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Model averaging methods for the evaluation of dose-response model uncertainty when assessing the suitability of studies for estimating risk.

ABSTRACT: This paper describes the use of multiple models and model averaging for considering dose-response uncertainties when extrapolating low-dose risk from studies of populations with high levels of exposure. The model averaging approach we applied builds upon innovative methods developed by the U.S. Food and Drug Administration (FDA), principally through the relaxing of model constraints. The relaxing of model constraints allowed us to evaluate model uncertainty using a broader set of model forms and, within the context of model averaging, did not result in the extreme supralinearity that is the primary concern associated with the application of individual unconstrained models. A study of the relationship between inorganic arsenic exposure to a Taiwanese population and potential carcinogenic effects is used to illustrate the approach. We adjusted the reported number of cases from two published prospective cohort studies of bladder and lung cancer in a Taiwanese population to account for potential covariates and less-than-lifetime exposure (for estimating effects on lifetime cancer incidence), used bootstrap methods to estimate the uncertainty surrounding the µg/kg-day inorganic arsenic dose from drinking water and dietary intakes, and fit multiple models weighted by Bayesian Information Criterion to the adjusted incidence and dose data to generate dose-specific mean, 2.5th and 97.5th percentile risk estimates. Widely divergent results from adequate model fits for a broad set of constrained and unconstrained models applied individually and in a model averaging framework suggest that substantial model uncertainty exists in risk extrapolation from estimated doses in the Taiwanese studies to lower doses more relevant to countries like the U.S. that have proportionally lower arsenic intake levels.

SUBMITTER: Mendez W

PROVIDER: S-EPMC7708422 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Immediate freezing at -20°C or below has been considered the gold standard for microbiome preservation, yet this approach is not feasible for many field studies, ranging from anthropology to wildlife conservation. Here we tested five methods for preserving human and dog fecal specimens for periods of up to 8 weeks, including such types of variation as freeze-thaw cycles and the high temperature fluctuations often encountered under field conditions. We found that three of the methods-95% ethanol, FTA cards, and the OMNIgene Gut kit-can preserve samples sufficiently well at ambient temperatures such that differences at 8 weeks are comparable to differences among technical replicates. However, even the worst methods, including those with no fixative, were able to reveal microbiome differences between species at 8 weeks and between individuals after a week, allowing meta-analyses of samples collected using various methods when the effect of interest is expected to be larger than interindividual variation (although use of a single method within a study is strongly recommended to reduce batch effects). Encouragingly for FTA cards, the differences caused by this method are systematic and can be detrended. As in other studies, we strongly caution against the use of 70% ethanol. The results, spanning 15 individuals and over 1,200 samples, provide our most comprehensive view to date of storage effects on stool and provide a paradigm for the future studies of other sample types that will be required to provide a global view of microbial diversity and its interaction among humans, animals, and the environment. IMPORTANCE Our study, spanning 15 individuals and over 1,200 samples, provides our most comprehensive view to date of storage and stabilization effects on stool. We tested five methods for preserving human and dog fecal specimens for periods of up to 8 weeks, including the types of variation often encountered under field conditions, such as freeze-thaw cycles and high temperature fluctuations. We show that several cost-effective methods provide excellent microbiome stability out to 8 weeks, opening up a range of field studies with humans and wildlife that would otherwise be cost-prohibitive.

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Model averaging methods for the evaluation of dose-response model uncertainty when assessing the suitability of studies for estimating risk.

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