Localized Pleural Thickening: Smoking and Exposure to Libby Vermiculite

ORIGINAL ARTICLE Localized pleural thickening: Smoking and exposure to Libby vermiculite

Krista Y. Christensen1 and Leonid Kopylev1

There is limited research on the combined effects of smoking and asbestos exposure on risk of localized pleural thickening (LPT). This analysis uses data from the Marysville cohort of workers occupationally exposed to Libby amphibole asbestos (LAA). Workers were interviewed to obtain work and health history, including ever/never smoking and chest X-rays. Cumulative exposure estimates were developed on the basis of fiber measurements from the plant and work history. Benchmark concentration (BMC) methodology was used to evaluate the exposure--response relationship for exposure to LAA and a 10% increased risk of LPT, considering potential confounders and statistical model forms. There were 12 LPT cases among 118 workers in the selected study population. The mean exposure was 0.42 (SD ¼ 0.77) fibers/cc-year, and the prevalence of smoking history was 75.0% among cases and 51.9% among non-cases. When controlling for LAA exposure, smoking history was of borderline statistical significance (P-value ¼ 0.099), and its inclusion improved model fit, as measured by Akaike’s Information Criterion. A comparison of BMC estimates was made to gauge the potential effect of smoking status. The BMC was 0.36 fibers/ cc-year, overall. The BMC for non-smokers was approximately three times as high (1.02 fibers/cc-year) as that for the full cohort, whereas the BMC for smokers was about 1/2 that of the full cohort (0.17 fibers/cc-year).

Journal of Exposure Science and Environmental Epidemiology (2012) 22, 320--323; doi:10.1038/jes.2012.18; published online 25 April 2012 Keywords: Libby; amphibole; asbestos; vermiculite; smoking; localized pleural thickening

INTRODUCTION vermiculite mine near Libby, MT, USA.9 Epidemiological studies of 10,11 12,13 Asbestos exposure and smoking are both known to impact the worker cohorts in Libby, MT, USA, and Marysville, OH, USA, risk of respiratory disease. The combined effects of asbestos and exposed to LAA fibers indicate increased risk of radiographic smoking have been evaluated for certain respiratory outcomes --- abnormalities, and that the latency period for development of for lung cancer,1 and possibly for asbestosis,2 the effects of radiographic abnormalities may be relatively short (median asbestos exposure and smoking combined appear to be greater latency of 8.6 years for pleural plaques in retrospective investiga- than effects predicted by additivity. In contrast, smoking does not tion of serial radiographs).14 Each of these cohort studies con- appear to increase the risk of mesothelioma.2 However, there have sidered smoking in their analytic approach. In the Libby workers been fewer informative studies evaluating the effects of these two cohort, McDonald et al.11 assessed pleural thickening of the chest factors together on radiographic abnormalities of the lung and wall and found smoking status (current, former, or never smoker) pleura. Radiographic non-cancer abnormalities are of interest was of borderline statistical significance (P ¼ 0.10) in a regression because they tend to occur sooner after exposure, compared model, controlling for LAA exposure and age. Amandus et al.10 with asbestosis and other severe outcomes (e.g., lung cancer, also evaluated radiographic abnormalities, constructing separate mesothelioma), and are irreversible pathological changes asso- models for the full cohort, and restricting to current and former ciated with decrements in lung function.3 One example of such a smokers. The parameter estimates for LAA exposure were not radiographic abnormality is pleural thickening, a condition in significant for the two models when controlling for age. In the which the pleural lining around the lungs (visceral pleura) or along Marysville workers cohort, smoking was characterized using pack- the chest wall and diaphragm (parietal pleura) thicken because of years in the original study,12 and was significantly associated with fibrosis and collagen deposits.3 This thickening may be character- risk of all radiographic changes using discriminant analysis. ized as either localized pleural thickening (LPT) or diffuse, with However, results for LPT specifically, or for the effect of smoking diffuse thickening representing an endpoint of greater severity. controlling for LAA exposure, were not reported. The follow-up In the current International Labour Organization (ILO) classifica- study by Rohs et al.13 did not find a difference in smoking pre- tion, LPT includes both pleural plaques (focal areas of pleural valence among those with and without any radiographic changes, thickening generally present at the parietal pleura, diaphragm but also did not report results for LPT specifically, or controlling for or chest wall) and pleural thickening that does not involve LAA exposure. blunting of the costophrenic angle between the rib cage and Among populations exposed to general asbestos, two studies the diaphragm.4 LPT is associated with constricting pain5,6 and reported a significant association between risk of all pleural reduced lung function.7,8 thickening (including both pleural plaques and diffuse pleural Libby amphibole asbestos (LAA) is a mixture of amphibole fibers thickening,15 or any pleural abnormality16) and smoking identified in the Rainy Creek complex and present in ore from the after controlling for some measure of asbestos exposure. A larger

1National Center for Environmental Assessment, Office of Research and Development, United States Environmental Protection Agency, Washington, District of Columbia, USA. Correspondence to: Dr Krista Y. Christensen, Mailstop 8623P, 1200 Pennsylvania Avenue NW, Washington, DC 20460, USA. Tel.: þ 1 703 347 0185. Fax: þ 1 703 347 8692. E-mail: [email protected] Received 26 January 2012; accepted 29 March 2012; published online 25 April 2012 Localized pleural thickening, smoking and Libby vermiculite Christensen and Kopylev 321 number of studies reported borderline --- or possible --- associa- a sub-cohort of the Marysville workers, which includes data on 118 workers tions when examining risk of pleural changes17--22 or no from the 280 workers in the 2002--2005 examination, and who began work association with smoking.23--27 Possible reasons for the different in 1972 or later (12 cases of LPT and 106 unaffected individuals), were findings include varying quality of the exposure assessment and selected from the full cohort for analysis. the smoking information (some used categories of ever/never or former/current/never, whereas others used pack-years) and Analysis differences in the specific outcome studied. For studies that 34 evaluated pleural thickening as an endpoint, it should be noted Benchmark concentration (BMC) methodology was used to evaluate the that the definition of LPT under the ILO classification system has exposure--response relationship for exposure to LAA and risk of LPT. In this changed over time. Discrete pleural plaques as defined in earlier approach, the available data are fit to a set of mathematical exposure-- ILO classification systems have not been associated with smoking response models to determine an appropriate empirical representation of in asbestos-exposed workers,28--30 but there is evidence that the data. General model fit was evaluated using the Hosmer--Lemeshow 2 asbestosis (small opacities) and diffuse pleural thickening may be test, a form of the Pearson’s w goodness-of-fit statistic used for dicho- 2,15 tomous models.35 Among models with adequate general fit, the model associated with smoking in asbestos-exposed individuals. 36 We are not aware of studies that assess the relationship with the best fit as measured by the Akaike’s Information Criterion (AIC; ) between LPT, as it is currently defined,4 and any measure of was selected. The AIC is a measure of model fit, and a smaller value is smoking status for LAA or general asbestos. Therefore, this considered to reflect better model fit. The BMC is estimated as the analysis investigates potential for smoking to modify the effect of exposure level, calculated from the best-fit model, which results in a LAA asbestos exposure on the prevalence of LPT. We used data specified benchmark response. A 10% extra risk is recommended for 37 from the Marysville cohort of workers exposed to LAA to evaluate standard reporting purposes and this value was used in this analysis. All the effect of smoking on risk of LPT. analyses were performed using SAS statistical software v. 9.1. Dichotomous statistical models (that allow estimation of the background term) describing the probability of individual response as a function of cumulative exposure (represented by CE in units of fibers/cc- METHODS year) were used. The candidate mathematical models were 3-parameter Study Population log-logistic, dichotomous Hill and dichotomous Michaelis--Menten models Vermiculite, mined in Libby, MT, USA, and contaminated with LAA, was (model forms are as follows, where CE ¼ cumulative exposure and g ¼ used in the production of numerous commercial products, including as a background rate: 3-parameter log-logistic: P(LPT) ¼ g þ (1Àg)/[1 þ exp potting soil amender and a carrier for pesticides and herbicides. The (ÀaÀb Â ln(CE))]; dichotomous Hill: P(LPT) ¼ g þ (PlateauÀg)/[1 þ exp(ÀaÀ Marysville cohort includes workers at a Marysville, OH, USA, plant that used b Â ln(CE))]; Michaelis--Menten: P(LPT) ¼ g þ (PlateauÀg)/[1 þ exp(ÀaÀ Libby vermiculite in the production of fertilizer, beginning around 1960 ln(CE))]). For each of the candidate models, exposure lags of 0, 5, 10, 15 to 1980.12 The first study of pulmonary effects in these workers was and 20 years were investigated. These lags were chosen to investigate conducted in 1980 and involved 512 workers who underwent physical the relative model fit, rather than being based on specific biological examination, spirometry and chest X-rays; trained interviewers gathered considerations. Although we explored models with exposure lagged by information on smoking history, work history at the plant and other 20 years, there were cases of LPT in the Marysville cohort with fewer than relevant work exposures.12 A follow-up study was conducted in 2002-- 20 years since first exposure; therefore, using such a long lag (which 2005, and included 298 (of the original 512) workers, of which 280 necessitates the assumption that these are background cases) was not completed the study interview and chest X-ray.13 As in the original study, judged to be appropriate. workers were interviewed to obtain work and health history, and Smoking history was characterized using a ‘‘yes/no’’ variable, indicating spirometry, pulmonary examination and chest X-rays were performed. ever or never smoker. To investigate the key explanatory variables for Smoking was self-reported at in-person interview (2004--2005) and analysis, a forward-selection process was used to evaluate the association classified as any smoking history or no smoking history.13 Three board- of each of the potential covariates with the risk of LPT, controlling for LAA certified radiologists, blinded to any identifying information, indepen- exposure, in the best-fitting model. Covariates considered for inclusion in dently classified the radiographs using the ILO classification system.4 the model were time from first exposure, age at X-ray, gender and BMI. The exposure reconstruction in Rohs et al.13 was updated in this study Covariates were evaluated according to statistical significance of the for all workers in the Marysville, OH, USA, cohort.13,31,32 The update took covariate, and whether inclusion of the covariate improved model fit as into account additional industrial hygiene data that were not available for assessed by the AIC. the studies by Rohs et al.13 or Lockey et al.12 Exposure estimates up through the year 2000 were developed on the basis of fiber measurements from the plant when available, and estimated fiber concentrations (based RESULTS on employee interview and later fiber measurements) for the period before Characteristics of the study population are presented in Table 1. industrial hygiene measurements were taken. Using available data on the The study population comprised 12 cases of LPT and 106 year of hire and the departments in which each person worked, the individuals with no radiographic abnormalities. There were 13 cumulative exposure (fibers/cc-year) for each worker for each year since women overall (11.0%), of which 1 was an LPT case. Age at X-ray thedateofhirewasestimated,incorporating seasonal fluctuations in working ranged from 42 to 82 years, with a mean of 52 (SD ¼ 7) years, hours and assuming any exposure off site to be zero. This assumption is whereas time from first exposure ranged from 23.2 to 32.6 years, likely to be justified, given that the company policy was to launder the with a mean of 28.2 (SD ¼ 2.5) years. Exposure, as characterized by employees’ work clothes and provide showers for use after work. Each CE, ranged from 0.001 to 5.51 fibers/cc-year, and the mean was worker’s cumulative exposure was then adjusted to a cumulative human 0.42 (SD ¼ 0.77) fibers/cc-year. The prevalence of any smoking equivalent exposure33 for continuous exposure (CE; fibers/cc-year). history was 54.2% overall, 75.0% (n ¼ 9) among cases and 51.9% In the Marysville cohort, the more accurate exposure data are con- (n ¼ 55) among non-cases. Age at X-ray and time from first sidered to be those from 1972 and later, as these data were based on exposure were similar for non-smokers and smokers (mean ages analytical measurements, whereas no analytical measurements exist of 51.2 (SD ¼ 5.8) and 52.5 (SD ¼ 7.9) years, respectively; mean before 1972. Because of the longer follow-up time and additional covariate times from first exposure of 28.1 (SD ¼ 2.5) and 28.9 (SD ¼ 2.8) information, the most informative outcome data come from the 2002 to years, respectively), as was CE (mean values of 0.44 (SD ¼ 0.91) and 2005 examination. To avoid any bias from previous occupational exposure 0.40 (SD ¼ 0.63) fibers/cc-year, respectively). Each of the candidate to asbestos, only the data from those who did not report any previous models evaluated had adequate general fit (all Hosmer--Leme- occupational exposure to asbestos were used. Based on these considerations, show goodness-of-fit P-values Z0.33), and the AIC values were

& 2012 Nature America, Inc. Journal of Exposure Science and Environmental Epidemiology (2012), 320 -- 323 Localized pleural thickening, smoking and Libby vermiculite Christensen and Kopylev 322 Table 1. Characteristics of the study population. was approximately six times lower compared with that for non- smokers, that is, comparable extra risk of health effects for N%smokers happen at an LAA concentration that is six times lower than that for non-smokers. This difference in the effect of LAA Total (n) 118 100 exposure across smoking strata indicates smoking may be an Localized pleural thickening 12 10.2 effect modifier of the association between LAA exposure and LPT. Female 13 11.0 A formal test of interaction was not statistically significant, but this Ever smoker 64 54.2 may be due to the limited sample size and relatively crude measure of smoking. It has long been known that smoking impairs clearance of Mean (SD) Range particles from the lung,42,43 and animal models indicate that cigarette smoke increases the deposition of asbestos fibers Age at X-ray (years) 52 (7) 42--82 44,45 Time from first exposure (years) 28.2 (2.5) 23.2--32.6 specifically. Therefore, smokers may retain more inhaled Job tenure (years) 18.7 (8.6) 0.3--29.0 asbestos fibers and for a longer period of time, compared with Cumulative exposure (fibers/cc-year) 0.42 (0.77) 0.001--5.51 non-smokers, even if both have the same initial exposure. Another Body mass index (BMI) 31.4 (6.9) 20.1--62.0 possibility is that smoking might affect the timing and progression of LPT development. If LPT develops sooner among smokers compared with non-smokers, this could lead to a higher prevalence of LPT among smokers at a given observation time, and quite similar (ranging from 75.2 to 77.2). The model with the lowest subsequently higher estimated risk. AIC was the Michaelis--Menten model with 10-year lagged exposure We evaluated age at X-ray, time from first exposure, gender and (AIC ¼ 75.2, Hosmer--Lemeshow goodness-of-fit P-value ¼ 0.71). BMI as potential covariates, but none of these were significantly When controlling for the effect of LAA exposure, there was no associated with risk of LPT after controlling for LAA exposure. It is association between risk of LPT and time from first exposure possible that the age or time from first exposure could act as a (P-value ¼ 0.94), age at X-ray (P-value ¼ 0.82) or gender (P-value ¼ proxy for smoking and vice versa, as among smokers, older/longer 0.45), and inclusion of each of these covariates increased the AIC. employed individuals would generally have a longer smoking history. Age is known to be significantly associated with risk of As some workers (n ¼ 21) were missing BMI information, the effect 10 of BMI could not be estimated simultaneously with the back- pleural changes even after controlling for LAA exposure ; ground parameter; therefore, the latter was fixed at 1% for this however, neither age nor time from first exposure were significant analysis only (P-value for BMI ¼ 0.38). This background value is here, nor did they improve the model fit as measured by the AIC. within the range of previously published estimates of the back- This is likely because of the decision to include only those workers ground incidence of LPT.38--41 These covariates were not con- hired in 1972 or later, which made workers in the sub-cohort more sidered in further analyses. similar to each other in age and time from first exposure. The variable representing smoking history was of borderline Therefore, it is unlikely that the possible effects of smoking statistical significance (P-value ¼ 0.099), and inclusion of this suggested in this analysis are surrogate for the effect of age or variable (Model 2) decreased the AIC by more than a unit (from time from first exposure. 75.2 to 74.0). The following Michaelis--Menten model forms were There are some limitations to this analysis. First, differing used for statistical analysis, where CE10 is the cumulative exposure definitions and classifications used for the outcome (discrete lagged 10 years: (Model 1) P(LPT) ¼ g þ (PlateauÀg)/[1 þ exp(À pleural plaques or LPT, under different versions of the ILO (a þ ln(CE10)))]; (Model 2) P(LPT) ¼ g þ (PlateauÀg)/[1 þ exp(À(a þ guidelines) limit the ability to compare these results with those ln(CE10) þ beta*Smoking))]; (Model 3) P(LPT) ¼ g þ (PlateauÀg)/ from many previous studies. In this study, the smoking variable [1 þ exp(À(a þ ln(CE 10) þ beta*Smoking þ beta2*ln(CE10) was of borderline statistical significance, potentially due to the *Smoking))]). A third model (Model 3) was fit, which added an limited number of individuals in the analysis. Also, we did not have interaction term between the exposure metric and smoking; in BMI information for all subjects, which limited our ability to this model, neither the smoking variable by itself nor the inter- evaluate the effect of BMI on risk of LPT. This is an important consideration, as fat pads may be mistaken for pleural thickening action term were significant (P-value ¼ 0.230 and 0.582, respec- 46 tively) and the AIC increased from the base model (AIC of 75.5). on radiographic examination, leading to potential misdiagnosis. The Michaelis--Menten model with exposure lagged by 10 years There were more analytical exposure measurements available yielded a BMC of 0.36 fibers/cc-year. Model 2, which includes the for later years than for the earlier years for the sub-cohort. The smoking variable, was used to derive estimates for smokers and lack of detailed smoking information in this cohort (such as pack- non-smokers separately. A comparison of BMC estimates was years) and the relatively small number of non-smokers (only three made to gauge the potential effect of smoking status. The BMC cases were non-smokers) implies some limitations for the analysis was derived by setting the beta coefficient for smoking to zero for of the effect of smoking on LPT risk among individuals exposed non-smokers, and to the MLE-estimated value (1.80) for smokers. to LAA. The BMC for non-smokers was about three times as high as that Nevertheless, these analyses suggest that smoking may be an for the full cohort (1.02 fibers/cc-year), whereas the BMC for important factor to consider in further studies of LPT among smokers was about 1/2 that of the full cohort (0.17 fibers/cc-year). populations exposed to LAA, and potentially, asbestos in general. The BMC (i.e., the level of exposure associated with a 10% extra risk of LPT in this study) estimated separately for smokers (0.17 fibers/cc-year) and non-smokers (1.02 fibers/cc-year) differs by six- DISCUSSION fold, which we consider a notable difference. For context, the We used data from the Marysville cohort of workers occupation- mean cumulative exposure in the study population was 0.42 ally exposed to LAA to evaluate the joint effects of LAA exposure fibers/cc-year --- about half of the difference between the two and smoking on risk of LPT. In the best-fitting model, a variable BMC estimates. Further studies using more detailed information suggesting an effect of smoking history on increased prevalence on smoking and more sensitive outcome evaluation methods (i.e., of pleural plaques was of borderline statistical significance. high-resolution computed tomography), as well as larger cohorts, We used this model to evaluate how smoking status could should add to our understanding of the interplay between potentially affect BMC estimates; the estimated BMC for smokers smoking and asbestos exposure on risk of health effects.

Journal of Exposure Science and Environmental Epidemiology (2012) 320 -- 323 & 2012 Nature America, Inc. Localized pleural thickening, smoking and Libby vermiculite Christensen and Kopylev 323 CONFLICT OF INTEREST 22 Zitting A.J., Karjalainen A., Impivaara O., Kuusela T., Maki J., and Tossavainen A., The authors declare no conflict of interest. et al. Radiographic small lung opacities and pleural abnormalities in relation to smoking, urbanization status, and occupational asbestos exposure in Finland. J Occup Environ Med 1996: 38(6): 602--609. ACKNOWLEDGEMENTS 23 Delclos G.L., Wilson R.K., and Bradley B.L. Influence of smoking on radiographic We would like to acknowledge James Lockey for provision of the data, and Bob profusion and pleural changes in asbestos-exposed subjects. J Occup Environ Med Benson and Danielle DeVoney for valuable technical advice. 1990: 32(7): 577--581. 24 Ehrlich R., Lilis R., Chan E., Nicholson W.J., and Selikoff I.J. 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& 2012 Nature America, Inc. Journal of Exposure Science and Environmental Epidemiology (2012), 320 -- 323