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Review Occupational Benzene Exposure and the Risk of Lymphoma Subtypes: A Meta-analysis of Cohort Studies Incorporating Three Study Quality Dimensions Jelle Vlaanderen,1 Qing Lan,2 Hans Kromhout,1 Nathaniel Rothman,2* and Roel Vermeulen1* 1Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands; 2Division of Cancer Epidemiology and Genetics, National Cancer Institute, Department of Health and Human Services, National Institutes of Health, Bethesda, Maryland, USA Background: The use of occupational cohort studies to assess the association of benzene and lymphoma is complicated by problems with exposure misclassification, outcome classification, and low statistical power. Objective: We performed meta-a nalyses of occupational cohort studies for five different lymphoma categories: Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), multiple myeloma (MM), acute lymphocytic leukemia (ALL), and chronic lymphocytic leukemia (CLL). Data extraction: We assessed three study quality dimensions to evaluate the impact of study quality variations on meta-relative risks (mRRs): stratification by the year of start of follow-up, stratification by the strength of the reported acute myelogenous leukemia association, and stratification by the quality of benzene exposure assessment. Data synthesis: mRRs for MM, ALL, and CLL increased with increasing study quality, regardless of the study quality dimension. mRRs for NHL also increased with increasing study quality, although this effect was less pronounced. We observed no association between occupational benzene exposure and HL. Conclusions: Our meta-analysis provides support for an association between occupational benzene exposure and risk of MM, ALL, and CLL. The evidence for an association with NHL is less clear, but this is likely complicated by the etiologic heterogeneity of this group of diseases. Further consideration of the association between benzene and NHL will require delineation of risks by NHL subtype. Key words: acute lymphocytic leukemia, benzene, chronic lymphocytic leukemia, Hodgkin lymphoma, leukemia, meta-analysis, multiple myeloma, non-Hodgkin lymphoma, occupational exposure. Environ Health Perspect 119:159167 (2011). doi:10.1289/ehp.1002318 [Online 29 September 2010] The International Agency for Research on Cancer (IARC) classified benzene as a group 1 carcinogen (carcinogenic to humans) in its 1982 and 1987 evaluations (IARC 1982, 1987) based primarily on reports of an association between occupational exposure to benzene and leukemia, particularly acute nonlymphocytic leukemia (ANLL), which consists primarily of acute myelogenous leukemia (AML). Recently, IARC updated its previous reviews of several chemicals and occupational exposure circumstances, including benzene, to reassess carcinogenicity and to consider potential associations with additional tumor sites (Baan et al. 2009). In that review, IARC determined for the first time that in addition to the confirmed association with ANLL, there was also limited evidence that benzene causes acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), non-Hodgkin lymphoma (NHL), and multiple myeloma (MM) in humans (Baan et al. 2009). At the same time, in recent years, there has been a plethora of reviews and meta-a nalyses of benzene and one or more lymphoid neoplasms, at times reaching diametrically opposed conclusions (Alexander and Wagner 2010; Bergsagel et al. 1999; Infante 2006; Kane and Newton 2010; Lamm et al. 2005; Savitz and Andrews 1997; Schnatter et al. 2005; Smith et al. 2007; Sonoda et al. 2001; Steinmaus et al. 2008; Wong and Fu 2005; Wong and Raabe 1995, 1997, 2000a, 2000b). There are two fundamental challenges in using the large number of occupational cohort studies that have been published over the last 30 or so years when considering the relationship between occupational benzene exposure and the risk of lymphoid neoplasms. First, there have been substantial changes in testing procedures, diagnostic criteria, and categorization of lymphoid neoplasms over the last halfcentury (Aisenberg 2000; Harris et al. 2000; Linet et al. 2007; Morton et al. 2007), the time period in which follow-up of these occupational cohorts took place. Indeed, diagnostic criteria that were used in these cohort studies were based on a range of classification strategies, including the International Classification of Diseases (ICD), Revisions 79, and ICD for Oncology, Revision 3 (ICD-O3) (World Health Organization 1955, 1965, 1975, 2000). The changing views on the categorization of lymphoid neoplasms is illustrated by the current categorization of ALL and CLL as subtypes of NHL in the most recent World Health Organization disease classification (Swerdlow et al. 2008), although these entities have been reported separately from NHL in essentially all occupational cohort studies of benzene-exposed workers. Second, there is heterogeneity in occupational cohort studies with regard to industry, sample size, documentation and level of benzene exposure, and documentation of the percentage of a given cohort that had true, nontrivial exposure to benzene. Inadequate documentation, uncertain quality of follow-up, and, most problematic, potential inclusion of "unexposed" workers in "exposed" categories would have likely resulted in attenuation of the observed associations. Further, for the purpose of reviews or meta-a nalyses, it can be challenging to separate informative from potentially noninformative cohorts in the face of uncertain documentation of key epidemiological study design and exposure assessment characteristics. Given the changing nature of the diagnosis of lymphoid neoplasms over time and the heterogeneity of occupational benzene cohort study quality in the literature, it is a challenge to discern the nature of the relationship between benzene and lymphoid neoplasms. To address this issue, we developed three strategies that we employ in a set of metaanalyses of occupational cohort studies for five lymphoma categories defined according to ICD-9: Hodgkin lymphoma (HL; ICD-9 code 201), NHL (ICD-9 200, 202), MM (ICD-9 203.0), ALL (ICD-9 204.0), and CLL (ICD-9 204.1). We applied the first strategy to assess the potential impact of the gradual increase in the quality of hematologic diagnoses over the last decades. This strategy involved stratification of the studies in the meta-analyses based on the reported start of follow-up. We used the year 1970 as a cutoff point for stratification (approximate midpoint of follow-up of all studies included in this analysis). We based the second strategy on the established strong Address correspondence to R. Vermeulen, Institute for Risk Assessment Sciences, Division Environmental Epidemiology, Jenalaan 18d, 3584 CK, Utrecht, the Netherlands. Telephone: 31-30-2539448. Fax: 31-30-2539499. E-mail: R.C.H.Vermeulen@uu.nl Supplemental Material is available online (doi:10. 1289/ehp.1002318 via http://dx.doi.org/). *These authors are co-senior authors. This work was performed as part of the work package "Integrated Risk Assessment" of the Environmental Cancer Risk, Nutrition, and Individual Susceptibility Network of Excellence, operating within the European Union 6th Framework Program, Priority 5: "Food Quality and Safety" (FOOD-CT-2005-513943). The authors declare they have no actual or potential competing financial interests. Received 20 April 2010; accepted 29 September 2010. Environmental Health Perspectives volume 119 | number 2 | February 2011 159 Vlaanderen et al. association between benzene and AML. We argue that any study that was not able to detect at least a suggestive association between benzene and AML most likely had serious methodologic limitations in one or more aspects of study design. Examples of possible limitations are trivial exposure to benzene in the studied cohort, inclusion of "unexposed" workers in "exposed" categories or flaws in the assessment (or categorization) of health effects (Goldstein and Shalat 2000). Therefore, we used the direction and significance level of a reported association between benzene and AML as proxies for the overall study quality (AML significance level). We based the third strategy on the evaluation of the quality of the exposure assessment carried out in each cohort. High-quality exposure assessment is essential to discriminate exposed individuals from nonexposed individuals (Vlaanderen et al. 2008). We assigned an exposure assessment quality classification to each study based on an a priori defined classification scheme and used this classification as an additional proxy of study quality, reasoning that those cohort studies with the highest quality exposure assessment had the greatest ability to identify and include workers who were truly exposed to benzene in their analyses. We hypothesized that application of the three study quality dimensions--stratification based on the start of follow-up, AML significance level, and exposure assessment quality-- would identify a subgroup of occupational cohort studies that is most informative for the evaluation of the possible association between benzene and lymphoid neoplasms. Materials and Methods Study identification and data extraction. We conducted a search of PubMed (http:// www.ncbi.nlm.nih.gov/sites/entrez) using the key words "benzene" and "cohort" or "case control." We included publications in the meta-analysis if they were published in the peerreviewed literature, reported results for any of the five lymphoma subtypes (HL, NHL, MM, ALL, and CLL), and were conducted in the occupational setting. We checked references in all identified publications for additional studies. When more than one paper was published on the same cohort, we chose the publication with the highest quality exposure assessment [e.g., in the Australian petroleum workers cohort for AML, we chose the nested casecontrol study that included an elaborated exposure assessment approach (Glass et al. 2003) over a more recent update on the full cohort that included no detailed benzene exposure assessment (Gun et al. 2006)]. When multiple publications with similar quality of exposure assessment were published on the same cohort, we chose the most recent update (with the longest follow-up time). In this meta-analysis, we pooled risk ratios, odds ratios (ORs), and standardized mortality ratios (SMRs). ORs and SMRs can be interpreted as reasonable approximations of the risk ratio when the disease is rare, and these measures have been pooled with risk ratios for meta-analyses before (McElvenny et al. 2004). We use the term "relative risk" (RR) to refer to the risk ratio, the OR, or the SMR. We extracted RRs based both on incidence and mortality. However, if a publication reported both, we chose incidence over mortality in the meta-a nalysis. Risk estimates. To allow the inclusion of studies without quantitative exposure assessment in our analysis, we used only RRs for "any occupational benzene exposure" versus "background benzene exposure" in the metaanalyses. If publications reported only RRs stratified for cumulative exposure and not for "any occupational benzene exposure" versus "background benzene exposure," we pooled RRs by summing observed and expected cases for studies that reported SMRs (percentage of RRs: AML, 4.8%; HL, 3.7%; NHL, 3.0%; MM, 3.8%; CLL, 5.6%) or by conducting a within-study random-effects meta-analysis of the nonreference exposure groups for studies that reported RRs or ORs (percentage of RRs: AML, 14.3%; NHL, 3.0%; MM, 7.7%; ALL, 5.9%; CLL, 16.7%). If publications reported only observed and expected number of cases and no RRs, we calculated RRs and estimated associated confidence intervals (CIs) with mid-P exact (Rothman and Boice 1979) (percentage of RRs: AML, 4.8%; HL, 7.4%; ALL, 17.6%). For publications that reported no observed cases for any of the lymphoma subtypes, we calculated continuity corrected RRs (observed and expected number of cases plus one) and we estimated associated CIs with mid-P exact (percentage of RRs: ALL, 11.8%; HL, 11.1%). If studies reported zero for the lower CI, we imputed a value of 0.1 to allow estimation of the variance (percentage of RRs: ALL, 5.9%; MM, 3.8%). Three strategies for the assessment of study quality dimensions. We stratified by the year of start of follow-up based on the information provided in the included publications (follow-up started before 1970 vs. follow-up started in or after 1970). The median start of follow-up in the stratum with studies that started follow-up before 1970 was 1947, and the median start of follow-up in the stratum with studies that started follow-up in 1970 or after was 1973. We assigned AML significance level to each publication based on a two-sided p-value of the z-score, which we estimated by dividing the reported log RR for AML by its standard error. Based on the calculated AML significance level, we assigned one of the following categories (AE) to each publication: A, AML RR > 1, p < 0.1; B, AML RR > 1, 0.1 p < 0.2; C, AML RR > 1, p 0.2; D, AML RR 1; E, no AML RR reported. We assigned quality of exposure assessment (AD) to each publication as follows: A, in the publication explicit quantitative exposure estimates for benzene were reported; B, in the publication semiquantitative estimates of benzene exposure or quantitative estimates of exposures containing benzene (e.g., gaso line) were reported; C, in the publication some industrial hygiene sampling results to indicate that benzene exposure was present in the cohort that was studied were reported; D, the publication qualitatively indicated that benzene exposure was present in the cohort. Statistical analyses. We conducted randomeffects meta-analyses to pool the RRs reported in the included publications. We used an of 0.05 to assess whether meta-relative risks (mRRs) were significantly elevated. We conducted the first set of meta-a nalyses on the full set of studies stratified for the start of follow-up (follow-up started before 1970 vs. follow-up started in or after 1970). We compared mRRs by strata using a test of interaction as suggested by Altman and Bland (2003). We applied the study quality dimensions of AML significance level and quality of exposure assessment in two series of meta-a nalyses. The initial analysis in each series included all studies regardless of quality. In each subsequent analysis, we excluded the group of studies with the lowest AML significance level or the lowest quality of exposure assessment. We used Cochran's Q-test to assess between study heterogeneity in all metaanalyses. A p-value < 0.1 was considered to be statistically significant evidence for between study heterogeneity. We used I2 to describe the percentage of total variation across studies that was due to heterogeneity rather than chance (Higgins et al. 2003). For analyses that displayed significant between study heterogeneity, we assessed the sensitivity of the outcome of the meta-a nalysis for individual studies by excluding studies one at the time (jackknife analysis). We assessed publication bias with Eggers graphical test (Egger et al. 1997). We performed all meta-analyses in Stata (version 11; StataCorp LP, College Station, TX, USA). Results We identified 44 publications that provided an RR for at least one of the lymphoma subtypespecific meta-a nalyses. We did not extract data from three publications: one study with likely underascertainment of cancer deaths as the result of the inability to identify the type of cancer for a number of cancer deaths (Infante 2005; Sorahan et al. 2005); one study for which we could not estimate the RR variance [a nested casecontrol study 160 volume 119 | number 2 | February 2011 Environmental Health Perspectives Occupational benzene and lymphoma subtypes that did not report CIs (Ott et al. 1989)]; and one study that reported proportionate mortality ratios, which tend to underestimate the RR (Thomas et al. 1982). Table 1 lists all publications that contributed to the metaanalyses, their (assigned) cohort name, the (assigned) name of the subcohort (if relevant), the literature reference, the type of industry in which the study was performed, the follow-up period, the lymphoma subtype for which the publication was included (if reported with ICD code and revision), an indicator of whether RRs were based on incidence or mortality, the assigned AML significance level, and the assigned quality of exposure assessment. The earliest included publication dates from 1983, and the most recent publication was from 2008. For two cohorts we used nonpeer-reviewed publications to extract RRs for MM (and NHL) that were not reported in the peer-reviewed publications (Atkinson et al. 2001; Delzell E, Sathiakumar N, Cole P, Brill I, unpublished report). Both reports were based on the exact same methodology and follow-up time as reports of these cohorts that appeared in the peer-reviewed literature (Glass et al. 2003; Sathiakumar et al. 1995). We included an RR for MM from a study by Decoufle et al. (1983) based on additional information that was reported in the preamble to the final Occupational Safety and Health Administration (OSHA) benzene standard of 1987 (OSHA 1987). We extracted NHL Table 1. Overview of publications included in the meta-a nalyses. Cohort Australian petroleum workers cohort Australian petroleum workers cohort Australian petroleum workers cohort Beaumont, Texas, petroleum refinery cohort Canadian petroleum company cohort Canadian petroleum company cohort Caprolactam workers Conoco chemical plant cohort Dow cohort Subcohort Reference Industry Atkinson et al. Petroleum industry 2001f Glass et al. 2003 Petroleum industry Gun et al. 2006 Petroleum industry Wong et al. Petroleum industry 2001a Schnatter et al. Petroleum industry 1996 Lewis et al. 2003 Petroleum industry Swaen et al. 2005 Decoufle et al. 1983 Bloemen et al. 2004 Chemical industry Chemical industry Chemical industry Exxon cohort Louisiana Huebner et al. Petroleum industry 2004 Exxon cohort Texas Huebner et al. Petroleum industry 2004 Finnish oil refinery workers French gas and electric utility workers Italian oil refinery Martinez and Wilmington refinery and petrochemical plants, California Monsanto cohort NCI-CAPM NCI-CAPM Norway upstream petroleum industry Paulsboro, New Jersey, refinery (Mobil) Petrochemical workers, Texas City, Texas Petroleum manufacturing plant, Illinois, USA (Shell) Petroleum manufacturing plant, Illinois, USA (Shell) Pliofilm cohort Pliofilm cohort Port Arthur, Texas, refinery workers Pukkala 1998 Guenel et al. 2002 Consonni et al. 1999 Tsai et al. 1993 Petroleum industry Gas and electric utility industry Petroleum industry Petroleum industry Collins et al. Chemical industry 2003 Yin et al. 1996 Multiple industries Hayes et al. Multiple industries 1997 Kirkeleit et al. Petroleum industry 2008 Collingwood Petroleum industry et al. 1996 Waxweiler et al. Petroleum industry 1983 McCraw et al. Petroleum industry 1985 Honda et al. Petroleum industry 1995 Wong 1995 Chemical industry Rinsky et al. 2002 Chemical industry Satin et al. 1996 Petroleum industry Follow-up period 19801998 Included for outcomes (ICDa) MM (203) AML Exposure ICD significance assessment revisiona,b I/Mc leveld qualitye 9I C A 19801998 AML (205.0, 208.0), CLL (204.1) 9I C A 19811999 ALL (204.0), NHL (200202) 9I C D 19451996 ALL (204.0), AML (205.0), CLL (204.1), MM (203), NHL (200, 202), HL (*) 19641983 MM (203), NHL (200, 202.0, 202.1, 202.2, 202.9) 19641994 ALL (204.0), AML (205.0), CLL (204.1), HL (201) 19512001 MM (31), HL (29) 8 8 9 B M M I M C E D E D A D A 19471977 MM (*) 8M E D 19401996 AML (205.0, 206.0, 207.0), CLL (204.1), MM (203), NHL (200.0200.8, 202.0, 202.8), HL (201) 19701997 ALL (204.0), AML (205.0, 206.0, 207.0, 207.2), CLL (204.1), MM (203.0), NHL (200.0200.2, 200.8, 202.0202.2, 202.8202.9), HL (201) 19701997 ALL (204.0), AML (205.0, 206.0, 207.0, 207.2), CLL (204.1), MM (203.0), NHL (200.0200.2, 200.8, 202.0202.2, 202.8202.9) HL (201) 19671994 NHL (*), HL (*) 19781989 ALL (*), AML (*), CLL (*) 9 9 9 (*) O M M M I I C B A E D A D D D B 19491991 NHL (200, 202), HL (201) 8M E D 19731989 NHL (200), HL (201) 8M E D 19401999 AML (205.0, 206.0), CLL (204.1), MM (203), NHL (200, 202), HL (201) 19721987 ALL (*), MM (*) 19721987 AML (205.0, 206.0, 207.0), NHL (200, 202) 19812003 ALL (*), AML (*), CLL (*), MM (*), NHL (*), HL (*) 19461987 NHL (200), HL (201) 19411977 NHL (200), HL (201) 19731982 ALL (*), AML (*), CLL (*) 19401989 NHL (*), HL (*) 19401987 19501996 19371987 AML (C) NHL (C), MM (C) ALL (204.0), AML (205.), CLL (204.1), MM (203), NHL (200, 202), HL (201) 8 9 9 7 8 7 8 9 C C 8 MA A IA IA A A IA D ME D ME D MA D ME D MA ME MD A A D continued next page Environmental Health Perspectives volume 119 | number 2 | February 2011 161 Vlaanderen et al. RRs for two studies by Wong and colleagues (Wong 1987a; Wong et al. 1993) from Wong (1998), a letter that provided results from additional analyses for these studies. Finally, there might have been a slight (nonidentifiable) overlap in the cohorts studied by Wong (1987a, 1987b) and Collins et al. (2003). Table 2 shows the mRR based on randomeffect meta-analyses for all studies and stratified by start of follow-up for AML and the five lymphoma subtypes (i.e., HL, NHL, MM, ALL, and CLL). The overall mRRs (95% CIs) for AML and ALL were significantly increased [mRR = 1.68 (1.352.10) and mRR = 1.44 (1.032.02), respectively]. The overall mRR for MM and CLL were slightly but not significantly elevated, whereas the overall mRRs for HL and NHL were close to unity. Stratified analyses by start of follow-up showed higher RRs for AML, NHL, and CLL for studies with a follow-up starting in or after 1970 than for studies that started the follow-up before 1970 (p < 0.10). We observed no significant difference in mRR between the follow-up strata for HL, MM, and ALL. We observed significant between-study heterogeneity for AML, NHL, and CLL overall and in the studies with start of follow-up before 1970 [see Supplemental Material, Figure 1 (doi:10.1289/ehp.1002318)]. Exclusion of the most influential studies/RRs (based on the distance of the RR to the mRR and the weight of the study) resulted in mRRs that were essentially similar (data not shown). Table 3 shows mRRs based on randomeffects meta-analyses stratified by AML significance level for AML, HL, NHL, MM, ALL, and CLL. As could be expected, the lymphoma mRRs based on only the studies that Table 1. continued Cohort Subcohort Reference Industry Follow-up period Included for outcomes (ICDa) AML Exposure ICD significance assessment revisiona,b I/Mc leveld qualitye Richmond and El Segundo refineries Sample of U.S. refineries Service station workers in Nordic countries Shell Deer Park refinery Shell Louisiana refinery Shoe workers cohort Shoe workers cohort Swedish seamen working on product or chemical tankers Texaco crude oil workers Texaco mortality study Texaco mortality study Torrance, California, petroleum refinery U.K. oil distribution and oil refinery workers U.K. oil distribution and oil refinery workers U.K. oil distribution and oil refinery workers U.K. oil distribution and oil refinery workers U.K. oil distribution and oil refinery workers Union Oil Company cohort Union Oil Company cohort Union Oil Company cohort U.S. chemical workers U.S. chemical workers U.S. chemical workers U.S. gasoline distribution employees U.S. gasoline distribution employees U.S. gasoline distribution employees Dagg et al. 1992 Petroleum industry Italian cohort U.K. cohort Kaplan 1986 Petroleum industry Lynge et al. 1997 Service station workers Tsai et al. 1996 Petroleum industry Tsai et al. 2003 Petroleum industry Fu et al. 1996 Shoe workers Fu et al. 1996 Nilsson et al. 1998 Shoe workers Petroleum tanker workers Divine and Petroleum workers Hartman 2000 Divine et al. Petroleum industry 1999a Divine et al. Petroleum industry 1999b Wong et al. Petroleum industry 2001b Refinery Rushton 1993 Petroleum industry Distribution Rushton 1993 Petroleum industry Refinery Rushton and Petroleum industry Romaniuk 1997 Sorahan 2007 Petroleum industry Distribution Sorahan 2007 Petroleum industry Oil and gas Delzell et al. division 1992f Refining Delzell et al. division 1992f Oil and gas Sathiakumar division et al. 1995 Wong 1987a Wong 1987b Wong 1998 Land based Wong et al. 1993 Marine Wong et al. 1993 Land based Wong 1998 and marine Petroleum industry Petroleum industry Petroleum industry Chemical industry Chemical industry Chemical industry Petroleum industry Petroleum industry Petroleum industry 19501986 19721980 19701990 19481989 19731999 19501990 19391991 19711978 19461994 19471993 19471993 19591997 19501989 19501989 19501993 19512003 19512003 19761990 19761990 19761990 19461977 19461977 19461977 19461986 19461986 19461986 NHL (200), HL (201) MM (*), HL (*) AML (*), CLL (*), MM (203), NHL (200, 202), HL (201) NHL (200), HL (201) NHL (200), HL (201) MM (203), NHL (200, 202) MM (203), NHL (200, 202) MM (203), NHL (200, 202), HL (201) ALL (*), AML (*), CLL (*), MM (*), NHL (*), HL (201) HL (201) ALL (*), AML (*), CLL (*), MM (*), NHL (*) ALL (204.0), AML (205.0), CLL (204.1), MM (203), NHL (200, 202), HL (*) ALL ALL AML (*), CLL (*) MM (203), NHL (200, 202), HL (201) MM (203), NHL (200, 202), HL (201) MM (203), NHL (200, 202) MM (203), NHL (200, 202) AML (*) HL (201) MM (203) NHL (200, 202) ALL (*), AML (*), CLL (*) ALL (*), AML (*), CLL (*) NHL (200, 202) 8 (*) 7 8 8 9 9 8 8 8 8 8 A A 9 9 9 9 9 9 8 8 8 8 8 8 M M I M M M M I M M M M M M M M M M M M M M M M M M E E C E E E E E A C C D D C A E E A E A E E E B D C D D C D D D D D D D D D D D A D D D D D A A A B B B NCI-CAPM, National Cancer InstituteChinese Academy of Preventive Medicine. a(*), ICD revision or specific ICD code was not reported. bA, deaths were coded according to a system developed by Statistics Netherlands (CBS); B, deaths were coded according to National Institute for Occupational Safety and Health life-table analysis system death categories; C, deaths were coded according to the ICD in effect at time of death. cI, incidence; M, mortality. dA, AML RR > 1, p < 0.1; B, AML RR > 1, 0.1 p < 0.2; C, AML RR > 1, p 0.2; D, AML RR 1; E, AML RR not reported. eA, quantitative exposure estimates for benzene; B, semiquantitative estimates of benzene exposure or quantitative estimates of exposures containing benzene; C, some industrial hygiene sampling results; D, qualitative indication that benzene exposure had occurred. fNon-peer-reviewed publication. 162 volume 119 | number 2 | February 2011 Environmental Health Perspectives Occupational benzene and lymphoma subtypes reported an RR for AML (AD) are largely similar to the mRRs based on all the studies (AE). These studies therefore provide a relatively unbiased representation of the full set of studies. All outcomes except HL demonstrated an increase in mRRs with increasing AML significance level. However, the 95% CIs successively widened as a result of the reduced number of studies/RRs that were retained with each increase in AML significance level. The increase in mRR was most pronounced for MM and ALL, and somewhat weaker for NHL and CLL. In contrast, the mRR for HL dropped with increasing AML significance level. We observed significant between-study heterogeneity for NHL and CLL in the subset of studies with AML significance level A (p < 0.10) [see Supplemental Material, Figure 2 (doi:10.1289/ehp.1002318)]. Jackknife analysis eliminating one study at the time demonstrated that, in the NHL analysis of the studies with AML significance level A, the RRs from Divine and Hartman (2000) and Delzell et al. (unpublished report) had considerable impact on the between-study heterogeneity. Exclusion of both RRs from this analysis resulted in a slight decrease in the mRR (95% CI) from 1.16 (0.771.76) to 1.12 (0.771.61), with an I2 (an estimate of the percentage of total variation across studies that was due to heterogeneity rather than chance) of 22.8% (p = 0.27). In the CLL analysis of the studies with AML significance level A, the RRs provided by Divine and Hartman (2000) and Rushton and Romaniuk (1997) appeared to be primarily responsible for the observed between-study heterogeneity. Exclusion of both RRs from the meta-a nalysis resulted in a slight decrease in the mRR from 1.39 (0.652.96) to 1.26 (0.652.43), with an I2 of 0% (p = 0.94). Table 4 shows mRRs based on randomeffects meta-a nalyses and stratified by quality of exposure assessment. mRRs for NHL, MM, and CLL increased with increasing quality of exposure assessment. The increase in mRR was most pronounced for MM and CLL. Forest plots for AML and the five lymphoma subtypes for all studies with quality of exposure categories A and B (A, quantitative exposure estimates for benzene; B, semiquantitative estimates of benzene exposure or quantitative estimates of exposures containing benzene) are shown in the Supplemental Material, Figure 3 (doi:10.1289/ ehp.1002318). Jackknife analysis eliminating one study at the time demonstrated that in the set of studies with quality of exposure categories A and B, the RRs provided by Wong et al. (1993) (land-based cohort) and Rushton and Romaniuk (1997) had considerable impact on the observed between-study heterogeneity in the CLL analysis. Exclusion of both RRs from the meta-analysis resulted in a slight decrease in the mRR (95% CI) from 1.54 (0.723.31) to 1.46 (0.792.72), with an I2 of 0% (p = 0.43). The RR provided by Wong (1998) (gasoline distribution employees) had a considerable impact on the observed between study heterogeneity in the NHL analysis of the set of studies in quality of exposure categories A and B. Exclusion of this RR resulted in a slight increase in the mRR from 1.04 (0.631.72) to 1.27 (0.901.79), with an I2 of 0% (p = 0.78). Cross-stratification of AML significance level and quality of exposure assessment with the stratification based on the start of follow-up, although limited by a loss of statistical power, showed that mRR patterns with increasing AML significance level and quality of exposure assessment [see Supplemental Material, Tables 1,2 (doi:10.1289/ehp. 1002318)] were generally consistent with the patterns observed when meta-analyses were stratified by start of follow-up (Table 2). Table 3. mRRs (95% CIs) for AML and five lymphoma subtypes in cohort studies of workers exposed to benzene: stratification by AML significance level. Lymphoma subtype AML significance levela n studies n exposed cases mRR AML AE (all studies) 21 217 1.68 (1.352.10)* AD 21 217 1.68 (1.352.10)* AC 16 192 1.88 (1.562.27) AB 11 132 2.20 (1.772.72) A 9 108 2.48 (1.943.18) HL AE (all studies) 27 146 0.99 (0.831.19) AD 12 69 0.99 (0.771.27) AC 9 39 0.82 (0.591.15) AB 5 7 0.47 (0.220.99) A 4 7 0.50 (0.231.08) NHLb AE (all studies) 33 647 1.00 (0.891.13)* AD 15 383 0.97 (0.811.16)* AC 13 344 0.99 (0.811.21)* AB 7 130 1.21 (0.851.72)* A 6 101 1.16 (0.771.76)* MM AE (all studies) 26 284 1.12 (0.981.27) AD 14 160 1.15 (0.951.40) AC 12 137 1.19 (0.941.49) AB 7 69 1.49 (1.131.95) A 6 56 1.56 (1.112.21) ALL AE (all studies) 17 47 1.44 (1.032.02) AD 17 47 1.44 (1.032.02) AC 11 29 1.41 (0.902.19) AB 7 16 1.74 (0.903.36) A 5 12 1.74 (0.773.90) CLL AE (all studies) 18 111 1.14 (0.781.67)* AD 18 111 1.14 (0.781.67)* AC 13 93 1.19 (0.741.90)* AB 8 57 1.37 (0.732.56)* A 6 45 1.39 (0.652.96)* aA, AML RR > 1, p < 0.1; B, AML RR > 1, 0.1 p < 0.2; C, AML RR > 1, p 0.2; D, AML RR 1; E, AML RR not reported. bNHL or lymphosarcoma/reticulosarcoma (preferred NHL if the study reported both). *Significant evidence for between study heterogeneity (p < 0.1). Table 2. mRRs (95% CIs) for AML and five lymphoma subtypes in cohort studies of workers exposed to benzene: stratification by start of follow-up. Lymphoma subtype n studies All studies n exposed cases mRR Start follow-up before 1970 n exposed mRR (start follow-up n studies cases before 1970) Start follow-up in or after 1970 n exposed mRR (start follow-up n studies cases 1970 and later) Test for difference by follow-up strata (p-value)a AML 21 217 1.68 (1.352.10)* 12 119 1.43 (1.071.92)* 9 98 2.08 (1.592.72) 0.06 HL 27 146 0.99 (0.831.19) 19 123 1.01 (0.831.23) 8 23 0.91 (0.591.40) 0.67 NHLb 33 647 1.00 (0.891.13)* 22 452 0.93 (0.811.06)* 11 195 1.21 (0.941.55)* 0.07 MM 26 284 1.12 (0.981.27) 16 204 1.07 (0.931.24) 10 80 1.26 (0.921.71) 0.35 ALL 17 47 1.44 (1.032.02) 10 30 1.30 (0.881.92) 7 17 1.92 (1.003.67) 0.31 CLL 18 111 1.14 (0.781.67)* 11 69 0.87 (0.501.50)* 7 42 1.63 (1.092.44) 0.07 aTest of interaction (Altman and Bland 2003). bNHL or lymphosarcoma/reticulosarcoma (preferred NHL if the study reported both). *Significant evidence for between study heterogeneity (p < 0.1). Environmental Health Perspectives volume 119 | number 2 | February 2011 163 Vlaanderen et al. Egger's test revealed no significant evidence for publication bias in the data available for AML, HL, NHL, ALL, or CLL [see Supplemental Material, Figure 4 (doi: 10.1289/ehp.1002318)]. We observed evidence for bias for MM (p = 0.03), but Egger's test became nonsignificant after exclusion of all quality of exposure assessment studies in category D (p = 0.72). Discussion We conducted a series of meta-analyses on occupational cohort studies to assess the possible association between benzene and lymphoid neoplasms. Using different dimensions of study quality, we report evidence for an association between occupational benzene exposure and lymphoma subtypes MM, ALL, and CLL. For these subtypes, mRRs increased with increasing study quality, regardless of the strategy that was used to assess study quality. mRRs for NHL also increased with increasing study quality, although this effect was less pronounced. We did not observe an association between occupational benzene exposure and HL. Importantly, with the exception of a chance finding, the increase in mRRs for NHL, MM, ALL, and CLL with increasing study quality most likely reflects an actual underlying association with at least some of these lymphoma subtypes. Because we observed mRR patterns consistent with a possible association between benzene and all lymphoma subtypes except HL, we formally explored quantitative exposureresponse relations for NHL, MM, ALL, and CLL, including all studies in quality of exposure assessment category A (studies with quantitative estimates of benzene exposure) based on flexible meta-regression analyses (Vlaanderen et al. 2009). The relatively limited number of studies in category A resulted in uncertain and unstable predictions of the exposureresponse curve for NHL, MM, and CLL (data not shown). For ALL, only one study in quality of exposure assessment category A was available that precluded conducting a meta-regression for this lymphoma subtype. Therefore, possible doseresponse associations can only be discussed informally on a study-by-study basis. Assessment of study quality dimensions. We developed three different quality dimensions that reflect the substantial changes in diagnosis and categorization of lymphoid neoplasms over the last half century and the heterogeneity in occupational cohort studies with regard to industry, sample size, and documentation of benzene exposure. The generally higher RRs in the strata with studies that started follow-up in or after 1970 is consistent with better quality of lymphoma diagnosis in more recent years. The higher RRs are particularly noteworthy given that overall benzene exposure was likely reduced in workplaces after 19701980. Another secular trend in the quality of cohort studies over time was the greater use of incidence rather than mortality Table 4. mRRs (95% CIs) for AML and five lymphoma subtypes in cohort studies of workers exposed to benzene: stratification by exposure assessment quality. Lymphoma subtype AML significance levela n studies n exposed cases mRR AML AD (all studies) 21 217 1.68 (1.352.10)* AC 10 108 1.73 (1.262.38) AB 9 95 1.82 (1.252.66) A 6 71 2.32 (1.553.47) HL AD (all studies) 27 146 0.99 (0.831.19) AC 5 16 0.99 (0.581.71) AB 4 6 0.98 (0.362.67) A 4 6 0.98 (0.362.67) NHLb AD (all studies) 33 647 1.00 (0.891.13)* AC 8 106 1.03 (0.701.51)* AB 7 69 1.04 (0.631.72)* A 6 50 1.27 (0.901.79) MM AD (all studies) 26 284 1.12 (0.981.27) AC 9 37 1.15 (0.741.79) AB 8 28 1.48 (0.962.27) A 8 28 1.48 (0.962.27) ALL AD (all studies) 17 47 1.44 (1.032.02) AC 4 11 1.26 (0.53.16) AB 4 11 1.26 (0.53.16) A 1 5 2.80 (0.2729.23) CLL AD (all studies) 18 111 1.14 (0.781.67)* AC 8 61 1.38 (0.712.69)* AB 7 53 1.54 (0.723.31)* A 4 43 2.44 (0.886.75) aA, quantitative exposure estimates for benzene; B, semiquantitative estimates of benzene exposure or quantitative estimates of exposures containing benzene; C, some industrial hygiene sampling results; D, qualitative indication that benzene exposure had occurred. bNHL or lymphosarcoma/reticulosarcoma (preferred NHL if the study reported both). *Significant evidence for between study heterogeneity (p < 0.1). as end point (e.g., 91% of cohorts reporting CLL RRs with start of follow-up before 1970 used mortality as the end point vs. 43% for studies with start of follow-up in 1970 or later). It is possible that for less aggressive subtypes (e.g., CLL), subjects that died from other causes did not have lymphoma coded on their death certificate (Linet et al. 2007). However, cross-stratification of results suggested that stratification by period of follow-up explained more of the observed heterogeneity than stratification by mortality/incidence (data not shown). Although it has been suggested that the RR for leukemia subtypes observed in occupational studies might decrease with prolonged follow-up time (Richardson 2008), we found only modest evidence for this phenomenon for lymphoma subtypes. Substitution of the most recent RRs with those of previous updates did not materially change the results (data not shown). Because the association between benzene and AML is established, we argue that a wellconducted large epidemiologic study on benzene and hemato- and lymphopoietic cancers should find such an association. If at least some evidence of association is not found, one could argue that there must be known or unknown methodologic limitations in the study design. Such studies would by extension most likely be noninformative regarding the association between benzene and lymphoid neoplasms. Naturally, one should realize that a failure to find evidence for an association could also be the result of insufficient statistical power. However, in our meta-a nalyses we observed that the strong increase in mRRs for AML with increasing AML significance levels was generally paralleled by increasing mRRs in lymphoma subtypes. In other words, studies that reported higher (and more significant) RRs for AML generally also reported higher RRs for NHL, MM, ALL, and CLL. The quality of exposure assessment has a large impact on the ability of an epidemiological study to identify modest increased RRs. The relevance of our quality of exposure assessment approach was illustrated with the strong increase in mRRs for AML with increasing quality of exposure assessment. This trend provides support for our assumption that studies that conducted a more detailed benzene exposure assessment likely provide higher overall quality of evidence for the potential association of benzene with adverse health outcomes. Although one would expect that the study quality indicators for AML significance level and quality of exposure assessment to be highly correlated, this is not necessarily the case. For instance, we did observe five studies in the lowest category quality of exposure assessment (D) that still reported a significant increased RR for AML, and we observed two studies from quality 164 volume 119 | number 2 | February 2011 Environmental Health Perspectives Occupational benzene and lymphoma subtypes of exposure assessment category B in the set of studies that reported an AML RR below unity (AML significance level category D). Therefore, the two study quality dimensions should be seen as complementary. NHL. We observed a moderate increased RR of NHL with increasing study quality. However, neither the overall mRR nor any of the strata-specific mRRs reached formal statistical significance. Because our formal meta-regression did not result in robust dose response associations, we qualitatively explored exposureresponse relations within each exposure assessment quality category A publication that provided RRs for NHL. Of the six exposure assessment quality category A studies that reported RRs for NHL only one study reported a significant increased RR (p for trend < 0.02) with increasing cumulative exposure to benzene (Hayes et al. 1997). In contrast, in three of six publications the authors reported no clear trend of RRs for NHL with increasing cumulative exposure to benzene (Bloemen et al. 2004; Collins et al. 2003; Schnatter et al. 1996), whereas the remaining two publications did not report on the quantitative relation between NHL and cumulative exposure to benzene (Rinsky et al. 2002; Wong 1987a). In addition to these six studies, two publications that included MM in the definition of NHL did report on the quantitative relation of NHL plus MM and cumulative exposure to benzene (Glass et al. 2003; Wong 1987b). One of these studies reported an initial increase in RR with increasing exposure to benzene followed by a drop in RR in the upper cumulative exposure group (Wong 1987b), whereas the other study reported no association (Glass et al. 2003). We note, however, that a recent meta-a nalysis including both casecontrol and cohort studies reported a significant elevated mRR for NHL when we restricted the analyses to the higher exposure groups and corrected for the healthy worker (inclusion) effect (Steinmaus et al. 2008). Overall, the epidemiologic evidence for the association between NHL and benzene is conflicting. This is illustrated by three recent meta-a nalyses that were based on largely the same data but reached a diametrically opposite conclusion on whether exposure to benzene is associated to NHL (Alexander and Wagner 2010; Kane and Newton 2010; Steinmaus et al. 2008). The inconsistency in findings is partly explained by study quality and failure to correct for biases but might also to a certain extent be explained by the etiologic heterogeneity within this group of diseases. If some NHL subtypes [e.g., diffuse large B-cell lymphoma (DLBCL) or follicular lymphoma (FL)] are associated with benzene, but others are not, any NHL RR will be attenuated because of the inclusion of non-benzene-associated NHL subtypes. This is even further complicated by the fact that the distribution of NHL subtypes may vary considerably from population to population, which could lead to significant variation in reported associations between potential risk factors and total NHL (Muller et al. 2005). A series of recent population-based case control studies provide evidence that the association between some genetic and environmental factors varies between major NHL subtypes such as DLBCL and FL (Lan et al. 2009; Morton et al. 2008; Rothman et al. 2006; Skibola et al. 2009, 2010). Another series of recent casecontrol studies that used relatively high-quality retrospective exposure assessment methods have provided evidence that this might also be true for the association between benzene and NHL subtypes (Cocco et al. 2010; Miligi et al. 2006; Wong et al. 2009). The studies by Cocco et al. (2010) and Wong et al. (2009) reported a stronger association with benzene with FL [OR = 1.6 (95% CI, 0.92.9) and OR = 7.00 (95% CI, 1.4533.70), respectively] than for DLBCL [OR = 0.9 (95% CI, 0.61.4) and OR = 0.66 (95% CI, 0.311.42), respectively]. The study by Miligi et al. (2006) did not report an RR for FL (due to the limited number of cases) but reported an OR of 2.4 (95% CI, 1.34.5) for DLBCL. MM. Our analyses are supportive of an association of benzene exposure with MM. mRRs increased considerably and reached near statistical significance regardless of the study quality dimension used except for the analyses stratified by AML significance level, where formal statistical significance was reached for the two highest quality strata. Our results are similar (albeit that the point estimates of the mRRs are slightly lower) to the results from a meta-analysis by Infante (2006), in which slightly different inclusion criteria were applied [mRR = 2.13 (95% CI, 1.313.46)]. Further evidence for an association between exposure to benzene and MM have been provided by two recent population-based casecontrol studies that reported increased MM RRs with increasing exposure to benzene (Cocco et al. 2010; Seniori Costantini et al. 2008). We qualitatively explored the quantitative exposure response relation between benzene and MM. Two of eight exposure assessment quality category A studies reported an increase in RR with increasing cumulative exposure (Collins et al. 2003; Rinsky et al. 2002); in two studies the authors reported no clear trend of RRs for MM with increasing cumulative exposure to benzene (Atkinson et al. 2001; Schnatter et al. 1996); and four studies did not report on the quantitative relation between cumulative exposure to benzene and MM (Bloemen et al. 2004; Swaen et al. 2005; Wong 1987b; Yin et al. 1996). Therefore, although the evidence for an association between "any occupational benzene exposure" versus "background benzene exposure" and the RR of MM appears to be consistent, the evidence for an exposureresponse relation between benzene and MM is more ambiguous. This would be explained partly by the much larger statistical power that is required to conduct quantitative exposureresponse analysis, often a complication for small-scale occupational cohort studies. ALL. The association between exposure to benzene and ALL is difficult to study because the disease is rare in adults (Faderl et al. 2010). It is therefore noteworthy that our analyses do strongly suggest increased RRs for ALL. We were able to identify only two population-based casecontrol studies that explored benzeneALL associations in adults (Adegoke et al. 2003; Richardson et al. 1992). One case control study reported a (nonsignificantly) increased RR for ALL with a suggestion of an exposureresponse relation (Adegoke et al. 2003), whereas the other study did not observe any cases with ALL (Richardson et al. 1992). Together, the evidence from both cohort and casecontrol studies are strongly suggestive of a positive association between exposure to benzene and the RR of adult ALL. CLL. Our analyses suggest that exposure to benzene is associated with an increased RR for CLL. This is in line with results from four recent casecontrol studies that reported RRs ranging from 1.4 to 2.05 (Cocco et al. 2010; Miligi et al. 2006; Seniori Costantini et al. 2008; Wong et al. 2009). Two of these casecontrol studies reported an increase in RR with increasing benzene exposure (Cocco et al. 2010; Seniori Costantini et al. 2008). Of the cohort studies with quantitative exposure assessment, one study reported that the RR for the group with higher cumulative exposure was higher than the RR for the group with lower exposure (Glass et al. 2003). However, two cohort studies reported no association with cumulative exposure to benzene (Collins et al. 2003; Rushton and Romaniuk 1997), whereas one study did not report on the quantitative relation between cumulative exposure to benzene and CLL (Bloemen et al. 2004). Conclusion In line with the recent IARC evaluation of the carcinogenicity of benzene, our meta-analyses provide evidence for the association of occupational benzene exposure to MM, ALL, and CLL (Baan et al. 2009). Although these findings are suggestive, it is important to realize that most analyses were based on data sets of limited size. The evidence for an association between benzene and NHL (as defined in ICD-9) is less convincing, but this could be explained by the heterogeneity in the association for particular subgroups of this disease or by not accounting Environmental Health Perspectives volume 119 | number 2 | February 2011 165 Vlaanderen et al. for certain biases. We observed no association between benzene and HL. The discussion on the association between benzene and NHL will likely benefit from NHL subtypespecific analyses. Unfortunately, most current occupational cohort studies lack sufficient statistical power to perform such detailed analyses. Cohort studies with central pathology review and well-designed casec ontrol studies using state-of-the-art retrospective exposure assessment methods will be needed to help evaluate the extent to which occupational benzene exposure is associated with specific subtypes of NHL. Finally, our overall findings, taken together with the substantial experimental and molecular epidemiologic evidence that benzene exposure alters key components of the immune system relevant for lymphomagenesis (e.g., CD4+ T-cell level and CD4+ T-cell:CD8+ T-cell ratio) (Lan et al. 2004), provide support that benzene is likely to be causally related to one or more subtypes of lymphoma. Correction In the manuscript originally published online, data shown for the "AML significance level" in Table 1 differed from the correct values used in the analysis due to a sorting error. In addition, one risk estimate used in the meta-analysis for NHL was classified incorrectly as "AML significance level" C instead of as "AML significance level" E. Correction of the "AML significance level" for this risk estimate resulted in minor changes in some of the meta relative risks reported in Table 3 and in Supplemental Material, Table 1. These errors have been corrected. References Adegoke OJ, Blair A, Shu XO, Sanderson M, Jin F, Dosemeci M, et al. 2003. Occupational history and exposure and the risk of adult leukemia in Shanghai. Ann Epidemiol 13(7):485494. Aisenberg AC. 2000. Historical review of lymphomas. Br J Haematol 109(3):466476. Alexander DD, Wagner ME. 2010. Benzene exposure and nonHodgkin lymphoma: a meta-analysis of epidemiologic studies. J Occup Environ Med 52(2):169189. Altman DG, Bland JM. 2003. Interaction revisited: the difference between two estimates. BMJ 326(7382):219. Atkinson S, Coppock J, Fritschi L, Glass DC, Gibbons C, Gray CN, et al. 2001. Lympho-haematopoietic Cancer and Exposure to Benzene in the Australian Petroleum Industry. Technical Report and Appendices. Victoria, Australia:Monash University and Deakin University. Baan R, Grosse Y, Straif K, Secretan B, El Ghissassi F, Bouvard V, et al. 2009. A review of human carcinogens-- part F: chemical agents and related occupations. Lancet Oncol 10(12):11431144. Bergsagel DE, Wong O, Bergsagel PL, Alexanian R, Anderson K, Kyle RA, et al. 1999. Benzene and multiple myeloma: appraisal of the scientific evidence. Blood 94(4):11741182. Bloemen LJ, Youk A, Bradley TD, Bodner KM, Marsh G. 2004. Lymphohaematopoietic cancer risk among chemical workers exposed to benzene. Occup Environ Med 61(3):270274. Cocco P, t'Mannetje A, Fadda D, Melis M, Becker N, de Sanjose S, et al. 2010. Occupational exposure to solvents and risk of lymphoma subtypes: results from the Epilymph case-control study. Occup Environ Med 67(5):341347. Collingwood KW, Raabe GK, Wong O. 1996. An updated cohort mortality study of workers at a northeastern United States petroleum refinery. Int Arch Occup Environ Health 68(5):277288. Collins JJ, Ireland B, Buckley CF, Shepperly D. 2003. Lymphohaematopoeitic cancer mortality among workers with benzene exposure. Occup Environ Med 60(9):676679. Consonni D, Pesatori AC, Tironi A, Bernucci I, Zocchetti C, Bertazzi PA. 1999. Mortality study in an Italian oil refinery: extension of the follow-up. Am J Ind Med 35(3):287294. Dagg TG, Satin KP, Bailey WJ, Wong O, Harmon LL, Swencicki RE. 1992. An updated cause specific mortality study of petroleum refinery workers. Br J Ind Med 49(3):203212. Decoufle P, Blattner WA, Blair A. 1983. Mortality among chemical workers exposed to benzene and other agents. Environ Res 30(1):1625. Divine BJ, Hartman CM. 2000. Update of a study of crude oil production workers 194694. Occup Environ Med 57(6):411417. Divine BJ, Hartman CM, Wendt JK. 1999a. Update of the Texaco mortality study 194793: part I. Analysis of overall patterns of mortality among refining, research, and petrochemical workers. Occup Environ Med 56(3):167173. Divine BJ, Hartman CM, Wendt JK. 1999b. Update of the Texaco mortality study 194793: part II. Analyses of specific causes of death for white men employed in refining, research, and petrochemicals. Occup Environ Med 56(3):174180. Egger M, Davey Smith G, Schneider M, Minder C. 1997. Bias in meta-a nalysis detected by a simple, graphical test. BMJ 315(7109):629634. Faderl S, O'Brien S, Pui CH, Stock W, Wetzler M, Hoelzer D, et al. 2010. Adult acute lymphoblastic leukemia: concepts and strategies. Cancer 116(5):11651176. Fu H, Demers PA, Costantini AS, Winter P, Colin D, Kogevinas M, et al. 1996. Cancer mortality among shoe manufacturing workers: an analysis of two cohorts. Occup Environ Med 53(6):394398. Glass DC, Gray CN, Jolley DJ, Gibbons C, Sim MR, Fritschi L, et al. 2003. Leukemia risk associated with low-level benzene exposure. Epidemiology 14(5):569577. Goldstein BD, Shalat S. 2000. Non-Hodgkin's lymphoma and exposure to benzene in petroleum workers. J Occup Environ Med 42(12):11331136. Guenel P, Imbernon E, Chevalier A, Crinquand-Calastreng A, Goldberg M. 2002. Leukemia in relation to occupational exposures to benzene and other agents: a case-control study nested in a cohort of gas and electric utility workers. Am J Ind Med 42(2):8797. Gun RT, Pratt N, Ryan P, Roder D. 2006. Update of mortality and cancer incidence in the Australian petroleum industry cohort. Occup Environ Med 63(7):476481. Harris NL, Jaffe ES, Diebold J, Flandrin G, Muller-Hermelink HK, Vardiman J. 2000. Lymphoma classification--from controversy to consensus: the R.E.A.L. and WHO classification of lymphoid neoplasms. Ann Oncol 11(suppl 1):310. Hayes RB, Yin SN, Dosemeci M, Li GL, Wacholder S, Travis LB, et al. 1997. Benzene and the dose-related incidence of hematologic neoplasms in China. Chinese Academy of Preventive Medicine--National Cancer Institute Benzene Study Group. J Natl Cancer Inst 89(14):10651071. Higgins JP, Thompson SG, Deeks JJ, Altman DG. 2003. Measuring inconsistency in meta-analyses. BMJ 327(7414):557560. Honda Y, Delzell E, Cole P. 1995. An updated study of mortality among workers at a petroleum manufacturing plant. J Occup Environ Med 37(2):194200. Huebner WW, Wojcik NC, Rosamilia K, Jorgensen G, Milano CA. 2004. Mortality updates (19701997) of two refinery/petrochemical plant cohorts at Baton Rouge, Louisiana, and Baytown, Texas. J Occup Environ Med 46(12):12291245. IARC (International Agency for Research on Cancer). 1982. Benzene. IARC Monogr Eval Carcinog Risk Chem Hum 29:93148. IARC (International Agency for Research on Cancer). 1987. Overall evaluations of carcinogenicity: an updating of IARC Monographs volumes 1 to 42. IARC Monogr Eval Carcinog Risks Hum Suppl 7:1440. Infante PF. 2005. Cancer risks in a UK benzene exposed cohort. Occup Environ Med 62(12):905906. Infante PF. 2006. Benzene exposure and multiple myeloma: a detailed meta-analysis of benzene cohort studies. Ann NY Acad Sci 1076:90109. Kane EV, Newton R. 2010. Benzene and the risk of non-Hodgkin lymphoma: a review and meta-analysis of the literature. Cancer Epidemiol 34(1):712. Kaplan SD. 1986. Update of a mortality study of workers in petroleum refineries. J Occup Med 28(7):514516. Kirkeleit J, Riise T, Bratveit M, Moen BE. 2008. Increased risk of acute myelogenous leukemia and multiple myeloma in a historical cohort of upstream petroleum workers exposed to crude oil. Cancer Causes Control 19(1):1323. Lamm SH, Engel A, Byrd DM. 2005. Non-Hodgkin lymphoma and benzene exposure: a systematic literature review. Chem Biol Interact 153154:231237. Lan Q, Morton LM, Armstrong B, Hartge P, Menashe I, Zheng T, et al. 2009. Genetic variation in caspase genes and risk of non-Hodgkin lymphoma: a pooled analysis of 3 populationbased case-control studies. Blood 114(2):264267. Lan Q, Zhang L, Li G, Vermeulen R, Weinberg RS, Dosemeci M, et al. 2004. Hematotoxicity in workers exposed to low levels of benzene. Science 306(5702):17741776. Lewis RJ, Schnatter AR, Drummond I, Murray N, Thompson FS, Katz AM, et al. 2003. Mortality and cancer morbidity in a cohort of Canadian petroleum workers. Occup Environ Med 60(12):918928. Linet MS, Schubauer-Berigan MK, Weisenburger DD, Richardson DB, Landgren O, Blair A, et al. 2007. Chronic lymphocytic leukaemia: an overview of aetiology in light of recent developments in classification and pathogenesis. Br J Haematol 139(5):672686. Lynge E, Anttila A, Hemminki K. 1997. Organic solvents and cancer. Cancer Causes Control 8(3):406419. McCraw DS, Joyner RE, Cole P. 1985. Excess leukemia in a refinery population. J Occup Med 27(3):220222. McElvenny DM, Armstrong BG, Jarup L, Higgins JP. 2004. Meta-analysis in occupational epidemiology: a review of practice. Occup Med (Lond) 54(5):336344. Miligi L, Costantini AS, Benvenuti A, Kriebel D, Bolejack V, Tumino R, et al. 2006. Occupational exposure to solvents and the risk of lymphomas. Epidemiology 17(5):552561. Morton LM, Turner JJ, Cerhan JR, Linet MS, Treseler PA, Clarke CA, et al. 2007. Proposed classification of lymphoid neoplasms for epidemiologic research from the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph). Blood 110(2):695708. Morton LM, Wang SS, Cozen W, Linet MS, Chatterjee N, Davis S, et al. 2008. Etiologic heterogeneity among nonHodgkin lymphoma subtypes. Blood 112(13):51505160. Muller AM, Ihorst G, Mertelsmann R, Engelhardt M. 2005. Epidemiology of non-Hodgkin's lymphoma (NHL): trends, geographic distribution, and etiology. Ann Hematol 84(1):112. Nilsson RI, Nordlinder R, Horte LG, Jarvholm B. 1998. Leukaemia, lymphoma, and multiple myeloma in seamen on tankers. Occup Environ Med 55(8):517521. OSHA (Occupational Safety and Health Administration). 1987. Preamble to the Final Rule for Benzene. Washingon, DC:OSHA. Ott MG, Teta MJ, Greenberg HL. 1989. Lymphatic and hematopoietic tissue cancer in a chemical manufacturing environment. Am J Ind Med 16(6):631643. Pukkala E. 1998. Cancer incidence among Finnish oil refinery workers, 19711994. J Occup Environ Med 40(8):675679. Richardson DB. 2008. Temporal variation in the association between benzene and leukemia mortality. Environ Health Perspect 116:370374. Richardson S, Zittoun R, Bastuji-Garin S, Lasserre V, Guihenneuc C, Cadiou M, et al. 1992. Occupational risk factors for acute leukaemia: a case-control study. Int J Epidemiol 21(6):10631073. Rinsky RA, Hornung RW, Silver SR, Tseng CY. 2002. Benzene exposure and hematopoietic mortality: a long-term epidemiologic risk assessment. Am J Ind Med 42(6):474480. Rothman KJ, Boice JD Jr. 1979. Epidemologic Analysis with a Programmable Calculator. Washington DC:U.S. Department of Health, Education and Welfare. Rothman N, Skibola CF, Wang SS, Morgan G, Lan Q, Smith MT, et al. 2006. Genetic variation in TNF and IL10 and risk of non-Hodgkin lymphoma: a report from the InterLymph Consortium. Lancet Oncol 7(1):2738. Rushton L. 1993. A 39-year follow-up of the U.K. oil refinery and distribution center studies: results for kidney cancer and leukemia. Environ Health Perspect 101(suppl 6):7784. 166 volume 119 | number 2 | February 2011 Environmental Health Perspectives Occupational benzene and lymphoma subtypes Rushton L, Romaniuk H. 1997. A case-control study to investigate the risk of leukaemia associated with exposure to benzene in petroleum marketing and distribution workers in the United Kingdom. Occup Environ Med 54(3):152166. Sathiakumar N, Delzell E, Cole P, Brill I, Frisch J, Spivey G. 1995. A case-control study of leukemia among petroleum workers. J Occup Environ Med 37(11):12691277. Satin KP, Wong O, Yuan LA, Bailey WJ, Newton KL, Wen CP, et al. 1996. A 50-year mortality follow-up of a large cohort of oil refinery workers in Texas. J Occup Environ Med 38(5):492506. Savitz DA, Andrews KW. 1997. Review of epidemiologic evidence on benzene and lymphatic and hematopoietic cancers. Am J Ind Med 31(3):287295. Schnatter AR, Armstrong TW, Nicolich MJ, Thompson FS, Katz AM, Huebner WW, et al. 1996. Lymphohaematopoietic malignancies and quantitative estimates of exposure to benzene in Canadian petroleum distribution workers. Occup Environ Med 53(11):773781. Schnatter AR, Rosamilia K, Wojcik NC. 2005. Review of the literature on benzene exposure and leukemia subtypes. Chem Biol Interact 153154:921. Seniori Costantini A, Benvenuti A, Vineis P, Kriebel D, Tumino R, Ramazzotti V, et al. 2008. Risk of leukemia and multiple myeloma associated with exposure to benzene and other organic solvents: evidence from the Italian Multicenter case-control study. Am J Ind Med 51(11):803811. Skibola CF, Bracci PM, Halperin E, Conde L, Craig DW, Agana L, et al. 2009. Genetic variants at 6p21.33 are associated with susceptibility to follicular lymphoma. Nat Genet 41(8):873875. Skibola CF, Bracci PM, Nieters A, Brooks-Wilson A, de Sanjose S, Hughes AM, et al. 2010. Tumor necrosis factor (TNF) and lymphotoxin-alpha (LTA) polymorphisms and risk of non-Hodgkin lymphoma in the InterLymph Consortium. Am J Epidemiol 171(3):267276. Smith MT, Jones RM, Smith AH. 2007. Benzene exposure and risk of non-Hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev 16(3):385391. Sonoda T, Nagata Y, Mori M, Ishida T, Imai K. 2001. Metaanalysis of multiple myeloma and benzene exposure. J Epidemiol 11(6):249254. Sorahan T. 2007. Mortality of UK oil refinery and petroleum distribution workers, 19512003. Occup Med (Lond) 57(3):177185. Sorahan T, Kinlen LJ, Doll R. 2005. Cancer risks in a historical UK cohort of benzene exposed workers. Occup Environ Med 62(4):231236. Steinmaus C, Smith AH, Jones RM, Smith MT. 2008. Meta-analysis of benzene exposure and non-Hodgkin lymphoma: biases could mask an important association. Occup Environ Med 65(6):371378. Swaen GM, Scheffers T, de Cock J, Slangen J, Drooge H. 2005. Leukemia risk in caprolactam workers exposed to benzene. Ann Epidemiol 15(1):2128. Swerdlow SH, Campo E, Harris N, Jaffe ES, Pileri S, Stein H, et al. 2008. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. Lyon, France:International Agency for Research on Cancer. Thomas TL, Waxweiler RJ, Moure-Eraso R, Itaya S, Fraumeni JF Jr. 1982. Mortality patterns among workers in three Texas oil refineries. J Occup Med 24(2):135141. Tsai SP, Gilstrap EL, Cowles SR, Snyder PJ, Ross CE. 1993. A cohort mortality study of two California refinery and petrochemical plants. J Occup Med 35(4):415421. Tsai SP, Gilstrap EL, Cowles SR, Snyder PJ, Ross CE. 1996. Long-term follow-up mortality study of petroleum refinery and chemical plant employees. Am J Ind Med 29(1):7587. Tsai SP, Wendt JK, Cardarelli KM, Fraser AE. 2003. A mortality and morbidity study of refinery and petrochemical employees in Louisiana. Occup Environ Med 60(9):627633. Vlaanderen J, Portengen L, Rothman N, Lan Q, Kromhout H, Vermeulen R. 2009. Flexible meta-regression to assess the shape of the benzene leukemia exposure response curve. Environ Health Perspect 118:526532. Vlaanderen J, Vermeulen R, Heederik D, Kromhout H. 2008. Guidelines to evaluate human observational studies for quantitative risk assessment. Environ Health Perspect 116:17001705. Waxweiler RJ, Alexander V, Leffingwell SS, Haring M, Lloyd JW. 1983. Mortality from brain tumor and other causes in a cohort of petrochemical workers. J Natl Cancer Inst 70(1):7581. World Health Organization. 1955. International Classification of Diseases, 7th Revision. Geneva:World Health Organization. World Health Organization. 1965. International Classification of Diseases, 8th Revision. Geneva:World Health Organization. World Health Organization. 1975. International Classification of Diseases, 9th Revision. Geneva:World Health Organization. World Health Organization. 2000. International Classification of Diseases for Oncology. 3rd ed. Geneva:World Health Organization. Wong O. 1987a. An industry wide mortality study of chemical workers occupationally exposed to benzene. I. General results. Br J Ind Med 44(6):365381. Wong O. 1987b. An industry wide mortality study of chemical workers occupationally exposed to benzene. II. Dose response analyses. Br J Ind Med 44(6):382395. Wong O. 1995. Risk of acute myeloid leukaemia and multiple myeloma in workers exposed to benzene. Occup Environ Med 52(6):380384. Wong O. 1998. Re: Benzene and the dose-related incidence of hematologic neoplasms in China [Letter]. J Natl Cancer Inst 90(6):469471. Wong O, Fu H. 2005. Exposure to benzene and non-Hodgkin lymphoma, an epidemiologic overview and an ongoing case-control study in Shanghai. Chem Biol Interact 153 154:3341. Wong O, Harris F, Armstrong TW, Hua F. 2009. A hospital-based case-control study of non-Hodgkin lymphoid neoplasms in Shanghai: analysis of environmental and occupational risk factors by subtypes of the WHO classification. Chem Biol Interact 184(12):129146. Wong O, Harris F, Rosamilia K, Raabe GK. 2001a. An updated mortality study of workers at a petroleum refinery in Beaumont, Texas, 1945 to 1996. J Occup Environ Med 43(4):384401. Wong O, Harris F, Rosamilia K, Raabe GK. 2001b. Updated mortality study of workers at a petroleum refinery in Torrance, California, 1959 to 1997. J Occup Environ Med 43(12):10891102. Wong O, Harris F, Smith TJ. 1993. Health effects of gasoline exposure. II. Mortality patterns of distribution workers in the United States. Environ Health Perspect 101(suppl 6):6376. Wong O, Raabe GK. 1995. Cell-type-specific leukemia analyses in a combined cohort of more than 208,000 petroleum workers in the United States and the United Kingdom, 19371989. Regul Toxicol Pharmacol 21(2):307321. Wong O, Raabe GK. 1997. Multiple myeloma and benzene exposure in a multinational cohort of more than 250,000 petroleum workers. Regul Toxicol Pharmacol 26(2):188199. Wong O, Raabe GK. 2000a. A critical review of cancer epidemiology in the petroleum industry, with a meta-analysis of a combined database of more than 350,000 workers. Regul Toxicol Pharmacol 32(1):7898. Wong O, Raabe GK. 2000b. Non-Hodgkin's lymphoma and exposure to benzene in a multinational cohort of more than 308,000 petroleum workers, 1937 to 1996. J Occup Environ Med 42(5):554568. Yin SN, Hayes RB, Linet MS, Li GL, Dosemeci M, Travis LB, et al. 1996. A cohort study of cancer among benzeneexposed workers in China: overall results. Am J Ind Med 29(3):227235. Environmental Health Perspectives volume 119 | number 2 | February 2011 167