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Journal of Occupational & Environmental Medicine:
doi: 10.1097/JOM.0b013e3182941a1c
Original Articles

Occupational Exposure to Chlorinated and Petroleum Solvents and Mycosis Fungoides

Morales-Suárez-Varela, Maria M. MD, PhD; Olsen, Jorn MD, PhD; Villeneuve, Sara; Johansen, Preben MD, PhD; Kaerlev, Linda MD, PhD; Llopis-González, Agustin MD, PhD; Wingren, Gun MD, PhD; Hardell, Lennart MD, PhD; Ahrens, Wolfgang MD, PhD; Stang, Andreas MD, PhD; Merletti, Franco MD, PhD; Gorini, Giuseppe MD, PhD; Aurrekoetxea, Juan José MD, PhD; Févotte, Joëlle MD, PhD; Cyr, Diane MD, PhD; Guénel, Pascal MD, PhD

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Author Information

From the Unit of Public Health and Environmental Care (Drs Morales-Suárez-Varela and Llopis-González), Department of Preventive Medicine, University of Valencia, Spain; CIBER Epidemiology and Public Health (CIBERESP) (Drs Morales-Suárez-Varela and Llopis-González), Spain; Center for Public Health Research (CSISP) (Drs Morales-Suárez-Varela and Llopis-González), Valencia, Spain; Research Unit of Clinical Epidemiology (Drs Olsen and Kaerlev), Institute of Clinical Research, University of Southern Denmark, Odense, Denmark; Inserm, CESP Center for research in Epidemiology and Population Health (Drs Villenueve, Cyr, and Guénel), U1018, Villejuif, France; University Paris-Sud (Drs Villenueve and Guénel), UMRS 1018, Villejuif, France; Institute of Pathology (Dr Johansen), Aalborg Hospital, Reberbansgade, Aalborg, Denmark; Division of Occupational and Environmental Medicine (Dr Wingren), Department of Clinical and Experimental Medicine, Faculty of Health Sciences, Linköping University, Sweden; Department of Oncology (Dr Hardell), University Hospital, Örebro, Sweden; Bremen Institute for Prevention Research and Social Medicine (Dr Ahrens), Division of Biometry and Data Processing, Bremen, Germany; Institute for Medical Informatics (Drs Ahrens and Stang), Biometry and Epidemiology, University Clinic Essen, Germany; Department of Medical Sciences (Dr Merletti), University of Turin, Italy; Cancer Prevention & Research Institute (Dr Gorini), Florence, Italy; Department of Preventive Medicine and Public Health (Dr José Aurrekoetxea), University of the Basque Country, Spain; UMRESTTE (Unité Mixte de Recherche Epidémiologique et de Surveillance en Transport, Travail et Environnement) (Dr Févotte), University Claude Bernard Lyon 1, Lyon, France; and University Versailles–Saint-Quentin en Yvelines, France (Dr Cyr).

Address correspondence to: María M. Morales-Suárez-Varela, MD, PhD, Unit of Public Health and Environmental Care, Department of Preventive Medicine, University of Valencia, Avda. Vicente Andrés Estellés s/n, 46100 Burjasot, Valencia, Spain (

The European Union (Biomed Programme) supported the project relating to occupational risk factors for rare cancers of unknown causes. Support was also provided by the F.I.S.S. between 1996 and 1998 (Spain), 96/0043-01, and GV99-2-1-12 (Valencian Community, Spain), INSERM, from Örebro County Council Research Committee, from the Federal Ministry for Education, Science, Research and Technology of Germany (BMBF, 01-HP-684/8), and from AIRC, Italy.

The authors declare no conflicts of interest.

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Objective: To evaluate the potential association between occupational exposure to chlorinated and petroleum solvents and mycosis fungoides (MF).

Methods: A questionnaire on lifetime job history was administered to 100 patients diagnosed with MF and 2846 controls. Odds ratios (ORs) were calculated as the measure of the association between exposure to each specific solvent and MF.

Results: In the total sample and in men, cases and controls did not differ in relation to exposure to any of the solvents studied. In women, an association with MF was seen for the highest level of estimated exposure to perchloroethylene (OR = 11.38; 95% confidence interval: 1.04 to 124.85) and for exposure less than the median to kerosene/fuel/gasoil (OR = 8.53; 95% confidence interval: 1.11 to 65.62).

Conclusions: These results do not provide conclusive evidence that exposure to solvents may increase risk of MF because they were not found in men.

Mycosis fungoides (MF) is the most common form of chronic T-cell cutaneous lymphoma,1 a heterogeneous group of non–Hodgkin's lymphomas of skin-homing T cells.2 It is a cancer with male predominance whose age profile and rare occurrence vary across countries.3 The incidence of MF is estimated at 1/100,000 persons per year in Europe4 and at 4.1/100.000 persons per year in the United States.5 Given its rarity, thus the inability to study a large number of patients, relatively little is known about its etiology.

Mycosis fungoides may vary from limited patchy skin disease to extensive cutaneous plaque and tumor involvement to extra-cutaneous compartments of blood, lymph nodes, and viscera6 Mycosis fungoides often starts with contact dermatitis.7

The rising incidence rates for MF suggest that environmental, occupational, and lifestyle factors play a role in the etiology of this disease.8 It is thought that the continuous activation of skin T-helper lymphocytes leads to a malignant transformation of a specific clone. Possible risk factors include occupational chemical exposure, radiation, drugs, and infection. The carcinogenic process is probably multifactorial and multistep and may combine an individual's genetic predisposition and immune status with various exogenous factors.

To date, no occupational or chemical exposure has been clearly established as a risk factor of MF, although associations with some occupations have been found.3,7,9 Machinists and machine operators10 exposed to various agents such as metals and plastics have been reported to be at increased risk. In a descriptive study from the United States, 29% of MF patients were employed in manufacturing industries, especially petrochemical, textile, and metal machinery.11 Studies in Scotland,12 California, and the state of Washington13 reported high risks in the paper and wood industry. An elevated risk of MF was also observed among Swedish women employed in hotels, restaurant work, and the garment industry.14

Long-term exposure to solvents may also trigger MF and hasten its progression from the patch stage to the plaque and tumor stage.15 Some of the industries associated with an elevated risk of MF share exposure to organic solvents, such as fuels and petroleum solvents. Cocco et al16 found an association between occupational exposure to solvents and lymphomas type B but discovered no associations with T-cell lymphoma The literature also reports increased risks of T-cell lymphoma in relation with occupational exposure to solvents such as benzene.17

Further assessments of occupational and environmental exposure may suggest preventive and surveillance measures, as well as the need to adjust existing health care policies. This study aims to assess the association between MF and occupational exposure to organic solvents, including chlorinated and petroleum solvents.

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This is a European multicenter case–control study at seven sites of rare cancers, including MF (gallbladder and extrahepatic bile ducts, small intestine, bone, eye melanoma, thymus, and breast cancer), which used a common control group and a common protocol. Cases and controls were recruited in 25 selected areas from six European countries between January 1, 1995, and June 30, 1997. In total, 100 MF cases were recruited in Denmark (the whole country), Sweden (Umea, Orebro/Uppsala, Linköping, and Lund), France (Calvados, Côte d'Or, Doubs, Hérault, Isère, Manche, Bas-Rhin, Haut-Rhin, Somme, and Tarn), Germany (Hamburg, Bremen, Essen, and Saarland), Italy (Torino, Firenze, and Padova), and Spain (Valencia, Navarre, and the Basque Country). The study design and data collection procedures were previously described in detail and are summarized hereafter.18,19

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Recruitment of Cases and Controls

Incident cases of MF were identified according to their International Classification of Diseases (ICD) diagnostic codes or according to codes from the International Classification of Diseases for Oncology (ICD-O 1976: codes for morphology 9700/3-97001/3 and topography 173.0-173.9). Case ascertainment (with clinical and pathological MF diagnoses) was based on repeated requests to hospital departments, pathology departments, and/or by frequent screening of regional or national cancer and pathology registers. For all the participating centers, geographical borders defined the study base, except Spain, where the participating hospitals' catchment areas defined the study base.

Patients aged between 35 and 69 years diagnosed with MF (n = 140) were recruited. Diagnoses were checked by a reference pathologist, who confirmed diagnoses in 118 cases and did not confirm diagnoses in 22 other patients, in accordance with morphological and topographical MF criteria. Among the 118 confirmed cases, 100 cases were interviewed and were available for the analysis. Only those 100 cases of patients who took part in the interview are presented in the tables of this article. The overall participation rate among cases was 84.75%.

Population controls were randomly selected from the same areas of case ascertainment.18 They were frequency-matched by sex and age (5-year age groups) with the combined set of cases from all seven cancer sites included in this study. The aim was to obtain at least four controls in each 5-year age and sex stratum for the most frequent case group in each region. Population registries or electoral rolls were used for sampling in Denmark, Sweden, France, Germany, and Italy. Because no population registry was available in Spain, colon cancer controls from the hospitals providing the cases were selected by a procedure identical to that used for the cases because no occupational exposure to chemicals is known to play a role in colon cancer. The controls served as a common pool of controls for all seven groups of rare cancer cases included in the European study. Of the 4629 eligible controls identified, 3156 were interviewed and included in the study (overall participation rate in the controls 68.2%). For this study, we used only the controls in the strata defined by age and study area where at least one MF patient case was diagnosed, leaving 2846 controls (1957 men and 889 women) available in the analyses.

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Data Collection

A set of common questionnaires on occupational exposures and lifestyle factors was developed and tested in cooperation with all the participating centers. The original version was written in English and translated into Danish, Swedish, German, French, Italian, Spanish, and Portuguese. Back-translation to English was performed to limit ambiguity as to how the questions were phrased.

The questionnaire included questions on sociodemographic characteristics, smoking habits, alcohol consumption, and lifelong occupational history. A complete lifetime job history was collected for each person by an interviewer using a structured questionnaire. For each job, we asked about occupation type and industry. For each occupational period, data on products and production processes, and on the year the job started and ended, were recorded, as were work tasks, job title, and working hours per week. The materials handled, chemical exposures, and occupations held by nearby workers were also recorded. The specific nature of the work was also addressed, such as work tasks, machines or products used, duration of their use (hours per week), and dates of job tenure. If the selected person was too ill to respond, a next of kin was selected (surrogate responder). Four cases and 95 controls were replaced with surrogates.20

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Exposure Assessment

Any job held for more than 6 months was coded by trained coders. Occupation was coded according to the International Standard Classification of Occupations of the International Labor Office, 1968 revision.14 Industry was coded according to the Classification of Activities in the European Community (NACE), 1996 revision.21

Occupational exposures to solvents were assessed using a job exposure matrix (JEM), developed at the Occupational Health Department of the French Institute of Health Surveillance (Institut de Veille Sanitaire InVS) by experts in occupation hygiene. Exposures to occupational hazards were assessed for all the jobs in the general population and for different calendar periods to account for exposure changes over time. Jobs were defined according to both the International Standard Classification of Occupations14 and a French classification of industrial activities (NAF), which was easily converted into the European classification code NACE, rev. 199621,22 because both classification systems are almost equivalent. Exposure to chlorinated solvents (trichloroethylene, perchloroethylene, carbone tetrachloride, chloroform, and methylene chloride) and to petroleum solvents (benzene, paraffinic and aliphatic hydrocarbons, gasoline, mineral spirit, and kerosene/fuel/gasoil) was determined for each job using semiquantitative indicators for exposure probability (0, not exposed; 1, possibly exposed; 2, probably exposed; 3, certainly exposed), exposure frequency (eg, for petroleum solvents 1: less than 30% of working hours; 2: 30% to 70%; 3: more than 70%) and exposure intensity (semiquantitative exposure scores on the basis of literature review of occupational measurement data, for example, for benzene: (1) 0.1 to 1 ppm; (2) 1 to 5 ppm; (3) 5 to 15 ppm; and (4) > 15 ppm).

Each job held by a case or a control included in the European study was assigned the corresponding exposure indices as reported in the JEM. A job-specific exposure score was then calculated as the result of exposure probability, frequency and intensity, and duration of the job in years. An individual cumulative exposure score was calculated for each study subject as the sum of the job-specific exposure scores over his or her lifetime job history.

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Statistical Analysis

For benzene, mineral spirit, and kerosene/fuel/gasoil, exposed workers were categorized according to the exposure tertiles among exposed controls, and unexposed subjects served as the reference group. For chlorinated solvents, paraffinic/alicyclic hydrocarbons and gasoline, exposed workers were categorized according to the exposure median among the exposed controls, by taking unexposed subjects as the reference group. For carbon tetrachloride and chloroform, workers were divided into exposed and unexposed because the number of exposed workers was very low. The analysis was conducted using unconditional logistic regressions with the SPSS v17 software (SPSS, Chicago, IL).

Odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated for each exposure agent as the measure of the association between the specific exposure and MF. The following confounders were considered in the adjusted analysis: age, sex, country, smoking habit, alcohol intake, body mass index (BMI), and level of education.

We also conducted several rounds of analyses by calculating cumulative exposure scores with a lag time of 5, 10, or 15 years before the diagnosis or interview for controls and by excluding jobs with a low exposure probability from the cumulative exposure scores. These sensitivity analyses did not modify our findings and have not been provided.

The study was conducted in accordance with the requirements of the Ethical Committees and data inspectorates in each participating country or region.

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Table 1 shows the characteristics of cases (n = 100) and controls (n = 2846). Controls had a slightly higher level of education than cases and were less likely to be smokers. Cases and controls were comparable in terms of their BMI and did not differ for alcohol consumption. Male controls presented a slightly higher level of education, were less likely to be smokers, and reported lower alcohol consumption than male cases; otherwise, male cases and controls were comparable in terms of their BMI. Female cases and controls were also comparable as regards level of education, smoking habit, BMI, and alcohol consumption.

Table 1
Table 1
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Table 2 summarizes the ORs describing the associations between exposure to different chlorinated solvents and MF. Cases and controls did not differ in relation to exposure of any of the chlorinated solvents studied (trichloroethylene, perchloroethylene, carbone tetrachloride, chloroform, and methylene chloride), except for a slightly higher OR in women exposed to perchloroethylene, which was more than the median.

Table 2
Table 2
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Table 3 shows the ORs, describing the associations between exposure to different petroleum solvents and MF. In the total sample, cases and controls did not differ in terms of exposure to any of the petroleum solvents studied (benzene, paraffinic/alicyclic hydrocarbons, gasoline, mineral spirit, and kerosene/fuel/gasoil). No association between MF and exposure to petroleum solvents was observed among men or among women, except for kerosene/fuel/gasoil among women. Nevertheless, only the OR for exposure less than the median was higher for this solvent (OR = 8.59; 95% CI: 1.14 to 64.49) but was based on only two exposed cases.

Table 3
Table 3
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All the analyses were repeated after excluding each country one after the other in the analyses. In another set of analyses, only the population controls were used. The results were similar to those presented.

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We noted earlier that environmental, occupational, or lifestyle factors were suspected to play a role in the etiology of MF.8 In this study the observation of an increased OR in persons with low educational level, particularly men, suggests that factors associated with education such as socioeconomic status and/or occupation may play a role in the etiology of MF. In the present analysis, we investigated occupational exposure to solvents as a possible cause of the disease.

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Chlorinated Solvents

Our results indicate no association with MF and chlorinated solvent, except for a possible risk for MF noted among those women who had a history of high exposure to perchloroethylene. This finding needs to be interpreted with caution because the association is based on only two exposed cases and only at the highest level and was not found in men.

Trichloroethylene is the most extensively studied chlorinated solvent. It is widely used as an industrial solvent and a degreasing agent and was classified by the International Agency for Research on Cancer as a probable carcinogen (Group 2A), be it with limited evidence of carcinogenicity in humans.23 Some studies have reported an association between trichloroethylene and non–Hodgkin's lymphoma,24,25 but others have not.26 In a review based on more than 80 studies, Wartenberg et al27 supported the hypothesis of an association between trichloroethylene exposure and non–Hodgkin's lymphoma, but this analysis was later questioned. Many comments have focused on how the studies were grouped and how the results were combined.28

Several issues may affect the interpretation of the results in these studies and the comparison of the findings. (1) Different subtypes of non–Hodgkin's lymphoma have been studied and distinct classifications have been used. The studies by Hansen et al24 and Raaschou-Nielsen et al25 classified non–Hodgkin's lymphoma according to the seventh revision of the ICD (ICD-7; World Health Organization 1957), but the present work was based on the 10th revision (ICD-10; World Health Organization 1976). (2) The methods used for assessing exposure to trichloroethylene varied widely, ranging from the use of broad job or industry categories to an analysis of biomonitoring data.29 Divergent observations may be due to an exposure misclassification bias, reflecting an incorrect assignment of study subjects to exposure groups. Hansen et al24 identified study subjects, using the trichloroethylene biological marker of urinary trichloroacetic acid, which provides some evidence of past trichloroethylene exposure, although usually not a full exposure history. In this study, exposure is assigned to subjects using a JEM. (3) Animal studies have reported the high risk of some hematopoietic cancers with trichloroethylene exposure.30,31

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Petroleum Solvents

Our results do not show any clear association between MF and petroleum solvent. The elevated risk observed for exposure to kerosene/fuel/gasoil less than median among women was not confirmed in the higher exposure category.

Occupational exposure to kerosene/fuel/gasoil occurs in oil refineries, petrochemical plants, petroleum distribution terminals, and marine petroleum tankers, and among car mechanics and filling station attendants.32 In a review by Kane and Newton,33 the authors found no epidemiologic evidence for occupational exposure to gasoil increasing the risk of incidence of non–Hodgkin's lymphoma.34–36 No study examined risk by subtypes.

No consensus has been reached as to whether benzene is associated with non–Hodgkin's lymphoma, but in their review among workers in industries, the authors concluded that there was no association.37

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Study Strengths and Limitations

A number of issues need to be considered when interpreting the results obtained in this study. First, only 100 MF cases are included and this small number of cases may lead to a low statistical power to detect any association. Mycosis fungoides is difficult to diagnose and to separate from other types of dermatosis.38,39 Only those cases with a diagnosis based on the strict criteria applied by one reference pathologist were included, increasing the precision of the case definition, but decreasing further the number of cases. Nevertheless, patients of this rare cancer were recruited from several European countries, which makes this study sample larger than in any other case–control studies on MF published to date.

Mean occupational exposure concentrations are relatively low in Europe, which implies a negative impact on statistical power.28 In addition, occupational exposure to solvents was assessed using a JEM. This exposure assessment method is considered less efficient than expert judgments made from reviewing individual job histories because exposure is assessed for groups of workers with the same job and not on an individual basis. For a fixed sample size, the interview and expert assessment design provide greater statistical power for detecting risks.40 Nondifferential exposure misclassification arises from using a JEM when assessing occupational exposure and is likely to bias the OR toward unity. Moreover, data were collected in this study from many centers and it is difficult to compare occupations across geographical borders, although a similar coding system was used. Also, specific work tasks, and thus occupational exposures, may differ within a given occupation from country to country. The use of the same JEM for all European countries may have introduced further errors in exposure assessment.

Overall, the increased OR of MF in persons with low educational level, particularly men, suggests that factors associated with socioeconomic status and/or occupation may play a role in the etiology of MF. Nevertheless, our findings do not indicate that occupational exposure to solvents may contribute to the risk gradient by educational level.

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This study does not provide credible evidence that exposure to petroleum or chlorinated solvents may increase the risk of MF.

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Rare Cancer Study Group members: Project management group: Wolfgang Ahrens, Mikael Eriksson, Pascal Guènel, Henrik Kolstad, Linda Kaerlev, Jean-Michel Lutz, Elsebeth Lynge, Franco Merletti, María M. Morales Suarez-Varela, Jorn Olsen, and Svend Sabroe. Other members: Denmark: Herman Autrup, Lisbeth Norum Pedersen, Preben Johansen, Stein Poulsen, Peter Stubbe Teglbjaerg, and Mogens Vyberg. France: Antoine Buemi, Paule-Marie Carli, Gilles Chaplain, Jean-Pierre Daurès, Jean Faivre, Joëlle Févotte, Pascale Grosclaude, Anne-Valérie Guizard, Michel Henry-Amar, Guy Launoy, Francois Ménégoz, Nicole Raverdy, and Paul Schaffer. Germany: Cornelia Baumgardt-Elms, Sibylle Gotthardt, Ingeborg Jahn, Karl-Heinz Jöckel, Hiltrud Merzenick, Andreas Stang, Christa Stegmaier, Antje Timmer, and Hartwig Ziegler. Italy Terri Ballard, Franco Bertoni, Giuseppe Gorini, Sandra Gostinicchi, Giovanna Masala, Enzo Merler, Lorenzo Richiardi, Lorenzo Simonato, and Paola Zambon. Latvia: Irena Rogovska, Galina Sharkova, and Aivars Stengrevics. Lithuania: Jolita Gibaviciene, Laimonas Jazukevicius, Juozas Kurtinaitis, and Roma Pociute. Portugal: Noemia Alfonso, Altamiro Costa-Pereira, Sonia Doria, Carlos Lopes, Jose Manuel Lopes, Ana Miranda, and Cristina Santos. Spain: Daniel Almenar, Inés Aguinaga, Juan J. Aurrekoetxea, Concepción Brun, Alicia Córdoba, Francisco Guillén, Rosa Guarch, Agustín Llopis, Rosa Llorente, Blanca Marín, Amparo Marquina, Miguel Angel Martínez, JM Martínez Peñuela, Ana Puras, Ma Adela Sanz, Francisco Vega, and Ma Aurora Villanueva. Sweden: Lennart Hardell, Irene Larsson, Hakan Olson, Mónica Sandstrom, and Gun Wingren. The United Kingdom: Janine Bell, Ian Cree, Tony Fletcher, and Alex JE Foss.

Copyright © 2013 by the American College of Occupational and Environmental Medicine


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