Estimation of benchmark dose ratio distributions for subchronic-to-chronic extrapolation using meta-analysis

Recently, the International Programme on Chemical Safety (IPCS) developed a unified probabilistic framework for deriving reference values and a software tool, Approximate Probabilistic Analysis (APROBA), to help implement this framework. The distributions of multiple sources of uncertainty and variability were estimated, including uncertainty when extrapolating from subchronic to chronic data. The subchronic-to-chronic distribution was estimated using ratios between subchronic and chronic benchmark doses (BMDs) and was determined to be approximately lognormal, with parameter values reported by IPCS. These parameters were estimated largely from historical data on body and organ weights from toxicological studies. We estimated the distribution using a larger collection of data, including histopathological and clinical endpoints. Our analysis determined that key assumptions of the method and the default values in APROBA are consistent with the results from the new data. However, the uncertainty of predictions for dichotomous response data was greater than assumed in APROBA, and the reference values derived using our new results were lower than those derived from APROBA (by 25% in an example case). Also, APROBA's default parameter values do not account fully for the uncertainty of predicted chronic BMDs. Most importantly, the uncertainty of the prediction can be much greater than assumed in APROBA if BMDs are accepted when they fall well outside the observed dose range or when an upper confidence limit is not quantifiable. Careful evaluation of dose-response model fit, including a number of indicators of model suitability in addition to standard goodness-of-fit statistics, is necessary to improve quantification of uncertainty.