Federal Institute of Occupational Safety and Health (BAuA), Berlin, Germany
Department of Medical Informatics, University Medical Center Hamburg-Eppendorf, Germany
Institute of Occupational Medicine, Johann Wolfgang Goethe-University, Frankfurt/Main, Germany
Bremen Institute for Prevention Research and Social Medicine, Bremen, Germany
German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
Abstract
Aims
To analyze the relationship between exposure to chlorinated and aromatic organic solvents and malignant lymphoma in a multi-centre, population-based case-control study.
Methods
Male and female patients with malignant lymphoma (n = 710) between 18 and 80 years of age were prospectively recruited in six study regions in Germany (Ludwigshafen/Upper Palatinate, Heidelberg/Rhine-Neckar-County, Würzburg/Lower Frankonia, Hamburg, Bielefeld/Gütersloh, and Munich). For each newly recruited lymphoma case, a gender, region and age-matched (± 1 year of birth) population control was drawn from the population registers. In a structured personal interview, we elicited a complete occupational history, including every occupational period that lasted at least one year. On the basis of job task-specific supplementary questionnaires, a trained occupational physician assessed the exposure to chlorinated hydrocarbons (trichloroethylene, tetrachloroethylene, dichloromethane, carbon tetrachloride) and aromatic hydrocarbons (benzene, toluene, xylene, styrene). Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional logistic regression analysis, adjusted for smoking (in pack years) and alcohol consumption. To increase the statistical power, patients with specific lymphoma subentities were additionally compared with the entire control group using unconditional logistic regression analysis.
Results
We observed a statistically significant association between high exposure to chlorinated hydrocarbons and malignant lymphoma (Odds ratio = 2.1; 95% confidence interval 1.1–4.3). In the analysis of lymphoma subentities, a pronounced risk elevation was found for follicular lymphoma and marginal zone lymphoma. When specific substances were considered, the association between trichloroethylene and malignant lymphoma was of borderline statistical significance. Aromatic hydrocarbons were not significantly associated with the lymphoma diagnosis.
Conclusion
In accordance with the literature, this data point to a potential etiologic role of chlorinated hydrocarbons (particularly trichloroethylene) and malignant lymphoma. Chlorinated hydrocarbons might affect specific lymphoma subentities differentially. Our study does not support a strong association between aromatic hydrocarbons (benzene, toluene, xylene, or styrene) and the diagnosis of a malignant lymphoma.
Background
During the past decades the incidence of Non-Hodgkin lymphoma (NHL) increased in most western countries
Several studies point to a potential etiologic role of solvents to malignant lymphoma. In the analysis of occupational groups with potential solvent exposure, Hodgkin lymphomas (HL) have been found in excess among painters
The aim of the present multi-centre, population-based case-control study is therefore to examine the association between exposure to chlorinated hydrocarbons and lymphoma based on an in-depth expert assessment of solvent exposure.
Methods
Study population
The study design has been described in detail in previous publications
For each newly recruited lymphoma case, a gender, region and age-matched (± 1 year of birth) population control was drawn from the population registration office. Control subjects that were not familiar with the German language were excluded from the study. For each participant who had to be excluded from the study or rejected participation, the recruitment procedure was repeated. Among population controls the participation rate was 44.3%. A total of 710 case-control pairs were included in the analysis.
Data collection
Intensively trained interviewers elicited detailed information about the medical history (including medication), lifestyle (including smoking, alcohol consumption, and leisure time activities), and occupation. The interviewers documented a complete occupational history, including every occupational period that lasted at least one year. For every job held, information was elicited about the start and the end of the job phase, about job title, industry, and specific job tasks. Study subjects having held jobs with potential relevance for lymphomagenesis (e.g., painters and lacquerers; metal workers and welders; chemical workers; shoemakers and leather workers; textile workers; dry cleaners; painters) were additionally asked to reply to job task-specific supplementary questions. For this purpose, a set of 14 job task-specific supplementary questionnaires had been developed following Bolm-Audorff et al.
Exposure assessment
A trained industrial physician (B.M.) assessed – blind to the case-control status – the intensity and frequency of exposure to specific chlorinated hydrocarbons (trichloroethylene, tetrachloroethylene, carbon tetrachlorine CTET, dichloromethane DCM) and to aromatic hydrocarbons (benzene, toluene, xylene, styrene). In a European collaborative research project with acronym EPILYMPH, this expert assessment has been coordinated by the International Agency for Research on Cancer (IARC) in Lyon. Quality assurance of expert exposure assessment included regular expert meetings and inter-rater-crosschecks of concrete assessment examples.
The intensity of exposure to specific solvents was assessed on a semiquantitative three point scale (low, medium, and high exposure), representing the absolute level of exposure in ppm. Intensity of exposure to trichloroethylene, perchloroethylene, carbon tetrachlorine, toluene, xylene, and styrene was categorized as follows: low intensity 2.5 ppm (0.5 to 5 ppm); medium intensity 25 ppm (>5 to 50 ppm); high exposure 100 ppm (>50 ppm). Intensity of exposure to dichloromethane was categorized as follows: low intensity 5 ppm (1 to 10 ppm); medium intensity 50 ppm (>10 to 100 ppm); high exposure 200 ppm (>100 ppm). Intensity of benzene exposure was categorized as follows: low intensity 2.5 ppm (0.5 to 5 ppm); medium intensity 15 ppm (>5 to 20 ppm); high intensity 50 ppm (>20 ppm).
The frequency of exposure to solvents represents the percentage of working time during which the exposure occurred (based on a 40 hours week). The frequency of exposure to specific solvents was again assessed on a semiquantitative three point scale as follows: low frequency 3% of working time (1 to 5%); medium frequency 17.5% of working time (>5 to 30%); high frequency 65% of working time (>30%). Finally, the confidence of exposure (meaning the degree of certainty according to the coder, that the worker had been exposed to the specific solvent) was assessed on a 3 point scale (possible but not probable; probable; certain).
To calculate cumulative exposure to a specific solvent [ppm*years], for every job held, the intensity of solvent was multiplied by the frequency of solvent exposure and by the corresponding duration of the job phase and summed up.
Characteristics of cases and control subjects
The characteristics of the cases with lymphoma and control subjects are given in table
Characteristics of cases and control subjects*
Control subjects
(n = 710)
All lymphoma
(n = 710)
Hodgkin lymphoma
(n = 116)
B-Non-Hodgkin lymphoma
(n = 554)
T-Non-Hodgkin lymphoma
(n = 35)
N
%
N
%
N
%
N
%
N
%
Gender
Female
320
45.1
320
45.1
49
42.2
251
45.3
16
45.7
Male
390
54.9
390
54.9
67
57.8
303
54.7
19
54.3
Age at diagnosis**
18 – 29 years
66
9.3
68
9.6
44
37.9
17
3.1
4
11.4
30 – 39 years
80
11.3
75
10.6
30
25.9
39
7.0
6
17.1
40 – 49 years
76
10.7
77
10.9
13
11.2
56
10.1
7
20.0
50 – 59 years
130
18.3
132
18.6
12
10.3
116
20.9
4
11.4
60 – 69 years
209
29.4
207
29.2
11
9.5
185
33.4
10
28.6
70 – 80 years
149
21.0
151
21.3
6
5.2
141
25.5
4
11.4
Smoking
Never smoked
314
44.2
297
41.8
46
39.7
236
42.6
14
40.0
>0, <6 packyears
125
17.6
95
13.4
22
19.0
67
12.1
4
11.4
>= 6, < 22.5 packyears
137
19.3
140
19.7
24
20.7
110
19.9
5
14.3
>= 22.5 packyears
132
18.6
166
23.4
23
19.8
131
23.7
11
31.4
Alcohol consumption
<2 g ethanol/day (men), <0.5 g ethanol/day (women)
126
17.7
186
26.2
47
40.9
127
22.9
11
31.4
>= 2 g ethanol/day (men), >= 0.5 g ethanol/day (women)
584
82.3
520
73.2
68
59.1
425
76.7
23
65.7
* Probands with missing information are not reported in the table
* Age of control subjects: at the time of diagnosis of the matched case
Data analysis
At first, we analyzed the relationship between specific solvents and lymphomas as a whole (n = 710). Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional logistic regression analysis, adjusted for smoking (in pack years) and alcohol consumption. The cumulative exposure was categorized according to the distribution among the control persons (50th and 90th percentile of the exposed controls). Only the results for exposure categories with at least 5 probands (cases and control subjects combined) are reported. Missing values were analyzed as a separate category (odds ratios not presented). To calculate tests for trend, the specific exposures were included as continuous variables in the logistic regression model.
Lymphomas comprise a multitude of pathogenetically different subentities with little information to what extent they are also etiologically different or share common environmental factors. Second, we therefore calculated odds ratios for the more frequent lymphoma subentities (with n > 30 cases). To increase the statistical power, patients with these lymphoma subentities were separately compared with the entire control group (n = 710) using unconditional logistic regression analysis. Covariates included in this unmatched analysis were age (as a continuous variable), sex, region, smoking, and alcohol consumption.
Results
Table
Exposure to chlorinated and aromatic hydrocarbons and lymphoma in total (n = 710 matched pairs)
Cases
Controls
Adj. ORa
95% CI
N
%
N
%
CHLORINATED HYDROCARBONS
Chlorinated hydrocarbons in total [ppm*yrs.]
0 ppm*yrs.
567
79.9
563
79.3
1.0
-
>0, <= 4.4 ppm*yrs.
53
7.5
74
10.4
0.7
0.5–1.0
>4.4, <= 47.3 ppm*yrs.
54
7.6
59
8.3
0.9
0.6–1.3
>47.3 ppm*yrs.
29
4.1
14
2.0
2.1
1.1–4.3
Trichloroethene [ppm*yrs.]
0 ppm*yrs.
610
85.9
602
84.4
1.0
-
>0, <= 4.4 ppm*yrs.
40
5.6
55
7.7
0.7
0.4–1.1
>4.4, <= 35 ppm*yrs.
32
4.5
44
6.2
0.7
0.5–1.2
>35 ppm*yrs.
21
3.0
9
1.3
2.1
1.0–4.8
Tetrachloroethene [ppm*yrs.]
0 ppm*yrs.
667
93.9
679
95.6
1.0
-
>0, <= 9.1 ppm*yrs.
16
2.3
16
2.3
1.1
0.5–2.3
>9.1, <= 78.8 ppm*yrs.
14
2.0
13
1.8
1.0
0.5–2.2
>78.8 ppm*yrs.
6
0.8
2
0.3
3.4
0.7–17.3
Carbon tetrachlorine [ppm*yrs.]
0 ppm*yrs.
681
95.9
696
98.0
1.0
-
>0, <= 2.3 ppm*yrs.
13
1.8
8
1.1
1.9
0.7–5.2
>2.3, <= 48.1 ppm*yrs.
8
1.1
5
0.7
2.0
0.6–6.9
>48.1 ppm*yrs.
1
0.1
1
0.1
-
-
Dichloromethane [ppm*yrs.]
0 ppm*yrs.
681
95.9
681
95.9
1.0
-
>0, <= 26.3 ppm*yrs.
8
1.1
16
2.3
0.4
0.2–1.0
>26.3, <= 175 ppm*yrs.
9
1.3
11
1.5
0.8
0.3–1.9
>175 ppm*yrs.
5
0.7
2
0.3
2.2
0.4–11.6
AROMATIC HYDROCARBONS
Benzene [ppm*yrs.]
0 ppm*yrs.
591
83.2
590
83.1
1.0
>0, <= 8.6 ppm*yrs.
53
7.5
60
8.5
0.9
0.6–1.3
>8.6, <= 130 ppm*yrs.
47
6.6
48
6.8
1.0
0.7–1.5
>130 ppm*yrs.
12
1.7
12
1.7
0.8
0.4–1.9
Toluene [ppm*yrs.]
0 ppm*yrs.
538
75.8
545
76.8
1.0
>0, <= 3.5 ppm*yrs.
81
11.4
80
11.3
1.0
0.7–1.5
>3.5, <= 207 ppm*yrs.
70
9.9
69
9.7
1.1
0.7–1.5
>207 ppm*yrs.
14
2.0
16
2.3
0.8
0.4–1.7
Xylene [ppm*yrs.]
0 ppm*yrs.
549
77.3
552
77.7
1.0
>0, <= 4.4 ppm*yrs.
74
10.4
80
11.3
0.9
0.7–1.3
>4.4, <= 230 ppm*yrs.
68
9.6
63
8.9
1.1
0.7–1.6
>230 ppm*yrs.
12
1.7
15
2.1
0.8
0.3–1.6
Styrene [ppm*yrs.]
0 ppm*yrs.
542
76.3
541
76.2
1.0
>0, <= 1.5 ppm*yrs.
70
9.9
85
12.0
0.7
0.5–1.0
>1.5, <= 67.1 ppm*yrs.
79
11.1
67
9.4
1.2
0.8–1.7
>67.1 ppm*yrs.
12
1.7
17
2.4
0.6
0.3–1.4
Missing values were included as a separate category (not shown)
a Odds Ratio (OR) adjusted for smoking [packyears] and alcohol consumption [g per day]
* To calculate tests for trend, the exposure scores were included as
Abbreviations: OR = odds ratio; CI = confidence interval; yrs. = years
In Table
Solvent exposure and HL, B-NHL, and T-NHL (unconditional logistic regression analysis)
Contr.
HL (n = 116)
B-NHL (n = 554)
T-NHL (n = 35)
N
N
Adj. ORa
95% CI
N
Adj. ORa
95% CI
N
Adj. ORa
95% CI
CHLORINATED HYDROCARBONS
Chlorinated hydrocarbons in total [ppm*yrs.]
0 ppm*yrs.
563
101
1.0
-
436
1.0
-
26
1.0
-
>0, <= 4.4 ppm*yrs.
74
5
0.3
0.1–0.8
45
0.8
0.5–1.2
2
0.5
0.1–2.5
>4.4, <= 47.3 ppm*yrs.
59
8
0.8
0.3–2.1
42
0.9
0.6–1.4
4
1.5
0.4–5.0
>47.3 ppm*yrs.
14
1
0.5
0.1–4.6
27
2.4
1.2–4.7
1
1.3
0.1–11.4
Trichloroethene [ppm*yrs.]
0 ppm*yrs.
602
10.4
1.0
-
47+
1.0
-
27
1.0
-
>0, <= 4.4 ppm*yrs.
55
6
0.4
0.2–1.1
32
0.7
0.5–1.2
2
0.7
0.2–3.3
>4.4, <= 35 ppm*yrs.
44
3
0.4
0.1–1.4
27
0.8
0.5–1.3
2
1.1
0.2–5.1
>35 ppm*yrs.
9
2
2.0
0.4–10.5
17
2.3
1.0–5.3
2
4.7
0.8–26.1
Tetrachloroethene [ppm*yrs.]
0 ppm*yrs.
679
111
1.0
-
521
1.0
-
30
1.0
-
>0, <= 9.1 ppm*yrs.
16
3
1.7
0.4–6.9
12
0.9
0.4–2.0
1
1.7
0.2–14.4
>9.1, <= 78.8 ppm*yrs.
13
1
0.7
0.1–6.3
12
1.0
0.5–2.3
1
1.5
0.2–12.5
>78.8 ppm*yrs.
2
-
-
-
5
3.2
0.6–16.7
1
-
-
CTET [ppm*yrs.]
0 ppm*yrs.
696
113
1.0
-
530
1.0
-
33
1.0
-
>0, <= 2.3 ppm*yrs.
8
1
0.8
0.1–8.5
12
1.8
0.7–4.6
-
-
-
>2.3, <= 48.1 ppm*yrs.
5
1
3.7
0.4–33.6
7
1.5
0.5–4.8
-
-
-
>48.1 ppm*yrs.
1
-
-
-
1
-
-
-
-
-
DCM [ppm*yrs.]
0 ppm*yrs.
681
531
1.0
-
32
1.0
-
>0, <= 26.3 ppm*yrs.
16
6
0.4
0.2–1.1
-
-
-
>26.3, <= 175 ppm*yrs.
11
8
0.9
0.3–2.3
1
1.2
0.1–10.9
>175 ppm*yrs.
2
5
2.7
0.5–14.5
-
-
-
AROMATIC HYDROCARBONS
Benzene [ppm*yrs.]
0 ppm*yrs.
590
101
1.0
-
459
1.0
-
26
1.0
-
>0, <= 8.6 ppm*yrs.
60
9
1.0
0.4–2.3
41
0.9
0.6–1.4
3
1.2
0.3–4.4
>8.6, <= 130 ppm*yrs.
48
5
0.9
0.3–2.5
39
1.0
0.6–1.5
3
1.7
0.5–6.1
>130 ppm*yrs.
12
-
-
-
11
1.0
0.4–2.3
1
1.7
0.2–15.0
Toluene [ppm*yrs.]
0 ppm*yrs.
545
88
1.0
-
421
1.0
-
24
1.0
-
>0, <= 3.5 ppm*yrs.
80
19
1.2
0.7–2.3
56
1.0
0.7–1.5
6
1.6
0.6–4.4
>3.5, <= 207 ppm*yrs.
69
8
0.9
0.4–2.0
60
1.1
0.8–1.6
2
0.8
0.2–3.5
>207 ppm*yrs.
16
-
-
13
0.9
0.4–2.0
1
1.3
0.2–1.6
Xylene [ppm*yrs.]
0 ppm*yrs.
552
88
1.0
-
432
1.0
-
24
1.0
-
>0, <= 4.4 ppm*yrs.
80
20
1.4
0.7–2.6
48
0.8
0.5–1.2
6
1.7
0.6–4.7
>4.4, <= 230 ppm*yrs.
63
8
0.8
0.3–2.0
59
1.2
0.8–1.7
2
0.8
0.2–3.6
>230 ppm*yrs.
15
-
-
-
11
0.9
0.4–1.9
1
1.5
0.2–13.0
Styrene [ppm*yrs.]
0 ppm*yrs.
541
91
1.0
-
423
1.0
-
23
1.0
-
>0, <= 1.5 ppm*yrs.
85
11
0.4
0.2–0.8
53
0.8
0.6–1.2
6
1.3
0.5–3.6
>1.5, <= 67.1 ppm*yrs.
67
13
1.5
0.7–3.1
62
1.2
0.8–1.7
4
1.6
0.5–4.8
>67.1 ppm*yrs.
17
-
-
-
12
0.8
0.4–1.8
-
-
-
Missing values were included as a separate category (not shown)
a Odds Ratio (OR) adjusted for age, sex, region, smoking [packyears] and alcohol consumption [g per day]
* To calculate tests for trend, the exposure scores were included as
Table
Solvent exposure and B-NHL subentities (unconditional logistic regression analysis)
Contr.
DLBCL
(n = 158)
FL
(n = 92)
CLL
(n = 104)
Multiple myeloma
(n = 76)
Marginal zone lymphoma
(n = 38)
N
N
Adj. ORa
95% CI
N
Adj. ORa
95% CI
N
Adj. ORa
95% CI
N
Adj. ORa
95% CI
N
Adj. ORa
95% CI
CHLORINATED HYDROCARBONS
Chlorinated hydrocarbons in total [ppm*yrs.]
0 ppm*yrs.
563
132
1.0
-
70
1.0
-
78
1.0
-
62
1.0
-
27
1.0
-
>0, <= 4.4 ppm*yrs.
74
10
0.6
0.3–1.2
9
1.4
0.6–3.1
11
0.9
0.4–1.9
3
0.4
0.1–1.3
4
1.6
0.5–5.1
>4.4, <= 47.3 ppm*yrs.
59
9
0.7
0.3–1.5
8
1.7
0.7–4.0
9
0.7
0.3–1.6
8
1.0
0.4–2.4
3
1.4
0.4–5.3
>47.3 ppm*yrs.
14
5
1.8
0.6–5.3
5
3.9
1.3–12.1
6
1,8
0.6–4.9
2
0.9
0.2–4.4
4
7.0
1.8–26.3
Trichloroethene [ppm*yrs.]
0 ppm*yrs.
602
139
1.0
-
79
1.0
-
86
1.0
-
65
1.0
-
32
1.0
-
>0, <= 4.4 ppm*yrs.
55
6
0.5
0.2–1.2
7
1.3
0.5–3.2
10
1.1
0.5–2.4
3
0.5
0.2–1.9
2
0.9
1.2–4.3
>4.4, <= 35 ppm*yrs.
44
7
0.8
0.3–1.8
3
0.7
0.2–2.6
6
0.7
0.3–1.7
6
1.0
0.4–2.7
2
4.2
0.8–23.9
>35 ppm*yrs.
9
4
2.6
0.7–3.0
3
3.2
0.8–12.9
2
0.9
0.2–4.5
1
0.7
0.1–5.5
2
4.2
0.8–23.9
Tetrachloroethene [ppm*yrs.]
0 ppm*yrs.
679
146
1.0
-
90
1.0
-
101
1.0
-
33
1.0
-
1.0
-
>0, <= 9.1 ppm*yrs.
16
3
0.9
0.3–3.9
2
1.2
0.3–5.5
1
-
-
3
1.8
0.5–6.7
1
-
-
>9.1, <= 78.8 ppm*yrs.
13
6
2.1
0.8–5.9
-
2
0.6
0.1–2.8
-
-
-
3
4.2
1.02–17.5
>78.8 ppm*yrs.
2
1
2.3
0.2–26.0
-
-
-
-
-
-
-
1
-
-
CTET [ppm*yrs.]
0 ppm*yrs.
696
153
1.0
-
87
1.0
-
98
1.0
-
72
1.0
-
37
1.0
-
>0, <= 2.3 ppm*yrs.
8
1
0.7
0.1–6.1
4
5.0
1.4–18.3
5
2.7
1.8–8.9
-
-
-
-
-
-
>2.3, <= 48.1 ppm*yrs.
5
2
1.6
0.3–8.9
1
2.1
0.2–19.4
-
-
-
3
4.5
0.57–20.9
1
3.6
0.4–34.6
>48.1 ppm*yrs.
1
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
DCM [ppm*yrs.]
0 ppm*yrs.
681
1.0
-
88
1.0
-
100
1.0
-
74
1.0
-
36
1.0
-
>0, <= 26.3 ppm*yrs.
16
0.8
0.2–2.9
1
0.5
0.1–4.3
1
0.3
0.04–2.4
-
-
-
1
1.5
0.2–11.9
>26.3, <= 175 ppm*yrs.
11
0.9
0.2–4.2
2
1.5
0.3–7.4
2
0.8
0.2–3.9
-
-
-
-
-
-
>175 ppm*yrs.
2
-
-
1
-
-
1
-
-
1
-
-
1
-
-
AROMATIC HYDROCARBONS
Benzene [ppm*yrs.]
0 ppm*yrs.
590
136
1.0
-
73
1.0
-
80
1.0
-
62
1.0
-
32
1.0
-
>0, <= 8.6 ppm*yrs.
60
9
0.7
0.3–1.4
10
1.8
0.8–3.8
8
0.8
0.4–1.8
6
1.0
0.4–2.4
2
0.7
0.2–3.0
>8.6, <= 130 ppm*yrs.
48
10
0.9
0.4–1.9
7
1.5
0.6–3.5
14
1.6
0.8–3.2
4
0.7
0.2–2.0
3
1.1
0.3–3.8
>130 ppm*yrs.
12
1
0.3
0.04–2.6
2
1.3
0.3–6.4
2
0.7
0.1–3.1
3
1.8
0.5–6.8
1
1.4
0.2–11.8
Toluene [ppm*yrs.]
0 ppm*yrs.
545
122
1.0
-
66
1.0
-
76
1.0
-
59
1.0
-
27
1.0
-
>0, <= 3.5 ppm*yrs.
80
18
1.1
0.6–2.0
8
1.1
0.5–2.4
11
0.9
0.4–1.8
6
0.8
0.3–1.9
4
1.0
0.3–3.3
>3.5, <= 207 ppm*yrs.
69
14
1.0
0.5–1.9
16
2.6
1.4–5.1
15
1.3
0.7–2.4
7
0.9
0.4–2.0
6
1.9
0.7–5.1
>207 ppm*yrs.
16
2
0.6
0.1–2.5
2
1.1
0.2–5.3
2
0.5
0.1–2.4
3
1.4
0.4–5.2
1
1.1
0.1–9.5
Xylene [ppm*yrs.]
0 ppm*yrs.
552
127
1.0
-
66
1.0
-
79
1.0
-
59
1.0
-
27
1.0
-
>0, <= 4.4 ppm*yrs.
80
13
0.8
0.4–1.5
7
1.0
0.4–2.3
9
0.7
0.3–1.5
6
0.8
0.3–1.9
5
1.4
0.5–4.0
>4.4, <= 230 ppm*yrs.
63
14
1.1
0.6–2.0
17
3.0
1.6–5.8
15
1.3
0.7–2.5
7
0.9
0.4–2.2
5
1.8
0.6–4.9
>230 ppm*yrs.
15
2
0.6
0.1–2.6
2
1.3
0.3–6.2
1
0.3
0.04–2.2
3
1.5
0.4–5.8
1
1.3
0.2–10.5
Styrene [ppm*yrs.]
0 ppm*yrs.
541
117
1.0
-
60
1.0
-
81
1.0
-
60
1.0
-
31
1.0
-
>0, <= 1.5 ppm*yrs.
85
15
0.8
0.4–1.5
12
1.1
0.5–2.1
10
1.0
0.5–2.2
6
0.8
0.3–1.9
4
1.0
0.3–3.0
>1.5, <= 67.1 ppm*yrs.
67
19
1.3
0.7–2.3
17
2.2
1.2–4.0
11
1.1
0.5–2.2
8
1.0
0.5–2.4
3
0.8
0.2–2.6
>67.1 ppm*yrs.
17
5
1.5
0.5–4.4
3
1.6
0.5–6.0
2
0.5
0.2–2.3
1
0.5
0.1–3.8
-
-
-
Missing values were included as a separate category (not shown)
a Odds Ratio (OR) adjusted for age, sex, region, smoking [packyears] and alcohol consumption [g per day]
* To calculate tests for trend, the exposure scores were included as
Abbreviations: OR = odds ratio; CI = confidence interval; yrs. = years
Discussion
In this study, we observed a statistically significant association between high exposure to chlorinated hydrocarbons – particularly trichloroethylene – and malignant lymphoma. In the analysis of lymphoma subentities, a pronounced risk elevation was found for follicular lymphoma and marginal zone lymphoma. Among the chlorinated hydrocarbons investigated, trichloroethylene was the solvent with the highest exposure prevalence among the control subjects: 15.2% of the control subjects were ever exposed to trichloroethylene, 20.7% were ever exposed to any chlorinated hydrocarbons, 49.0% were ever exposed to any aromatic hydrocarbons. However, the proportion of control persons ever exposed to solvents decreased to 7.9% (trichloroethylene), 10.6 (any aromatic hydrocarbons), resp. 24.9% (any aromatic solvents), when only persons with "certain" trichloroethylene exposure were regarded as exposed. Therefore, the exposure assessment might be regarded as rather sensitive, but less specific, introducing possible non-differential misclassification bias. When in an additional analysis, solely "certain" exposures were considered (regarding persons with possible and probable exposure as unexposed), odds ratios were attenuated (results not shown).
In 1995 the International Agency for Research on Cancer (IARC) classified trichloroethylene as a probable human carcinogen (Group 2A); the lymphatic system was regarded as a target for trichloroethylene toxicity
Tetrachloroethylene (synonym perchloroethylene PCE), has also been used as an industrial solvent for several decades. Exposure to PCE is widely prevalent especially in dry-cleaning companies, where it was the dominant solvent since the seventies. In 1995 the IARC concluded from a limited database that exposure to PCE leads to an increased NHL risk
Only 2% of the control subjects are exposed to carbon tetrachloride according to expert assessment, leading as well to a limited power. In the early 20th century, carbon tetrachloride was widely used as a dry cleaning solvent, as a refrigerant, and in fire extinguishers; later, it was used as a grain fumigant. The use of carbon tetrachloride is clearly declining since the seventies. In our study, we found an OR of about 2 among carbon tetrachloride-exposed persons, which was of borderline statistical significance. This is in accordance with the results of a Canadian case-control study, including 517 cases and 1,506 control subjects
Dichloromethane (DCM), also known as methylene chloride, is mainly used as a paint remover but is also applied as a solvent and cleaning agent in a variety of industries. The few epidemiological studies investigating occupational exposures to DCM do not report increased lymphoma risks
There is a sufficient body of evidence concerning the leukaemogenicity of benzene. Recent results in the fields of toxicology and molecular oncology have shown that not only precursor cells in bone marrow but even peripheral lymphatic cells are targeted by the genotoxic metabolites of benzene in humans in vivo, thus making it probable that all kinds of lymphoma may be induced by the compound
Toluene and xylene are the aromatic hydrocarbons with the highest exposure prevalence in our cohort; roughly a quarter of the control subjects were ever exposed to toluene resp. xylene (including rather uncertain exposures). Toluene and xylene exposure are highly inter-correlated; furthermore, exposure to both substances is highly correlated with benzene exposure (Pearson correlation coefficient between 0.94 and 0.97). Therefore, we are virtually unable to distinguish between the effects of benzene, toluene, and xylene (BTX exposure). However, we could not find any increased risks in the separate analysis of the mentioned substances as well as in the analysis of BTX exposure as a whole (results not shown). In a recently published large case-control study in Italy, Miligi and colleagues
Styrene, the fourth aromatic hydrocarbon investigated in our study, is widely used in lamination of reinforced plastics, in the production of – inter alia – rubber, plastic, insulation, and fibreglass. The exposure prevalence in control subjects (23.8%) was comparable with the exposure prevalence of other aromatic hydrocarbons. The correlation between styrene and BTX solvents (Pearson correlation coefficient = 0.25) was considerably lower than the correlation within the BTX group. Our results do not support the hypothesis of a dose-response relationship between styrene and lymphoma risk.
Strengths of our study include the expert-based calculation of cumulative solvent exposure during the entire work time and adjustment for several potential confounders. The exposure assessment was conducted blind for the case-control study; we therefore regard a differential exposure misclassification as rather improbable. However, limitations of the present analysis should be considered when interpreting the results. Retrospective exposure assessment on semi-quantitative intensity and frequency scales always implies non-differential misclassification which tends to bias the effect estimate to the null. When only definite exposures were taken into consideration, specifity of the exposure assessment was expected to increase (at the cost of decreasing sensitivity): However, when only definite exposures were regarded, we did not find any risk elevations.
Conclusion
To conclude, our study adds further evidence to the potential relevance of trichloroethylene exposure – possibly also of exposure to other chlorinated hydrocarbons – on the etiology of lymphomas. The risk for specific lymphoma subentities might differ from the overall risk for malignant lymphoma: in our study, particularly pronounced risk elevations are found for the association between high exposure to chlorinated hydrocarbons and follicular NHL as well as marginal zone NHL.
Competing interests
The author(s) declare that they have no competing interests.
Authors' contributions
AS participated in the design of the study, drafted the manuscript and performed the statistical analysis. MM participated in the statistical analysis and in drafting the manuscript. JB participated in the coordination of the data collection and in the critical revision of the study. BM and GE participated in the exposure assessment and in the critical revision of the manuscript. ES is the data manager of the German lymphoma study and participated in the statistical analysis and in the critical revision of this manuscript. AN and NB who is the PI prepared, designed and coordinated the study and helped to draft the manuscript. All authors read and approved the final manuscript.
Acknowledgements
We are indebted to the participants of the study and to the many colleagues who supported the performance of the study. Detailed lists are presented in former publications
The study was funded by the Federal Office for Radiation Protection (StSch4261 and StSch4420). The European Community supported the set up of a common protocol for assessment of occupational exposures (SOC 98 201307 05F02) and implementation of additional study areas (QLK4-CT-2000-00422). A recent workshop of the industrial hygienists in Heidelberg was funded by the German Research Foundation (4850/161/03).