Biomedical subjects

Wout Slob

Publications and source records attributed to Wout Slob.

9 recordsLinked to original sources

PubMed2006

A 28-day oral dose toxicity study enhanced to detect endocrine effects of hexabromocyclododecane in Wistar rats.

A 28-day repeated dose study in rats (OECD407) enhanced for endocrine and immune parameters was performed with hexabromocyclododecane (HBCD). Rats were exposed by daily gavage to HBCD dissolved in corn oil in 8 dose groups with doses ranging between 0 and 200 mg/kg bw per day (mkd). Evaluation consisted of dose-response analysis with calculation of a benchmark dose at the lower 95% one-sided confidence bound (BMDL) at predefined critical effect sizes (CESs) of 10-20%. The most remarkable findings were dose-related effects on the thyroid hormone axis, that is, decreased total thyroxin (TT4, BMDL 55.5 mkd at CES--10%), increased pituitary weight (29 mkd at 10%) and increased immunostaining of TSH in the pituitary, increased thyroid weight (1.6 mkd at 10%), and thyroid follicle cell activation. These effects were restricted to females. Female rats also showed increased absolute liver weights (22.9 mkd at 20%) and induction of T4-glucuronyl transferase (4.1 mkd at 10%), suggesting that aberrant metabolization of T4 triggers feedback activation of the thyroid hormone system. These effects were accompanied by possibly secondary effects, including increased cholesterol (7.4 mkd at 10%), increased tibial bone mineral density (> 49 mkd at 10%), both in females, and decreased splenocyte counts (0.3-6.3 mkd at 20%; only evaluated in males). Overall, female rats appeared to be more sensitive to HBCD than male rats, and an overall BMDL is proposed at 1.6 mkd, based on a 10% increase of the thyroid weight, which was the most sensitive parameter in the sequence of events.

Administration, Oral↗

PubMed2006

Probabilistic dietary exposure assessment taking into account variability in both amount and frequency of consumption.

Probabilistic dietary exposure assessments that are fully based on Monte Carlo sampling from the raw intake data may not be appropriate. This paper shows that the data should first be analysed by using a statistical model that is able to take the various dimensions of food consumption patterns into account. A (parametric) model is discussed that takes into account the interindividual variation in (daily) consumption frequencies, as well as in amounts consumed. Further, the model can be used to include covariates, such as age, sex, or other individual attributes. Some illustrative examples show how this model may be used to estimate the probability of exceeding an (acute or chronic) exposure limit. These results are compared with the results based on directly counting the fraction of observed intakes exceeding the limit value. This comparison shows that the latter method is not adequate, in particular for the acute exposure situation. A two-step approach for probabilistic (acute) exposure assessment is proposed: first analyse the consumption data by a (parametric) statistical model as discussed in this paper, and then use Monte Carlo techniques for combining the variation in concentrations with the variation in consumption (by sampling from the statistical model). This approach results in an estimate of the fraction of the population as a function of the fraction of days at which the exposure limit is exceeded by the individual.

Adolescent↗

PubMed2005

A comparison of ratio distributions based on the NOAEL and the benchmark approach for subchronic-to-chronic extrapolation.

One approach to derive a data-based assessment factor (AF) for subchronic-to-chronic extrapolation is to determine ratios between the NOAEL(subchronic) and NOAEL(chronic) for the same compounds. Instead of using ratios of NOAELs, the distribution can also be estimated by ratios of subchronic and chronic Benchmark Doses (or Critical Effect Doses, CEDs, for continuous data). In this study 314 dose-response datasets on body weights and liver weights of mice and rats were selected providing dose-response information after both subchronic and chronic exposure. NOAEL ratios could be derived in only 68 of these datasets, while CED ratios could be derived in 189 datasets. When only the (53) datasets suitable for both approaches were evaluated the variation of the CED ratio distribution (GSD [geometric standard deviation]: 2.9) was smaller than the one of the NOAEL ratio distribution (GSD: 3.3). After correcting for the estimation error of the individual CED ratios the GSD of the CED distribution decreased to 2.3. The geometric means (GMs) of the NOAEL and CED distributions were similar (1.2 and 1.6, respectively). Comparing the NOAEL distribution based on all 68 datasets suitable for deriving NOAEL ratios with the CED distribution based on the 189 ratios suitable for deriving CED ratios resulted in similar GMs (1.5 and 1.7, respectively), but the GSDs differed considerably (5.3 and 2.3 respectively). It is concluded that usage of the CED approach results in less wide distributions. Furthermore, a larger fraction of available datasets is useful to inform the ratio distribution. This results in more accurate, and less conservative distributions of AFs in general compared to the distributions based on NOAEL ratios that have been proposed so far.

Algorithms↗

PubMed2005

Probabilistic risk characterization: an example with di(2-ethylhexyl) phthalate.

While probabilistic methods gain attention in hazard characterization and are increasingly used in exposure assessment, full use of the available probabilistic information in risk characterization is still uncommon. Usually, after probabilistic hazard characterization and/or exposure assessment, percentiles from the obtained distributions are used as point estimates in risk characterization. In this way, all information on variability and uncertainty is lost, while these aspects are crucial in any risk assessment. In this paper, we present a method to integrate the entire distributions from probabilistic hazard characterization and exposure assessment into one risk characterization plot. This method is illustrated using di(2-ethylhexyl) phthalate as an example. The final result of this probabilistic risk assessment is summarized in a single plot, containing two pieces of information: the confidence we may have in concluding there is no risk, and the fraction of the population this conclusion applies to. This information leads to a better informed conclusion on the risk of a substance, and may be very useful to define the necessary measures for risk reduction.

Adult↗

PubMed2004

A statistical evaluation of toxicity study designs for the estimation of the benchmark dose in continuous endpoints.

The benchmark approach is gaining attention as an alternative to the No-Observed-Adverse-Effect-Level (NOAEL) approach. However, current guidelines for the design of toxicity tests are based on assessing a NOAEL. It has been suggested that the current study design may not be optimal for assessing a Benchmark Dose (BMD). To further investigate this we performed three simulation studies in which a large number of designs were compared, focusing on continuous endpoints. Four fictitious endpoints were considered, their underlying dose-response curves having a linear, sublinear, supralinear, or sigmoidal shape. In each simulation run the BMD was derived from a model fitted to the generated data, where the selection of the model was based on that particular data set (according to a formal likelihood ratio test procedure). Thus, the model used for deriving the BMD in a single generated data set may not be the same as the one used for generating the data. In this way, model uncertainty is taken into account as well. The results show that the performance of a design is, first of all, determined by the total number of animals used. Distributing them over more dose groups does not result in a poorer performance of the study, despite the smaller number of animals per dose group. Dose placement is another crucial factor, and to minimize the risk of inadequate dose placement, the use of multiple dose studies is favorable. As a concomitant advantage, the use of multiple doses mitigates the disturbing effect of potential systematic errors in single dose groups. However, for endpoints with large residual variation (CV > or = 18%) there is a substantial probability of not detecting the overall dose-response, and this probability increases in designs with increasing number of dose groups. In such situations, six dose groups may be used as a compromise. Designs with high dose levels (i.e., associated with relatively high effects) are helpful in estimating doses with smaller effects (such as the benchmark dose), and it appears bad practice to omit higher dose groups to improve the fit at lower doses. The typical 28-day study design of four dose groups with five animals (per sex) may not be adequate to assess endpoints with large residual variation (CV > or = 18%), both in assessing a benchmark dose and in assessing a NOAEL.

Animals↗

PubMed2004

Reduced intake of deoxynivalenol in The Netherlands: a risk assessment update.

In 1998 and 1999, wheat contained high levels of deoxynivalenol (DON) in The Netherlands. Eighty percent of the 1-year-old children exceeded the TDI (20% exceeded 2TDI). Assuming a long-term intake a negative effect on body weight might be possible. In 1999 the Dutch government took several risk management measures. We performed a probabilistic exposure and effect assessment and compared current and previous DON exposure and potential health effects for young children. The DON contamination of wheat was reduced for 50%. The estimated DON-intake was reduced to one-third of the previous levels. One-year-old children showed the highest DON-intake with a median of 0.46 microg/kgbw/day (95th percentile: 1.00 microg/kgbw/day). The probabilistic effect assessment showed that at the 95th percentile of DON-intake a reduced body weight was unlikely to exceed 9%. Taking into account the possible (partly) reversibility of this effect we conclude that no clear adverse health effects will be associated to the exposure (February 2000-December 2002) to DON in The Netherlands.

Adolescent↗

PubMed2004

A comparison of three methods for calculating confidence intervals for the benchmark dose.

Various methods exist to calculate confidence intervals for the benchmark dose in risk analysis. This study compares the performance of three such methods in fitting nonlinear dose-response models: the delta method, the likelihood-ratio method, and the bootstrap method. A data set from a developmental toxicity test with continuous, ordinal, and quantal dose-response data is used for the comparison of these methods. Nonlinear dose-response models, with various shapes, were fitted to these data. The results indicate that a few thousand runs are generally needed to get stable confidence limits when using the bootstrap method. Further, the bootstrap and the likelihood-ratio method were found to give fairly similar results. The delta method, however, resulted in some cases in different (usually narrower) intervals, and appears unreliable for nonlinear dose-response models. Since the bootstrap method is more time consuming than the likelihood-ratio method, the latter is more attractive for routine dose-response analysis. In the context of a probabilistic risk assessment the bootstrap method has the advantage that it directly links to Monte Carlo analysis.

Animals↗

PubMed2002

Risk assessment of deoxynivalenol in food: concentration limits, exposure and effects.

The mycotoxin, deoxynivalenol (DON), is produced world-wide by the Fusarium genus in different cereal crops. We derived a provisional TDI of 1.1 microg/kg body weight (bw) and proposed a concentration limit of 129 microg DON/kg wheat based on this TDI and a high wheat consumption of children. In the period September 1998-January 2000, the average DON concentration in wheat was 446 microg/kg (n = 219) in The Netherlands. During this period, the dietary intake of DON exceeded the provisional TDI, especially in children. Eighty percent of the one-year-olds showed a DON intake above the provisional TDI and 20% of these children exceeded twice the provisional TDI. Our probabilistic effect assessment shows that at these exposure levels, health effects may occur. Suppressive effects on body weights and relative liver weight were estimated at 2.2 and 2.7%. However, the large confidence intervals around these estimates indicated that the magnitudes of these effects are uncertain.

Animals↗

PubMed2002

Dose-response modeling of continuous endpoints.

A family of (nested) dose-response models is introduced herein that can be used for describing the change in any continuous endpoint as a function of dose. A member from this family of models may be selected using the likelihood ratio test as a criterion, to prevent overparameterization. The proposed methodology provides for a formal approach of model selection, and a transparent way of assessing the benchmark dose. Apart from a number of natural constraints, the model expressions follow from an obvious way of quantifying differences in sensitivity between populations. As a consequence, dose-response data that relate to both sexes can be efficiently analyzed by incorporating the data from both sexes in the same analysis, even if the sexes are not equally sensitive to the compound studied. The idea of differences in sensitivity is closely related to the assessment factors used in risk assessment. Thus, the models are directly applicable to estimating such factors, if data concerning populations to be compared are available. Such information is valuable for further validation or adjustment of default assessment factors, as well as for informing distributional assessment factors in a probabilistic risk assessment. The various applications of the proposed methodology are illustrated by real data sets.

Animals↗