health endpoint determination used a relatively
sensitive endpoint (ILO 1/1) and exposure measures although not by the
latest preferred method appear to have been systematic and consistent.
This is a significant contrast to the study (Miller et al., 1998) chosen