Steenland et al. (2001a) estimated excess lifetime risk of lung
cancer based on a 10-cohort pooled study, which included several
cohorts with significant numbers of workers with median cumulative and
average exposures below those allowed by the previous general industry
PEL (Document ID 0452). Results indicated that 45 years of exposure at
0.1 mg/m\3\ (100 [mu]g/m\3\) would result in a lifetime risk of 28
excess lung cancer deaths per 1,000 workers (95% confidence interval
(CI) 13-46 per 1,000). An alternative (non-linear) model yielded a
lower risk estimate of 17 per 1,000 (95% CI 2-36 per 1,000).
    A follow-up letter by Steenland and Deddens (2002, Document ID
1124) addressed the possibility of an exposure threshold effect in the
pooled lung cancer analysis conducted by Steenland et al. in 2001.
According to Dr. Steenland, ``We further investigated whether there was
a level below which there was no increase in risk, the so-called
threshold. So we fit models that had a threshold versus those that
didn't, and we explored various thresholds that might apply'' (Document
ID 3580, Tr. 1229). Threshold models using average exposure and
cumulative exposure failed to show a statistically significant
improvement in fit over models without a threshold. However, the
authors found that when they used the log of cumulative exposure (a
transformation commonly used to reduce the influence of high exposure
points on a model), a threshold model with a 15-year lag fit better
than a no-threshold model. The authors reported the best threshold
estimate at 4.8 log mg/m\3\-days (Document ID 1124, p. 781), or an
average exposure of approximately 10 [mu]g/m\3\ over a 45-year working
lifetime, one-fifth of the final PEL. Dr. Steenland explained what his
analysis indicated regarding a cumulative exposure threshold for lung
cancer: ``we found, in fact, that there was a threshold model that fit
better than a no-threshold model, not enormously better but better
statistically, but that threshold was extremely low . . . far below the
. . . silica standard proposed by OSHA'' (Document ID 3580, Tr. 1229).
    In response to comments from ACC Panel members Dr. Valberg and Dr.
Long that the analysis presented by Steenland et al. showed a clear
threshold at a level of cumulative exposure high enough to bear on
OSHA's choice of PEL (Document ID 2330, p. 20), Dr. Steenland explained
that their conclusion was based on a misreading of an illustration in
his study:

    [I]f you look at the figure, you see that the curve of the
spline [a flexible, nonlinear exposure-response model] starts to go
up around four on the log scale of microgram per meter cubed days.
And if you transform that from the log to the regular scale, that is
quite consistent with the threshold we got when we did a formal
analysis using the log transform model [discussed above] (Document
ID 3580, Tr. 1255).

    The ACC representatives' comments do appear to be based on a
misunderstanding of the figure in question, due to an error in Dr.
Steenland's 2001 publication in which the axis of the figure under
discussion was incorrectly labeled. This error was later corrected in
an erratum (Document ID 3580, Tr. 1257; Steenland et al., 2002,
Erratum. Cancer Causes Control, 13:777).
    In addition, at OSHA's request, Drs. Steenland and Bartell
(ToxaChemica, 2004, Document ID 0469) conducted a quantitative
uncertainty analysis to examine the effects of possible exposure
measurement error on the pooled lung cancer study results (see Section
V.K, Comments and Responses Concerning Exposure Estimation Error and
ToxaChemica's Uncertainty Analysis). These analyses showed no evidence
of a threshold effect for lung cancer at the final or previous PELs.
Based on Dr. Steenland's work, therefore, OSHA believes that no-
threshold models are appropriate for evaluating the exposure-response
relationship between silica exposure and lung cancer. Even if
commenters are correct that threshold models are preferable, the
threshold is likely at a level of cumulative exposure significantly
below what a worker would accumulate in 45 years of exposure at the
final PEL, and is therefore immaterial to this rulemaking (see Document
ID 1124, p. 781).
b. Vermont Granite Workers
    In the Preliminary QRA and supplemental literature review, OSHA
reviewed several studies on lung cancer among silica-exposed workers in
the Vermont granite industry, whose exposures were reduced to
relatively low levels due to a program for dust control initiated in
1938-1940 by the Vermont Division of Industrial Hygiene (Document ID
1711, pp. 97-102; 1711, Attachment 1, pp. 2-5; 1487, p. 73). As
discussed above, Verma et al. (2012) reported that all jobs in the
industry had average exposure concentrations at or below 100 [mu]g/
m\3\--most of them well below this level--in the time period 1950-2004
after implementation of exposure controls (Document ID 1487, Table IV,
p. 75).
    Attfield and Costello (2004) examined a cohort of 5,414 Vermont
granite workers, including 201 workers who died of lung cancer
(Document ID 0285, pp. 130, 134). In this study, cancer risk was
elevated at cumulative exposure levels below 4.5 mg/m\3\-yrs, the
amount of exposure that would result from a 45-year working lifetime of
exposure at the previous PEL. The authors reported elevated lung cancer
in all exposure groups, observing statistically significant elevation
among workers with cumulative exposures between 0.5 and 1 mg/m\3\-yrs
(p < 0.05), cumulative exposures between 2 and 3 mg/m\3\-yrs (p <
0.01), and cumulative exposures between 3 and 6 mg/m\3\-yrs (p < 0.05)
(Document ID 0285, p. 135). These findings indicate that a threshold in
exposure-response for lung cancer is unlikely at cumulative exposure
levels associated with 45 years of exposure at the previous PEL and
below.
    Vacek et al. (2011) examined a group of 7,052 men, overlapping with
the Attfield and Costello cohort, who worked in the Vermont granite
industry at any time between January 1, 1947 and December 31, 1998
(Document ID 1486). Like Attfield and Costello, Vacek et al. reported
significantly elevated lung cancer (p < 0.01) (Document ID 1486, p.
315). Most of the lung cancer cases in Vacek et al. (305/356) had
cumulative exposures less than or equal to 4.1 mg/m\3\-yrs (Document ID
1486, p. 316), below the cumulative exposure level of 4.5 mg/m\3\-yrs
associated with 45 years of exposure at the previous PEL and below.
However, unlike Attfield and Costello, Vacek et al. did not find a
statistically significant relationship of increasing lung cancer risk
with increasing silica exposure, leading Vacek et al. to conclude that
increased lung cancer mortality in the cohort may not have been due to
silica exposure (Document ID 1486, p. 312).
    The strengths and weaknesses of both studies and the differences
between them that could account for their conflicting conclusions were
discussed in great detail in Section V.F, Comments and Responses
Concerning Lung Cancer Mortality. For the purpose of evaluating the
effects of low concentrations of silica exposure, as well as whether a
threshold exposure exists, OSHA believes the Attfield and Costello
study may merit greater weight than Vacek et al. As discussed in
Section V.F, Comments and Responses Concerning Lung Cancer Mortality,
OSHA believes Attfield and Costello's choice to exclude the highest
exposure group from their analysis likely improved their study's

estimate of the exposure-response relationship at lower exposures; by
making this choice, they limited the influence of highly uncertain
exposure estimates at higher levels and helped to reduce the impact of
the healthy worker survivor effect. The Agency acknowledges the
strengths of the Vacek et al. analysis as well, including longer
follow-up of workers.
    In conclusion, OSHA does not find compelling evidence in these
studies of Vermont granite workers of a cumulative exposure threshold
for lung cancer in the exposure range below the previous general
industry PEL. This conclusion is based on the statistically significant
elevations in lung cancer reported in both cohorts described above,
which were composed primarily of workers whose cumulative exposures
were below the level associated with a working lifetime of exposure.
However, OSHA acknowledges that a strong conclusion regarding a
threshold is difficult to draw from these studies, due to the
disagreement between Attfield and Costello and Vacek et al. regarding
the likelihood that excess lung cancer among Vermont granite workers
was due to their silica exposures.
c. Industrial Sand Workers
    OSHA's Preliminary QRA (Document ID 1711, pp. 285-287) evaluated a
2001 case-control analysis of industrial sand workers including 2,640
men employed before 1980 for at least three years in one of nine North
American sand-producing plants. One of the sites was a large associated
office complex where workers' exposures were lower than those typically
experienced by production workers (Hughes et al., 2001, Document ID
1060). A later update by McDonald et al. (2005, Document ID 1091)
eliminated one plant, following 2,452 men from the 8 remaining U.S.
plants. Both cohorts overlapped with an earlier industrial sand cohort,
including 4,626 workers at 18 plants, which was included in Steenland
et al.'s pooled analysis (2001a, Document ID 0452). OSHA noted that
these studies (Hughes et al., 2001, Document ID 1060; McDonald et al.,
2005, 1092; Steenland and Sanderson, 2001, 0455) showed similar
exposure-response patterns of increased lung cancer mortality with
increased exposure.
    In the Final Peer Review Report, Dr. Ginsberg commented on the
relevance of the industrial sand cohort studies, which included low-
exposed workers with exceptionally well-characterized exposures, for
threshold issues:

    With respect to the body of silica epidemiology literature,
perhaps the case with the least amount of measurement error is of US
industrial sand workers wherein many measurements were made with
filter samples and SRD determination of crystalline silica and in
which there was very careful estimation of historical exposure for
both silica and smoking (MacDonald et al. 2005; Steenland and
Sanderson 2001; Hughes et al. 2001) (Document ID 3574, pp. 22-23).

    OSHA agrees with Dr. Ginsberg's assessment of these studies and has
found them to be particularly high quality. Thus, the Agency was
especially interested in the studies' findings, which showed that
cancer risk was elevated at cumulative exposure levels below 4.5 mg/
m\3\-yrs, the amount of exposure that would result from a 45-year
working lifetime of exposure at the previous PEL. OSHA believes these
results provide strong evidence against a threshold in cumulative
exposure at any level high enough to impact OSHA's choice of PEL. Dr.
Ginsberg agrees with OSHA's conclusion (Document ID 3574, p. 23).
d. Other Studies
    Comments submitted by the ACC briefly mentioned several
epidemiological studies that, they claim, ``suggest the existence of a
threshold for any increased risk of silica-related lung cancer,''
including studies by Sogl et al. (2012), Mundt et al. (2011), Pukkala
et al. (2005), Calvert et al. (2003), Checkoway et al. (1997), and
Steenland et al. (2001a). OSHA previously reviewed several of these
studies in the Review of Health Effects Literature and Preliminary
Quantitative Risk Assessment, and the Supplemental Literature Review,
though not with specific attention to their implications for exposure-
response thresholds (Document ID 1711, pp. 139-155; 1711, Attachment 1,
pp. 6-12). The studies cited by ACC are discussed below, with the
exception of Steenland et al. (2001a), which was previously reviewed in
this section.
e. German Porcelain Workers
    OSHA reviewed Mundt et al. (2011, Document ID 1478) in its
Supplemental Literature Review (Document ID 1711, Attachment 1, pp. 6-
12). As discussed there, Mundt et al. examined the risks of silicosis
morbidity and lung cancer mortality in a cohort of 17,644 German
porcelain manufacturing workers who had participated in medical
surveillance programs for silicosis between 1985 and 1987. This cohort
was also examined in a previous paper by Birk et al. (2009, Document ID
4002, Attachment 2).
    Quantitative exposure estimates for this cohort showed an average
annual exposure of 110 [mu]g/m\3\ for workers hired prior to 1960 and
an average of 30 [mu]g/m\3\ for workers hired after 1960. More than 40
percent of the cohort had cumulative exposures less than 0.5 mg/m\3\-
yrs at the end of follow-up, and nearly 70 percent of the cohort had
average annual exposures less than 50 [mu]g/m\3\ (Mundt et al., 2011,
Document ID 1478, pp. 283-284).
    The lung cancer mortality hazard ratios (HRs) associated with
average annual exposure were statistically significant in two of the
four average annual exposure groups: 2.1 (95% CI 1.1-4.0) for average
annual exposure group >50-100 [mu]g/m\3\ and 2.4 (95% CI 1.1-5.2) for
average annual exposure group >150-200 [mu]g/m\3\, controlling for age,
smoking, and duration of employment. In contrast, the HRs for lung
cancer mortality associated with cumulative exposure were not
statistically elevated after controlling for age and smoking.
    The authors suggested the possibility of a threshold for lung
cancer mortality. However, no formal threshold analysis for lung cancer
was conducted in this study or in the follow-up threshold analysis
conducted on this population by Morfeld et al. for silicosis (2013,
Document ID 4175). Having reviewed this study carefully, OSHA believes
it is inconclusive on the issue of thresholds due to the elevated risk
of lung cancer seen among low-exposed workers (for example, those with
average exposures of 50-100 [mu]g/m\3\), which is inconsistent with the
ACC's claim that a threshold exists at or above the previous PEL of 100
[mu]g/m\3\, and due to several limitations which may preclude detection
of a relationship between cumulative exposure and lung cancer in this
cohort. As discussed in the Preliminary QRA, these include: (1) A
strong healthy worker effect observed for lung cancer; (2) Mundt et al.
did not follow the typical convention of considering lagged exposures
to account for disease latency; and (3) the relatively young age of
this cohort (median age 56 years old at time of silicosis
determination) (Document ID 1478, p. 288) and limited follow-up period
(average of 19 years per subject) (Birk et al. 2009, Document ID 4002,
Attachment 2, p. 377). Only 9.2 percent of the cohort was deceased by
the end of the follow up period. Mundt et al. (2011) acknowledged this
limitation, stating that the lack of increased risk of lung cancer was
a preliminary finding (Document ID 1478, p. 288).
f. German Uranium Miners
    In pre-hearing comments, Dr. Morfeld described a study of 58,677
German uranium miners by Sogl et al. (2012,

Document ID 3842; 2307, Attachment 2, p. 11). Dr. Morfeld noted that
the study was based on a detailed exposure assessment of respirable
crystalline silica (RCS) dust. According to Dr. Morfeld, Sogl et al.
``showed that no lung cancer excess risk was observed at RCS dust
exposure levels below 10 mg/m\3\-years'' (Document ID 2307, Attachment
2, p. 11). OSHA's review of this publication confirmed that the authors
reported a spline function with a single knot at 10 mg/m\3\-yrs, which
Morfeld interprets to suggest a threshold for lung cancer of
approximately 250 [mu]g/m\3\ average exposure concentration for workers
exposed over the course of 40 years. However, the authors also noted
that an increase in risk below this level could not be ruled out due to
strong confounding with radon, resulting in possible over-adjustment
(Sogl et al., Document ID 3842, p. 9). That is, because workers with
high exposures to silica would also have had high exposures to the lung
carcinogen radon, the models used by Sogl et al. may have been unable
to detect a relationship between silica and lung cancer in the presence
of radon. As described previously, excess lung cancer has been observed
among workers with lower cumulative exposures than the Sogl et al.
``threshold'' in other studies which do not suffer from confounding
from potent lung carcinogens other than silica (for example, industrial
sand workers), and which are, therefore, likely to provide more
reliable evidence on the issue of thresholds. OSHA concludes that the
Sogl et al. study does not provide convincing evidence of a cumulative
exposure threshold for lung cancer.
g. U.S. Diatomaceous Earth Workers
    Checkoway et al. (1997) investigated the risk of lung cancer among
diatomaceous earth (DE) workers exposed to respirable cristobalite (a
type of silica found in DE) (Document ID 0326; 1711, pp. 139-143).
Exposure samples were collected primarily at one of the two plants in
the study by plant industrial hygienists over a 40-year timeframe from
1948 to 1988 and used to estimate exposure for each individual in the
cohort (Seixas et al., 1997, Document ID 0431, p. 593). Based on 77
deaths from cancer of the trachea, lung, and bronchus, the standardized
mortality ratios (SMR) were 129 (95% CI 101-161) and 144 (95% CI 114-
180) based on rates for U.S. and local county males, respectively
(Document ID 0326, pp. 683-684). The authors found a positive, but not
monotonic, exposure-response trend for lung cancer. The risk ratios for
lung cancer with increasing quintiles of respirable crystalline silica
exposure were 1.00, 0.96, 0.77, 1.26 and 2.15 with a 15-year exposure
lag. Lung cancer mortality was thus elevated for workers with
cumulative exposures greater than 2.1 mg/m\3\-yrs, but was only
statistically significantly elevated for the highest exposure category
(RR = 2.15; 95% CI 1.08-4.28) (Document ID 0326, p. 686). OSHA notes
that this highest exposure category includes cumulative exposures only
slightly higher than 4.5 mg/m\3\-yrs, the level of cumulative exposure
resulting from a 45-year working lifetime at the previous PEL of 100
[mu]g/m\3\. OSHA does not believe that the appearance of a
statistically significantly elevated lung cancer risk in the highest
category should be interpreted as evidence of an exposure-response
threshold, especially in light of the somewhat elevated risk seen at
lower exposure levels. OSHA believes it is more likely to reflect
limited power to detect excess risk at lower exposure levels, a common
issue in epidemiological studies which was emphasized by peer reviewer
Dr. Andrew Salmon in relation to purported thresholds (Document ID
3574, p. 37).
h. Finnish Nationwide Job Exposure Matrix
    OSHA reviewed Pukkala et al. (2005, Document ID 0412) in the Review
of Health Effects Literature and Preliminary Quantitative Risk
Assessment (Document ID 1711, pp. 153-154). As discussed there, Pukkala
et al. (2005) evaluated the occupational silica exposure among all
Finns born between 1906 and 1945 who participated in a national
population census on December 31, 1970. Follow-up of the cohort was
through 1995. Between 1970 and 1995, there were 30,137 cases of
incident lung cancer among men and 3,527 among women. Exposure data
from 1972 to 2000 was collected by the Finnish Institute of
Occupational Health (FIOH). Cumulative exposure categories for
respirable quartz were defined as: <1.0 mg/m\3\-yrs (low), 1.0-9.9 mg/
m\3\-yrs (medium) and >10 mg/m\3\-yrs (high). For men, over 18 percent
of the 30,137 lung cancer cases worked in occupations with potential
exposure to silica dust. The cohort showed statistically significantly
increased lung cancer among men in the lowest occupationally exposed
group (those with less than 1.0 mg/m\3\-yrs cumulative silica
exposure), as well as for men with exposures in the two higher groups
(1.0-9.9 mg/m\3\-yrs and >10 mg/m\3\-yrs). For women, the cohort showed
statistically significantly increased lung cancer among women with at
least 1.0 mg/m\3\-yrs cumulative silica exposure. Given these results,
it is unclear why ACC stated that Pukkula's results suggest that
``excess risk of lung cancer is mainly attributable to . . . cumulative
exposure exceeding 10 mg/m\3\-years'' (Document ID 4209, p. 54).
Indeed, Pukkula's analysis appears to show excess risk of lung cancer
among men with any level of occupational exposure and among women whose
cumulative exposures were quite low (at least equivalent to about 25
[mu]g/m\3\ over 45 years). It does not support the ACC's contention
that lung cancer is seen primarily in workers with exposures greater
than 200 [mu]g/m\3\ (Document ID 4209, p. 54), but rather suggests that
any threshold for lung cancer risk would likely be well below 100
[mu]g/m\3\.
i. U.S. National (27 states) Case-Control Study
    As discussed in the Review of Health Effects Literature and
Preliminary Quantitative Risk Assessment (Document ID 1711, pp. 152-
153), Calvert et al. (2003, Document ID 3890) conducted a case-control
study using 4.8 million death certificates from the National
Occupational Mortality Surveillance data set. Death certificates were
collected from 27 states covering the period from 1982 to 1995. Cases
were persons who had died from any of several diseases of interest:
Silicosis, tuberculosis, lung cancer, chronic obstructive pulmonary
disease (COPD), gastrointestinal cancers, autoimmune-related diseases,
or renal disease. Worker exposure to crystalline silica was categorized
as no/low, medium, high, or super-high based on their industry and
occupation. The authors acknowledged the potential for confounding by
higher smoking rates for cases compared to controls, and partially
controlled for this by eliminating white-collar workers from the
control group in the analysis. Following this adjustment, the authors
reported weak, but statistically significantly elevated, lung cancer
mortality odds ratios (OR) of 1.07 (95% CI 1.06-1.09) and 1.08 (95% CI
1.01-1.15) for the high- and super-high exposure groups, respectively
(Calvert et al., 2003, Document ID 3890, p. 126). Upon careful review
of this study, OSHA maintains its position that it should not be used
for quantitative risk analysis (including determination of threshold
effects) because it lacks an exposure characterization based on
sampling. Any determination regarding the existence or location of a
threshold based on Calvert et al. (2003) must, therefore, be considered
highly speculative.

j. Conclusion--Lung Cancer
    In conclusion, OSHA has determined that the best available evidence
on the issue of a threshold for silica-related lung cancer does not
support the ACC's contention that an exposure-response threshold, below
which respirable crystalline silica exposure is not expected to cause
cancer, exists at or above the previous general industry PEL of 100
[mu]g/m3. While there are some studies that claim to point
to thresholds above the previous general industry PEL, multiple studies
contradict this evidence, most convincingly through evidence that
cohort members with low cumulative silica exposures suffered from lung
cancer as a result of their exposure. These studies indicate that there
is either no threshold for silica-related lung cancer, or that this
threshold is at such a low level that workers cumulatively exposed at
or below the level allowed by the new PEL of 50 [mu]g/m3
will still be at risk of developing lung cancer. Thus, OSHA does not
agree with commenters who have stated that the previous general
industry PEL is fully protective and that reducing it will yield no
health benefits to silica-exposed workers (e.g., Document ID 4224, p.
2-5; Tr. 3582, pp. 1951-1963).
4. Exposure Uncertainty and Thresholds
    In his pre-hearing comments, Dr. Cox stated that the observation of
a positive and monotonic exposure-response relationship in
epidemiological studies ``does not constitute valid evidence against
the hypothesis of a threshold,'' and that OSHA's findings of risk at
exposures below the previous PEL for general industry ``could be due
simply to exposure misclassification'' in studies of silica-related
health effects in exposed workers (Document ID 2307, Attachment 4, pp.
41-42). His statements closely followed his analyses from a 2011 paper,
in which Cox presented a series of simulation analyses designed to show
that common concerns in epidemiological analyses, such as uncontrolled
confounding, errors in exposure estimates, and model specification
errors, can obscure evidence of an exposure-response threshold, if such
a threshold exists (Document ID 3600, Attachment 7). Dr. Cox concluded
that the currently available epidemiological studies ``do not provide
trustworthy information about the presence or absence of thresholds in
exposure-response relations'' with respect to an exposure concentration
threshold for lung cancer (Document ID 3600, Attachment 7, p. 1548).
    OSHA has reviewed Dr. Cox's comments and testimony, and concludes
that uncertainty about risk due to exposure estimation and confounding
cannot be resolved through the application of the statistical
procedures recommended by Dr. Cox. (Similar comments from Dr. Cox about
alleged biases in the studies relied upon are addressed in the next
section, where OSHA reaches similar conclusions). A reviewer on the
independent peer review panel, Dr. Ginsberg, commented that:

epidemiology studies will always have issues of exposure
misclassification or other types of error that may create
uncertainty when it comes to model specification. However, these
types of error will also bias correlations to the null such that if
they were sufficiently influential to obscure a threshold they may
also substantially weaken regression results and underestimate the
true risk (Document ID 3574, p. 23).

    OSHA agrees with Dr. Ginsberg. As discussed in Section V.K,
Comments and Responses Concerning Exposure Estimation Error and
ToxaChemica's Uncertainty Analysis, a ``gold standard'' exposure sample
is not available for the epidemiological studies in the silica
literature, so it is not possible to determine the direction or
magnitude of the effects of exposure misclassification on OSHA's risk
estimates. The silica literature is not unique in this sense. As stated
by Mr. Robert Park of NIOSH, ``modeling exposure uncertainty as
described by Dr. Cox . . . is infeasible in the vast majority of
retrospective observational studies. Nevertheless, mainstream
scientific thought holds that valid conclusions regarding disease
causality can still be drawn from such studies'' (Document ID 4233, p.
32).
    For the reasons discussed throughout this analysis of the
scientific literature, OSHA concludes that, even acknowledging a
variety of uncertainties in the studies relied upon, these
uncertainties are, for the most part, typical or inherent in these
types of studies. OSHA therefore finds that the weight of evidence in
these studies, representing the best available evidence on the health
effects of silica exposure, strongly supports the findings of
significant risk from silicosis, NMRD, lung cancer, and renal disease
discussed in this section and in the quantitative risk assessment that
follows in the next section (see Benzene, 448 U.S. at 656 (``OSHA is
not required to support its finding that a significant risk exists with
anything approaching scientific certainty. Although the Agency's
findings must be supported by substantial evidence, 29 U.S.C. 655(f),
6(b)(5) specifically allows the Secretary to regulate on the basis of
the `best available evidence.' '')).
5. Conclusion
    In summary, OSHA acknowledges that common issues with
epidemiological studies limit the Agency's ability to determine whether
and where a threshold effect exists for silicosis and lung cancer.
However, as shown in the foregoing discussion, there is evidence in the
epidemiological literature that workers exposed to silica at
concentrations and cumulative levels allowable under the previous
general industry PEL not only develop silicosis, but face a risk of
silicosis high enough to be significant ( >1 per 1,000 exposed
workers). Although the evidence is less clear for lung cancer, studies
nevertheless show excess cases of lung cancer among workers with
cumulative exposures in the range of interest to OSHA. Furthermore, the
statistical model-based approaches proposed in public comments do not
demonstrate the existence or location of a ``threshold'' level of
silica exposure below which silica exposure is harmless to workers. The
above considerations lead the Agency to conclude that any possible
exposure threshold is likely to be at a low level, such that some
workers will continue to suffer the health effects of silica exposure
even at the new PEL of 50 [mu]g/m3.
    There is a great deal of argument and analysis directed at the
question of thresholds in silica exposure-response relationships, but
nothing like a scientific consensus about the appropriate approach to
the question has emerged. If OSHA were to accept the ACC's claim that
exposure to 100 [mu]g/m3 silica is safe for all workers (due
to a threshold at or above an exposure concentration of 100 [mu]g/
m3) and set a PEL at 100 [mu]g/m3 for all
industry sectors, and if that claim is in fact erroneous, the
consequences of that error to silica-exposed workers would be grave. A
large population of workers would remain at significant risk of serious
occupational disease despite feasible options for exposure reduction.

J. Comments and Responses Concerning Biases in Key Studies

    OSHA received numerous comments and testimony, particularly from
representatives of the ACC, regarding biases in the data that the
Agency relied upon to conduct its Preliminary Quantitative Risk
Assessment (Preliminary QRA). In this section, OSHA focuses on these
comments regarding biases, particularly with respect to how such biases
may have affected the data and findings from the

key peer-reviewed, published studies that OSHA relied upon in its
Preliminary QRA.
    The data utilized by OSHA to conduct its Preliminary QRA came from
published studies in the peer-reviewed scientific literature. When
developing health standards, OSHA is not required or expected to
conduct original research or wait for better data or new studies (see
29 U.S.C. 655(b)(5); e.g., United Steelworkers v. Marshall, 647 F.2d
1189, 1266 (D.C. Cir. 1980), cert. denied, 453 U.S. 913 (1981)).
Generally, OSHA bases its determinations of significant risk of
material impairment of health on the cumulative evidence found in a
number of studies, no one of which may be conclusive by itself (see
Public Citizen Health Research Group v. Tyson, 796 F.2d 1479, 1495
(D.C. Cir. 1986) (reviewing courts do not ``seek a single dispositive
study that fully supports the Administrator's determination . . .
Rather, [OSHA's] decision may be fully supportable if it is based . . .
on the inconclusive but suggestive results of numerous studies.'').
OSHA's critical reading and interpretation of scientific studies is
thus appropriately guided by the instructions of the Supreme Court's
Benzene decision that ``so long as they are supported by a body of
reputable scientific thought, OSHA is free to use conservative
assumptions in interpreting the data with respect to carcinogens,
risking error on the side of overprotection rather than
underprotection'' (Industrial Union Dep't v. American Petroleum Inst.,
448 U.S. 607, 656 (1980)).
    Since OSHA is not a research agency, it draws from the best
available existing data in the scientific literature to conduct its
quantitative risk assessments. In most cases, with the exception of
certain risk and uncertainty analyses prepared for OSHA by its
contractor ToxaChemica, OSHA had no involvement in the data generation
or analyses reported in those studies. Thus, in calculating its risk
estimates, OSHA used published regression coefficients or equations
from key peer-reviewed, published studies, but had no control over the
actual published data; nor did the Agency have access to the raw data
from such studies.
    As discussed throughout Section V of this preamble, the weight of
scientific opinion indicates that respirable crystalline silica is a
human carcinogen that causes serious, life-threatening disease at the
previously-permitted exposure levels. Under its statutory mandate, the
Agency can and does take into account the potential for statistical and
other biases to skew study results in either direction. However, the
potential biases of concern to the commenters are well known among
epidemiologists. OSHA therefore believes that the scientists who
conduct the studies and subject them to peer review before publication
have taken the potential for biases into account in evaluating the
quality of the data and analysis. As discussed further below, OSHA
heard testimony from David Goldsmith, Ph.D., describing how scientists
use ``absolutely the best evidence they can lay their hands on'' and
place higher value on studies that are the least confounded by other
factors that, if unaccounted for, could contribute to the effect (e.g.,
lung cancer mortality). (Document ID 3577, Tr. 894-895). Dr. Goldsmith
also testified that many of the assertions of biases put forth in the
rulemaking docket are speculative in nature, with no actual evidence
presented (Document ID 3577, Tr. 901). Thus, while taking seriously the
critiques of the ``body of reputable scientific thought'' OSHA has used
to support this final silica standard, the Agency finds no reason, as
discussed below, to consider discredited in any material way its key
conclusions regarding causation or significant risk of harm.
    In his pre-hearing comments, Dr. Cox, on behalf of the ACC, claimed
that the Preliminary QRA did not address a number of sources of
potential bias:

    The Preliminary QRA and the published articles that it relies on
do not correct for well-known biases in modeling statistical
associations between exposures and response. (These include study,
data, and model selection biases; model form specification and model
over-fitting biases; biases due to residual confounding, e.g.,
because age is positively correlated with both cumulative exposure
and risk of lung diseases within each age category (typically 5 or
more years long); and biases due to the effects of errors in
exposure estimates on shifting apparent thresholds to lower
concentrations). As a result, OSHA has not demonstrated that there
is any non-random association between crystalline silica exposure
and adverse health responses (e.g., lung cancer, non-malignant
respiratory disease, renal disease) at exposure levels at or below
100 [[micro]g/m\3\]. The reported findings of such an association,
e.g., based on significantly elevated relative risks or
statistically significant positive regression coefficients for
exposed compared to unexposed workers, are based on unverified
modeling assumptions and on ignoring uncertainty about those
assumptions (Document ID 2307, Attachment 4, pp. 1-2).

    These biases, according to Dr. Cox, nearly always result in false
positives, i.e., finding that an exposure-response relationship exists
when there really is no such relationship (Document ID 3576, Tr. 380).
Although his comments appear to be directed to all published, peer-
reviewed studies relied upon by OSHA in estimating risks, Dr. Cox
admitted at the hearing that his statements about false positives were
based on his review of the Preliminary QRA with relation to lung cancer
only, and that he ``[didn't] really know'' whether the same allegations
of bias he directed at the lung cancer studies are relevant to the
studies of silica's other health risks (Document ID 3576, Tr. 426). In
his comments, Dr. Cox discussed each source of bias in detail; OSHA
will address them in turn. The concerns expressed by commenters,
including Dr. Cox, about exposure uncertainty--another potential source
of bias--are addressed in Section V.K, Comments and Responses
Concerning Exposure Estimation Error and ToxaChemica's Uncertainty
Analysis.
1. Model Specification Bias
    Dr. Cox stated that model specification error occurs when the model
form, such as the linear absolute risk model, does not correctly
describe the data (Document ID 2307, Attachment 4, p. 21). Using a
simple linear regression example from Wikipedia, Dr. Cox asserted that
common indicators of goodness-of-fit, including sum of square residuals
and correlation coefficients, can be weak in identifying
``nonlinearities, outliers, influential single observations, and other
violations of modeling assumptions'' (Document ID 2307, Attachment 4,
pp. 52-53). He advocated for the use of diagnostic tests to check that
a model is a valid and robust choice, stating, ``[u]nfortunately,
OSHA's Preliminary QRA and the underlying papers and reports on which
it relies are not meticulous in reporting the results of such model
diagnostics, as good statistical and epidemiological practice
requires'' (Document ID 2307, Attachment 4, p. 21). In his post-hearing
brief, Dr. Cox further described these diagnostic tests to include
plots of residuals, quantification of the effects of removing outliers
and influential observations, and comparisons of alternative model
forms using model cross-validation (Document ID 4027, p. 2). He also
suggested using Bayesian Model Averaging (BMA) or other model ensemble
methods to quantify the effects of model uncertainty (Document ID 4027,
p. 3).
    OSHA believes that guidelines for which diagnostic procedures
should be performed, and whether and how they are reported in published
papers, are best determined by the scientific community through the
pre-publication peer review process. Many studies in

the silica literature did not report the results of diagnostic tests.
For example, the Vacek et al. (2009) study of lung cancer and silicosis
mortality, which was submitted to the rulemaking record by the ACC to
support its position, made no mention of the results of model
diagnostic tests; rather, the authors simply stated that models were
fitted by maximum likelihood, with the deviance used to examine model
fitting (Document ID 2307, Attachment 6, pp. 11-12). As illustrated by
this example, authors of epidemiological studies do not normally report
the results of diagnostic tests; nor do such authors publish their raw
data. Therefore, there is no data readily available to OSHA with which
it could perform the diagnostic analysis that Dr. Cox states is
necessary. If the suggestion is that no well-conducted epidemiological
study that failed to report a battery of diagnostic tests or disclose
what they showed should be relied upon for regulatory purposes, there
would be virtually no body of scientific study left for OSHA to
consider, raising the legal standard for issuing toxic substance
standards far above what the Benzene decision requires. Despite this,
OSHA maintains that, given the large number of peer-reviewed studies in
the published scientific literature on crystalline silica, subjecting
each model in each study to diagnostic testing along the lines
advocated by Dr. Cox would not fundamentally change the collective
conclusions when examining the literature base as a whole. Despite Dr.
Cox's criticisms, the scientific literature that OSHA reviewed to draw
its conclusions regarding material impairment of health and used in its
quantitative risk assessment, constitutes the best available evidence
upon which to base this toxic substance standard, in accordance with 29
U.S.C. 655(b) and the Benzene decision and subsequent case law.
    Dr. Cox's other suggested approach to addressing model uncertainty,
BMA, can be used to construct a risk estimate based on multiple
exposure-response models. Unlike BMA, standard statistical practice in
the epidemiological literature is to evaluate multiple possible models,
identify the model that best represents the observations in the data
set, and use this model to estimate risk. In some cases, analysts may
report the results of two or more models, along with their respective
fit statistics and other information to aid model selection for risk
assessment and show the sensitivity of the results to modeling choices
(e.g., Rice et al., 2001, Document ID 1118). These standard approaches
were used in each of the studies relied on by OSHA in its Preliminary
QRA.
    In contrast, BMA is a probabilistic approach designed to account
for uncertainty inherent in the model selection process. The analyst
begins with a set of possible models (Mi) and assigns each a
prior probability (Pr[Mi]) that reflects the analyst's
initial belief that model Mi represents the true exposure-
response relationship. Next, a data set is used to update the
probabilities assigned to the models, generating the posterior
probability for each model. Finally, the models are used in combination
to derive a risk estimate that is a composite of the risk estimates
from each model, weighted by each model's posterior probability (see
Viallefont et al., 2001, Document ID 3600, Attachment 34, pp. 3216-
3217). Thus, BMA combines multiple models, and uses quantitative
weights accounting for the analyst's belief about the plausibility of
each model, to generate a single weighted-average risk estimate. These
aspects of BMA are regarded by some analysts as improvements to the
standard approaches to exposure-response modeling.
    However, Kyle Steenland, Ph.D., Professor, Department of
Environmental Health, Rollins School of Public Health, Emory
University, the principal author of a pooled study that OSHA heavily
relied upon, noted that BMA is not a standard method for risk
assessment. ``[Bayesian] model averaging, to my knowledge, has not been
used in risk assessment ever. And so, sure, you could try that. You
could try a million things. But I think OSHA has correctly used
standard methods to do their risk assessment and [BMA] is not one of
those standard methods'' (Document ID 3580, Tr. 1259).
    Indeed, BMA is a relatively new method in risk analysis. Because of
its novelty, best practices for important steps in BMA, such as
defining the class of models to include in the analysis, and choosing
prior probabilities, have not been developed. Until best practices for
BMA are established, it would be difficult for OSHA to conduct and
properly evaluate the quality of BMA analyses. Evaluation of the
quality of available analyses is a key step in the Agency's
identification of the best available evidence on which to base its
significant risk determination and benefits analysis.
    OSHA also emphasizes that, as noted by Dr. Steenland,
scientifically accepted and standard practices were used to estimate
risk from occupational exposure to crystalline silica (Document ID
3580, Tr. 1259). Thus OSHA has decided that it is not necessary to use
BMA in its QRA, and that the standard statistical methods used in the
studies it relies upon to estimate risk are appropriate as a basis for
risk estimation. OSHA notes that it is possible to incorporate risk
estimates based on more than one model in its risk assessment by
presenting ranges of risk, a strategy often used by OSHA when the best
available evidence includes more than one model, analytical approach,
or data set. In its Preliminary QRA, OSHA presented ranges of risks for
silica-related lung cancer and silicosis based on different data sets
and models, thus further lessening the utility of using more complex
techniques such as BMA. OSHA continued this practice in its final risk
assessment, presented in Section VI, Final Quantitative Risk Assessment
and Significance of Risk.
2. Study Selection Bias
    Another bias described by Dr. Cox is study selection bias, which he
stated occurs when only studies that support a positive exposure-
response relationship are included in the risk assessment, and when
criteria for the inclusion and exclusion of studies are not clearly
specified in advance (Document ID 2307, Attachment 4, pp. 22-23). Dr.
Cox noted the criteria used by OSHA to select studies, as described in
the Supplemental Literature Review of Epidemiological Studies on Lung
Cancer Associated with Exposure to Respirable Crystalline Silica
(Supplemental Literature Review) (Document ID 1711, Attachment 1, p.
29). Dr. Cox, however, claimed that OSHA did not apply these criteria
consistently, in that there may still be exposure misclassification or
confounding present in the studies OSHA relied upon to estimate the
risk of the health effects evaluated by the Agency (Document ID 2307,
Attachment 4, pp. 24-25). Similarly, the American Foundry Society
(AFS), in its post-hearing brief, asserted that, ``No formal process is
described for search criteria or study selection'' and that OSHA's
approach of identifying studies based upon the IARC (1997) and NIOSH
(2002) evaluations of the literature ``is a haphazard approach that is
not reproducible and is subject to bias. Moreover it appears to rely
primarily on information that is more than 10 years old'' (Document ID
4229, p. 4).
    OSHA disagrees with the arguments presented by Dr. Cox and the AFS,
as did some commenters. The American Public Health Association (APHA),
in its post-hearing brief, expressed strong

support for OSHA's study selection methods. Dr. Georges Benjamin,
Executive Director, wrote, ``APHA recognizes that OSHA has thoroughly
reviewed and evaluated the peer-reviewed literature on the health
effects associated with exposure to respirable crystalline silica.
OSHA's quantitative risk assessment is sound. The agency has relied on
the best available evidence and acted appropriately in giving greater
weight to those studies with the most robust designs and statistical
analyses'' (Document ID 2178, Attachment 1, p. 1). Similarly, Dr.
Steenland testified that ``OSHA has done a very capable job in
conducting the summary of the literature'' (Document ID 3580, Tr.
1235).
    In response to the criticisms by Dr. Cox and the AFS, OSHA notes
that the silica literature was exhaustively reviewed by IARC in 1997
and NIOSH in 2002 (Document ID 1062; 1110). As a result, there was no
need for OSHA to initiate a new review of the historical literature.
Instead, OSHA used the IARC and NIOSH reviews as a starting point for
its own review. As recognized by the APHA, OSHA evaluated and
summarized many of the studies referenced in the IARC and NIOSH
reviews, and then performed literature searches to identify new studies
published since the time of the IARC and NIOSH reviews. OSHA clearly
described this process in its Review of Health Effects Literature:
``OSHA has included in its review all published studies that the Agency
deems relevant to assessing the hazards associated with exposure to
respirable crystalline silica. These studies were identified from
numerous scientific reviews that have been published previously such as
the IARC (1997) and NIOSH (2002) evaluations of the scientific
literature as well as from literature searches and contact with experts
and stakeholders'' (Document ID 1711, p. 8). For its Preliminary QRA,
OSHA relied heavily on the IARC pooled exposure-response analyses and
risk assessment for lung cancer in 10 cohorts of silica-exposed workers
(Steenland et al., 2001a, Document ID 0452) and multi-center study of
silicosis mortality (Mannetje et al., 2002b, Document ID 1089). As
stated in the Review of Health Effects Literature, these two studies
``relied on all available cohort data from previously published
epidemiological studies for which there were adequate quantitative data
on worker exposures to crystalline silica to derive pooled estimates of
disease risk'' (Document ID 1711, p. 267).
    In addition to relying on these two pooled IARC multi-center
studies, OSHA also identified single cohort studies with sufficient
quantitative information on exposures and disease incidence and
mortality rates. As pointed out by Dr. Cox, OSHA described the criteria
used for selection of the single cohort studies of lung cancer
mortality:

    OSHA gave studies greater weight and consideration if they (1)
included a robust number of workers; (2) had adequate length of
follow-up; (3) had sufficient power to detect modest increases in
lung cancer incidence and mortality; (4) used quantitative exposure
data of sufficient quality to avoid exposure misclassification; (5)
evaluated exposure-response relationships between exposure to silica
and lung cancer; and (6) considered confounding factors including
smoking and exposure to other carcinogens (Document ID 1711,
Attachment 1, p. 29).

    Using these criteria, OSHA identified four single-cohort studies of
lung cancer mortality that were suitable for quantitative risk
assessment; two of these cohorts (Attfield and Costello, 2004, Document
ID 0285; Rice et al., 2001, 1118) were included among the 10 used in
the IARC multi-center study and two appeared later (Hughes et al.,
2001, Document ID 1060; Miller and MacCalman, 2009, 1306) (Document ID
1711, p. 267). For NMRD mortality, in addition to the IARC multi-center
study (Mannetje et al., 2002b, Document ID 1089), OSHA relied on Park
et al. (2002) (Document ID 0405), who presented an exposure-response
analysis of NMRD mortality (including silicosis and other chronic
obstructive pulmonary diseases) among diatomaceous earth workers
(Document ID 1711, p. 267). For silicosis morbidity, several single-
cohort studies with exposure-response analyses were selected (Chen et
al., 2005, Document ID 0985; Hnizdo and Sluis-Cremer, 1993, 1052;
Steenland and Brown, 1995b, 0451; Miller et al., 1998, 0374; Buchanan
et al., 2003, 0306) (Document ID 1711, p. 267).
    With respect to Dr. Cox's claim that OSHA did not apply its
criteria consistently, on the basis that there may still be exposure
misclassification or confounding present, OSHA notes that it selected
studies that best addressed the criteria; OSHA did not state that it
only selected studies that addressed all of the criteria. Given the
fact that some of the epidemiological studies concern exposures of
worker populations dating back to the 1930's, there is always some
potential for exposure misclassification or the absence of information
on smoking. When this was the case, OSHA discussed these limitations in
its Review of Health Effects Literature and Preliminary QRA (Document
ID 1711). For example, OSHA discussed the lack of smoking information
for cases and controls in the Steenland et al. (2001a, Document ID
0452) pooled lung cancer analysis (Document ID 1711, pp. 150-151).
    With respect to the AFS's claim that OSHA relied on studies that
were more than 10 years old, OSHA again notes that it reviewed, in its
Review of Health Effects Literature and its Supplemental Literature
Review, the studies in the silica literature and selected the ones that
best met the criteria described above (Document ID 1711; 1711,
Attachment 1). It would be improper to only select the most recent
studies, particularly if the older studies are of higher quality based
on the criteria. Furthermore, the studies OSHA relied upon in its
Preliminary QRA were published between 1993 and 2009; the claim that
OSHA primarily relied on older studies is thus misleading, when the
studies were of relatively recent vintage and determined to be of high
quality based on the criteria described above. The AFS also suggested
that OSHA examine several additional foundry studies of lung cancer
(Document ID 2379, Attachment 2, p. 24); OSHA retrieved all of these
suggested studies, added them to the rulemaking docket following the
informal public hearings, and discusses them in Section V.F, Comments
and Responses Concerning Lung Cancer Mortality.
3. Data Selection Bias
    A related bias presented by Dr. Cox is data selection bias, which
he stated occurs when only a subset of the data is used in the analysis
``to guarantee a finding of a positive'' exposure-response relationship
(Document ID 2307, Attachment 4, p. 26). He provided an example, the
Attfield and Costello (2004, Document ID 0285) study of lung cancer
mortality, which excluded data as a result of attenuation observed in
the highest exposure group (Document ID 2307, Attachment 4, pp. 26-27).
Attenuation of response means the exposure-response relationship
leveled off or decreased in the highest exposure group. Referring to
another study of the same cohort, Vacek et al. (2009, Document ID 2307,
Attachment 6; 2011, 1486), Dr. Cox stated, ``OSHA endorses the Attfield
and Costello findings, based on dropping cases that do not support the
hypothesis of an ER [exposure-response] relation for lung cancer, while
rejecting the Vacek et al. study that included more complete data (that
was not subjected to post hoc subset selection) but that did not find a
significant ER [exposure-response]

relation'' (Document ID 2307, Attachment 4, pp. 26-27).
    OSHA believes there are very valid reasons for the observance of
attenuation of response in the highest exposure group that would
justify the exclusion of data in Attfield and Costello (2004, Document
ID 0285) and other studies. This issue was discussed by Gary Ginsberg,
Ph.D., an OSHA peer reviewer from the Connecticut Department of Public
Health, in his post-hearing comments. Dr. Ginsberg noted that several
epidemiological studies have found an attenuation of response at higher
doses, with possible explanations including: (1) Measurement error,
which arises from the fact that the highest doses are associated with
the oldest datasets, which are most prone to measurement error; (2)
``intercurrent causes of mortality'' from high dose exposures that
result in death to the subject prior to the completion of the long
latency period for cancer; and (3) the healthy worker survivor effect,
which occurs when workers with ill health leave the workforce early
(Document ID 3574, p. 24). As discussed in Section V.F, Comments and
Responses Concerning Lung Cancer Mortality, OSHA disagrees strongly
with Dr. Cox's assertion that data were excluded to ensure a positive
exposure-response relationship (Document ID 2307, Attachment 4, p. 26).
In addition, as detailed in Section VI, Final Quantitative Risk
Assessment and Significance of Risk, OSHA calculated quantitative risk
estimates for lung cancer mortality from several other studies that did
not rely on a subset of the data (Rice et al., 2001, Document ID 1118;
Hughes et al., 2001, 1060; Miller and MacCalman, 2009, 1306;
ToxaChemica, 2004, 0469; 1711, p. 351). These studies also demonstrated
positive exposure-response relationships.
4. Model Selection Bias
    Another selection bias presented by Dr. Cox is model selection
bias, which he said occurs when many different combinations of models,
including alternative exposure metrics, different lags, alternative
model forms, and different subsets of data, are tried with respect to
their ``ability to produce `significant'-looking regression
coefficients'' (Document ID 2307, Attachment 4, p. 27). This is another
aspect of model specification error, as discussed above under model
averaging. Dr. Cox wrote:

    This type of multiple testing of hypotheses and multiple
comparisons of alternative approaches, followed by selection of a
final choice based [on] the outcomes of these multiple attempts,
completely invalidates the claimed significance levels and
confidence intervals reported for the final ER [exposure-response]
associations. Trying in multiple ways to find a positive
association, and then selecting a combination that succeeds in doing
so and reporting it as `significant,' while leaving the nominal
(reported) statistical significance level of the final selection
unchanged (typically at p=0.05), is a well-known recipe for
producing false-positive associations (Document ID 2307, Attachment
4, p. 28).

    Dr. Cox further stated that unless methods of significance level
reduction (i.e., reducing the nominal statistical significance level of
the final selection) are used, the study is biased towards false-
positive results (Document ID 2307, Attachment 4, p. 28).
    During the informal public hearings, counsel for the ACC asked Mr.
Park of NIOSH's Risk Evaluation Branch about this issue, i.e., trying a
number of modeling choices, including exposure metrics, log-
transformations, lag periods, and model subsets (Document ID 3579, Tr.
149-150). Mr. Park's reply supports the use of multiple modeling
choices in the risk assessment as a form of sensitivity analysis:

    Investigations like this look at a number of options. They come
into the study not totally na[iuml]ve. They, in fact, have some very
strong preference even before looking at the data based on prior
knowledge. So cumulative exposure, for example, is a generally very
high confidence choice in a metric. Trying different lags is
interesting. It helps validate the study because you know what it
ought to look like sort of. And in many cases, the choice does not
make a lot of difference. So it's kind of a robust test, and
similarly, the choice of the final model is not just coming in
na[iuml]ve. A linear exposure response has a lot of biological
support in many different contexts, but it could be not the best
choice (Document ID 3579, Tr. 150-151).

    ACC counsel further asked, ``And does one at the end of this
process, though, make any adjustment in what you consider to be the
statistically significant relationship in light of the fact that you've
looked at so many different models and arrangements?'' (Document ID
3579, Tr. 151-152). Mr. Park replied, ``No, I don't think that's a
legitimate application of a multiple comparison question'' (Document ID
3579, Tr. 152). OSHA agrees with Mr. Park that significance level
reduction is not appropriate in the context of testing model forms for
risk estimation, and notes that, in the Agency's experience,
significance level reduction is not typically performed in the
occupational epidemiology literature. In addition, OSHA notes that, in
many of the key studies relied upon by the Agency to estimate
quantitative risks, the authors presented the results of multiple
models that showed statistically significant exposure-response
relationships. For example, Rice et al. (2001) presented the results of
six model forms, with all except one being significant (Table 1,
Document ID 1118, p. 41). Attfield and Costello (2004) presented the
results of their model with and without a 15-year lag and log
transformation, with many results being significant (Table VII,
Document ID 0285, p. 135). Thus, OSHA concludes that model selection
bias is not a problem in its quantitative risk assessment.
    Furthermore, OSHA disagrees with Dr. Cox's assertion that modeling
choices are used to ``produce `significant'-looking regression
coefficients'' (Document ID 2307, Attachment 4, p. 27). OSHA believes
that the investigators of the studies it relied upon in its
Preliminary, and now final, QRA made knowledgeable modeling choices
based upon the exposure distribution and health outcome being examined.
For example, in long-term cohort studies, such as those of lung cancer
mortality relied upon by OSHA, most authors relied upon cumulative
exposure (mg/m\3\-yrs or mg/m\3\-days), i.e., the concentration of
crystalline silica exposure (mg/m\3\) multiplied by the duration of
exposure (years or days), as an exposure metric. Consistent with
standard statistical techniques used in epidemiology, the cumulative
exposure metric may then be log-transformed to account for an
asymmetric distribution with a long right tail, or attenuation, and the
metric may be lagged by several years to account for the long latency
period between the exposure and the development of lung cancer. When
investigators use subsets of the data, they typically explain the
rationale and the effect of using the subset in the analysis. These
choices all have important justifications and are not used purely to
produce the authors' desired results, as Dr. Cox suggested (Document ID
2307, Attachment 4, p. 27).
5. Model Uncertainty Bias
    Related to model selection bias is Dr. Cox's assertion of model
uncertainty bias, which he said occurs when many different models are
examined and then one is selected on which to base risk calculations;
this approach ``treats the finally selected model as if it were known
to be correct, for purposes of calculating confidence intervals and
significance levels. But, in reality, there remains great uncertainty
about what the true causal relation between exposure and response looks
like (if there is one)'' (Document ID 2307,

Attachment 4, pp. 28-29). He further stated that ignoring this bias
leads to artificially narrow confidence intervals, which bias
conclusions towards false-positive findings. He then cited a paper
(Piegorsch, 2013, included in Document ID 3600) describing statistical
methods for overcoming this bias by ``including multiple possible
models in the calculation of results'' (Document ID 2307, Attachment 4,
p. 29). OSHA concludes this bias is really an extension of model
specification error and model selection bias, previously discussed, and
maintains that best practices for model averaging have not yet been
established, making it difficult for the Agency to conduct and properly
evaluate the quality of BMA analyses.
6. Model Over-Fitting Bias
    Next, Dr. Cox discussed model over-fitting bias, which he said
occurs when the same data set is used both to fit a model and to assess
the fit; this ``leads to biased results: Estimated confidence intervals
are too narrow (and hence lower confidence limits on estimated ER
[exposure-response] slopes are too high); estimated significance levels
are too small (i.e., significance is exaggerated); and estimated
measures of goodness-of-fit overstate how well the model fits the
data'' (Document ID 2307, Attachment 4, p. 39). He suggested using
appropriate statistical methods, such as ``k-fold cross-validation,''
to overcome the bias (Document ID 2307, Attachment 4, p. 39).
    OSHA does not agree that using the same data set to fit and assess
a model necessarily results in an over-fitting bias. The Agency
understands over-fitting to occur when a model is excessively complex
relative to the amount of data available such that there are a large
number of predictors relative to the total number of observations
available. For survival models, it is the number of events, i.e.,
deaths, that is relevant, rather than the size of the entire sample
(Babyak, 2004, included in Document ID 3600, p. 415). If the number of
predictors (e.g., exposure, age, gender) is small relative to the
number of events, then there should be no bias from over-fitting. In an
article cited and submitted to the rulemaking docket by Dr. Cox, Babyak
(2004) discussed a simulation study that found, for survival models, an
unacceptable bias when there were fewer than 10 to 15 events per
independent predictor (included in Document ID 3600, p. 415). In the
studies that OSHA relied on in its Preliminary QRA, there were
generally a large number of events relative to the small number of
predictors. For example, in the Miller and MacCalman (2009) study of
British coal miners, in the lung cancer model using both quartz and
coal dust exposures, there was a large number of events (973 lung
cancer deaths) relative to the few predictors in the model (quartz
exposure, coal dust exposure, cohort entry date, smoking habits at
entry, cohort effects, and differences in regional background cause-
specific rates) (Document ID 1306, pp. 6, 9). Thus, OSHA does not agree
the studies it relied upon were substantially influenced by over-
fitting bias. OSHA also notes that k-fold cross-validation, as
recommended by Dr. Cox, is not typically reported in published
occupational epidemiology studies, and that the studies the Agency
relied upon in the Preliminary QRA were published in peer-reviewed
journals and used statistical techniques typically used in the field of
occupational epidemiology and epidemiology generally.
7. Residual Confounding Bias
    Dr. Cox also asserted a bias due to residual confounding by age.
Bias due to confounding occurs in an epidemiological study, in very
general terms, when the effect of an exposure is mixed together with
the effect of another variable (e.g., age) not accounted for in the
analysis. Residual confounding occurs when additional confounding
factors are not considered, control of confounding is not precise
enough (e.g., controlling for age by using groups with age spans that
are too wide), or subjects are misclassified with respect to
confounders (Document ID 3607, p. 1). Dr. Cox stated in his comments
that:

key studies relied on by OSHA, such as Park et al. (2002), do not
correct for biases in reported ER [exposure-response] relations due
to residual confounding by age (within age categories), i.e., the
fact that older workers may tend to have both higher lung cancer
risks and higher values of occupational exposure metrics, even if
one does not cause the other. This can induce a non-causal
association between the occupational exposure metrics and the risk
of cancer (Document ID 2307, Attachment 4, p. 29).

    The Park et al. (2002) study of non-malignant respiratory disease
mortality, which Dr. Cox cited as not considering residual confounding
by age, used 13 five-year age groups (<25, 25-29, 30-34, etc.) in the
models (Document ID 0405, p. 37). Regarding this issue in the Park et
al. (2002) study, in its post-hearing comments, NIOSH stated:

    This is a non-issue. The five-year categorization was used only
for deriving the expected numbers of cases as an offset in the
Poisson analysis using national rates which typically are classified
in five-year intervals (on age and chronological time). The
cumulative exposures were calculated with a 10-day resolution over
follow-up and then averaged across observation time within 50
cumulative exposure levels cross-classified with the five-year age-
chronological time cells of the classification table. There would be
virtually no confounding between age and exposure [using this
approach] (Document ID 4233, p. 33).

    OSHA agrees with this assessment, noting that it appears that age
groups were adequately constructed to prevent residual confounding.
OSHA thus rejects this assertion of residual confounding by age in the
Park et al. (2002) study.
8. Summary of Biases
    In summary, OSHA received comments and heard testimony on potential
biases in the studies upon which it relied for its QRA. The ACC's Dr.
Cox, in particular, posited a long list of biases, including model form
specification bias, study selection bias, data selection bias, model
selection bias, model over-fitting bias, model uncertainty bias,
residual confounding bias, and bias as a result of exposure measurement
error. OSHA, in this section, has specifically addressed each of these
types of bias (except for bias due to exposure estimation error, which
is addressed in Section V.K, Comments and Responses Concerning Exposure
Estimation Error and ToxaChemica's Uncertainty Analysis).
    In addition, OSHA heard testimony that countered the claims of
biases and their potential to cause false positive results. When asked
about the biases alleged by Dr. Cox and Dr. Long, Dr. Goldsmith
testified, ``All of these other things, it seems to me, are smoke
screens for an inability to want to try and see what the body of
evidence really shows'' (Document ID 3577, Tr. 895-896). Later in his
testimony, when asked about exposure misclassification, Dr. Goldsmith
similarly noted, ``[a]nd for a lot of the arguments that are being put
forward by industry, they are speculating that there is the potential
for these biases, but they haven't gotten, [from] my perspective, the
actual evidence that this is the case'' (Document ID 3577, Tr. 901).
Similarly, OSHA has reviewed the record evidence extensively and is not
aware of any specific, non-speculative evidence of biases in the
studies that it relied upon.
    There also is a question of the extent to which Dr. Cox actually
reviewed all of the studies that he asserted to be biased. Upon
questioning from Anne Ryder, Attorney in the Office of the Solicitor,
Department of Labor, Dr. Cox admitted that he had not examined the

issue of silica and silicosis, and that his statements about false
positives were based on his review of the Preliminary QRA with relation
to lung cancer only:

    MS. RYDER: . . . You talked a little bit earlier about the false
positives that are . . . present with a lot of the studies on lung
cancer. And, but I believe, in your comment you didn't say that
there are any of those same false positives with studies dealing
with silicosis and silica exposure. Is that correct?
    DR. COX: I don't think I opined on that. So--and I really
haven't looked carefully at the question. I do take it as given that
silica at sufficiently high and prolonged exposures causes
silicosis. I've not really examined that literature.
    MS. RYDER: So you don't think that those studies have the same
issues that some of the lung cancer studies have?
    DR. COX: I don't really know (Document ID 3576, Tr. 426).

    Dr. Cox further testified, regarding the likelihood that the
conclusions of the Preliminary QRA for silicosis are correct, ``I
expect that the evidence is much stronger for silica and silicosis. But
I haven't reviewed it, so I can't testify to it'' (Document ID 3576,
Tr. 427).
    OSHA believes this testimony to be inconsistent with some of the
broad conclusions in Dr. Cox's pre-hearing written submission to the
rulemaking record, in which he claimed that all adverse outcomes in the
Preliminary QRA may have been affected by false positives. Dr. Cox
concluded in this submission that:

    These multiple uncontrolled sources of false-positive bias can
generate findings of statistically ``significant'' positive ER
[exposure-response] associations even in random data, or in data for
which there is no true causal relation between exposure and risk of
adverse health responses. Because OSHA's Preliminary QRA and the
studies on which it relies did not apply appropriate technical
methods (which are readily available, as discussed in the
references) to diagnose, avoid, or correct for these sources of
false-positive conclusions, the reported findings of
``significantly'' positive ER [exposure-response] associations
between crystalline silica exposures at and below the current PEL
and adverse outcomes (lung cancer, non-malignant lung disease, renal
disease) are not different from what might be expected in the
absence of any true ER [exposure-response] relations. They therefore
provide no evidence for (or against) the hypothesis that a true ER
[exposure-response] relation exists. Thus, OSHA has not established
that a non-random association exists between crystalline silica
exposures at or below the current PEL and the adverse health effects
on which it bases its determination of significant risk and
calculates supposed health effect benefits (Document ID 2307,
Attachment 4, pp. 29-30).

    OSHA notes that ``non-malignant lung disease'' includes silicosis,
studies of which Dr. Cox subsequently testified that he did not
examine.
    In conclusion, the studies relied upon by OSHA for its risk
assessment were peer-reviewed and used methods for epidemiology and
risk assessment that are commonly used. Dr. Cox provided no study-
specific evidence (e.g., data re-analysis) to support his comments that
the studies OSHA relied upon were adversely affected by numerous
different types of bias. As described above, OSHA recognizes that there
are uncertainties associated with the results of the studies relied on
for its risk assessment, as is typically the case for epidemiological
studies such as these. Nevertheless, as previously stated, OSHA
maintains that it has used a body of peer-reviewed scientific
literature that, as a whole, constitutes the best available evidence of
the relationship between respirable crystalline silica exposure and
silicosis, lung cancer, and the other health effects studied by the
Agency in promulgating this final rule.

K. Comments and Responses Concerning Exposure Estimation Error and
ToxaChemica's Uncertainty Analysis

    Exposure estimation error, a typical feature of epidemiological
studies, occurs when the authors of an exposure-response study
construct estimates of the study subjects' exposures using uncertain or
incomplete exposure data. Prior to the publication of its Preliminary
Quantitative Risk Assessment (Preliminary QRA), the Agency commissioned
an uncertainty analysis conducted by Drs. Kyle Steenland and Scott
Bartell, through its contractor, ToxaChemica, Inc., to address exposure
estimation error in OSHA's risk assessment, and incorporated the
results into the Preliminary QRA. After reviewing comments submitted to
the record on the topic of exposure estimation error, OSHA maintains
that it has relied upon the best available evidence by: (1) Using high-
quality exposure-response studies and modeling approaches; (2)
performing an uncertainty analysis of the effect of exposure estimation
error on the risk assessment results; and (3) further submitting that
analysis to peer review. OSHA concludes from its uncertainty analysis
that exposure estimation error did not substantially affect the results
in the majority of studies examined (Document ID 1711, pp. 299-314).
    Furthermore, having carefully considered the public comments
criticizing ToxaChemica's uncertainty analysis, OSHA has concluded that
it was not necessary to conduct additional analyses to modify the
approach adopted by Drs. Steenland and Bartell in the uncertainty
analysis. Nor was it necessary to incorporate additional sources of
uncertainty in the analysis. Also, given the evidence in the rulemaking
record that these estimation errors bias results towards
underestimating rather than overestimating the risks from exposure in
many circumstances, it is very unlikely that regression coefficients
and risk estimates from all of the different studies relied on in the
Preliminary QRA were biased upward. Accordingly, OSHA remains convinced
that the conclusions of the Agency's risk assessment are correct and
largely unaffected by potential error in exposure measurement.
    OSHA received significant comments on the topic of exposure
estimation error in the studies it relied on in its Review of Health
Effects Literature and Preliminary QRA (Document ID 1711). A number of
commenters discussed the importance of accounting for exposure
estimation error. Dr. Cox, representing the ACC, described exposure
estimation error as perhaps the ``most quantitatively important'' issue
in the studies OSHA relied upon (Document ID 2307, Attachment 4, p.
40). Similarly, Christopher M. Long, Sc.D., Principal Scientist at
Gradient, representing the U.S. Chamber of Commerce (Chamber),
testified that exposure measurement error is a ``common source of
uncertainty in most occupational and environmental epidemiologic
studies'' (Document ID 3576, Tr. 298). According to Dr. Long, this type
of error can lead to inaccurate risk estimates by creating error in the
exposure-response curve derived from a data set and obscuring the
presence of a threshold (Document ID 3576, Tr. 300; see Section V.I,
Comments and Responses Concerning Thresholds for Silica-Related
Diseases, for further discussion on thresholds). Dr. Long further
stated that exposure measurement error can lead to over- or under-
estimation of risk: ``the impact of exposure measurement error . . .
can bias either high or low. It can bias towards the null. It can be a
source of positive bias.'' (Document ID 3576, Tr. 358-359). A bias to
the null in an exposure-response model used in a quantitative risk
assessment is an underestimation of the relationship between exposure
level and the rate of the disease or health effect of interest, and
results in underestimation of risk.
    OSHA agrees with the assessments of the ACC and the Chamber with
respect to the importance of exposure

measurement error. Indeed, OSHA peer reviewer, Dr. Gary Ginsberg, in
his peer review comments (Document ID 3574, p. 21), and OSHA's risk
assessment contractor, Dr. Steenland, in his hearing testimony
(Document ID 3580, Tr. 1266-1267), noted the potential for exposure
measurement error to bias exposure-response coefficients towards the
null. Dr. Steenland explained: ``misclassification I would say in
general tends to bias things to the null. It's harder to see positive
exposure-response trends in the face of misclassification. It depends
partly on the type of error. . . . But, on the whole, I would say that
exposure measurement tends to bias things down rather than up''
(Document ID 3580, Tr. 1266-1267). Fewell et al., the authors of a
paper on residual confounding submitted by the ACC, wrote, ``It is well
recognized that under certain conditions, nondifferential measurement
error in the exposure variable produces bias towards the null'' (2007,
Document ID 3606, p. 646).
    Several commenters representing the ACC challenged the methods used
in ToxaChemica's uncertainty analysis on the grounds that the analysis
failed to adequately address exposure estimation error. In spite of
their criticisms, critics were unable to supply better studies than
those OSHA used. Indeed, when asked during the hearing, Dr. Long was
unable to identify any studies that the Agency could use that
acceptably account for the impact of exposure measurement error on
exposure-response associations for crystalline silica (Document ID
3576, Tr. 356-357), and none was supplied following the hearings.
    Taking into account the record evidence discussed above, OSHA
concludes that it is possible for exposure measurement error to lead to
either over- or under-estimation of risk and that this issue of
exposure measurement error is not specific to the silica literature. It
further concludes that industry representatives could not identify, and
failed to submit, any published epidemiological studies of occupational
disease that corrected for such bias to their satisfaction (Document ID
3576, Tr. 356-357).
    Nevertheless, because OSHA agreed that an analysis of exposure
estimation error as a source of uncertainty is important, it
commissioned the uncertainty analysis discussed above to explore the
potential effects of exposure measurement error on the conclusions of
OSHA's risk assessment (Document ID 0469). The analysis examined the
potential effects of exposure measurement error on the mortality risk
estimates derived from the pooled studies of lung cancer (Steenland et
al. 2001a, Document ID 0452) and silicosis (Mannetje 2002b, Document ID
1089). This included the effects of estimation error on the detection
and location of a possible threshold effect in exposure-response
models.
    The uncertainty analysis OSHA commissioned from Drs. Steenland and
Bartell (2004, Document ID 0469) addressed possible error in silica
exposure estimates from: (1) Random error in individual workers'
exposure estimates and (2) error in the conversion of dust measurements
(typically particle count concentrations) to gravimetric respirable
silica concentrations, which could have affected estimates of average
exposure for job categories in the job-exposure matrices used to
estimate workers' silica exposure. To address possible error in
individual workers' exposure estimates, the analysts performed a Monte
Carlo analysis, a type of simulation analysis which varies the values
of an uncertain input to an analysis (in this case, exposure estimates)
to explore the effects of different values on the outcome of the
analysis. The Monte Carlo analysis sampled new values for workers' job-
specific exposure levels from distributions they believed characterized
the exposures of individual workers in each job. In each run of the
Monte Carlo analysis, the sampled exposure values were used to
calculate new estimates of each worker's cumulative exposures, and the
resulting set was used to fit a new exposure-response model.
    Similarly, the analysts performed a Monte Carlo analysis to address
the issue of uncertainty in conversion from dust to respirable silica
exposure, sampling new conversion factors from a normal distribution
with means equal to the original conversion factor, calculating new
estimates of workers' cumulative exposures, and re-fitting the
exposure-response model for each Monte Carlo run. To examine the
sensitivity of the model to the joint effects of both error types, the
analysts ran 50 Monte Carlo simulations using the sampling procedure
for both individual exposures and job-specific conversion factors. They
also examined the effects of systematic bias in conversion factors,
considering that these may have been consistently under-estimated or
over-estimated for any given cohort. They addressed possible biases in
either direction, conducting 20 simulations where the true silica
content was assumed to be either half or double the estimated silica
content of measured exposures.
    The results of their analysis indicated that the conclusions of the
pooled lung cancer study conducted previously by Steenland et al.
(Document ID 0452) and included in OSHA's Preliminary QRA were unlikely
to be affected by the types of exposure estimation error examined by
Drs. Steenland and Bartell, whose analysis of the underlying data was
itself reviewed by OSHA's peer review panel. As explained below, after
reviewing comments critical of the uncertainty analysis, OSHA reaffirms
its conclusion that workers exposed to silica at the previous PELs are
at significant risk of disease from their exposure.
    Drs. Long and Valberg, representing the Chamber, commented that
Drs. Steenland and Bartell's uncertainty analysis did not address all
potential sources of error and variability in exposure measurement,
such as possible instrument error; possible sampling error; random
variability in exposure levels; variability in exposure levels
resulting from changes in worker job functions during work shifts,
production process changes, or control system changes; variability in
sampler type used; variability in laboratory methods for determining
sampling results and laboratory errors; variability in duration of
exposure sampling; variability in sampling locations; variability in
reasons for sample data collection (e.g., compliance sampling, periodic
sampling, random survey sampling); variability in type of samples
collected (e.g., bulk samples, respirable dust samples); variation
among workers and over time in the size distribution, surface area,
recency of fracture, and other characteristics of the particles
inhaled; and extrapolation of exposure sampling data to time periods
for which sampling data are not available (Document ID 2330, pp. 4-5).
OSHA notes that these sources of potential error and variability are
common in occupational exposure estimation, and are sources of
uncertainty in most epidemiological studies, a point with which Drs.
Valberg and Long agree (Document ID 2330, p. 14).
    OSHA has determined that its reliance on the best available
evidence provided it with a solid, scientifically sound foundation from
which to conclude that exposure to crystalline silica poses a
significant risk of harm, notwithstanding the various uncertainties
inherent in epidemiology generally or potentially affecting any given
study and that no studies exist entirely free from the types of data
limitations or error and variability Drs. Valberg and Long identified.
During the public hearing Dr. Long acknowledged

that OSHA had not overlooked studies that he believed adequately
addressed the sources of error cited in his comments. He was also
unable to provide examples of such analyses in the silica literature,
or in any other area of occupational epidemiology (Document ID 3576,
Tr. 355-358; see also Document ID 3577, Tr. 641, 648 (testimony of Dr.
Kenneth Mundt)). Additionally, Drs. Valberg and Long's critique of Drs.
Steenland and Bartell's uncertainty analysis ignores constraints on the
available data and reasonable limits on the analysts' ability to
investigate the full variety of possible errors and their potential
effects on OSHA's risk assessment.
    OSHA additionally notes that Dr. Kenneth Crump, an OSHA peer
reviewer, in his examination of ToxaChemica's (Document ID 0469) study
of exposure uncertainty in the Steenland et al. pooled study, opined
that it was sound. He further observed that the ``analysis of error
conducted by [ToxaChemica] is a very strong effort. The assumptions are
clearly described and the data upon [which] they are based appear to be
appropriate and appropriately applied.'' Dr. Crump was careful to note,
however, that ``there are questions, as there will always be with such
an analysis . . . 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'' (Document ID 3574, pp. 161-
162). Dr. Cox referenced Dr. Crump's comment in his own pre-hearing
comments, in the context of a discussion on the importance of exposure
uncertainty in OSHA's risk analysis (Document ID 2307, p. 40). OSHA
addressed this particular criticism in the Review of Health Effects
Literature and Preliminary QRA. There, it stated that it is possible
that some job exposure estimates were above or below the true average
for a job; however, there was no ``gold standard'' measurement
available to appropriately test or adjust for this potential source of
error (Document ID 1711, p. xv). The Agency further stated that the
uncertainty, or sensitivity, analysis included potential error in job
averages, and found that most cohorts in the lung cancer and silicosis
mortality pooled studies were not highly sensitive to random or
systematic error in job-average exposure estimates (Document ID 1711,
pp. 303-314). In his final evaluation of OSHA's response to his
comments of 2009, Dr. Crump stated, ``I believe that my comments have
been fairly taken into account in the current draft and I have no
further comments to make'' (Document ID 3574, p. 17).
    Similarly, Dr. Morfeld, representing the ACC, criticized Drs.
Steenland and Bartell for performing only 50 simulations of workplace
exposures as part of the uncertainty analysis (Document ID 2307,
Attachment 2, p. 10). Peer reviewer Mr. Bruce Allen also remarked that
this type of uncertainty analysis typically requires more than 50
simulations (Document ID 3574, p. 114). However, as stated by OSHA in
the response to peer review section of the Review of Health Effects
Literature and Preliminary QRA (Document ID 1711, pp. 379-400), the
results did not appear to change much with an increased number of
simulations. Thus, OSHA has concluded that the sensitivity findings
would not have changed substantially by running more simulations.
Indeed, in the final peer review report conveying his evaluation of
OSHA's response to his comments of 2009, Mr. Allen stated that OSHA
adequately addressed his comments in the updated risk assessment
(Document ID 3574, p. 5).
    The overall salient conclusion that OSHA draws from this peer-
reviewed analysis is that even in those cohorts where exposure error
had some impact on exposure-response models for lung cancer or
silicosis, the resulting risk estimates at the previous and new PELs
remain clearly significant. Therefore, OSHA continues to rely on, and
have confidence in, the risk analysis it had performed. In particular,
OSHA concludes that Drs. Steenland and Bartell's modeling choices were
based on the best available data from a variety of industrial sources
and, through their uncertainty analysis, reached conclusions that
survive the ACC and Chamber criticisms of the study methodology. OSHA
further concludes that it is not necessary to conduct additional
analysis to modify the approach adopted by Drs. Steenland and Bartell
or to incorporate additional sources of exposure estimation uncertainty
in the analysis.
    OSHA also disagrees with other specific criticisms that Drs. Long
and Valberg made concerning the uncertainty analysis. Dr. Long
testified that ``there are no formal analyses conducted to determine
the error structures of the three sources of exposure measurement error
included in the sensitivity analyses; for example, without any formal
analysis, the OSHA assessment simply assumed a purely Berkson type
error structure from the assignment of job-specific average exposure
levels for individual exposures'' (Document ID 3576, 304-305).\9\ Dr.
Cox expressed a similar concern that
---------------------------------------------------------------------------

    \9\ The first component of ToxaChemica's analysis takes the
exposure level for each job in the job-exposure matrix as the mean
exposure level for workers in that job, with error (that results
from using the mean to estimate each individual worker's exposure)
varying randomly around the mean (Document ID 0469, P. 10). The
second type of error examined by ToxaChemica, resulting from the
assignment of a single conversion factor to represent quartz
percentage in dust samples for multiple jobs, similarly might be
expected to vary randomly around a mean equal to the recorded
conversion factor. Errors resulting from the assignment of job-
specific mean exposures (or conversion factors) to individual
workers or jobs results in a type of error known as Berkson error,
in which the true exposure level is assumed to vary randomly around
the assigned or ``observed'' exposure level for the job (Snedecor
and Cochran, 1989).

    OSHA has not developed an appropriate error model specifically
for the exposure estimates in the crystalline silica studies and has
not validated (e.g., using a validation subset) that any of the ad
hoc error models that they discuss describes the real exposure
estimate errors of concern. They have also provided no justification
for ToxaChemica's assumption of a log-normal distribution without
outliers or mixtures of different distributions . . . and have
provided no rationale for the assumption that a=0.8*p (Document ID
---------------------------------------------------------------------------
2307, Attachment 4, p. 45).

    OSHA disagrees with Dr. Long's and Dr. Cox's characterizations,
which implies that Drs. Steenland and Bartell did not adequately
investigate the patterns of error in the data available to them. As
noted in their 2004 report and by Dr. Steenland during the public
hearings, ToxaChemica did not have the internal validation data (true
exposures for a subset of the data set) that would be required to
conduct formal analyses or validation of the error structure within
each cohort of the pooled analysis (Document ID 0469, p. 16; 3580, pp.
1229-1231). Such data are not often available to analysts. However,
Drs. Steenland and Bartell researched and reviewed worker exposure and
dust composition data from several worksites to inform the error
structures used in their analyses. For example, their analysis of
individual workers' exposure data from the pooled analyses' industrial
sand cohort formed the basis of the equation used for the exposure
error simulation, which Dr. Cox represented as an assumption lacking
any rationale. Drs. Steenland and Bartell also reviewed a number of
studies characterizing the distribution of conversion factors across
and within jobs at different worksites. OSHA concludes that Drs.
Steenland and Bartell made a strong effort to collect data to inform
their modeling choices, and that their choices were based on the

best available information on error structure.
    Dr. Long stated that ``another limitation of the [ToxaChemica
uncertainty] assessment was its assumption of log-linear . . . types of
models, including log linear models with log-transformed exposure
variables, and it focused on cumulative measures of silica exposure
that obscure both within-person and between-person variability in
exposure rates'' (Document ID 3576 pp. 305-306). Dr. Long's assertion
regarding the choice of exposure models is incorrect, as the
sensitivity analysis was not limited to log-linear models. It included
models with flexibility to capture nonlinearities in exposure-response,
including spline analyses and categorical analyses, and log-
transformation of the exposure variable was used only in the lung
cancer analysis where it was shown in the original pooled analysis to
better fit the data and address issues of heterogeneity between cohorts
(Document ID 0469). Drs. Steenland and Bartell found only slight
differences between the adjusted exposure-response estimates for each
type of model.
    Drs. Long and Valberg also contended that the cumulative exposure
metric used in the Steenland and Bartell pooled study did not
sufficiently allow for examination of the effects of exposure
measurement uncertainty on the results of OSHA's risk assessment,
because other exposure metrics could be more relevant. OSHA disagrees.
As discussed in Section V.M, Comments and Responses Concerning Working
Life, Life Tables, and Dose Metric, cumulative exposure is widely
acknowledged by health experts as a driver of chronic diseases such as
silicosis and lung cancer, has been found to fit the exposure-response
data well in many studies of silicosis and lung cancer in the silica
literature, and best fit the exposure-response data in the underlying
pooled data sets to which Drs. Steenland and Bartell applied their
subsequent uncertainty analyses. Thus, OSHA believes it was appropriate
for this investigation of exposure estimation error to focus on the
cumulative exposure metric, for reasons including data fit and general
scientific understanding of this disease.
    Furthermore, Dr. Long's concern that the choice of cumulative
silica exposure might ``obscure within-person variability in exposure
rates'' is not well supported in the context of lung cancer and
silicosis mortality. Because death from these diseases typically occurs
many years after the exposure that caused it, and complete records of
past exposures do not typically exist, it is very difficult, using any
metric, to trace within-person exposure variability (that is, changes
in a person's exposure over time); these factors, not the choice of
cumulative exposure metric, make it difficult to address variability in
individuals' exposures over time and their effects on risk. OSHA notes
that some analysts have explored the use of other exposure metrics in
threshold analyses, submitting studies to the record which the Agency
has reviewed and discussed in Section V.I, Comments and Responses
Concerning Thresholds for Silica-Related Diseases.
    Dr. Long also testified that ``[t]here's very little discussion in
the OSHA report regarding the potential impacts of exposure measurement
error on identification of thresholds . . . [ToxaChemica's 2004 report]
noted that exposure-response threshold estimates are imprecise and
appear to be highly sensitive to measurement errors'' (Document ID 3576
p. 306). Dr. Cox further noted that exposure misclassification can
``create the appearance of a smooth, monotonically increasing estimated
ER [exposure-response] relation'' and shift thresholds to the left
(Document ID 2307, Attachment 4, pp. 41-42); that is, create the
appearance that a threshold effect occurs at a lower exposure level
than would be seen in a data set without exposure misclassification.
    In their uncertainty analysis, Drs. Steenland and Bartell estimated
an exposure-response threshold for the pooled cohorts in each of the 50
runs conducted for their lung cancer analysis. They defined the
``threshold'' as the highest cumulative exposure for which the
estimated odds ratio was less than or equal to 1.0, reporting a mean
value of 3.04 mg/m\3\-days and median of 33.5 mg/m\3\-days across the
50 runs (Document ID 0469, p. 15). The authors observed that ``[t]hese
estimates are somewhat lower than the original estimate (Steenland and
Deddens 2002) of a threshold at 121 mg/m\3\-days (4.8 on the log
scale), which translates to about 0.01 mg/m\3\ [10 [micro]g/m\3\] over
a working 30-year lifetime (considering a 15-year lag), or 0.007
[7[micro]g/m\3\] over a 45-year lifetime without considering a 15-year
lag'' (Document ID 0469, p. 15). These exposure levels are about one-
fifth the PEL of 50 [mu]g/m\3\ included in the final standard.
    As noted by Dr. Long, the threshold estimates were highly variable
across the 50 iterations (SD of 1.64 on the log scale), in keeping with
other comments received by OSHA that estimates of exposure-response
thresholds based on epidemiological data tend to be highly sensitive to
sources of measurement error and other issues common to epidemiological
investigations (see Section V.I, Comments and Responses Concerning
Thresholds for Silica-Related Diseases). However, the Agency notes that
the results of the uncertainty analysis, suggesting a possible
cumulative exposure threshold at approximately one-fifth the final 50
[mu]g/m3 PEL, provide no cause to doubt OSHA's determination
that significant risk exists at both the previous and the revised PEL.
    An additional concern raised by Dr. Cox was based on his
misunderstanding that the equation used to characterize the
relationship between true and observed exposure in Drs. Steenland and
Bartell's simulation, ``Exposuretrue = Exposureobserved + E'',
concerned cumulative exposure. Dr. Cox stated that the equation is
``inappropriate for cumulative exposures [because] both the mean and
the variance of actual cumulative exposure received typically increase
in direct proportion to duration'' (Document ID 2307, Attachment 4, p.
45). That is, the longer period of time over which a cumulative
exposure is acquired, the higher variance is likely to be, because
cumulative exposure is the sum of the randomly varying exposures
received on different days. However, the exposures referred to in the
equation are the mean job-specific concentrations recorded in the job-
exposure matrix (Exposureobserved) and individuals' actual exposure
concentrations from each job worked (Exposuretrue), not their
cumulative exposures (Document ID 0469, p. 11). Therefore, Dr. Cox's
criticism is unfounded.
    Dr. Cox additionally criticized the simulation analysis on the
basis that ``[t]he usual starting point for inhalation exposures [is]
with the random number of particles inhaled per breath modeled as a
time-varying (non-homogenous) Poisson process . . . It is unclear why
ToxaChemica decided to assume (and why OSHA accepted the assumption) of
an underdispersed distribution . . . rather than assuming a Poisson
distribution'' (Document ID 2307, Attachment 4, pp. 45-46). OSHA
believes this criticism also reflects a misunderstanding of Drs.
Steenland and Bartell's analysis. While it could be pertinent to an
analysis of workers' silica dose (the amount of silica that enters the
body), the analysis addresses the concentration of silica in the air
near a worker's breathing zone, not internal dose. The worker's
airborne concentration is the regulated exposure endpoint and the
exposure of interest for OSHA's risk assessment. Thus, the uncertainty
analysis does not need to

account for the number of particles inhaled per breath.
    More broadly, Dr. Cox asserted that the Monte Carlo analysis ``is
an inappropriate tool for analyzing the effects of exposure measurement
error on estimated exposure-response data,'' citing a paper by Gryparis
et al. (2009) (Document ID 2307, Attachment 4, p. 44). This paper
indicates that by randomly simulating exposure measurement error, the
Monte Carlo approach can introduce classical error (Document ID 3870,
p. 262). Peer reviewer Dr. Noah Seixas similarly commented that ``[t]he
typical Monte Carlo simulation, which is what appears to have been
done, would introduce classical error,'' that is, error which is
independent of the unobserved variable (in this case, the true exposure
value). He explained that, as a result, ``the estimated risks [from the
simulation analyses] are most likely to be underestimates, or
conservatively estimating risk. This is an important aspect of
measurement error with significant implications for risk assessment and
should not be overlooked.'' (Document ID 3574, pp. 116-117). Addressing
Dr. Cox's broader point, Dr. Seixas in his peer review stated that the
``simulation of exposure measurement error in assessing the degree of
bias that may have been present is a reasonable approach to assessing
this source of uncertainty'' (Document ID 3574, pp. 116). Dr. Crump
similarly characterized the uncertainty analysis used in the Steenland
and Bartell study as ``a strong effort'' that ``appropriately applied''
this method (Document ID 3574, pp. 161-162). In this regard, OSHA
generally notes that the advantages and limitations of various methods
to address exposure measurement error in exposure-response models is an
area of ongoing investigation in risk assessment. As shown by the
comments of OSHA's peer reviewers above, there is no scientific
consensus to support Dr. Cox's opinion that the Monte Carlo analysis is
an inappropriate approach to analyze the effects of exposure
measurement error.
    In conclusion, through use of high quality studies and modeling,
performance of an uncertainty analysis, and submission of the results
of that analysis to peer review, OSHA maintains that it has relied upon
the best available evidence. In addition, OSHA has carefully considered
the public comments criticizing ToxaChemica's uncertainty analysis and
has concluded that exposure estimation error did not substantially
affect the results in the majority of studies examined (Document ID
1711, pp. 299-314). As a result, it was not necessary to conduct
additional analyses modifying the approach adopted by Drs. Steenland
and Bartell. Accordingly, OSHA reaffirms its determination that the
conclusions of the Agency's risk assessment are correct and largely
unaffected by potential error in exposure measurement.

L. Comments and Responses Concerning Causation

    As discussed in Section V.C, Summary of the Review of Health
Effects Literature and Preliminary QRA, OSHA finds, based upon the best
available evidence in the published, peer-reviewed scientific
literature, that exposure to respirable crystalline silica increases
the risk of silicosis, lung cancer, other non-malignant respiratory
disease (NMRD), and renal and autoimmune effects. Exposure to
respirable crystalline silica causes silicosis and is the only known
cause of silicosis. For other health endpoints like lung cancer that
have both occupational and non-occupational sources of exposure, OSHA
used a comprehensive weight-of-evidence approach to evaluate the
published, peer-reviewed scientific studies in the literature to
determine their overall quality and whether there is substantial
evidence that exposure to respirable crystalline silica increases the
risk of a particular health effect. For example, with respect to lung
cancer, OSHA reviewed 60 epidemiological studies covering more than 30
occupational groups in over a dozen industrial sectors and concluded
that exposure to respirable crystalline silica increases the risk of
lung cancer (Document ID 1711, pp. 77-170). This conclusion is
consistent with that of the World Health Organization's International
Agency for Research on Cancer (IARC), HHS' National Toxicology Program
(NTP), the National Institute for Occupational Safety and Health
(NIOSH), and many other organizations and individuals, as evidenced in
the rulemaking record and discussed throughout this section.
    In spite of this, and in addition to asserting that OSHA's
Preliminary QRA was affected by many biases, Dr. Cox, on behalf of the
ACC, argued that OSHA failed to conduct statistical analyses of
causation, which led to inaccurate conclusions about causation. He
specifically challenged OSHA's reliance upon the IARC determination of
carcinogenicity, as discussed in Section V.F, Comments and Responses
Concerning Lung Cancer Mortality, and its use of the criteria for
evaluating causality developed by the noted epidemiologist Bradford
Hill (Document ID 2307, Attachment 4, pp. 13-14; 4027, p. 28). The Hill
criteria are nine aspects of an association that should be considered
when examining causation: (1) The strength of the association; (2) the
consistency of the association; (3) the specificity of the association;
(4) the temporal relationship of the association; (5) the biological
gradient (i.e., dose-response curve); (6) the biological plausibility
of the association; (7) coherency; (8) experimentation; and (9) analogy
(Document ID 3948, pp. 295-299).
    Instead, Dr. Cox suggested that OSHA use the methods listed in
Table 1 of his 2013 paper, ``Improving causal inferences in risk
analysis,'' which he described as ``the most useful study designs and
methods for valid causal analysis and modeling of causal exposure-
response (CER) relations'' (Document ID 2307, Attachment 4, p. 11).
Because OSHA did not use these methods, Dr. Cox maintained that the
Agency's Preliminary QRA ``asserts causal conclusions based on non-
causal studies, data, and analyses'' (Document ID 2307, Attachment 4,
p. 3). He also contended that OSHA ``ha[d] conflated association and
causation, ignoring the fact that modeling choices can create findings
of statistical associations that do not predict correctly the changes
in health effects (if any) that would be caused by changes in
exposures'' (Document ID 2307, Attachment 4, p. 3). He claimed that
``[t]his lapse all by itself invalidates the Preliminary QRA's
predictions and conclusions'' (Document ID 2307, Attachment 4, p. 3).
As discussed below, since OSHA's methodology and conclusions regarding
causation are based on the best available evidence, they are sound.
Consequently, Dr. Cox's contrary position is unpersuasive.
1. IARC Determination
    Dr. Cox asserted that OSHA erred in its reliance on the IARC
determination of carcinogenicity for crystalline silica inhaled in the
forms of quartz or cristobalite. He believed OSHA only relied on the
IARC findings because they aligned with the Agency's opinion, noting
that the ``IARC analysis involved some of the same researchers, same
methodological flaws, and same gaps in explicit, well-documented
derivations of benefits and conclusions as OSHA's own preliminary QRA''
(Document ID 2307, Attachment 4, pp. 13-14). OSHA, however, relied on
IARC's determination to include lung cancer in its quantitative risk
assessment because it constitutes the best available evidence. For this
reason, Dr. Cox's position is without merit and OSHA's

findings are supported by substantial evidence in the record and
reasonable.
    As discussed in Section V.F, Comments and Responses Concerning Lung
Cancer Mortality, the IARC classifications and accompanying monographs
are well recognized in the scientific community, and have been
described by scientists as ``the most comprehensive and respected
collection of systematically evaluated agents in the field of cancer
epidemiology'' (Demetriou et al., 2012, Document ID 4131, p. 1273).
IARC's conclusions resulted from a thorough expert committee review of
the peer-reviewed scientific literature, in which crystalline silica
dust, in the form of quartz or cristobalite, was classified as Group 1,
``carcinogenic to humans,'' in 1997 (Document ID 2258, Attachment 8, p.
210). Since the publication of these conclusions, the scientific
community has reaffirmed their soundness. In March of 2009, 27
scientists from eight countries participated in an additional IARC
review of the scientific literature and reaffirmed that crystalline
silica dust is a Group 1 carcinogen, i.e., ``carcinogenic to humans''
(Document ID 1473, p. 396). Additionally, the HHS' U.S. National
Toxicology Program also concluded that respirable crystalline silica is
a known human carcinogen (Document ID 1164, p. 1).
    Further supporting OSHA's reliance on IARC's determination of
carcinogenicity for its quantitative risk assessment is testimony
offered by scientists during the informal public hearings. This
testimony highlighted IARC's carcinogenicity determinations as very
thorough examinations of the scientific literature that demonstrate
that exposure to respirable crystalline silica causes lung cancer. For
example, when asked about Dr. Cox's causation claims during the
informal public hearings, David Goldsmith, Ph.D., noted that causation
was very carefully examined by IARC. He believed that IARC, in its 1997
evaluation of evidence for cancer and silica, ``. . . chose . . . the
best six studies that were the least confounded for inability to
control for smoking or other kinds of hazardous exposures like
radiation and asbestos and arsenic . . .'' (Document ID 3577, Tr. 894-
896). He also believed it ``. . . crucial . . . that we pay attention
to those kinds of studies, that we pay attention to the kinds of
studies that were looked at by the IARC cohort that Steenland did from
2001. That's where they had the best evidence'' (Document ID 3577, Tr.
894-896).
    Regarding IARC's evaluation of possible biases and confounders in
epidemiological studies, as well as its overall determination, Frank
Mirer, Ph.D., of CUNY School of Public Health, representing the AFL-
CIO, testified:

    IARC has active practicing scientists review--I've been on two
IARC monographs, but not these monographs, monograph working groups.
It's been dealt with. It's been dealt with over a week of intense
discussion between the scientists who are on these committees, as to
whether there's chance bias in confounding which might have led to
these results, and by 1987 for foundries and 1997 for silica, and
it's been decided and reaffirmed.
    So people who don't believe it are deniers, pure and simple.
This is the scientific consensus. I was on the NTP Board of
Scientific Counselors when we reviewed the same data. Known to be a
human carcinogen. Once you know it's a human carcinogen from studies
in humans, you can calculate risk rates (Document ID 3578, Tr. 937).

    That OSHA relied on the best available evidence to draw its
conclusions was also affirmed by Dr. Cox's inability to provide
additional studies that would have cast doubt on the Agency's causal
analysis. Indeed, during the informal public hearings, Kenneth Crump,
Ph.D., an OSHA peer reviewer from the Louisiana Tech University
Foundation, asked Dr. Cox if he could identify ``any causal studies of
silica that they [OSHA] should have used but did not use?'' Dr. Cox
responded: ``I think OSHA could look at a paper from around 2007 of
Brown's, on some of the issues and causal analysis, but I think the
crystalline silica area has been behind other particulate matter areas
. . . in not using causal analysis methods. So no, I can't point to a
good study that they should have included but didn't'' (Document ID
3576, Tr. 401-402). In light of the above, OSHA maintains that in
relying on IARC's determination of carcinogenicity, its conclusions on
causation are rooted in the best available evidence.
2. Bradford Hill Criteria and Causality
    Dr. Cox also challenged OSHA's use of Hill's criteria for
causation. He claimed that the Bradford Hill considerations were
neither necessary nor sufficient for establishing causation, which was
his reason for failing to include them in the statistical methods
listed in Table 1 of his written comments for objectively establishing
evidence about causation (Document ID 4027, p. 28). As explained below,
based on its review of the record, OSHA finds this position meritless,
as it is unsupported by the best available evidence.
    As a preliminary matter, Hill's criteria for causation (Document ID
3948) are generally accepted as a gold standard for causation in the
scientific community. Indeed, OSHA heard testimony during the informal
public hearings and received post-hearing comments indicating that Dr.
Cox's assertion that statistical methods should be used to establish
causality is not consistent with common scientific practice. For
example, Andrew Salmon, Ph.D., an OSHA peer reviewer, wrote:

    The identification of causality as opposed to statistical
association is, as described by Bradford Hill in his well-known
criteria, based mainly on non-statistical considerations such as
consistence, temporality and mechanistic plausibility: the role of
statistics is mostly limited to establishing that there is in fact a
quantitatively credible association to which causality may (or may
not) be ascribed. OSHA correctly cites the substantial body of
evidence supporting the association and causality for silicosis and
lung cancer following silica exposure, and also quotes previous
expert reviews (such as IARC). The causal nature of these
associations has already been established beyond any reasonable
doubt, and OSHA's analysis sufficiently reflects this (Document ID
3574, p. 38).

    Similarly, Kyle Steenland, Ph.D., Professor, Department of
Environmental Health, Rollins School of Public Health, Emory
University, in response to a question about Dr. Cox's testimony on
causation from Darius Sivin, Ph.D., of the UAW Health and Safety
Department, stated that the Bradford Hill criteria are met for lung
cancer and silicosis:

    [M]ost of the Bradford Hill criteria apply here. You know you
can never prove causality. But when the evidence builds up to such
an extent and you have 100 studies and they tend to be fairly
consistent, that's when we draw a causal conclusion. And that was
the case for cigarette smoke in lung cancer. That was the case for
asbestos in lung cancer. And when the evidence builds up to a
certain point, you say, yeah, it's a reasonable assumption that this
thing causes, X causes Y (Document ID 3580, pp. 1243-1244).

    As a follow-up, OSHA asked if Dr. Steenland felt that the Bradford
Hill criteria were met for silica health endpoints. Dr. Steenland
replied, ``For silicosis or for lung cancer. I had said they're met for
both'' (Document ID 3580, p. 1262).
    Gary Ginsberg, Ph.D., an OSHA peer reviewer, agreed with Dr.
Steenland, remarking to Dr. Cox during questioning, ``I'm a little
dumbfounded about the concern over causality, given all the animal
evidence'' (Document ID 3576, Tr. 406). Mr. Park from NIOSH's Risk
Evaluation Branch, in his question to Dr. Cox, echoed the sentiments of
Dr. Ginsberg, stating:

    It's ludicrous to hear someone question causality. There's 100
years of research in occupational medicine, in exposure assessment.
People here even in industry would agree that silica they say causes
silicosis, which causes lung cancer. There's some debate about
whether the middle step is required. There's no question that
there's excess lung cancer in silica-exposed populations. We look at
literature, and we identify what we call good studies. Good studies
are ones that look at confounding, asbestos, whatever. We make
judgments. If there's data that allows one to control for
confounding, that's part of the analysis. If there is confounding
that we can't control for, we evaluate it. We ask how bad could it
be? There's a lot of empirical judgment from people who know these
populations, know these exposures, know these industries, who can
make very good judgments about that. We aren't stupid. So I don't
know where you're coming from (Document ID 3576, Tr. 410-411).

    Indeed, Kenneth Mundt, Ph.D., testifying on behalf of the
International Diatomite Producers Association (part of the ACC
Crystalline Silica Panel, which included Dr. Cox), and whose research
study was the basis for the Morfeld et al. (2013, Document ID 3843)
paper that reportedly identified a high exposure threshold for
silicosis, also appeared to disagree with Dr. Cox's view of causation.
Dr. Mundt testified that while he thought he could appreciate Dr. Cox's
testimony, at some point there is sufficiently accumulated evidence of
a causal association; he concluded, ``I think here, over time, we've
had the advantage with the reduction of exposure to see reduction in
disease, which I think just makes it a home run that the diseases are
caused by, therefore can be prevented by appropriate intervention''
(Document ID 3577, Tr. 639-640).
    OSHA notes that Dr. Cox, upon further questioning by Mr. Park,
appeared to concede that exposure to respirable crystalline silica
causes silicosis; Dr. Cox stated, ``I do not question that at
sufficiently high exposures, there are real effects'' (Document ID
3576, Tr. 412). Later, when questioned by Anne Ryder, an attorney in
the Solicitor of Labor's office, he made a similar statement: ``I do
take it as given that silica at sufficiently high and prolonged
exposures causes silicosis'' (Document ID 3576, Tr. 426). Based upon
this testimony of Dr. Cox acknowledging that silica exposure causes
silicosis, OSHA interprets his concern with respect to silicosis to be
not one of causation, but rather a concern with whether there is a
silicosis threshold (i.e., that exposure to crystalline silica must
generally be above some level in order for silicosis to occur). Indeed,
OSHA peer reviewer Brian Miller, Ph.D., noted in his post-hearing
comments that Dr. Cox, when challenged, accepted that silica was causal
for silicosis, ``but questioned whether there was evidence for
increased risks at low concentrations; i.e. whether there was a
threshold'' (Document ID 3574, p. 31). Thresholds for silicosis are
addressed in great detail in Section V.I, Comments and Responses
Concerning Thresholds for Silica-Related Diseases.
    Based on the testimony and written comments of numerous scientists
representing both public health and industry--all of whom agree that
causation is established by applying the Bradford Hill criteria and
examining the totality of the evidence--OSHA strongly disagrees with
Dr. Cox's claims that the Bradford Hill criteria are inadequate to
evaluate causation in epidemiology and that additional statistical
techniques are needed to establish causation. OSHA defends its reliance
on the IARC determination of 1997 and re-determination of 2012 that
crystalline silica is a causal agent for lung cancer. OSHA's own Review
of Health Effects Literature further demonstrates the totality of the
evidence supporting the causality determination (Document ID 1711).
Indeed, other than Dr. Cox representing the ACC, no other individual or
entity questioned causation with respect to silicosis. Even Dr. Cox's
questioning of causation for silicosis appears to be more of a question
about thresholds, which is discussed in Section V.I, Comments and
Responses Concerning Thresholds for Silica-Related Diseases.
3. Dr. Cox's Proposed Statistical Methods
    OSHA reviewed the statistical methods provided by Dr. Cox in Table
1 of his 2013 paper, ``Improving causal inferences in risk analysis,''
(Document ID 2307, Attachment 4, p. 11), and explains below why the
Agency did not adopt them. For example, Intervention Time Series
Analysis (ITSA), as proposed by Dr. Cox in his Table 1, is a method for
assessing the impact of an intervention or shock on the trend of
outcomes of interest (Gilmour et al., 2006, cited in Document ID 2307,
Attachment 4, p. 11). Implementing ITSA requires time series data
before and after the intervention for both the dependent variable
(e.g., disease outcome) and independent variables (e.g., silica
exposure and other predictors), as well as the point of occurrence of
the intervention. Although time-series data are frequently available in
epidemiological studies, for silica we do not have a specific
``intervention point'' comparable to the implementation of a new OSHA
standard that can be identified and analyzed. Rather, changes in
exposure controls tend to be iterative and piecemeal, gradually
bringing workers' exposures down over the course of a facility's
history and affecting job-specific exposures differently at different
points in time. Furthermore, individual workers' exposures change
continually with new job assignments and employment. In addition, in a
situation where the intervention really reduces the adverse outcome to
a low level, such as 1/1000 lifetime excess risk, ITSA would require an
enormous observational database in order to be able to estimate the
actual post-intervention level of risk. OSHA believes the standard risk
analysis approach of estimating an exposure-response relationship based
on workers' exposures over time and using this model to predict the
effects of a new standard on risk appropriately reflects the typical
pattern of multiple and gradual changes in the workers' exposures over
time found in most industrial facilities.
    Another method listed in Dr. Cox's Table 1, marginal structural
models (MSM), was introduced in the late 1990s (Robins, 1998, cited in
Document ID 2307, Attachment 4, p. 11) to address issues that can arise
in standard modeling approaches when time-varying exposure and/or time-
dependent confounders are present.\10\ These methods are actively being
explored in the epidemiological literature, but have not yet become a
standard method in occupational epidemiology. As such, OSHA faces some
of the same issues with MSM as were previously noted with BMA:
Published, peer-reviewed studies using this approach are not available
for the silica literature, and best practices are not yet well
established. Thus, the incorporation of MSM in the silica risk
assessment is not possible using the currently available literature and
would be premature for OSHA's risk assessment generally.
---------------------------------------------------------------------------

    \10\ A time-dependent confounder is a covariate whose post-
baseline value is a risk factor for both the subsequent exposure and
the outcome.
---------------------------------------------------------------------------

    In addition, in his post-hearing brief, Dr. Cox contended that
``[a] well-done QRA should explicitly address the causal fraction (and
explain the value used), rather than tacitly assuming that it is 1''
(Document ID 4027, p. 4). However, this claim is without grounds. OSHA
understands Dr. Cox's reference to the ``causal fraction'' to mean
that,

when estimating risk from an exposure-response model, only a fraction
of the total estimated risk should be attributed to disease caused by
the occupational exposure of interest. The Agency notes that the
``causal fraction'' of risk is typically addressed through the use of
life table analyses, which incorporate background rates for the disease
in question. Such analyses, which OSHA used in its Preliminary QRA,
calculate the excess risk, over and above background risk, that is
solely attributable to the exposure in question. Thus, there is no need
to estimate a causal fraction due to exposure. These approaches are
further discussed in Section V.M, Comments and Responses Concerning
Working Life, Life Tables, and Dose Metric. Furthermore, nowhere in the
silica epidemiological literature has the use of an alternative
``causal fraction'' approach to ascribing the causal relationship
between silica exposure and silicosis and lung cancer been deemed
necessary to reliably estimate risk.
4. The Assertion That the Silica Scientific Literature May Be False
    Dr. Cox also asserted that the same biases and issues with
causation in OSHA's Quantitative Risk Assessment (QRA) were likewise
present in the silica literature. He wrote, ``In general, the
statistical methods and causal inferences described in this literature
are no more credible or sound than those in OSHA's Preliminary QRA, and
for the same reasons'' (Document ID 2307, Attachment 4, p. 30).
    The rulemaking record contains evidence that contradicts Dr. Cox's
claims with respect to the scientific foundation of the QRA. Such
evidence includes scientific testimony and the findings of many expert
bodies, including IARC, the HHS National Toxicology Program, and NIOSH,
concluding that exposure to respirable crystalline silica causes lung
cancer. At the public hearing, Dr. Steenland, Professor at Emory
University, testified that the body of evidence pertaining to silica
was of equal quality to that of other occupational health hazards
(Document ID 3580, pp. 1245-1246). Dr. Goldsmith similarly testified:

    Silica dust . . . is like asbestos and cigarette smoking in that
exposure clearly increases the risk of many diseases. There have
been literally thousands of research studies on exposure to
crystalline silica in the past 30 years. Almost every study tells
the occupational research community that workers need better
protection to prevent severe chronic respiratory diseases, including
lung cancer and other diseases in the future. What OSHA is proposing
to do in revising the workplace standard for silica seems to be a
rational response to the accumulation of published evidence
(Document ID 3577, Tr. 865-866).

    OSHA agrees with these experts, whose positive view of the science
supporting the need for better protection from silica exposures stands
in contrast to Dr. Cox's claim regarding what he believes to be the
problematic nature of the silica literature. Dr. Cox asserted in his
written statement:

    Scientists with subject matter expertise in areas such as
crystalline silica health effects epidemiology are not necessarily
or usually also experts in causal analysis and valid causal
interpretation of data, and their causal conclusions are often
mistaken, with a pronounced bias toward declaring and publishing
findings of `significant' effects where none actually exists (false
positives). This has led some commentators to worry that `science is
failing us,' due largely to widely publicized but false beliefs
about causation (Lehrer, 2012); and that, in recent times, `Most
published research findings are wrong' (Ioannadis, 2005), with the
most sensational and publicized claims being most likely to be
wrong. (Document ID 2307, Attachment 4, pp. 15-16).

    Moreover, during the public hearing, Dr. Cox stated that, with