Quantitative meta-analytic approaches for the systematic synthesis of data and hazard identification: A case study of decreased pain sensitivity due to trimethylbenzene exposure

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Abstract

Traditionally, human health risk assessments have relied on qualitative approaches for hazard identification, which involves weight of evidence determinations that integrate evidence across multiple studies. Recently, the National Research Council has recommended the development of quantitative approaches for evidence integration, including the application of meta-analyses, to help summarize and evaluate the results of a systematic review. In the meta-analytic approach, a pooled effect size is calculated after consideration of multiple potential confounding factors in order to determine whether the entire database under consideration indicates a chemical is a hazard. The following case-study applies qualitative and quantitative approaches to determine whether trimethylbenzene (TMB) isomers represent a neurotoxic hazard, specifically focusing on pain sensitivity. Following a thorough literature search, the only pain sensitivity studies available for TMBs initially seem discordant in their results: effects on pain sensitivity are seen immediately after termination of exposure, appear to resolve 24 h after exposure, and then reappear 50 days later following foot-shock. Qualitative consideration of toxicological and toxicokinetic characteristics of the TMB isomers suggests that the observed differences between studies are likely due to testing time and the application of external stressors. Meta-analyses and –regressions support this conclusion: when all studies are included and possible confounders (isomer, testing time, laboratory, etc.) are accounted for, the pooled effect sizes are statistically significant, thus supporting that TMBs are a possible neurotoxic hazard to human health. Ultimately, this case study demonstrates how qualitative and quantitative methods can be combined to provide a robust hazard identification analysis by incorporating more of the available information.

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