Comparison of false-positive rates of 2 hypothesis-test approaches in relation to laboratory toxicity test performance

We compared 2 statistical hypothesis-test approaches (no-observed-effect concentration [NOEC] and test of significant toxicity [TST]) to determine the influence of laboratory test performance on the false-positive error rate using the US Environmental Protection Agency's Ceriodaphnia dubia reproduction whole-effluent toxicity (WET) test endpoint. Simulation and power calculations were used to determine error rates based on observed control coefficients of variation (CV) for 8 laboratories over a range of effect levels. Average C. dubia control reproduction among laboratories was 20 to 40 offspring per female, and the 75th percentile CV was 0.10 to 0.31, reflecting a range in laboratory performance. The 2 approaches behave similarly for CVs of 0.2 to 0.3. At effects <10%, as CV decreases, TST is less likely to declare toxicity and NOEC is more likely to do so. Laboratory performance affects whether a sample is declared toxic and influences the probability of false-positive (and -negative) error rates using either approach. At the 75th percentile control CV observed for each laboratory, 4 laboratories would achieve approximately a 5% false-positive rate using 13 or fewer replicates for this test method. For the remaining 4 laboratories, more replicates would be needed to achieve a 5% false-positive rate. The present analyses demonstrate how false-positive rates are influenced by laboratory performance and WET test design. Environ Toxicol Chem 2019;38:511-523. Published 2019 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

Dose-Response Modeling with Summary Data from Developmental Toxicity Studies

Dose-response analysis of binary developmental data (e.g., implant loss, fetal abnormalities) is best done using individual fetus data (identified to litter) or litter-specific statistics such as number of offspring per litter and proportion abnormal. However, such data are not often available to risk assessors. Scientific articles usually present only dose-group summaries for the number or average proportion abnormal and the total number of fetuses. Without litter-specific data, it is not possible to estimate variances correctly (often characterized as a problem of overdispersion, intralitter correlation, or "litter effect"). However, it is possible to use group summary data when the design effect has been estimated for each dose group. Previous studies have demonstrated useful dose-response and trend test analyses based on design effect estimates using litter-specific data from the same study. This simplifies the analysis but does not help when litter-specific data are unavailable. In the present study, we show that summary data on fetal malformations can be adjusted satisfactorily using estimates of the design effect based on historical data. When adjusted data are then analyzed with models designed for binomial responses, the resulting benchmark doses are similar to those obtained from analyzing litter-level data with nested dichotomous models.

Human health effects of trichloroethylene: key findings and scientific issues

BACKGROUND

In support of the Integrated Risk Information System (IRIS), the U.S. Environmental Protection Agency (EPA) completed a toxicological review of trichloroethylene (TCE) in September 2011, which was the result of an effort spanning > 20 years.

OBJECTIVES

We summarized the key findings and scientific issues regarding the human health effects of TCE in the U.S. EPA's toxicological review.

METHODS

In this assessment we synthesized and characterized thousands of epidemiologic, experimental animal, and mechanistic studies, and addressed several key scientific issues through modeling of TCE toxicokinetics, meta-analyses of epidemiologic studies, and analyses of mechanistic data.

DISCUSSION

Toxicokinetic modeling aided in characterizing the toxicological role of the complex metabolism and multiple metabolites of TCE. Meta-analyses of the epidemiologic data strongly supported the conclusions that TCE causes kidney cancer in humans and that TCE may also cause liver cancer and non-Hodgkin lymphoma. Mechanistic analyses support a key role for mutagenicity in TCE-induced kidney carcinogenicity. Recent evidence from studies in both humans and experimental animals point to the involvement of TCE exposure in autoimmune disease and hypersensitivity. Recent avian and in vitro mechanistic studies provided biological plausibility that TCE plays a role in developmental cardiac toxicity, the subject of substantial debate due to mixed results from epidemiologic and rodent studies.

CONCLUSIONS

TCE is carcinogenic to humans by all routes of exposure and poses a potential human health hazard for noncancer toxicity to the central nervous system, kidney, liver, immune system, male reproductive system, and the developing embryo/fetus.

Uncertainties in biologically-based modeling of formaldehyde-induced respiratory cancer risk: identification of key issues

In a series of articles and a health-risk assessment report, scientists at the CIIT Hamner Institutes developed a model (CIIT model) for estimating respiratory cancer risk due to inhaled formaldehyde within a conceptual framework incorporating extensive mechanistic information and advanced computational methods at the toxicokinetic and toxicodynamic levels. Several regulatory bodies have utilized predictions from this model; on the other hand, upon detailed evaluation the California EPA has decided against doing so. In this article, we study the CIIT model to identify key biological and statistical uncertainties that need careful evaluation if such two-stage clonal expansion models are to be used for extrapolation of cancer risk from animal bioassays to human exposure. Broadly, these issues pertain to the use and interpretation of experimental labeling index and tumor data, the evaluation and biological interpretation of estimated parameters, and uncertainties in model specification, in particular that of initiated cells. We also identify key uncertainties in the scale-up of the CIIT model to humans, focusing on assumptions underlying model parameters for cell replication rates and formaldehyde-induced mutation. We discuss uncertainties in identifying parameter values in the model used to estimate and extrapolate DNA protein cross-link levels. The authors of the CIIT modeling endeavor characterized their human risk estimates as "conservative in the face of modeling uncertainties." The uncertainties discussed in this article indicate that such a claim is premature.

Enhancing toxicity test performance by using a statistical criterion

Aquatic toxicity tests are laboratory experiments that measure the biological effect (e.g., growth, survival, reproduction) of effluents, receiving waters, or storm water on aquatic organisms. These toxicity tests must be performed using the best laboratory practices, and every effort must be made to enhance repeatability of the test method. We evaluated the generated reference toxicant test data for insurance of a level of quality assurance for tests over time within a laboratory and among laboratories. We recommend the reporting and evaluation of the percent minimum significant difference (PMSD) value for all toxicity test results. The minimum significant difference (MSD) represents the smallest difference between the control mean and a treatment mean that leads to the statistical rejection of the null hypothesis (i.e., no toxicity) at each concentration of the toxicity test dilution series. The MSD provides an indication of within-test variability, and smaller values of MSD are associated with increased power to detect a toxic effect. We recommend upper and lower PMSD bounds for each test method in order to minimize within-test variability and increase statistical power. To ensure that PMSD does not exceed an upper bound, testing laboratories may need to increase replication, decrease variability among replicates, or increase the control mean performance.

Influence of baseline hematocrit and hemodilution on BOLD fMRI activation

Current understanding of blood oxygenation level dependent (BOLD) fMRI physiology predicts a close relationship between BOLD signal and blood hematocrit level. However, neither this relationship nor its effect on BOLD percent activation (BPA) has been empirically examined in man. To that end, BPA in primary visual cortex in response to photic stimulation was determined in a group of 24 normal subjects. A positive linear relationship between BPA and hematocrit was seen, particularly in men. To evaluate the effect of change in hematocrit on BPA, 9 men were studied before and following isotonic saline hemodilution, resulting in an average 6% reduction in hematocrit and an 8-31% reduction in BPA. No significant change in the number of activated pixels was seen. A model of predicted BPA as a function of hematocrit and vessel size was developed, and results from this model closely mirrored the empiric data. These results suggest that hematocrit significantly influences the magnitude of BPA and that such baseline factors should be accounted for when comparing BOLD data across groups of subjects, particularly in the many instances in which hematocrit may vary systematically. Such instances include several disease states as well as studies involving sex differences, drug administration, stress and other factors. Finally, the robust agreement between predicted and empiric data serves to validate a semiquantitative approach to the analysis of BOLD fMRI data.

Evaluation of the proximal flow field to circular and noncircular orifices of different aspect ratios

Investigations of valvular regurgitation attempt to specify flow field characteristics and apply them to the proximal isovelocity surface area (PISA) method for quantifying regurgitant flow. Most investigators assume a hemispherical shape to these equivelocity shells proximal to an axisymmetric (circular) orifice. However, in vivo flow fields are viscous and regurgitant openings vary in shape and size. By using centerline profiles and isovelocity surfaces, this investigation describes the flow field proximal to circular and elliptical orifices. Steady, proximal flow fields are obtained with two- and three-dimensional computational fluid dynamic (CFD) simulations. These simulations are verified by in vitro, laser-Doppler velocimetry (LDV) experiments. The data show that a unique, normalized proximal flow field results for each orifice shape independent of orifice flow or size. The distinct differences in flow field characteristics with orifice shape may provide a mechanism for evaluating orifice characteristics and regurgitant flows. Instead of the hemispherical approximation technique, this study attempts to show the potential to define a universal flow evaluation method based on the details of the flowfield according to orifice shape. Preliminary results indicate that Magnetic Resonance (MR) and Color Doppler (CD) may reproduce these flow details and allow such a procedure in vivo.

Forest fires and the snowshoe hare-Canada lynx cycle

This paper shows that there is a reasonable coincidence between the Canada lynx cycle and the occurrence of forest and brush fires. Fires set in motion plant succession, potentially leading to an increase in snowshoe hares (Grange, 1965). Snowfall is also correlated with the lynx cycle and tends to account for the variation not accounted for by fires. I conclude that Grange's (1949, 1965) hypothesis that fire and plant succession drive the snowshoe hare cycle deserves serious consideration, as do Butler's (1962) and Watt's (1968, 1973) suggestions that precipitation may drive or decisively modify furbearer 'cycles'. On this evidence, the snowshoe hare-Canada lynx cycle seems likely to be a forced oscillation rather than a predator-prey, parasitehost, or herbivore-vegetation limit cycle, as proposed by several authors. Fire clearly appear to be a periodic phenomenon, not-withstanding the difficulty of showing periodicity in simple weather time series. Fire is itself a meteorological phenomenon, although complexly related to simple weather variables.