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Division of Surveillance, Hazard Evaluations and Field Studies [E. M. W., P. S., B. G., J. D., J. F., N. R., M. W.], and Division of Biological and Behavioral Sciences [M. A. B.], National Institute for Occupational Safety and Health, Cincinnati, Ohio 45226; National Center for Environmental Health, Atlanta, Georgia 30333 [D. P., W. T., E. D., L. L. N.]; Department of Mathematical Sciences, University of Cincinnati [J. D.], Cincinnati Ohio, 45221 [J. D.]; Janus Serum Bank, 0027 Oslo, Norway [E. J.]; and The Norwegian Cancer Registry, 0310 Oslo, Norway [A. A.]; Unit of Environmental Cancer Epidemiology, International Agency for Research on Cancer, Lyon, France 69003 [E. W.]
| Abstract |
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| Introduction |
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| Materials and Methods |
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One g of serum from each case and control were provided to the Toxicology Branch, Division of Environmental Health Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control for analysis. Serum samples were stored by the Janus Serum Bank at -25°C, were hand carried from the serum bank to the laboratory, and were verified to be frozen upon arrival. Samples were blind-coded. Analysis was conducted for a total of 71 compounds: 22 dioxins, furans, and non-ortho co-planar PCBs; 36 other PCB congeners; and 13 pesticides or their metabolites. Chemical structures and a summary of the metabolism of the pesticides and other organochlorines were presented in Ahlborg et al. (4) . The analytical technique and quality control procedures have been described previously (17, 18, 19) . Polychlorinated dibenzo-p-dioxins, dibenzofurans, biphenyls, chlorinated pesticides, and selected metabolites were measured in serum by high resolution gas chromatography/high resolution isotope dilution mass spectrometry. The analytes of interest were isolated from serum using a C18 solid-phase extraction procedure and then by a multicolumn automated cleanup procedure. The analytes were separated on a DB-5 ms capillary column and quantified using selected ion monitoring high resolution (10,000 resolving power) mass spectrometry. Total cholesterol and triglyceride measurements were made using standard enzymatic procedures on an Abbott Spectrum CCx Series II analyzer (Abbott Laboratories, Diagnostics Division, Abbott Park, IL). The cholesterol procedure is based on the hydrolysis of cholesterol esters in serum to free cholesterol by cholesterol esterase. The cholesterol produced is oxidized by cholesterol oxidase in a reaction that results in the formation of hydrogen peroxide. Hydrogen peroxide reacts with 4-aminoantipyrine and phenol in the presence of horseradish peroxidase to yield a quinoneimine dye that absorbs at 500 nm. In the triglycerides procedure, serum triglycerides are converted to glycerol and free fatty acids by lipoprotein lipase. The glycerol is then converted to glycerol-3-phosphate by glycerol kinase in the presence of ATP. The glycerol-3-phosphate is reacted with glycerol-3-phosphate oxidase in the presence of oxygen to form hydrogen peroxide. This in turn forms a colored complex with aminoantipyrine and chlorophenol in the presence of peroxidase. The concentration of each analyte is calculated from its individual standard linear calibration. Results were reported on both a whole-weight and lipid-adjusted basis. Total lipids were calculated according to the following formula: (2.27 x total cholesterol + triglycerides + 62.3) (20) . Detection limits, on a whole-weight and lipid-adjusted basis, were reported for each sample and corrected for sample weight and analyte recovery (21 , 22) . A total of eight samples for which total lipids could not be determined were assigned a value of 600 mg/dl. If the results for an analyte could not be reported because of an interference, or if QA parameters did not meet specified QA criteria, this was indicated, and a missing value was reported.
The distribution of both reported data and LD for each analyte was examined before linking the data with case-control status to determine how nondetected samples would be treated in the analysis. For those analytes that had >90% of samples above the LD, the value of the LD divided by the square root of 2 was used to estimate the value of samples below the LD for analyses comparing serum organochlorine concentrations in cancer cases and controls. This procedure is recommended when the data are not highly skewed (23) . For analytes with >90% of sample values above the LD, paired t tests were used to compare the whole-weight and lipid-adjusted serum concentrations of each analyte between each matched case and control. In addition, the distribution of each analyte (or analyte group) was divided into quartiles, based on the distribution in controls, and an OR was calculated for each quartile compared with the lowest. Conditional logistic regression was used to examine the relationship between each analyte and breast cancer, taking into account the potential confounders and the effect modifiers (occupational category, age at first birth, number of births prior to donation of blood sample, region of residence, and region of birth).
For those analytes which had >0 and <90% of samples with detectable values, a high degree of overlap was observed between the range of organochlorine concentrations in detected samples and the LD for nondetected samples. This precluded substitution of a meaningful estimate for sample values below the LD. Therefore, for these analytes, a more limited analysis was carried out that compared the odds of having a sample above the LD for cancer cases and controls. ORs and confidence intervals were calculated using conditional logistic regression (24) .
PCB congeners were also analyzed in groups on the basis of predicted estrogenicity and enzyme induction, as proposed by Wolff et al. (25 , 26) . These groups are as follows: group 1 (potentially estrogenic); group 1A (weak phenobarbitol inducers, estrogenic, not persistent); group 1B (weak phenobarbitol inducers, persistent); group 2 (potentially antiestrogenic and immunotoxic, dioxinlike); group 2A, non-ortho and mono-ortho (moderately persistent); group 2B, di-ortho substituted (limited dioxin activity, persistent); and group 3 (phenobarbitol, CYP1A and CYP2B inducers, biologically persistent).
For all study participants, data on age at birth of first child, number
of children as of shortly before the specimen was taken, county of
birth, county of residence at blood sample, and occupation as of 1960,
1970, and 1980 were provided by the Janus Serum Bank and the Norwegian
Cancer Registry. Neither BMI nor menopausal status are available for
the women in the sample. Diagnosis date, histology, stage, and number
of children before diagnosis of cancer were provided for breast cancer
cases. ER and PR concentrations were abstracted from original medical
records. Parity, occupation, and residence data were categorized into
45 strata (Table 1)
. For individuals
whose occupations were identified in more than one census, the most
recent occupation was used in the analysis. Stratified analyses for DDE
and total PCBs were conducted by age at breast cancer diagnosis (<50
years and
50 years), by interval between blood sample and diagnosis,
and by ER and PR concentration. To examine trends in organochlorine
concentrations by date of blood collection, mean organochlorine levels
were calculated for each of four time strata; cut points were defined
to have approximately equal numbers of samples/strata. All data
analyses were conducted using the Statistical Analysis System
(27)
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90% of values
above the LD. These a priori hypotheses are
summarized below. Among the pesticides and their metabolites that had >90% of sample values above the LD, our a priori hypothesis was that serum concentrations of B-HCCH, p,p'-DDE, and p,p'-DDT would be positively associated with breast cancer risk, and that there would be no association between levels of hepatachlor epoxide, oxychlordane, or trans-nonachlor and breast cancer risk. Among the 26 PCB congeners with >90% detectable samples, none were in the category of "estrogenic, nonpersistent, weak phenobarbitol inducers" [Wolff et al.s (25 , 26) Group 1A] likely to be associated with increased breast cancer risk through an estrogenic mechanism. We hypothesized a priori that we would see the following associations with breast cancer: (a) no association with the sum of PCB congeners; (b) positive association with Congener 99, based on one previous study (28) ; and (c) a negative association with the dioxin-like non-ortho and mono-ortho coplanar compounds (Wolff Group 2A). We made no hypothesis a priori about the Wolff group 1B and three congeners because it was unclear to what extent the congeners measured in these groups are estrogenic.
| Results |
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2
= 145; P = 0.001);
however, there was no evidence that matched cancer cases and controls
were more likely to be concordant on region of residence than would be
predicted by chance alone (
statistic = 0.1). Cancer cases
tended to have lower serum cholesterol and total lipids than controls,
although neither difference was statistically significant (Table 1)
Table 2
presents mean organochlorine
levels in both whole-weight and lipid-adjusted units for each pesticide
or metabolite and PCB congener measures, and for groups of PCB
congeners. Analyses presented in Table 2
include only those
organochlorine compounds for which
90% of samples were above the LD.
ORs by quartile, based on the lipid-adjusted data, are also shown. None
of the six pesticides/metabolites or 26 individual PCB congeners
measured showed a positive association with breast cancer risk; in
fact, all of the observed differences in means were in a slightly
negative direction. ORs by quartile generally showed an inverse trend
with breast cancer risk, although a few compounds showed ORs >1 in the
higher quartiles. PCB congener 99, for which a positive association was
hypothesized a priori based on one previous study, had no
association with breast cancer in the current study. All of the PCB
congener groups seemed to have an inverse relationship with breast
cancer risk; there was no evidence that the compounds in group 2A,
thought to be antiestrogenic, had a stronger inverse relationship than
compounds in other groups. The combined effect of high DDE and high
total PCBs was explored by examining the matched OR for being in the
top quartile for both organochlorines. A total of 15 breast cancer
cases and 19 controls fell in the top quartile for both; the matched OR
was 0.75. Conditional logistic regression models examining the
relationship between the individual pesticides or metabolites, PCB
congeners, and PCB groups and breast cancer risk, controlling for the
various covariates both singly and in combination, found that none of
the covariates changed either the magnitude or direction of the
unadjusted estimate. Therefore, only the unadjusted data are presented.
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10 years between blood sample and diagnosis. For total
PCBs, slightly higher concentrations were found in cancer cases than in
controls for women age 50 years and older at diagnosis, and for the
highest tertiles of ER and PR concentration. However, none of the
observed differences were statistically significant. No significant
differences were noted in stratified analyses for the other pesticides
or their metabolites and PCB groups.
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1 but <90% of samples above the LD. There were
no samples above the LD for six dioxins and dibenzofurans, including
2,3,7,8-TCDD, for which the LD ranged from 0.22 to 1.7 fg/g serum. The
data in Table 4
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| Discussion |
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Table 6
summarizes data from eight
previous studies examining the relationship between
p,p'-DDE levels in serum and breast cancer. In
comparing serum organochlorine levels between studies, it is important
to note that previous studies have reported concentrations in a number
of units (ppb, ng/ml, and ng/g). The levels measured in different
studies are, however, directly comparable because 1 ppb is equal to 1
ng/g and 1 ml serum weighs
1.026 g. DDE concentrations measured
among controls in these studies ranged from 2.9 ppb in samples
collected in Columbia in 1998 (8)
to 43.1 ppb in samples
collected in the United States in the 1960s (Ref. 5
; Table 7
); the average concentration measured
among controls in our study was 8.2 ng/g serum (Table 2)
. Two previous
studies reported positive findings (1
, 8)
, and a third
(5)
reported nonsignificant positive trends in ORs by
tertile for whites and blacks, but not for Asians. Recent studies have
found an association between serum levels of
p,p'-DDT and breast cancer (13)
and
higher levels of p,p'-DDE in the plasma of women
with large breast tumors and lymph node involvement (14)
.
Among five relatively small studies measuring DDE in breast tissue
(2
, 28
, 30, 31, 32)
, Falck et al. (2)
reported higher concentrations of DDE in breast fat samples from
unselected breast cancer cases compared with controls with nonmalignant
breast disease, whereas Dewailly et al. (28)
found increased DDE concentrations only in ER-positive cancer cases
compared with controls with nonmalignant breast disease. One large
case-control study of breast cancer in Europe, which examined DDE
concentrations in adipose tissue collected by aspiration from the
buttocks, found decreased DDE concentrations in cancer cases compared
with controls, a difference that was more pronounced after adjustment
for BMI, age at first birth, and current alcohol drinking
(33)
. Two large recent studies, conducted in Germany and
Canada, found no significant difference between DDE concentrations of
breast cancer cases and controls (34
, 35)
.
p,p'-DDE, o,p-DDT,
and p,p'-DDT are considered estrogenic and give positive
results in the E-Screen assay (36)
, although
o,p-DDT, which was not detectable in our
study, appears to be the most highly estrogenic of these compounds
(4
, 36)
. Although there have been conflicting results in
human studies, our study results and accumulating evidence from several
recent studies do not support the hypothesis that breast cancer is
associated with environmental exposure to DDT or DDE.
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A major difficulty in interpreting the human data on PCB exposure and breast cancer is that the PCB congeners with the highest potential estrogenicity are also the most quickly metabolized (26) . Exposure to these short-lived congeners may or may not be correlated with exposure to the more persistent congeners, depending on the commercial PCB products from which the contamination arose (39) . Measurement of stable PCB congeners during midlife may not reflect exposure to the relatively short-lived, more estrogenic, congeners early in life, which may be a sensitive period for breast cancer induction (40) . Moreover, there are many potential toxicities associated with PCB congeners, some of which are antiestrogenic, and which may vary, for example, with respect to P-450 enzyme induction and other properties (41) . For these reasons, Hansen (41) has encouraged the reporting of congener-specific data in studies of the relationship between PCB exposure and health effects, and Moysich et al. (42) have proposed the use of multiple congener groupings in epidemiological research. In our study, the trends in ORs by quartile were uniformly negative, so it was not considered useful to analyze congeners by additional groupings. However, levels of specific congeners are reported to facilitate comparison with future studies conducting congener-specific analyses.
No associations with breast cancer risk were observed for four other organochlorines (B-HCCH, heptachlor epoxide, oxychlordane, and trans-nonachlor) evaluated in this study. B-HCCH has estrogenic properties (43 , 44) , and previous epidemiological studies have yielded conflicting results (7 , 11 , 13 , 28 , 30 , 34 , 35) . Previous toxicological and epidemiological studies of heptachlor epoxide, oxychlordane and trans-nonachlor do not suggest any association with breast cancer risk (2 , 11 , 13 , 28 , 30 , 35 , 45 , 46) .
The consistency of the slightly negative associations found between
specific organochlorine levels and breast cancer risk in our study
warrants some discussion. Some of the possible explanations for this
unexpected consistency are methodological, including systematic bias in
the selection of either cancer cases or controls, overmatching, which
could lead to bias toward the null, or random sampling error, which
could have caused differences in the distribution of important
predictors of organochlorine levels among cancer cases and controls. We
evaluated these possibilities through review of the methods used for
selecting cancer cases and controls, and by examining available
covariate data and stratified organochlorine results. We did not find
any evidence for systematic bias in the procedures used to select
cancer cases and controls. We were concerned that matching by date of
specimen would have inadvertently caused overmatching by region of
residence, because the health surveys that collected the blood samples
contributed to the Janus Serum Bank were conducted in different parts
of Norway at different times. However, cancer cases and controls were
not more likely to be matched on region of residence than would have
occurred by chance. Finally, although it appeared (Table 1)
that there
were some differences in region of residence and region of birth
between cancer cases and controls, the pattern of regional differences
varied by compound, and controlling for region of birth and region of
residence in the analysis did not in any way alter the outcome.
Aside from methodological issues, one possible explanation for the consistently negative associations is that, in the absence of a significant etiological relationship between organochlorines and breast cancer, there may be a tendency toward a slightly negative relationship through an association of organochlorine levels with one or more unmeasured negative risk factor. For example, some studies show that higher levels of fish consumption are protective against breast cancer, possibly attributable to the n-3 PUFAs fish contain (47) . Fish are also a dietary source of PCBs (48) . However, a previous study conducted using samples from the Janus Serum Bank found no relationship between levels of n-3 PUFAs in serum and breast cancer risk (49) . Neither fish consumption nor n-3 PUFAs were measured in the current study.
Other studies have reported negative trends in ORs with increasing levels of total PCBs and DDE (6 , 9) .
When our data were stratified according to age of diagnosis of breast cancer as a surrogate for menopausal status, DDE showed slightly positive relationships for women older than age 50 years and negative relationships for women younger than age 50 years, and both DDE and total PCBs showed higher concentrations in cancer case sera compared with control sera collected >10 years before diagnosis. Some breast cancer risk factors differ between pre- and postmenopausal women. For example, a prospective study of 24,329 Norwegian women found an inverse relation between serum cholesterol and risk of breast cancer that was confined to women younger than age 51 years (50) . We had no data on several risk factors for breast cancer that may also be related to serum organochlorine levels, including height, BMI, and lactation history, some of which have been controlled for in the analysis of other studies. Our population differed from other populations in which the association between serum organochlorines and breast cancer has been studied by having a preponderance of women younger than age 50 years (60.4%), which may have caused organochlorine levels in our study to be more influenced by unmeasured biological correlates of premenopausal breast cancer. It is also possible that some organochlorines, particularly those which are antiestrogenic, may have a protective effect for breast cancer.
The major strengths of this study are its prospective design, which ensured that the blood samples had been collected at least 2 years before diagnosis, and that serum organochlorine levels were not affected by disease status, the number of organochlorine compounds for which measurements were available, and the availability of some data on potential confounders including age at first birth and number of children prior to blood sample donation. The major limitations include the absence of data on two important confounders: menopausal status and BMI. BMI has recently been found to be inversely correlated with PCB levels in serum (15) . Because of limitations in the occupational history information available for study participants and the relatively small sample size, the occupational categories used in the analysis were quite broad. We were unable to examine association of organochlorine levels with specific occupations that are historically likely to have substantial organochlorine exposure, such as women working in the manufacture of electrical transformers and capacitors.
In summary, our study did not provide evidence that increased breast cancer risk is associated with serum levels of the organochlorines measured. The evidence to date on the association between serum organochlorines is not consistent, but suggests that exposure to the organochlorines commonly measured (DDE and total PCBs, a measure that reflects primarily the more highly chlorinated, persistent congeners) is not an important risk factor for breast cancer in the general population, at least in the countries where studies have been conducted. Studies to date have not been able to evaluate whether exposure to the more highly estrogenic, short-lived PCB congeners increases breast cancer risk, nor have they fully evaluated the risk associated with organochlorine exposure in susceptible subgroups or at levels above general population exposure, including women with occupational exposure.
| Acknowledgments |
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| Footnotes |
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1 The research described in this article was
supported by the United States Department of Defense under MIPR
94 MM4563GR7: AIBS 2513. ![]()
2 To whom requests for reprints should be
addressed, at NIOSH MS R-13, Robert A. Taft Laboratory, 4676 Columbia
Park, Cincinnati, OH 45226. ![]()
3 The abbreviations used are: PCB, polychlorinated
biphenyl; B-HCCH,
B-hexachlorocyclohexane; DDE,
p,p'-1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene;
DDT, 2,2-bis(p-chlorophenyl)-1,1,1-trichloroethane; QA,
quality assurance; LD, limit(s) of detection; ER, estrogen receptor;
PR, progesterone receptor; OR, odds ratio; BMI, body mass index; PUFA,
polyunsaturated fatty acid; CI, confidence interval. ![]()
Received 1/11/00; revised 8/31/00; accepted 9/18/00.
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