Document X7g7b6zkYdaYwO33v4jggw16G
FILE NAME Brakes BRK
DATE 2011
DOC BRK218
DOCUMENT DESCRIPTION Journal Article - Asbestos Fiber Concentrations
in the Lungs of Brake Repair Workers
t
Inhalation Toxicology 2011 23 681 688 '2011 Informa Healthcare USA Inc. ISSN 0895-8378 print 1091-7691 online DOI 08958378.2011.580472 08958378.2011.580472
RESEARCH ARTICLE
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Asbestos fiber concentrations in the lungs of brake repair workers commercial amphiboles levels are predictive of chrysotile levels
Gary M. Marsh Ada O. Youk,,and Victor L. Roggli
Department of Biostatistics Graduate School ofPublic Health Centerfor DukaBiostatistics and Epidemiology University ofPittsburgh Pittsburgh PA USA and 2Department of Pathology Duka University Medical Center
Durham NC USA
Abstract
2009 Objectives To investigate the impact of extreme data points in
lung levels of commercial and commercial amphiboles high
of association association association between
tremolite as marker for chrysotile asbestos
in brake repair workers with mesothelioma
Methods We first identified potential potential outliers high po)
whe! commercial amphiboles and tremolite among 15 br We brake repair work used sensitivity analysis and a
commercial amphibole levels as a predictor of as
We
quantile reported duration duration employment employment employment
repair
employment worker predicted tremolite
employment
nd- rexts points was through levels of
ronly known rexts was through through
used for rexts data points and model
used
rexts to evaluate whether
predicted lung rexts commercial amphiboles or
amphiboles Results We found lung levels of amphiboles
istically sensitivity analysis = 0.82 slope estimate value that
0.0001 Our data provide no e
duration duration levels of tremolite or amphiboles
amphiboles that
amphiboles
duration
of tremolite tremolite levels via via
call tas dictor regression slope estimate value
tas tas repair worker was a predictor of lung
Conclusions Our findings amphiboles that elevated levels of amphiboles arose
elevated lung duration duration repair repair repair workers workers workers workers with with
from concurrent SITUolite commercial amphibole and chrysotile asbestos
in occupational settingthan than brake repair for SITUolite lungs are supported by five new cases The weight of
role for the scientific of mesothelioma
support a
for exposure to brake dust and other friction products in
of the development mesothelioma
Keywords Asbestos amphibolestremolite chrysotile amosite crocidolite occupational diseases lung cancer
mesothelioma robust regression sensitivity analysis
Introduction
Canadian chrysotile which accounted for the vast majority of chrysotile used in the United States in the manufacture of asbestos products is recognized to be contaminated with tremolite It has been suggested that tremolite might be a reasonably good biomarker for exposure to Canadian chrysotile as chrysotile tends to be degraded and removed from the lungs over time whereas amphiboles like tremolite are more biopersistent
Churg 1988 Indeed analyses of lung tissue samples from Canadian chrysotile miners and millers have shown predominance of tremolite fibers Churg et al 1993 Furthermore mesothelioma occurrence among
Canadian miners and millers correlates best with the
degree of tremolite contamination in the various mines McDonald et al 1997
In 2002 Roggli et al reported the correlation between type of occupational asbestos exposure and asbestos fiber
Addressfor Correspondence Gary M. Marsh Department of Biostatistics Graduate School of Public Health University of Pittsburgh
Pittsburgh PA 15261 USA Tel 412-624-3032 Fax 412-624-9969 mail gmarsh@cobe.pitt.edu gmarsh@cobe.pitt.edu Received 19 February 2011 revised 05 April 2011 accepted 08 April 2011
681
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682 G.M. Marsh al
lung burden levels for 1445 malignant mesothelioma cases Butnor et al 2003 reported results of lung fiber analysis for 10 malignant mesothelioma cases from Roggli et al 2002 whose only known exposure to asbestos was occupational contact with friction products e.g. brake dust as a brake repair worker Commercial amphiboles amosite or crocidolite asbestos were found in eight cases with excessive commercial amphibole fibers found in five of
the cases The authors concluded that the presence of the
elevated commercial amphiboles in the lungs of some of these cases suggested exposures other than occupational exposure to brake dust which contains small amounts
0.1-1 of mostly short < ...min length chrysotile asbes-
tos fibers Lynch 1968 Hatch 1970 Davis and Coniam 1973 Williams and Muhlbaier 1982 Wong 2001
Finkelstein 2008 reported a reanalysis of the data in Butnor et al 2003 using an alternative computation for
mean fiber concentration which resulted in mean con-
centrations of commercial asbestos exposure principally tremolite with some actinolite and anthophyllite measured as a marker of chrysotile exposure that were higher than reported by Butnor et al 2003 In a letter to the editor Roggli et al 2009 considered this finding consistent with those of Butnor et al 2003 In response to the Roggli et al 2009 letter Finkelstein 2009 concluded from a regression analysis of the same 10 cases Butnor et al 2003 that levels of commercial amphiboles are not predictive of the levels of tremolite as a marker of chrysotile exposure thus implicating exposure to chrysotile fibers from friction products as a causative fac-
tor for these mesothelioma cases
We questioned the validity of Finkelstein's 2009 conclusion due to the observation in his Figure 1 of at least two extreme data points that were not appropriately weighted in the regression analysis The purpose of our
_
reanalysis reported here was to investigate the robustness ofFinkelstein's 2009 findings with respect to the presence of these extreme points Our reanalysis also extends the work of Finkelstein 2009 by including amphibole and
tremolite fiber concentration levels for five new cases
of malignant mesothelioma from the Roggli et al case series whose only known asbestos exposure was occupational contact as a brake repair worker We also examined whether reported duration of employment as
a brake repair worker was a predictor of lung levels of
commercial amphiboles or tremolite
Methods
We abstracted from Butnor et al 2003 data on the levels of commercial amphibole fiber and tremolite fiber found in the lungs of 10 mesothelioma cases used in the Finkelstein 2008 2009 analyses The 10 cases from Butnor et al 2003 were selected on the basis of three criteria 1 having mesothelioma 2 only known asbestos exposure was occupational contact as a brake repair worker and 3 lung tissue was available for analysis In the process of preparing this manuscript we identified and corrected three errors in Butnor et al 2003 related to the lung fiber levels of two of the 10 cases Specifically for Case 2 the commercial amphiboles level changed from 4810 to 3940 for Case 3 commercial amphiboles changed from 380 to 970 and tremolite changed from 4630 to 4110 We also included lung levels of commercial amphibole
and tremolite fibers for the five new mesothelioma cases
from the Roggli et al series who were observed since the publication of Butnor et al 2003 and who met the same
three inclusion criteria We also included information on
reported duration of employment as a brake repair worker for all 15 cases Table 1
4000
'CCaassee 3
3000
TremoliteLevels 2000 C as1e0 L
e
1000
Model 1
Case9 e
e@ Case2
T
2000
4000
Commercial Amphibole Levels
r
6000
Figure 1. The relationship between the levels of commercial amphibole fibers and tremolite fibers in the lungs of brake repair workers fitted simple linear regression model with 10 original data points Model 1 From Butnor et al 2003 and revised per Methods section
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Fiber analyses and ascertainment of the diagnosis of
mesothelioma in the five new cases were as described
previously by Butnor et al 2003 and are summarized in Table 2 along with other relevant case information All were males with ages ranging from 40 to 70 years median 58 years Four were pleural mesotheliomas and one was peritoneal Four out of five were smokers or smokers The length of employment as a brake repair worker ranged from 5 to 32 years median 20 years
As in previous analyses Roggli et al 2002 Butnor et al 2003 Finkelstein 2009 we substituted a value of
1/2 the detection limit for fiber levels below the limit of
detection Cases with a less than < sign before the value are at the detection limit for that value For example
as shown in Table 1 in Case 11 no asbestos fibers were
Amphibole lung levels predict chrysotile levels 683
detected and the detection limit was 520. In Case 12 the
asbestos body count is clearly elevated and a single cro-
cidolite fiber was identified by SEM the detection limit
was 810 for that case The detection limit varies from case
to case because the amount of tissue available to analyze varied from case to case i.e. the weight of the sample For Case 15 one commercial amphibole fiber and one noncommercial amphibole fiber were identified Chrysotile was not detected Table 2
We recognized that 15 cases represent relatively small
sample from which to infer whether tremolite levels are correlated with commercial amphibole levels or whether either level is correlated with duration of employment Moreover many data points for amphibole and tremolite levels were below the detection limit detects These
Table 1. Lung levels of commercial amphiboles and tremolite and reported duration of employment for 15 mesothelioma cases whose only known exposure to asbestos was occupational contact as a brake repair worker
Case
12316
Commercial amphiboles
3270
Tremolitec.d 2180
Duration of employment years
322
12316
3940
440
322
12316
970
4110
322
12316
720 used 360
12316
580 used 290
720
40
1160
11
6
490
490
7
7
340
340 used 170
15
&
120
240
40
----
6000
3280
17
10
1440
2170
257322
11b
520 used 260
520 used 260
257322
12b
810
810 used 405
257322
13b
480 used 240
480 used 240
257322
14b
390 used 195
390 used 195
257322
15b
490
490
257322
Data abstracted from Butnor et al 2003 and revised per Methods section New cases from Roggli case series Fibers per gram ofwet lung tissue for fibers 5 ...mor greater in length One the detection limit value used in analysis and shown in parentheses
Table 2. Demographic pathologic and occupational information and results of lung tissue analysis for five new mesothelioma cases whose only known exposure to asbestos was occupational contact as a brake repair worker
Case from Table 1
11
Age years
sex
69
Tumor type Occupation
BP1
clutch
repair IH
Smoking pack 1-1.5 ppd XS years
Pleural plaque
ND
ABAB
7
Chrysotileb
520
12
70
EPI
Auto mechanic
Pipe many years
ND
90
810
13
58
EP1
Auto mechanic
NS
ND
6.7
480
14
58
EPI
Auto mechanic
1.5 ppd 45 years
ND
29
390
15
40
EPe
QC inspector 0.5 ppd 23 years
ND
2
490
Median
58
Reference
casesc
-_
_-
_
-
_
-
7
490
_
3 0.2-22 600 100-1000
B Biphasic E epithelial IH International Harvester M male ND not determined NS smoker Pe peritoneal Pl pleural ppd packs per day QC quality control XS smoker AB asbestos bodies NAMF asbestos mineral fiber AB asbestos bodies wet lung by light microscopy Total coated AB and uncoated fibers 5...mlength wet lung as determined by scanning electron microscopy and energy dispersive ray analysis Median values and range in parentheses for 20 cases with normal lungs at autopsy normal range tissue asbestos body counts and no evidence of asbestos disease Butnor et al 2003
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684 G.M. Marsh et
limitations notwithstanding these 15 cases represent all
eligible cases from the Butnor et al 2003 and Roggli
al case series Obtaining additional cases and using or developing methods that lower fiber detection levels were not practical options for our analysis
We first attempted to replicate the Finkelstein 2009 results by fitting a simple linear regression on the 10 data
points from Butnor et 2003 Second to assess whether
commercial amphiboles are predictive oftremolite levels
we performed a simple linear regression and used regres-
sion diagnostics to locate any potential outliers high leverage or influential points using all 15 data points An outlier is defined as any point with a large residual difference between observed and fitted values value a high leverage point is an observation with an extreme value in one of the predictor variables and an influential point is one that substantially changes the estimates of the coef-
ficients when removed A standardized residual is the
residual divided by the estimate of its standard error Any standardized residual value over 2.0 is typically considered to be large A standard marker for high leverage is anything greater than k where is the number of
predictors in the model and n is the sample size Criteria for a point to be considered a highly influential point is
typically any value larger than n Chatterjee and Hadi
200W6e then sensita isenvsiititviyty analysibsy remov-
ing any points that were considered to be extreme outliers high leverage or influential refitting the regression model and comparing these results to the model based on all 15 points
We also fit a quantile regression model to account for the undue influence of the extreme points without omitting them as in the sensitivity analysis Unlike simple
linear regression which is based on a least squared devi-
ation criterion quantile regression minimizes the sum of absolute residuals using a linear absolute value function Because this function is symmetric minimizing the
sum of absolute residuals ensures that the same number of observations occur above and below the median
Because the quantile regression model estimates the relationship between a predictor variable and specific quantiles of the outcome variable rather than the mean of the outcome variable as in simple linear regression the parameter estimates are robust with respect to large outliers or influential points Koenker and Hallock 2001 Hao and Naiman 2007 Cameron and Travedi 2009
We also used simple linear regression and quantile regression to evaluate the relationship between duration of employment as a brake repair worker and lung levels of commercial amphiboles or tremolite All statistical models were fit using the Stata Statistical Software Release 11 StataCorp 2009
Results
While data are not shown here we replicated exactly the simple linear regression results ofFinkelstein 2009 Using
the revised data for Cases 2 and 3 we refit the simple linear regression model as shown in Model 1 and Figure 1
Tremolite level =
981.01 + 0.29 commercial amphiboles level Model )
As found using the original data commercial amphi-
boles level was not a statistically significant predictor of
tremolite r 0.43 slope estimate value = 0.21 and the R= 0.19 was low indicating a poor fit only 19 of the variance explained by Model 1
We refit the Finkelstein 2009 model using all 15 data points as shown in Model 2 and Figure 2
Tremolite level =
615.09 +0.38 +0.38 commercial amphiboles level
Model 2
Unlike Model 1 commercial amphiboles level was a statistically significant predictor of tremolite r = 0.53 slope estimate value = 0.04 but the R= 0.28 was low indicating a poor fit only 28 of the variance explained by Model 2 Model 2 remains an inferior model because it does not properly account for extreme values
In Models 1 and 2 Case 2 Case 3 and possibly Cases 9 and 10 appear as extreme points that could affect the fit-
ted line Figures 1 and 2 We performed regression diagnostics to determine if these points were in fact causing undue influence to the fitted equation Table 3 shows the computed residuals standardized residuals leverage and influence statistics For these data the cutoff for high leverage is 0.40 and for a highly influential point it is 0.27
In Table 3 the highlighted values are those that exceed the typical cutoff values Case 3 is an outlier and an influential point Cases 2 and 10 also have the potential to be outliers as their residuals are much larger than the other residuals Case 2 is also an influential point Case 9 is a high leverage point
We performed a sensitivity analysis by refitting the simple linear regression of tremolite versus commercial amphiboles with the three extreme points removed Cases 2 3 and 9 Case 10 was not removed
because the cutoff was not exceeded for the standard-
ized residual leverage and influence The fitted line
without these three points is shown in Model 3 and Figure 2
Tremolite level =
257.49 +0.68 +0.68 commercial amphiboles level
Model 3
The constant term in Model 3 is about 1/3 that of Model
2 and the slope estimate for commercial amphiboles increased almost fold Commercial amphibole con-
centration is a now statistically significant predictor of
tremolite 0.82 slope estimate value and the 0.68 68 of the variation is explained by this Model 3
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The fitted quantile regression model is shown in Model 4 and Figure 2
Tremolite level =
177.96 +0.52 +0.52 commercial amphiboles level Model 4
As revealed by the slope estimates and the fitted lines in Figure 2 Model 4 falls between the model using all 15
points Model 2 and the model with the three extreme
points omitted Model 3 In our quantile regression model that properly accounts for extreme values without
Table 3. Results of regression diagnostics residuals standardized residuals leverage and influence
Standardized
Case E
CN
Residuals
318.583
-1676.780
residuals
0.317
-1.745
Leverage
0.160 0.234
Influence 0.010 0.465
CN
3125.201
A
32.305
2,951 -0.031
0.069 0.087
0.322 0.0001
5a
434.374
0.415
0.090
0.008
6"
-311.853
-0.296
0.081
0.004
1
-574.682
*
-420.832
-0.548 -0.404
0.088 0.099
0.014 0.009
----
378.076
0.540
0.594
0.213
10
1006.066
0.949
0.067
0.032
11b
-454.191
-0.434
0.091
0.009
12b
-518.827
-0.491
0.072
0.009
13b
-466.569
-0.446
0.092
0.010
14b
-494.417
-0.473
0.095
0.012
15b
-311.853
-0.296
0.081
0.004
Data abstracted from Butnor et al 2003 and revised per
Methods section
New cases from Roggli et al case series
Amphibole lung levels predict chrysotile levels 685
omitting them Model 4 commercial amphibole concentration is a statistically significant predictor of tremolite concentration slope estimate value 0.0001 The
correlation coefficient and Rare not shown for the
quantile regression as no accepted method exists for calculating these statistics
Figures 3 and 4 show the scatterplots of duration of employment lung levels oftremolite and commercial amphiboles respectively as well as the fitted lines based on the simple linear regression and quantile regression Each scatterplot reveals evidence of influential points The fitted quantile regression models are given by
Tremolite level = 359.23 + 6.54 duration of employment
Commercial amphiboles level = 517.58 3.94 duration of employment
Neither model revealed any evidence that duration of
employment as a brake repair worker was a predictor of lung fiber level slope estimate values for both models
Discussion
Regression diagnostics sensitivity analysis and quantile regression are rigorous accepted and commonly used analytical procedures to ensure that the fit of a particular statistical model is not overly influenced by one or few observations Koenker and Hallock 2001 Chatterjee and Hadi 2006 Hao and Naiman 2007 Cameron and Travedi 2009 Our use of these rigorous procedures clearly showed that four extreme data points Cases 2 3 9 and 10 led Finkelstein 2009 to conclude incorrectly
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Levels
e Case 10
Tremolite 2000 L
Case 2
0 T
0
T
T
2000
4000
Commercial Amphibole Levels
T
6000
Figure 2. The relationship between the levels of commercial amphibole fibers and tremolite fibers in the lungs of brake repair workers fitted simple linear regression model with all 15 data points Model 2 and omitting three extreme points Model 3 Also showing quantile regression model Model 4 From Butnor et al 2003 and revised per Methods section and including five new cases from Roggli et al case series
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686 G.M. Marsh
that lung levels of commercial amphiboles are not predictive of the levels of tremolite as a marker ofchrysotile
asbestos When we removed or properly accounted for _
these extreme observations using an appropriate regres-
sion model we found that lung levels of commercial
amphiboles area statistically significant predictor oflung
levels of tremolite
We performed several confirmatory analyses to
determine if our results were sensitive to the method of
data substitution or data analysis For example since quantile regression is only one of several statistical approaches for handling data sets that deviate from the
usual assumptions of simple linear regression such as extreme observations and absence of homoscedasticity we fit two regression models as alternatives to Model 4
We also evaluated whether the results of Model 4 and the
alternative models were sensitive to the method used
1/2 detectable level DL for substituting values for detectable lung levels of asbestos Finally we refit Models 2-4 using the original 10 data points reported by Finkelstein 2009 and revised per the Methods section
The first alternative regression model considered was robust regression This model first removes points with an influence statistic greater than 1.0 none in our
4000 'Case 3
e Case 9
Levels
Levels
Tremolite 2000 4
Tremolite
Tremolite
Tremolite
1000
1000
' +
T
0
@ Case 10
Case 1
e
Simple linear regression
ae
Quantile regression model
eet -- -- SAID SNE MATTER SS
_-
e
ee
e
T
T
T
v
10
20 Duration
40
Duration of Employment
Figure 3. The relationship between duration of employment as a brake repair worker and the levels of tremolite fibers in the lungs of brake repair workers fitted simple linear regression model with all 15 data points and quantile regression model
6000 Case 9 e
Levels 4000
4000
fiCase 2
Amphibole
e
Case 1
Comercial2000 a ed ae oe aee taree eae ore am esas me ama san _
o.
LU )
e
e
eg oe
LU
T
LU
T
10
20
40
Duration of Employment
Figure 4. The relationship between duration of employment as a brake repair worker and the levels of commercial amphibole fibers in the lungs of brake repair workers fitted simple linear regression model with all 15 data points and quantile regression model
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analysis then performs a weighted least squares regres-
sion using weights that give small or zero weight to points with large residuals Berk 1990 Chatterjee and Hadi 2006 In the second alternative regression model an unweighted least squares criterion simple linear regression was used to fit transformed values of tremolite and commercial amphibole lung levels Here the logarithmic transformation gives less weight to the
extreme values Alternative methods considered for the substitution of detects were DL and 2DL as
proposed by Sanford et al 1993 and discussed by Helsel 2006 2010
Although data are not shown here both alternative regression models considered led to similar fitted
models that corroborated the central result of Model
4 that is lung levels of commercial amphiboles are a statistically significant predictor of lung levels of
tremolite Moreover the choice of detect substitu-
tion method had negligible impact on the based results of Model 4 and the two alternative regression
models We also found similar results when Models 2-4
were refit using the 10 original data points revised per
the Methods section
Our finding that lung levels ofcommercial amphiboles predict lung levels of tremolite was supported by our related findings that reported duration of employment as a brake repair worker was not associated with lung levels of tremolite or commercial amphiboles That is one would expect lung levels of tremolite chrysotile to increase with increasing duration of employment only
if there was an association between friction products and mesothelioma Also because automotive brakes in the
United States include only the chrysotile form of asbestos one would not expect lung levels of commercial amphiboles to increase with increasing duration of employment as a brake repair worker This lack of correlation between exposure duration and lung levels of tremolite or commercial amphiboles is an important and heretofore unreported observation although the raw data were available in the original Butnor et al's 2003 work Thus our findings suggest that elevated lung levels of tremolite as a marker of chrysotile in the lungs of some brake repair workers with elevated levels of amphiboles arose from concurrent exposures to commercial amphibole and chrysotile asbestos in occupational settings other than brake repair work
Regarding the study by Butnor et al 2003 some investigators have questioned the validity of using scanning electron microscopy SEM for the analysis of lung tissue samples Reanalyzing lung tissue from Case 1 of Butnor et al 2003 Dodson et al 2008 claimed that transmission electron microscopy TEM is the superior instrument As we have stated elsewhere this is a moot
point because lung fiber burden studies ofmesothelioma
using TEM have come to similar conclusions as studies using SEM Srebo et al 1995 Roggli and Vollmer 2008 Roggli et al 2008 Moreover studies from two laboratories employing TEM to analyze a smaller number of lung
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Amphibole lung levels predict chrysotile levels 687
tissue samples of brake mechanics with mesothelioma found similar results to those we reported Dodson et al 2005 2008 reported two cases of mesothelioma one in a brake mechanic and the other an auto machinist both of which had elevated levels of commercial amphiboles the auto machinist case was a reanalysis of Case 1 from Butnor et al 2003 In fact Hammar and Dodson have written elsewhere that the question as to whether automotive mechanics ... have an increased risk of malignant
mesothelioma remains unresolved and contentious
Hammar et al 2008 Furthermore Gordon and Dikman reported eight cases of mesothelioma in brake mechanics All eight had only chrysotile in their lung tissue samples and the chrysotile in each instance was within their reported background population range Gordon and Dikman 2009 Because the findings in these two TEM studies are the same as what we have reported either background levels of asbestos or elevated commercial amphiboles with or without elevated tremolite or chryso-
tile there is no validity to the claim that TEM is superior
to SEM for this purpose
As noted in the study of Butnor et al 2003 and summarized here our reanalysis and extension of the work of Finkelstein 2009 has some underlying limitations First our reanalysis is based on a case series of 15 medico cases that may not be representative of all individuals exposed to friction products occupationally Also historical information obtained by patient interview is subject to recall bias for events occurring decades previously This may explain the absence of reported exposures to commercial amphiboles among the cases considered Additionally many data points for amphibole and tremolite levels associated with the 15 cases were below the detection limit detects As detects can complicate statistical analysis they reflect the very low levels of asbestos in lung tissue which in itself is indicative of a lack of a relationship
between asbestos exposure and mesothelioma in brake
repair workers
Conclusions
Finkelstein's 2009 finding that lung levels of commercial amphiboles are not predictive of the levels of tremolite asbestos chrysotile is invalid because the regression analysis did not properly account for extreme data points Our regression diagnostics sensitivity analysis
quantile regression and evaluation of reported duration of employment as a brake repair worker suggest that elevated lung levels of tremolite chrysotile in the lungs
of brake repair workers with elevated levels of amphi-
boles arose from concurrent exposures to commercial
amphibole and chrysotile asbestos in occupational settings other than brake repair work These findings are supported by the five additionally reported cases in the current study Despite suggestions to the contrary by Dodson et al 2008 and Finkelstein 2008 2009 the weight of the scientific evidence does not support a role
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688 G.M. Marsh et al
for occupational exposure to brake dust and other friction products in the development of mesothelioma
Declaration of interest
Drs Marsh and Youk performed this work study and manuscript preparation as a private consulting activity for Honeywell International Inc. Dr. Marsh was on the Asbestos Panel of the Scientific Advisory Board of the US Environmental Protection Agency He provided expert testimony for defendants in three asbestos liti-
gation cases including two involving friction products Dr. Marsh also provided epidemiological and biostatistical consultation for defendants including Honeywell International Inc. in cases involving friction products
Dr. Youk a was statistical consultant and performed
analyses in preparation for the trial of a defendant in an asbestos litigation case
Dr. Roggli has served as an expert witness for both plaintiffs and defendants in asbestos litigation including Honeywell in cases involving friction products
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