Environment International 127 (2019) 216–225 Contents lists available at ScienceDirect Environment International journal homepage: www.elsevier.com/locate/envint Toenail concentrations of trace elements and occupational history in T pancreatic cancer Judit Camargoa,b, José A. Pumaregab,c, Joan Alguacilc,d, Pere Sanz-Galléne, Magda Gasulla,b,c, ⁎ George L. Delclosb,c,f,g, André F.S. Amaralh, Miquel Portaa,b,c, a School of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain b Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain c CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain d Universidad de Huelva, Huelva, Spain e Clinical Toxicology Unit, Hospital Clínic, Barcelona, Spain f Center for Research in Occupational Health (CiSAL), Universitat Pompeu Fabra, Barcelona, Spain g The University of Texas School of Public Health, Houston, TX, USA h Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College London, London, UK A R T I C LE I N FO A B S T R A C T Handling Editor: Adrian Covaci Background: Some occupations potentially entailing exposure to cadmium, arsenic, lead, selenium, nickel, and chromium have been associated with an increased risk of exocrine pancreatic cancer (EPC), but no studies have Keywords: assessed whether body concentrations of such compounds differed among subjects occupationally exposed and Trace elements Cadmium unexposed. No studies which found that exposure to such metals increased the risk of EPC assessed whether past Manganese occupations were the source of exposure. Arsenic Objective: The aim was to analyse the relationship between toenail concentrations of trace elements and occu- Occupation pational history in EPC patients. Pancreatic cancer Methods: The study included 114 EPC cases personally interviewed on occupational history and lifestyle factors. Occupations were coded according to the International Standard Classification of Occupations 1988. Selected occupational exposures were assessed by two industrial hygienists and with the Finnish job-exposure matrix (Finjem). Concentrations of 12 trace elements were determined in toenail samples by inductively coupled plasma mass spectrometry. Adjusted geometric means (aGMs) and 95% confidence intervals (95% CI) were calculated. Results: Patients occupationally exposed to aromatic hydrocarbon solvents (AHs) had higher concentrations of cadmium, manganese, lead, iron and vanadium. The aGM of cadmium concentrations for cases exposed to any pesticide was 0.056 μg/g [95% CI: 0.029–0.108], and, for unexposed cases, 0.023 μg/g [0.017–0.031]. Patients occupationally exposed to pesticides had higher concentrations of cadmium and manganese. Higher con- centrations of vanadium, lead and arsenic were related to exposure to formaldehyde. Vanadium and lead were also associated with exposure to chlorinated hydrocarbon solvents, and arsenic was related to exposure to polycyclic aromatic hydrocarbons (PAHs). Conclusions: Patients occupationally exposed to AHs, pesticides, chlorinated hydrocarbon solvents, for- maldehyde, volatile sulphur compounds and PAHs had higher concentrations of several metals. These elements may account for some of the occupational risks previously reported for pancreatic cancer. 1. Introduction increased risk of exocrine pancreatic cancer (EPC) (Alguacil et al., 2003; Amaral et al., 2012; Andreotti and Silverman, 2012; Ojajärvi Occupational and non-occupational exposures to cadmium, arsenic, et al., 2000) and other diseases (McCarty and DiNicolantonio, 2016; lead, selenium, nickel, and chromium have been associated with an Menke et al., 2016). However, evidence is limited and not always Abbreviations: aGM, adjusted geometric mean; AHs, aromatic hydrocarbon solvents; CI, confidence interval; EPC, exocrine pancreatic cancer; IH, industrial hy- gienists; ISCO, International Standard Classification of Occupations; PAHs, polycyclic aromatic hydrocarbons ⁎ Corresponding author at: Hospital del Mar Medical Research Institute (IMIM), Universitat Autònoma de Barcelona, Carrer del Dr. Aiguader, 88, E-08003 Barcelona, Spain. E-mail address: mporta@imim.es (M. Porta). https://doi.org/10.1016/j.envint.2019.03.037 Received 12 November 2018; Received in revised form 14 March 2019; Accepted 14 March 2019 Available online 28 March 2019 0160-4120/ © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). J. Camargo, et al. Environment International 127 (2019) 216–225 consistent, and few studies used biomarkers to assess such exposures tumour's clinical stage at diagnosis were also recorded on this form. (Boffetta, 2014; Cheng et al., 2015; Fritschi et al., 2015; Luckett et al., Clinical stage was classified according to the tumour-node-metastasis 2012; Maisonneuve and Lowenfels, 2015; Reul et al., 2016). This lack of (TNM) system, and the histological type was classified according to the consistency might partly be explained by unaccounted differences in International Classification of Diseases for Oncology. All cases were exposure to specific chemical or physical agents (Ojajärvi et al., 2000). independently reviewed by the study reference pathologists, blinded to Also, workers are subject to complex chemical mixtures, whose exact the original diagnoses. Furthermore, a panel of clinical and surgical composition is seldom fully characterized (Reul et al., 2016; Sexton and experts in gastrointestinal diseases reviewed the hospital discharge di- Hattis, 2007). agnosis of all patients and, based on all clinical and pathological in- Exposure to chlorinated hydrocarbon solvents and similar com- formation available, including follow-up, achieved a consensual clin- pounds is considered a major occupational risk factor for EPC (Amaral ical-pathological diagnosis. The ethics committees of participating et al., 2012; Antwi and Eckert, 2015; Barone et al., 2016; Bosch de hospitals approved the study protocol, and patients gave informed Basea et al., 2011) and high levels of cadmium and arsenic have also consent to participate. been associated with an increased risk (Amaral et al., 2012; Andreotti and Silverman, 2012; Antwi and Eckert, 2015; Barone et al., 2016; 2.2. Personal interviews and information on occupational history Luckett et al., 2012). In contrast, levels of selenium may be inversely associated with EPC (Amaral et al., 2012; Barone et al., 2016). An in- All 114 EPC cases were interviewed face-to-face by trained monitors creased incidence of EPC has been identified among metal plating during hospital stay, soon after the time of diagnosis (Alguacil et al., workers, in particular in those exposed to nickel and chromium 2000, 2002, 2003; Bosch de Basea et al., 2011; Porta et al., 2007, (Alguacil et al., 2003; Amaral et al., 2012; Antwi and Eckert, 2015; 2008a, 2008b; Soler et al., 1999). The respondent was the patient in Barone et al., 2016; Maisonneuve and Lowenfels, 2015; Ojajärvi et al., 94.7% of cases and a relative in 5.3%. Interviews included questions on 2000). Lead exposure has also been inconclusively associated with EPC past clinical history, signs and symptoms of pancreatic cancer, diet, (Amaral et al., 2012; Ojajärvi et al., 2000). Only two previous studies coffee, alcohol and tobacco consumption, education, and occupation on trace elements as possible etiologic factors of EPC used biomarkers (Alguacil et al., 2000, 2002, 2003; Bosch de Basea et al., 2011; Crous- of chromium exposure (Amaral et al., 2012; Lener et al., 2016). Two Bou et al., 2007; Morales et al., 2007; Porta et al., 2000, 2008a, 2008b; additional studies measured serum and urinary cadmium concentra- Soler et al., 1999). Coffee and alcohol consumption were not related to tions to assess the role of occupational exposure to cadmium in EPC occupation. To assess the reliability of interviews, a sample of relatives (Luckett et al., 2012; Kriegel et al., 2006). To our knowledge there are was concurrently and separately interviewed about the same questions no data relating occupational history and biomarkers of exposure to and agreement between the two sets of responses was compared trace elements in EPC. In the present study we analysed toenail con- (Alguacil et al., 2003; Bosch de Basea et al., 2011; Ojajärvi et al., 2000; centrations of the following trace elements in EPC cases: cadmium, Soler et al., 1999). arsenic, selenium, nickel, lead, chromium, manganese, aluminium, Participants were asked if they had ever worked in any of 10 ac- iron, vanadium, copper and zinc (Amaral et al., 2012). Contrary to tivities a priori defined to be potentially related with pancreatic ductal concentrations in urine and blood –which might reflect more recent and biliary adenocarcinomas (Alguacil et al., 2000, 2002, 2003; Porta exposures–, concentrations of trace elements in hair and nails reflect et al., 2008a). These activities were pesticide use, handling of petro- exposures over several months, and are thus preferable as an estimate leum derivatives, the chemical industry, graphic arts, jewellery making, of longer exposures (Golasik et al., 2015; Goyer and Clarkson, 2001; manufacture or repair of automobiles, leather tanning, and the textile Hopps, 1977; Slotnick and Nriagu, 2006). industry. Patients who reported having ever worked in any of these The aim of the present study was to assess the relationship between activities were asked about the duration of the employment, specific concentrations of trace elements and occupational exposures in EPC activity, and products to which they had been exposed. The same in- patients. Knowledge of this relationship may help understand processes formation was also requested for any other activities (up to two) that through which certain trace elements and occupations influence EPC the patient might have performed over their lifetime. Information on risk. occupational history was not available for controls (Amaral et al., 2012). The occupational history of EPC cases collected during the in- 2. Methods terview was used in three ways. First, occupations were coded according to the Spanish version of 2.1. Study population the International Standard of Occupations 1988 (ISCO 88) (Alguacil et al., 2000; Bosch de Basea et al., 2011; Porta et al., 2008a). Occu- Methods of the PANKRAS II study have been described in detail pations classified as ISCO group 1 to 4 (all office-related) were merged elsewhere (Alguacil et al., 2000, 2002, 2003; Amaral et al., 2012; Bosch into one category, since they were not discriminating factors in a de Basea et al., 2011; Crous-Bou et al., 2007; Gasull et al., 2010; qualitative sense in the occupational classification (Table 1, footnote). Mendez et al., 2006; Morales et al., 2007; Porta et al., 1999, 2000, When patients had several occupations, the most recent was used in the 2007, 2008a, 2008b; Soler et al., 1999). Briefly, subject recruitment analyses. There were some differences in the distribution of age and sex took place between 1992 and 1995 at five general hospitals in the among participants belonging to the different ISCO major groups eastern part of Spain, where 185 incident cases of EPC were pro- (Table 1). Most occupations were performed by males. Only within spectively identified. The present report is based on 114 cases (70 men elementary occupations (ISCO 9) were participants mostly women and 44 women, mean age 62.9 and 71.4 years, respectively) with (81.5%), all of whom (N = 22) were housewives. Among participants in complete data on toenail concentrations of trace elements, occupation the “skilled agricultural occupations” (ISCO 6 major group), 46.2% and lifestyle. There were no significant differences between these 114 were women. There were no significant differences among the major and the remaining cases with respect to a broad range of socio- ISCO groups in the time interval between the first symptom of the demographic and clinical variables (including age, sex, occupational disease and its diagnosis, the time interval between the first symptom history, education and social class, hospital, tumour stage, signs and and the collection of the toenail samples in which trace elements were symptoms of pancreatic cancer, duration of the interview, energy in- analysed, or in tumour stage at diagnosis (Table 1). take, and consumption of coffee, tobacco and alcohol). A structured Second, using all information on occupational history available form was used to collect clinico-pathological information from medical from the interview, two industrial hygienists (IH) assessed exposure to records, including details on diagnostic procedures, laboratory results 22 suspected carcinogens: pesticides, aromatic hydrocarbon solvents and follow-up. The primary and secondary discharge diagnoses and the (AHs), hexavalent and trivalent chromium, lead, nickel compounds, 217 J. Camargo, et al. Environment International 127 (2019) 216–225 Table 1 Characteristics of pancreatic cancer patients by last occupation classified by major groups of the International Standard Classification of Occupations 1988 (ISCO 88). Characteristics Total Major ISCO groupsa p-Valueb ISCO 1 to 4 ISCO 5 ISCO 6 ISCO 7 ISCO 8 ISCO 9 (N = 114) (N = 16) (N = 10) (N = 13) (N = 27) (N = 21) (N = 27) Agec (years) 66.2 ± 12.4 66.9 ± 14.0 63.0 ± 14.6 70.5 ± 10.2 60.5 ± 10.9 65.1 ± 13.6 71.4 ± 9.9 0.021d Gender (% males) 61.4 81.2 70.0 53.8 85.2 71.4 18.5 < 0.001 Education (%) 0.009 Illiterate/can only read and write 40.7 12.5 30.0 66.7 29.6 42.9 59.3 Up to 10 years of schooling 51.3 56.3 70.0 33.3 66.7 52.4 33.3 More than 10 years of schooling 8.0 31.3 0 0 3.7 4.8 7.4 Years of educationc 4.7 ± 4.5 8.7 ± 5.0 4.7 ± 3.2 2.3 ± 2.9 4.7 ± 3.7 4.0 ± 3.6 3.9 ± 5.3 0.003d First symptom to diagnosis intervalc 107.8 ± 122.1 90.3 ± 138.6 116.0 ± 113.6 139.9 ± 99.3 123.2 ± 153.9 138.4 ± 140.2 60.6 ± 43.6 0.217d (days) First symptom to nail sample intervalc 113.9 ± 125.4 89.3 ± 139.4 113.2 ± 115.6 142.8 ± 114.4 135.0 ± 156.1 144.3 ± 138.0 70.1 ± 58.8 0.254d (days) Occupational social class (%) < 0.001 Non-manual workers 37.2 87.5 30.0 92.3 3.7 14.3 34.6 Manual workers 62.8 12.5 70.0 7.7 96.3 85.7 65.4 Total intakec (Kcal) 1735 ± 325.5 1713 ± 332.2 1738 ± 200.1 1462 ± 345.8 1833 ± 293.7 1766 ± 363.7 1758 ± 301.7 0.031d Smoking status (%) Non smoker 43.0 25.0 30.0 53.8 25.9 33.3 77.8 0.011 Former 22.8 31.3 20.0 15.4 25.9 33.3 11.1 Current 34.2 43.8 50.0 30.8 48.1 33.3 11.1 Alcohol consumption (%) 0.248 No and occasional 27.2 18.8 50.0 23.1 14.8 28.6 37.0 Moderate and Heavy 72.8 81.3 50.0 76.9 85.2 71.4 63.0 Tumour stage (%) 0.922 Stage I 21.4 18.8 20.0 16.7 19.2 28.6 22.2 Stage II 15.2 6.2 10.0 8.3 15.4 9.5 29.6 Stage III 14.3 18.8 10.0 25.0 15.4 14.3 7.4 Stage IV 49.1 56.2 60.0 50.0 50.0 47.6 40.7 ISCO 1: Legislators, senior officials and managers. ISCO 2: Professionals. ISCO 3: Technicians and associate professionals. ISCO 4: Clerks. ISCO 5: Service, shop and market sales workers ISCO 6: Skilled agricultural and fishery workers. ISCO 7: Craftsmen and related trades workers. ISCO 8: Plant and machine operators and assemblers. ISCO 9: Elementary occupations. a Based on subjects' last occupation. b Unless otherwise specified, p-value derived from Fisher's exact test (two-tailed). c Mean ± standard deviation. d ANOVA. aluminium and others, and classified subjects as non-exposed or ex- aromatic hydrocarbons (PAHs). posed. The “exposed” classification required a substantiated source of Patients were asked about the frequency of consumption of food exposure (Alguacil et al., 2000, 2002, 2003; Bosch de Basea et al., groups during the year before the first symptom of the current illness. 2011). If exposure was unsubstantiated but possible, the category ‘un- For this purpose a brief food frequency questionnaire was administered known’ was used. The intensity of exposure was coded as high, low, (Gasull et al., 2010; Mendez et al., 2006; Morales et al., 2007). unknown or none. The IH developed algorithms for the exposure as- sessment. Two occupational epidemiologists evaluated and accepted 2.3. Assessment of trace elements the algorithms. The IH were also given information about the ages at which subjects started and stopped schooling, and about the calendar Trace elements analysed were cadmium, arsenic, selenium, nickel, year and the place of residence (Alguacil et al., 2000, 2002). Patients lead, chromium, manganese, aluminium, iron, vanadium, copper and exposed to organochlorine pesticides (N = 11) were also exposed to zinc (Amaral et al., 2012). Toenails were collected during the hospital arsenical pesticides by the IH classification. Also according to the IH stay where EPC was diagnosed (Bosch de Basea et al., 2011; Gasull classification, the total number of patients exposed to any type of et al., 2010; Porta et al., 1999, 2007). Information on time of treatment pesticide was 13: a) including 11 patients exposed to organochlorine/ onset was available for 73 patients, of whom two started treatment arsenical pesticides; b) two of 12 exposed to organophosphorus pesti- before collection of toenails. Samples were stored at room temperature cides and not exposed to organochlorine pesticides; and c) one exposed until the time of analysis. After cleaning and washing to remove ex- to other pesticides and not exposed to organochlorine or to organo- ternal contaminants, trace elements were quantified at the Trace Ele- phosphorus pesticides. ment Analysis Core (Dartmouth College, NH, USA), using inductively And third, we used the Finnish job-exposure matrix (Finjem) to coupled plasma-mass spectrometry (Amaral et al., 2012). evaluate occupational exposure to 21 chemical agents and 2 physical exposures (Alguacil et al., 2000, 2002, 2003; Bosch de Basea et al., 2.4. Statistical analyses 2011). The exposure categories used were ‘substantial’, ‘low’, and ‘un- exposed’. The cut-off point between exposed and non-exposed was set Univariate statistics were computed as customary. Thus, for in- as close as possible to the median of the distribution of the product of stance, means and medians of toenail concentrations were compared for the probability of exposure and the intensity of exposure (most in mg/ levels of ISCO 88 groups, IH-based metrics, and Finjem-based metrics. m3 or ppm) (Alguacil et al., 2000, 2002, 2003). Exposure to aromatic General linear models were applied to analyse variations in con- hydrocarbon solvents by the Finjem matrix was restricted to polycyclic centrations of trace elements (Bosch de Basea et al., 2011; Porta et al., 218 J. Camargo, et al. Environment International 127 (2019) 216–225 2008a). The main effects of all predictors were independently explored highest concentrations were in patients of ISCO group 8 than in patients in the base models. Geometric means and their 95% confidence inter- of other ISCO groups (data not shown). vals (CIs) were estimated for the occupational exposures by the codes of When adjusting for age, sex and total caloric intake (Kcal), the aGM the IH and by Finjem codes (exposed vs. unexposed). Adjusted models of iron concentrations of patients in the major group 8 were higher than for each trace element included age, gender, and total caloric intake concentrations of patients in the majors groups 1 to 4 (aGM = 24.08 (Kcal) as covariates. Region of residence (Hashemian et al., 2017) and [16.86–34.40] and aGM = 11.72 [7.75–17.72], respectively; p- specific diet variables were also considered as potential confounders value = 0.010); they only remained statistically significant for men (NRC, 1989). In models for cadmium and lead concentrations, tobacco (aGM = 20.76 [13.87–31.10] and aGM = 11.24 [7.31–17.28], respec- smoking was included as a covariate. The level of statistical significance tively; p-value = 0.043). aGM of copper concentrations were higher in was set at 0.05, and all tests were two-tailed. Statistical analyses were patients whose last occupation was in ISCO major group 8 performed using Stata software version·10.1 (StataCorp, College Sta- (aGM = 4.51 μg/g [95% CI: 3.77, 5.39]) than in patients whose last tion, TX) and SPSS version 18.0.0 (SPSS, Chicago, IL, USA, 2009). occupation was in an ISCO group 1 to 4 (aGM = 3.25 [2.65, 4.00], p- value = 0.018). 3. Results Exposure to chlorinated hydrocarbon solvents, formaldehyde and volatile sulphur compounds, assessed through the Finjem, was related Median toenail concentrations of cadmium and manganese were to vanadium concentrations, whose median was higher in the corre- significantly higher in EPC patients exposed to aromatic hydrocarbon sponding exposed EPC cases (> 0.03 μg/g) than in the non-exposed solvents (AHs), assessed by IH, than in patients unexposed to AHs. Such cases (0.019 μg/g) (p-values < 0.035 for Mann-Whitney's U test) concentrations were also higher in patients exposed to organochlorine (Table 4). aGM of vanadium concentrations of patients exposed to and arsenical pesticides (vs. patients unexposed to these pesticides), to chlorinated hydrocarbon solvents, and of those exposed to for- organophosphorus pesticides (again vs. unexposed) and to other pes- maldehyde, doubled the aGM of the non-exposed when adjusted for age ticides (vs. unexposed); always, as assessed by IH (Table 2). Con- and sex, and also when further adjusted for Kcal (Table 5). aGM of centrations of lead, selenium, iron and arsenic, were significantly vanadium concentrations for patients exposed to volatile sulphur higher in patients exposed to AHs (again vs. unexposed to AHs) (Table 2 compounds also was statistically higher than concentrations of patients and Supplemental Table 1). non-exposed (0.034 μg/g and 0.021 μg/g, respectively, p- In multivariate models, concentrations of cadmium, lead, manga- value = 0.048). Exposure to chlorinated hydrocarbon solvents ac- nese, iron and vanadium were higher in patients exposed to AHs than in cording to Finjem was also related with higher copper concentrations, patients unexposed: e.g., for cadmium, when adjusting for age, sex, although it was not statistically significant when dietary factors were tobacco smoking, and intake of fresh vegetables and fruit, the aGM for included in the regression model (Table 5). exposed patients was 0.056 μg/g for exposed patients vs. 0.023 μg/g for Lead concentrations were significantly higher for patients exposed unexposed; p-value = 0.022 (Table 3). Cadmium and manganese con- to chlorinated hydrocarbon solvents, and also to formaldehyde, than for centrations were also higher in patients exposed to pesticides regardless the respective non-exposed (Table 5). Levels of arsenic assessed through of the kind of pesticide, even when models were fully adjusted. Con- Finjem were higher in cases exposed to formaldehyde than in the non- centrations of aluminium were significantly higher in patients exposed exposed (median concentrations of 0.149 μg/g and 0.070 μg/g, re- to organophosphorus pesticides (vs. non-exposed) and, although not spectively, p-value = 0.009) (Supplemental Table 3); in multivariate statistically significant, were also higher in patients exposed to other models, aGMs for the exposed remained significantly higher than for pesticides (vs. non-exposed) (Table 3). the non-exposed (0.137 μg/g vs. 0.075 μg/g, p-value = 0.017) Median concentrations of cadmium in EPC patients whose last oc- (Table 5). cupations were included in ISCO major groups 7 (median of 0.038 μg/g) Patients exposed to polycyclic aromatic hydrocarbons (PAHs) and 9 (median of 0.034 μg/g) were slightly higher than concentrations showed higher arsenic concentrations than the non-exposed (median of of other patients whose last occupation was another major group (range 0.121 μg/g and 0.071 μg/g, respectively; p-value = 0.021) between 0.017 μg/g and 0.025 μg/g) (Supplemental Table 2). Copper (Supplemental Table 3). In adjusted models, the aGM for arsenic of concentrations were significantly higher in patients whose last occu- cases exposed to PAHs was significantly higher than that of the un- pation was included in ISCO major group 8 (4.35 μg/g) (plant and exposed/non-exposed (Table 5). machine operators and assemblers) than in patients whose last occu- In cases exposed to cadmium, lead, chromium and nickel (according pation was another major group (range between 3.20 μg/g and 3.69 μg/ to IH and Finjem), concentrations of cadmium and nickel were higher g; p-value = 0.027). For zinc, median concentrations of cases whose last than in non-exposed cases (Supplemental Figs. 1 and 2); but in the occupation was included in ISCO major groups 8 and 9 (116.7 μg/g and regression models these differences were not significant (data not 115.1 μg/g, respectively) were also higher than concentrations of pa- shown). tients whose last occupation was another major group (range between Patients exposed and unexposed to other substances, assessed by IH 101.7 and 112.4; p-value = 0.064) (Supplemental Table 2). and Finjem (industrial chromium, lead, cadmium, nickel, organic pig- Concentrations of aluminium of patients of major group 6 (skilled ments, benzene and other organic components, gasoline and diesel agricultural and fishery workers) were higher than groups 1 to 4 (all exhaust, cotton and synthetic polymer dust, and asbestos), did not show office-related) and group 9, (median concentrations of 19.43 μg/g, significant difference in concentrations of trace elements. 7.24 μg/g and 7.38 μg/g, respectively, both p-values ≤ 0.045). For iron, concentrations of patients with a last occupation in ISCO major groups 4. Discussion 6 and 8 were higher than concentrations of patients in major groups 1 to 4; median concentrations were 22.63 μg/g, 14.35 μg/g and 11.31 μg/ Higher body concentrations of several trace elements –notably, g, respectively; p-value = 0.050 for the contrast between concentra- cadmium, manganese, lead, aluminium, vanadium, copper, iron and tions of major groups 6 and 1 to 4, and p-value = 0.083 for the contrast arsenic– were found in patients with pancreatic cancer who had been between concentrations of major groups 8 and 1 to 4. Concentrations of occupationally exposed to AHs, pesticides, chlorinated hydrocarbon nickel were significantly higher in ISCO major group 9 (0.310 μg/g) solvents, formaldehyde, volatile sulphur compounds and PAHs. than in patients whose last occupation was in another group (median Findings thus suggest that these elements may account for some of the range between 0.128 μg/g and 0.219 μg/g; p-value = 0.022) occupational risks previously reported for this cancer (Alguacil et al., (Supplemental Table 2). When we stratified by gender, differences in 2003; Amaral et al., 2012; Andreotti and Silverman, 2012; Ojajärvi copper concentrations remained statistically significant in men, and the et al., 2000). 219 J. Camargo, et al. Table 2 Trace element concentrations (μg/g) by occupational exposure assessed by industrial hygienists in pancreatic cancer patients. Trace element concentration (μg/g) Aromatic hydrocarbon solvents Organochlorine and arsenical pesticides Organophosphorus pesticides Other pesticides Total Exposed Non-exposed Exposed Non-exposed Exposed Non-exposed Exposed Non-exposed p-Value (N = 114) (N = 23) (N = 91) p-Value (N = 11) (N = 103) p-Value (N = 12) (N = 102) p-Value (N = 13) (N = 101) Cadmium Mean ± SD 0.103 ± 0.431 0.089 ± 0.143 0.107 ± 0.477 0.863a 0.134 ± 0.183 0.100 ± 0.450 0.806a 0.125 ± 0.178 0.101 ± 0.452 0.853a 0.129 ± 0.171 0.100 ± 0.454 0.824a Median 0.030 0.036 0.025 0.063b 0.067 0.028 0.010b 0.068 0.028 0.025b 0.069 0.028 0.010b Lead Mean ± SD 2.73 ± 14.76 8.26 ± 32.41 1.33 ± 2.66 0.044a 1.15 ± 1.14 2.90 ± 15.53 0.711a 1.52 ± 1.65 2.87 ± 15.60 0.765a 1.48 ± 1.59 2.89 ± 15.68 0.748a Median 0.879 1.12 0.804 0.078b 1.33 0.870 0.867b 1.34 0.863 0.685b 1.33 0.856 0.608b Selenium Mean ± SD 0.516 ± 0.113 0.551 ± 0.082 0.507 ± 0.118 0.089a 0.527 ± 0.102 0.514 ± 0.114 0.726a 0.536 ± 0.095 0.513 ± 0.115 0.510a 0.538 ± 0.091 0.513 ± 0.115 0.448a Median 0.513 0.550 0.503 0.075b 0.498 0.515 0.981b 0.538 0.510 0.592b 0.543 0.509 0.473b Chromium 220 Mean ± SD 1.13 ± 3.14 1.02 ± 1.85 1.15 ± 3.40 0.860a 1.04 ± 1.12 1.14 ± 3.29 0.924a 1.63 ± 2.42 1.07 ± 3.22 0.560a 1.52 ± 2.35 1.08 ± 3.23 0.634a Median 0.418 0.410 0.425 0.802b 0.587 0.394 0.110b 0.704 0.400 0.112b 0.587 0.406 0.198b Manganese Mean ± SD 0.490 ± 0.772 0.688 ± 0.822 0.440 ± 0.756 0.170a 0.840 ± 0.848 0.453 ± 0.759 0.115a 0.992 ± 1.02 0.431 ± 0.721 0.089a 0.939 ± 0.997 0.433 ± 0.725 0.099a Median 0.218 0.289 0.205 0.053b 0.387 0.200 0.026b 0.426 0.203 0.035b 0.387 0.200 0.029b Aluminium Mean ± SD 14.47 ± 18.74 21.59 ± 30.91 12.66 ± 13.83 0.189a 28.57 ± 40.80 12.96 ± 14.22 0.235a 31.49 ± 40.52 12.46 ± 13.26 0.134a 29.45 ± 39.48 12.54 ± 13.30 0.150a Median 8.08 11.01 7.57 0.153b 12.87 7.42 0.143b 12.98 7.49 0.088b 12.87 7.57 0.180b Iron Mean ± SD 36.18 ± 153.6 33.76 ± 36.15 36.79 ± 171.2 0.933a 37.97 ± 44.30 35.98 ± 161.1 0.968a 43.25 ± 46.64 35.34 ± 161.7 0.867a 40.41 ± 45.81 35.63 ± 162.5 0.916a Median 13.21 22.14 12.68 0.053b 18.91 12.69 0.117b 19.84 12.68 0.062b 17.06 12.69 0.183b Vanadium Mean ± SD 0.040 ± 0.082 0.052 ± 0.067 0.037 ± 0.085 0.433a 0.064 ± 0.080 0.038 ± 0.082 0.303a 0.074 ± 0.087 0.036 ± 0.081 0.134a 0.069 ± 0.085 0.036 ± 0.081 0.170a Median 0.020 0.022 0.020 0.149b 0.030 0.019 0.082b 0.029 0.019 0.095b 0.028 0.020 0.114b SD: standard deviation. a Student's t-test (two-tail). b Mann-Whitney's U test (two-tail). Environment International 127 (2019) 216–225 J. Camargo, et al. Environment International 127 (2019) 216–225 Table 3 Influence on trace element concentrations (μg/g) of occupational exposures assessed by industrial hygienists in pancreatic cancer patients. Model Ia Model IIb Trace element Exposure aGM (95% CI) P-value aGM (95% CI) P-value c Cadmium (μg/g) Aromatic hydrocarbon solvents 0.066 0.022 Non exposed 0.023 (0.017, 0.033) 0.023 (0.017, 0.031) Exposed 0.049 (0.025, 0.098) 0.056 (0.029, 0.108) Organochlorine pesticidesd 0.013 0.006 Non exposed 0.024 (0.018, 0.033) 0.024 (0.018, 0.032) Exposed 0.083 (0.033, 0.209) 0.088 (0.037, 0.211) Organophosphorus pesticides 0.029 0.023 Non exposed 0.024 (0.018, 0.033) 0.024 (0.018, 0.032) Exposed 0.070 (0.029, 0.170) 0.069 (0.030, 0.159) Other pesticides 0.012 0.005 Non exposed 0.024 (0.018, 0.032) 0.024 (0.018, 0.031) Exposed 0.077 (0.033, 0.179) 0.081 (0.036, 0.181) Any pesticide 0.010 0.004 Non exposed 0.024 (0.017, 0.032) 0.023 (0.018, 0.031) Exposed 0.075 (0.033, 0.170) 0.081 (0.038, 0.176) Leade (μg/g) Aromatic hydrocarbon solvents 0.049 0.067 Non exposed 0.778 (0.626, 0.967) 0.781 (0.628, 0.971) Exposed 1.317 (0.836, 2.09) 1.298 (0.808, 2.084) Manganesef (μg/g) Aromatic hydrocarbon solvents 0.073 0.032 Non exposed 0.233 (0.187, 0.289) 0.228 (0.185, 0.282) Exposed 0.375 (0.237, 0.592) 0.402 (0.256, 0.631) Organochlorine pesticidesd 0.028 0.062 Non exposed 0.239 (0.196, 0.291) 0.241 (0.199, 0.293) Exposed 0.491 (0.267, 0.903) 0.445 (0.242, 0.820) Organophosphorus pesticides 0.012 0.030 Non exposed 0.236 (0.194, 0.287) 0.238 (0.196, 0.290) Exposed 0.519 (0.291, 0.928) 0.470 (0.264, 0.837) Other pesticides 0.013 0.023 Non exposed 0.235 (0.193, 0.286) 0.237 (0.195, 0.288) Exposed 0.502 (0.287, 0.877) 0.469 (0.270, 0.815) Any pesticide 0.013 0.022 Non exposed 0.234 (0.192, 0.285) 0.236 (0.194, 0.287) Exposed 0.490 (0.286, 0.841) 0.462 (0.271, 0.788) Aluminiumg (μg/g) Organochlorine pesticidesd 0.085 0.141 Non exposed 9.00 (7.63, 10.63) 9.07 (7.71, 10.66) Exposed 14.44 (8.66, 24.09) 13.53 (8.15, 22.46) Organophosphorus pesticides 0.024 0.054 Non exposed 8.85 (7.51, 10.44) 8.94 (7.61, 10.51) Exposed 16.04 (9.87, 26.06) 14.75 (9.13, 23.84) Other pesticides 0.050 0.098 Non exposed 8.90 (7.54, 10.52) 8.99 (7.63, 10.58) Exposed 14.67 (9.17, 23.47) 13.62 (8.57, 21.65) Any pesticide 0.063 0.109 Non exposed 8.91 (7.53, 10.53) 8.98 (7.71, 10.66) Exposed 14.12 (8.96, 22.25) 13.28 (8.48, 20.78) Iron (μg/g) Aromatic hydrocarbon solvents 0.065 0.018 Non exposed 14.99 (12.53, 17.93) 14.66 (12.32, 17.45) Exposed 22.52 (15.41, 32.91) 24.57 (16.94, 35.65) Vanadium (μg/g) Aromatic hydrocarbon solvents 0.072 0.040 Non exposed 0.020 (0.017, 0.025) 0.020 (0.017, 0.025) Exposed 0.032 (0.021, 0.049) 0.034 (0.022, 0.052) aGM: Adjusted geometric mean. a Each Model I is adjusted for age and sex. b Each Model II is adjusted for age, sex and total intake (Kcal). c Further adjusted for tobacco smoking (ever/never), and in each Model II also for intake of fresh vegetables and fruit (low, medium and high intake). d The classification includes exposure to organochlorine and arsenical pesticides. e Further adjusted for tobacco smoking (ever/never), and in each Model II also for intake of fish and shellfish (low, medium and high intake). f In each Model II further adjusted for intake of milk, dairy products and butter (low, medium and high intake). g In each Model II further adjusted for intake of fruit (low, middle and high intake). AHs are found in numerous products (Sexton and Hattis, 2007). In a chemical compounds, including trace metals (MacBean, 2012; Sexton previous analysis of our study, occupations involving use of solvents and Hattis, 2007). Almost all phosphate fertilisers produced from included farmers, machine and engine mechanics, sheet-metal workers, phosphate rock contain traces of cadmium (Cupit et al., 2002; de Meeûs service station attendants, machine-tool setters, and painters (Alguacil et al., 2002). However, there are no data about cadmium concentra- et al., 2000). In the present report, patients occupationally exposed to tions in farmers or other exposed populations. Glyphosate-based her- AHs had significantly higher concentrations of cadmium, manganese, bicide mixtures may contain arsenic, chromium, cobalt, lead and nickel lead, iron, and vanadium. (Defarge et al., 2018). Among subjects exposed to pesticides we observed higher levels of Manganese ethylenebis (maneb) is widely used as fungicide and its cadmium and manganese. Pesticide mixtures can contain different toxicity is well known (Houeto et al., 1995). However, there are no 221 J. Camargo, et al. Environment International 127 (2019) 216–225 Table 4 Trace element concentrations (μg/g) by occupational exposure assessed by Finnish job-exposure matrix (Finjem). Trace element concentration (μg/g) Chlorinated hydrocarbon Formaldehyde Volatile sulphur solvents compounds Exposed Non-exposed Exposed Non-exposed Exposed Non-exposed (N = 7) (N = 107) p-Value (N = 8) (N = 106) p-Value (N = 18) (N = 96) p-Value Cadmium Mean ± standard deviation 0.077 ± 0.119 0.105 ± 0.444 0.870a 0.067 ± 0.075 0.106 ± 0.446 0.805a 0.072 ± 0.098 0.109 ± 0.468 0.736a Median 0.024 0.031 0.583b 0.028 0.030 0.903b 0.031 0.029 0.647b Lead Mean ± standard deviation 23.68 ± 58.72 1.36 ± 2.52 0.353a 20.91 ± 54.92 1.36 ± 2.54 0.348a 9.95 ± 36.69 1.38 ± 2.58 0.336a Median 1.13 0.870 0.126b 1.52 0.863 0.067b 0.778 0.898 0.777b Selenium Mean ± standard deviation 0.531 ± 0.093 0.515 ± 0.114 0.712a 0.557 ± 0.126 0.513 ± 0.112 0.288a 0.543 ± 0.104 0.511 ± 0.114 0.269a Median 0.501 0.515 0.948b 0.512 0.513 0.587b 0.522 0.513 0.423b Chromium Mean ± standard deviation 0.851 ± 0.627 1.15 ± 3.24 0.811a 0.830 ± 0.677 1.15 ± 3.25 0.782a 1.32 ± 2.02 1.09 ± 3.31 0.781a Median 0.782 0.394 0.222b 0.724 0.400 0.399b 0.642 0.363 0.071b Manganese Mean ± standard deviation 0.510 ± 0.386 0.489 ± 0.792 0.945a 0.479 ± 0.384 0.491 ± 0.795 0.965a 0.706 ± 0.789 0.450 ± 0.767 0.197a Median 0.375 0.200 0.082b 0.318 0.203 0.166b 0.381 0.188 0.018b Aluminium Mean ± standard deviation 11.15 ± 4.55 14.68 ± 19.30 0.631a 11.59 ± 4.46 14.68 ± 19.39 0.655a 22.42 ± 30.89 12.97 ± 15.26 0.220a Median 13.43 7.57 0.583b 13.47 7.55 0.405b 12.54 7.42 0.192b Iron Mean ± standard deviation 24.11 ± 10.34 36.97 ± 159 0.831a 19.46 ± 9.79 37.44 ± 159 0.751a 31.35 ± 34.06 37.08 ± 167 0.885a Median 22.46 12.68 0.076b 18.19 12.86 0.351b 16.98 12.68 0.181b Vanadium Mean ± standard deviation 0.048 ± 0.023 0.040 ± 0.084 0.801a 0.045 ± 0.022 0.040 ± 0.084 0.863a 0.058 ± 0.070 0.037 ± 0.084 0.300a Median 0.037 0.019 0.013b 0.034 0.019 0.014b 0.031 0.019 0.033b a Student's t-test (two-tail). b Mann-Whitney's U test (two-tail). reports on the relationship between maneb exposure and manganese knowledge there are no epidemiologic studies showing an association body concentrations. There is a large amount of literature on occupa- between copper and EPC; thus, there is a need to clarify the role of this tional exposure to aluminium phosphide, but there are no reports of an trace element in EPC risk, as well as its association with exposure to association between aluminium phosphide exposure and aluminium chlorinated hydrocarbon solvents (Lener et al., 2016; Manousos et al., body concentrations (Sudakin, 2005). Further research should clarify 1981). the possible role of manganese and aluminium in EPC risk, mediated Occupational environments are usually characterized by exposure and unmediated by exposure to pesticides. to complex chemical mixtures rather than to single agents, potentially Formaldehyde is used mainly in the production of various resins, as leading to combined and cumulative toxic exposures. Knowledge on an intermediate in the manufacture of industrial chemicals, and as a how best monitor complex exposures is limited and, in this sense, the disinfectant and preservative in many applications (IARC, 2012). It is findings here reported suggest possible pathways connecting exposures an established human carcinogen for cancer of the nasal passages and to chemical mixtures and pathological effects (Silins and Högberg, leukaemia (IARC, 2012), and there is evidence that it also causes a 2011). The variety of occupational instruments is a strength of the modest increase of EPC risk (Collins et al., 2001; Maisonneuve and study. ISCO is a standard international classification that allows com- Lowenfels, 2015). EPC patients with occupational exposure to for- parison with past and future similar studies from other countries. It maldehyde had significantly higher levels of arsenic, lead and vana- captures exposures related to all tasks performed by a given occupation. dium. We previously found an association between arsenic and lead and Finjem is a job exposure matrix that captures exposure to 21 selected EPC risk (Amaral et al., 2012). exposures starting with a low probability (5%) of exposure to each Cases that performed occupations with a risk of exposure to volatile agent. Hence, it is a rather sensitive approach. The evaluation by in- sulphur compounds had significantly higher concentrations of vana- dustrial hygienists focused on 22 suspected carcinogens, and the as- dium and manganese. Such compounds are found in a myriad of che- signment of exposure to each exposure needed high evidence of the mical products. Exposed workers are most common in chemical and presence of the exposure; thus, it can be considered a more specific metal plating industry plants, where sulphur compounds occur as a by- exposure metric (Alguacil et al., 2000, 2003). product; e.g., in the copper smelting industry and in the processing or Even though the study sample was small, it adds important in- burning of coal or oil (Amaral et al., 2012). In a previous analysis of our formation to the body of knowledge on the possible contribution of study, an association was apparent for volatile sulphur compounds and trace elements to the aetiology of EPC, as previous studies rarely in- EPC (Alguacil et al., 2000). cluded biomarkers of exposure (Amaral et al., 2012; Collins et al., 2001; Significantly higher levels of lead, vanadium and copper were ob- Luckett et al., 2012). Only two other studies used an exposure bio- served in EPC patients who had worked in occupations associated with marker for cadmium to assess the role of an occupational exposure in a risk of exposure to chlorinated hydrocarbon solvents. They are usually EPC (Barone et al., 2016; Kriegel et al., 2006). In contrast, we examined released to the environment during the formulation process and several trace elements. Ours is the first study to analyse the relationship through their use in some formulated products such as pesticides. between concentrations of trace elements and occupational history in Chlorinated hydrocarbon solvents are considered a major occupational any human cancer. risk factor for EPC (Antwi and Eckert, 2015; Bosch de Basea et al., 2011; An increased risk of EPC has been associated with exposure to Maisonneuve and Lowenfels, 2015; Ojajärvi et al., 2000). To our chromium and nickel (Antwi and Eckert, 2015; Ojajärvi et al., 2000). 222 J. Camargo, et al. Environment International 127 (2019) 216–225 Table 5 Influence on trace element concentrations (μg/g) in pancreatic cancer patients by occupational exposure assessed by the Finnish job-exposure matrix (Finjem). Trace element Exposure Model Ia p-Value Model IIb p-Value aGM (95% CI) aGM (95% CI) c Lead (μg/g) Chlorinated hydrocarbon solvents 0.003 0.004 Non exposed 0.801 (0.660, 0.973) 0.804 (0.665, 0.973) Exposed 2.80 (1.29 6.08) 2.64 (1.22, 5.72) Formaldehyde 0.002 0.003 Non exposed 0.794 (0.653, 0.964) 0.797 (0.659 0.964) Exposed 2.72 (1.32, 5.62) 2.58 (1.25, 5.31) Any pesticide 0.060 0.085 Non exposed 0.835 (0.686, 1.02) 0.838 (0.692, 1.015) Exposed 2.30 (0.816, 6.49) 2.09 (0.751, 5.84) Manganesed (μg/g) Volatile sulphur compounds 0.027 0.027 Non exposed 0.233 (0.190, 0.286) 0.234 (0.191, 0.286) Exposed 0.421 (0.261, 0.678) 0.417 (0.261, 0.667) Vanadium (μg/g) Chlorinated hydrocarbon solvents 0.050 0.039 Non exposed 0.021 (0.018, 0.026) 0.021 (0.018, 0.026) Exposed 0.045 (0.022, 0.094) 0.047 (0.023, 0.097) Formaldehyde 0.055 0.041 Non exposed 0.021 (0.018, 0.026) 0.021 (0.018, 0.026) Exposed 0.043 (0.022, 0.084) 0.045 (0.023, 0.088) Volatile sulphur compounds 0.043 0.048 Non exposed 0.021 (0.017, 0.025) 0.021 (0.017, 0.025) Exposed 0.034 (0.022, 0.054) 0.034 (0.022, 0.053) Arsenice (μg/g) Formaldehyde 0.008 0.017 Non exposed 0.075 (0.066, 0.085) 0.075 (0.067, 0.085) Exposed 0.143 (0.091, 0.226) 0.137 (0.086, 0.218) Polycyclic aromatic hydrocarbons 0.024 0.024 Non exposed 0.075 (0.067, 0.085) 0.075 (0.067, 0.085) Exposed 0.128 (0.082, 0.199) 0.128 (0.083, 0.198) Copperf (μg/g) Chlorinated hydrocarbon solvents 0.048 0.077 Non exposed 3.65 (3.37, 3.95) 3.66 (3.38, 3.95) Exposed 5.08 (3.70, 6.98) 4.91 (3.58, 6.74) Zincg (μg/g) Any pesticide 0.003 0.007 Non exposed 113.4 (107.7, 119.5) 113.6 (107.9, 119.6) Exposed 174.5 (132.7, 229.3) 167.6 (127.2, 220.8) aGM: Adjusted geometric mean. a Each Model I is adjusted for age and sex. b Each Model II is adjusted for age, sex and total intake (Kcal). c Further adjusted for tobacco smoking (ever/never), and in each Model II also for intake of fish and shellfish (low, medium and high intake). d In each Model II further adjusted for intake of milk, dairy products and butter (low, medium and high intake). e In each Model II further adjusted for intake of butter (low, medium and high intake). f In each Model II further adjusted for intake of oil in two categories. g In each Model II further adjusted for intake of fish and shellfish (low, middle and high intake). We did not find differences in toenail concentrations of these elements past. Metals in nails come from metabolic processes after formation and among subjects with different historical occupational exposures (Sup- thus may be stable markers of past exposure (Hopps, 1977). In our plemental Figs. 1 and 2); e.g., patients with past occupations that po- study, a large number of cases were interviewed and had toenail sam- tentially entailed exposure to chromium and nickel had similar con- ples drawn soon after their cancer diagnosis. Lack of differences be- centrations of these metals than unexposed patients. One explanation is tween patients included and excluded in the study further argues that no actual exposure to chromium and nickel occurred; hence, ex- against selection bias (Hoppin et al., 2002). posure to these metals can be misclassified by studies that rely on oc- In summary, the present study identifies occupational sources of cupational titles and do not use biomarkers. Another possibility con- trace elements; strictly, just in EPC, although the processes may be si- cerns the chemical and oxidative state of the metals, which can affect milar in other diseases. The study also makes a relevant contribution by whether they accumulate inside the body or instead are eliminated assessing the extent to which trace elements may explain some occu- (WHO, 2006). pational risks previously observed for pancreatic cancer. Lipid mobilization and the other metabolic changes that commonly characterize progression of pancreatic cancer (Gasull et al., 2019; Porta et al., 2008b) are unlikely to have had an influence on toenail levels of 5. Conclusions the trace elements. Unlike blood and urine, hair and nail samples reflect the concentration of elements in the organism over several months, and Higher toenail concentrations of several metals were observed in are thus useful for the evaluation of long term exposure (Golasik et al., patients occupationally exposed to AHs, pesticides, chlorinated hydro- 2015). Trace elements in nails are incorporated during their formation carbon solvents, formaldehyde, volatile sulphur compounds, and PAHs. (12–18 months) from blood, lymph vessels, body tissues and epidermis; The findings suggest that these elements may account for some of the thus, they reflect exposures that have occurred in such months (Goyer occupational risks previously reported for EPC. Results also show oc- and Clarkson, 2001; Hopps, 1977; Slotnick and Nriagu, 2006). How- cupations likely to be a source of exposure to metals. Biomarkers of ever, the rationale for their use in studies on disease aetiology is that exposure to trace elements may help understand the role of chemical the ranking of toenail concentrations in a group of individuals at one mixtures in the aetiology of EPC and, potentially, of other diseases. point in time will be highly similar to the ranking in the more distant 223 J. Camargo, et al. Environment International 127 (2019) 216–225 Declarations of interest 156–163. Fritschi, L., Benke, G., Risch, H.A., Schulte, A., Webb, P.M., Whiteman, D.C., et al., 2015. Occupational exposure to N-nitrosamines and pesticides and risk of pancreatic The authors declare no competing interests. cancer. Occup. Environ. Med. 72, 678–683. Gasull, M., Pumarega, J., Kiviranta, H., Rantakokko, P., Raaschou-Nielsen, O., Bergdahl, I. Funding A., et al., 2019. Methodological issues in a prospective study on plasma concentra- tions of persistent organic pollutants and pancreatic cancer risk within the EPIC co- hort. Environ. Res. 169, 417–433. This work was partly supported by research grants from Instituto de Gasull, M., Porta, M., Pumarega, J., Vioque, J., Bosch de Basea, M., Puigdomènech, E., Salud Carlos III, Ministry of Health, Government of Spain (FIS PI13/ et al., 2010. The relative influence of diet and serum concentrations of organo- chlorine compounds on K-ras mutations in exocrine pancreatic cancer. Chemosphere 00020, FIS PI17/00088, and CIBER de Epidemiología y Salud Pública - 79, 686–697. CIBERESP); the Hospital del Mar Medical Research Institute (IMIM), Golasik, M., Przybylowicz, A., Wozniac, A., Herman, M., Gawęcki, W., Golusiński, W., Barcelona; Fundació La Marató de TV3 (20132910); and the et al., 2015. Essential metals profile of the hair and nails of patients with laryngeal cancer. J. Trace Elem. Med. Biol. 31, 67–73. 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