A meta-analysis of asbestos and lung cancer: is better quality exposure assessment associated with steeper slopes of the exposure-response relationships?

Our plain-English summary of A meta-analysis of asbestos and lung cancer: is better quality exposure assessment associated with steeper slopes of the exposure-response relationships?, by V. Lenters, R. Vermeulen, S. Dogger, et al (Environmental Health Perspectives, 2011).

The study

• Authors: V. Lenters, R. Vermeulen, S. Dogger, L. Stayner, L. Portengen, A. Burdorf, D. Heederik
• Journal: Environmental Health Perspectives
• Published: 2011;119(11):1547-55
• Type of article: Meta-analysis, Review
• Cited by: 65 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Background: Asbestos is a well-recognized cause of lung cancer, but there is considerable between-study heterogeneity in the slope of the exposure-response relationship.

Objective: We considered the role of quality of the exposure assessment to potentially explain heterogeneity in exposure-response slope estimates.

Data Sources: We searched PubMed MEDLINE (1950-2009) for studies with quantitative estimates of cumulative asbestos exposure and lung cancer mortality and identified 19 original epidemiological studies. One was a population-based case-control study, and the others were industry-based cohort studies.

Data Extraction: Cumulative exposure categories and corresponding risks were abstracted. Exposure-response slopes [KL (lung cancer potency factor of asbestos)] were calculated using linear relative risk regression models.

Data Synthesis: We assessed the quality of five exposure assessment aspects of each study and conducted random effects univariate and multivariate meta-regressions. Heterogeneity in exposure-response relationships was greater than expected by chance (I2 = 64%). Stratification by exposure assessment characteristics revealed that studies with well-documented exposure assessment, larger contrast in exposure, greater coverage of the exposure history by exposure measurement data, and more complete job histories had higher meta-KL values than did studies without these characteristics. The latter two covariates were most strongly associated with the KL value. Meta-KL values increased when we incrementally restricted analyses to higher-quality studies.

Conclusions: This meta-analysis indicates that studies with higher-quality asbestos exposure assessment yield higher meta-estimates of the lung cancer risk per unit of exposure. Potency differences for predominantly chrysotile versus amphibole asbestos-exposed cohorts become difficult to ascertain when meta-analyses are restricted to studies with fewer exposure assessment limitations.

In plain English

This review was a meta-analysis of 19 studies of asbestos and lung cancer: 18 industry-based and one population-based case-control study. For each, the authors calculated KL, the rise in lung cancer relative risk per fiber-year per milliliter. They also rated five aspects of exposure assessment quality. Results varied more than chance would explain (I2 = 64%). Overall, KL (times 100) was 0.13 (95% CI 0.04 to 0.22). It was 0.33 (95% CI 0.09 to 0.56) for four mainly amphibole studies, 0.04 (-0.05 to 0.12) for five chrysotile studies and 0.13 (0.03 to 0.23) for ten mixed-exposure studies. Studies with better exposure assessment tended to show steeper slopes. Removing poorer-quality studies step by step raised KL to 0.55 (95% CI 0.11 to 0.99), based on the two studies left. Adjusting for job-history quality shrank the amphibole/mixed versus chrysotile difference from 0.13 (95% CI -0.03 to 0.29) to 0.05 (-0.22 to 0.31). The authors said the strong link between job history and fiber type complicates this comparison. They concluded that lung cancer potency differences between fiber types were difficult to distinguish.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Review: meta-analysis and meta-regression of published epidemiological studies, with an assessment of the quality of each study's exposure assessment
• Who was studied: 19 published studies with quantitative cumulative asbestos exposure and lung cancer risk estimates, found by searching PubMed/MEDLINE and EMBASE for studies published before 2010. 18 were industry-based studies (including one nested case-control study) of mines, mills, textile, friction product, cement and insulation workplaces in North America, Europe and Australia. One was a population-based case-control study in Stockholm County, Sweden (1,038 cases, 2,359 referents).
• Exposure: Cumulative asbestos exposure in fiber-years per milliliter (older particle counts converted to fibers). Each study was assigned a predominant fiber type: chrysotile (5 studies); amphiboles, meaning crocidolite, amosite or tremolite (4 studies); or mixed chrysotile and amphibole exposure (10 studies).
• Main results:
  • Across all 19 studies, the random effects meta-KL (times 100) was 0.13 (95% CI: 0.04, 0.22) with an intercept of 1.47. Heterogeneity between studies was high (I2 = 64%).
  • Under this model, that corresponds to a relative risk of 1.66 (95% CI: 1.53, 1.79) for lung cancer for each 100 fiber-years/mL increase in exposure.
  • By fiber type, the meta-KL (times 100) was 0.33 (95% CI: 0.09, 0.56) for amphiboles (four studies), roughly eight times higher than 0.04 (95% CI: -0.05, 0.12) for chrysotile (five studies). It was 0.13 (95% CI: 0.03, 0.23) for mixed fiber exposure (10 studies).
  • Studies with better exposure assessment had higher meta-KL values. The difference was most pronounced for coverage of the exposure history by measurements: 0.27 (95% CI: 0.08, 0.46) for more than 30% coverage versus 0.08 (95% CI: -0.01, 0.18) for 30% or less. It was also pronounced for job histories: 0.19 (95% CI: 0.08, 0.30) for sufficient versus 0.03 (95% CI: -0.10, 0.17) for insufficient. Both differences had p = 0.08.
  • Adjusting for sufficiency of job histories reduced the estimated KL difference for amphiboles/mixed versus chrysotile from 0.13 (95% CI: -0.03, 0.29) to 0.05 (95% CI: -0.22, 0.31). The authors noted that the strong correlation between job history and fiber type complicates inferences from this model.
  • Excluding poorer-quality studies step by step raised the meta-KL (times 100) from 0.13 (95% CI: 0.04, 0.22) with all 19 studies to 0.55 (95% CI: 0.11, 0.99) with the two remaining studies (South Carolina textile plant and Libby, MT vermiculite mines and mills).
  • A funnel plot and Egger's test gave some evidence of potential publication bias.
• The authors' conclusion: The authors concluded that combining only higher-quality studies gives higher estimates of lung cancer risk per unit of exposure. They found it difficult to distinguish lung cancer potency differences between chrysotile and amphiboles, because too many studies have major exposure assessment limitations. They wrote that the results cast doubt on assertions that the epidemiological evidence strongly supports a potency difference between fiber types.
• Limitations the authors state:
  • Only five exposure assessment covariates were analyzed. Other factors, such as sufficient latency, may also be related to the exposure-response slopes.
  • Rating the more subjective covariates (documentation and job histories) was limited by how much information the original study authors provided.
  • Point estimates for exposure categories, including the open-ended highest categories, were based on grouped rather than individual data, so information was lost.
  • Fiber type and job-history quality were strongly correlated, which complicates interpretation of the adjusted fiber-type comparison.
  • Restricting the analysis to fewer, higher-quality studies gave less precise estimates, and the exclusion strategy is not completely immune to bias.
  • Although the pattern of results held in sensitivity analyses, the absolute combined potency values depended on model assumptions.

Topics

The National Library of Medicine indexes this study under subjects our site covers: Chrysotile, Lung cancer.

Medical terms in this study, explained in our Lexicon: Meta-Analysis, Lung Cancer, Asbestos Exposure, Case-Control Study, Cumulative Exposure, Relative Risk, Exposure History, Chrysotile.

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• Lung cancer risk at low cumulative asbestos exposure: meta-regression of the exposure-response relationship — S. van der Bij, H. Koffijberg, et al. (2013)
• Quality of evidence must guide risk assessment of asbestos — V. Lenters, A. Burdorf, et al. (2012)
• Rapporteur's Report Session 5: assessment of health risk associated with exposure to non-asbestiform amphiboles including ingestion studies — B. Price (2008)
• Thinking about Occupation-Response and Exposure-Response Relationships: Vehicle Mechanics, Chrysotile, and Mesothelioma — K. Teschke (2016)
• Comparison of expert and job-exposure matrix-based retrospective exposure assessment of occupational carcinogens in The Netherlands Cohort Study — N.S. Offermans, R. Vermeulen, et al. (2012)

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