The comment by the authors about the computer code IREP used by NIOSH, namely: “IREP includes a DDREF, which lowers the probability of causation [PC] for low-dose-rate exposures,” has the potential to be misinterpreted. IREP contains two discrete DDREF distributions, one for most solid cancers and another, more restricted, distribution for thyroid and female breast cancers. The first mentioned, with values of DDREF ranging from 0.5 to 5, is most comparable to the inverse of the risk ratio calculated by Jacob et al.

The IREP-based PC depends on the value selected from this distribution. To be correct, the PC is never lowered by the DDREF for any U.S. radiation worker whose claim for compensation is evaluated using IREP. This is because the 99th percentile of PC is used in making compensation decisions, unlike the U.K. compensation scheme in which the 50th percentile estimate is used.

In the U.S., values from the lower end of the DDREF distribution (i.e., <1, which corresponds to a risk ratio >1 in the authors’ parlance) drive PC estimates at the 99th percentile. Thus, the effective “risk ratio” produced by the DDREF in IREP as it is currently used in making compensation decisions is influenced by values greater than 1, which is consistent with current uncertainties in DDREF. This differs from the approach used in the U.K., which does currently not allow for risk ratios greater than 1. [jrt@senes.com]

Meta-analysis on benzene exposure and non Hodgkin lymphoma

June 30 2009

Gerard M H Swaen1 Shan P. Tsai2 Carol Burns1

1 Department of Epidemiology, The Dow Chemical Company, Midland, Michigan USA. 2 Shell Health, Shell Oil Company, Houston Texas, USA.

Corresponding Author: Gerard M H Swaen, The Dow Chemical Company, P.O. Box 444, 4530 AK Terneuzen, The Netherlands 31-(0)43-3626042. E- mail: gswaen@dow.com

Key words: benzene, non Hodgkin lymphoma, epidemiology, meta- analysis, occupation, risk

Sir, A recent meta-analysis on benzene exposure and non Hodgkin lymphoma (NHL) concluded that the reviewed epidemiological studies provide “new evidence that benzene causes NHL.” 1 The meta-analysis conducted by Steinmaus et al differed from the others in several aspects. Firstly, it selected subgroups with the highest putative exposure to avoid dilution. Secondly, cohort studies were adjusted for the Healthy Worker Effect (HWE) by considering the NHL deaths as cases and all other deaths as controls. A HWE for cancer endpoints is small if any, compared to non cancer endpoints.2. The results from a meta-analysis of 150 occupational cohort studies suggest that HWE adjustment may artificially inflate the true RR for cancer endpoints. 3 Thirdly, outdated cohort study results were used instead of more recent updates. Fourthly, Steinmaus et al did not consistently apply their own selection criteria. We have re-analyzed the Steinmaus et al meta-analysis by precisely applying their inclusion and exclusion criteria. These include selecting the highest exposure category relative risk (RR), selecting cancer incidence versus mortality data and we used the most recent results from cohort updates whenever available. To maintain consistency, we adjusted the RR estimates for the HWE by using the all cancer SMR of the selected sub cohort instead of the all mortality SMR. Herein we present only a summary table of results. Additional comparative tables are available upon request.

There were 16 case-control studies included in the Steinmaus et al. review. We excluded the study by Dryver since it provided no odds ratio (OR) for benzene exclusively. For the Fabbro-Peray et al. study, Steinmaus et al selected the OR of those with over 810 days of exposure. However, we used the subcategory with exposure duration of over 15 years since it represents the group with longer exposure. For the study by Schnatter et al the OR for the highest intensity was 0 and Steinmaus et al selected the OR for the second highest exposure intensity group. We combined the highest and the second highest exposure intensity groups (OR=0.49 95% CI: 0.10-2.32). The revised meta-OR for the 15 case-control studies was 1.17 (95% CI 0.96 – 1.44) (see Table 1).

For the six non refinery cohort studies, we observed inconsistencies in the authors’ use of the selection sequence. For the Bloemen study, the longest duration RR was used by Steinmaus et al. although RRs by cumulative exposure were given. We combined the two cumulative exposure categories into one category of 28.3+ ppm-years (SMR=0.63 95% CI: 0.08- 2.28). For the Rinsky study, we selected the RR for men (1.00), assuming that the men were higher exposed, since the jobs with benzene exposure were generally done by men. Lastly, for Wong et al. the RR for highest cumulative exposure was replaced with that for highest intensity exposure. The revised meta-RR for these non-refinery studies was 1.13 (95% CI: 0.80- 1.61) and a meta-RR of 1.05 (95% CI: 0.75-1.47) after adjusting for the HWE.

In the meta-analysis of the refinery studies, as per the recommendations of Steinmaus et al., cancer incidence data were selected if both incidence and mortality were reported. There were two refineries included in the 1993 study published by Tsai, et al, and the combined results were used instead of selecting only one of the refineries. Additionally, we used the combined results from maintenance and process workers for the study conducted at the Beaumont refinery by Wong since it is unclear that process workers were more exposed. We selected results based on the longer duration of work for the study by Pukkala et al, following the Steinmaus et al. hierarchy. We used the updated data for the following refinery studies (Sorahan, Thomas and Tsai et al, 1996) 4 5 6. In the update by Tsai and colleagues NHL was listed as one of the specific disease categories, replacing reticulosarcoma used in the 1996 paper. We selected the updated RR although the longest duration of employment was shorter. 7 The revised meta-RR for the 21 refinery studies was 1.00 (95% CI: 0.89-1.12) and 1.06 (95% CI: 0.95-1.18) after adjusting for the HWE. All the models gave similar results and we only present those of the fixed model.

All of the meta-RRs calculated in the re-analysis were less than those reported by Steinmaus et al and most were close to unity. The only meta-RR that remained statistically significant was that for the high exposure non refinery studies, consisting of four cohort studies and nine case-control studies (meta-RR of 1.33, 95% CI: 1.02-1.74), for which exposure was largely based on self-reported data. The statistical significance of this meta-RR was lost after adjustment for the heterogeneity effect (95% CI: 0.99-1.80).

The re-analysis shows that the differences of the applied analytical methods and relative risks selected can vastly alter the overall meta- relative risk. The re-analyzed evidence provides little if any support for an association between benzene exposure and NHL.

Gerard M H Swaen1, Shan P. Tsai2 Carol Burns1. 1 Department of Epidemiology, The Dow Chemical Company, Midland, Michigan USA.

2 Shell Health, Shell Oil Company, Houston Texas, USA.

Table 1 Summary results of the meta-analysis on benzene exposure and NHL and for refinery workers and NHL, comparing the results by Steinmaus et al to our findings (fixed models, other models gave similar results)).

N RR as in Steinmaus RR in the re-analysis Benzene and NHL

All studies 22 1.22 (1.03-1.46) 1.16 (0.97-1.38)

Case control studies 16 1.23 (1.00-1.50) 1.17 (0.96-1.44)

Cohort studies 6 1.21 (0.86-1.71) 1.13 (0.80-1.61)

All high exposure studies 13 1.49 (1.15-1.92) 1.33 (1.02-1.74)1

HWE adjusted cohort studies 6 1.22 (0.89-1.67 1.05 (0.75-1.47) Refinery work and NHL

All studies 21 1.21 (1.06-1.38) 1.00 (0.89-1.12)

High exposure studies 14 1.30 (1.04-1.62) 1.07 (0.87-1.31)

HWE adjusted all studies 21 1.42 (1.25-1.62) 1.06 (0.95-1.18)

HWE adjusted high exposure studies 14 1.51 (1.22-1.88) 1.20 (0.99- 1.47) 1 statistical significance was lost after adjustment for heterogeneity (95% CI: 0.99-1.80)

References

1. Steinmaus C, Smith AH, Jones RM, Smith MT. Meta-analysis of benzene exposure and non-Hodgkin lymphoma: biases could mask an important association. Occup Environ Med 2008;65(6):371-8.

2. Li CY, Sung FC. A review of the healthy worker effect in occupational epidemiology. Occup Med (Lond) 1999;49(4):225-9.

3. Greenberg RS, Mandel JS, Pastides H, Britton NL, Rudenko L, Starr TB. A meta-analysis of cohort studies describing mortality and cancer incidence among chemical workers in the United States and western Europe. Epidemiology 2001;12(6):727-40.

4. Sorahan T. Mortality of UK oil refinery and petroleum distribution workers, 1951-2003. Occup Med (Lond) 2007;57(3):177-85.

5. Dement JM, Hensley L, Kieding S, Lipscomb H. Proportionate mortality among union members employed at three Texas refineries. Am J Ind Med 1998;33(4):327-40.>

6. Tsai SP, Ahmed FS, Wendt JK, Foster DE, Donnelly RP, Strawmyer TR. A 56-year mortality follow-up of Texas petroleum refinery and chemical employees, 1948-2003. J Occup Environ Med 2007;49(5):557-67.

7. Tsai SP, Chen VW, Fox EE, Wendt JK, Cheng Wu X, Foster DE, et al. Cancer incidence among refinery and petrochemical employees in Louisiana, 1983-1999. Ann Epidemiol 2004;14(9):722-30.

Licence Statement: The Corresponding author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence on a worldwide basis to the BMJ Publishing Group Ltd to permit this article (if accepted) to be published in OEM and any other BMJPGL products and sublicences such use and exploit all subsidiary rights, as set out in our licence

Pere Sanz-Gallén, Santiago Nogué, Eva Muñoz and Francisco Sabater*

Clinical Toxicology Unit and *Otorhinolaryngology Service. Hospital Clínic. Barcelona

Sir,

The case-control study by D' Errico et al (1) on occupational risk factors for sinonasal cancer concludes that exposure to arsenic is one such factor and suggests more cases should be reported, as there are only two studies at present (2,3). We contribute a new case of a worker in the glassware industry, in order to reinforce the relationship between sinonasal cancer and occupational exposure to arsenic.

A middle-aged, non-smoking patient was diagnosed more than a decade previously with squamous cell carcinoma affecting the left maxilla. The initial computed tomography (CT) scan had shown a lesion occupying the space of the left maxillary sinus that had destroyed the bone structure of the left maxilla and invaded the soft facial tissue and the pterygopalatine fossa. A CT scan more than a decade later after surgery and radiotherapy shows changes in the nasal fossa and left maxillary sinus, with a fibrotic mass of scar tissue.

The patient worked in the glassware industry for over twenty years. The main materials forming the mix introduced in the glass furnace were silica, sodium carbonate, potassium carbonate, zinc oxide and lead oxide. The dyes, which represented 0.1% of the mixture, included cadmium sulphide and oxides of cobalt, copper, chromium, manganese and nickel. One per cent of arsenic trioxide was added to the mixture to increase the transparency of the glass. An onsite workplace study showed environmental levels of chromium and nickel <3 µg/m3, but levels of arsenic of 85 µg/m3 (Threshold Limit Value: 10 µg/m3).

Although chromium and nickel oxides, known sinonasal carcinogens, are used in the glassware industry, the environmental levels found were very low. However, the levels of arsenic were very high, in agreement with the study by Battista et al in various glassware companies (3). Therefore, arsenic trioxide should be replaced by other metals and preventive measures should be introduced to minimize the health risks of workers exposed to these substances in the workplace.

References

1. d'Errico A, Pasian S, Baratti A, Zanelli R, Alfonzo S, Gilardi L et al. A case-control study on occupational risk factors for sino-nasal cancer. Occup Environ Med. Publish Ahead of Print, January 19, 2009

2. Roth F. Uber den bronchialkrebs arsengeschadigter winzer. Virchows Arch Pathol Anat 1958;331: 119-137.

3. Battista G, Bartoli D, Iaia TE, Dini F, Fiumalbi C, Ciglioli S et al. Art glassware and sinonasal cancer: report of three cases. Am J Ind Med 1996; 30: 31-35.

Dear Editor,

As described in this investigation only a minority workers with an occupational asthma due to a diisocyanate exposure have specific IgE antibodies towards the monomers (1).

Therefore, it is likely the host factors play an important role (2). However, their significance may not be so firm so as to be used as predictors of a disease. The concept is, however, important in the workers´ compensation cases if only those with specific antibodies or positive provocation test results outside the work place are accepted as valid cases.

1 Savolainen H. New mechanistic model for organic diisocyanate- induced respiratory disease. Schweiz Med Wochenschr 1999; 129: 465-7.

2 Berode M, Jost M, Ruegger M, Savolainen H. Host factors in occupational diisocyanate asthma: a Swiss longitudinal study. Int Arch Occup Environ Health 2005; 158-163.