A theoretical framework for estimation of AUCs in complete and incomplete sampling designs.

Nonclinical in vivo animal studies have to be completed before starting clinical studies of the pharmacokinetic behavior of a drug in humans. The drug exposure in animal studies is often measured by the area under the concentration versus time curve (AUC). The classic complete data design, where each animal is sampled for analysis once per time point, is usually only applicable for large animals. In the case of rats and mice, where blood sampling is restricted, the batch design or the serial sampling design needs to be considered. In batch designs samples are taken more than once from each animal, but not at all time points. In serial sampling designs only one sample is taken from each animal. In this paper we present an estimator for the AUC from 0 to the last time point that is applicable to all three designs. The variance and asymptotic distribution of the estimator are derived and confidence intervals based upon the asymptotic results are discussed and evaluated in a simulation study. Further, we define an estimator for linear combinations of AUCs and investigate its asymptotic properties mathematically as well as in simulation

Adaptive Survival Trials

Mid-study design modifications are becoming increasingly accepted in confirmatory clinical trials, so long as appropriate methods are applied such that error rates are controlled. It is therefore unfortunate that the important case of time-to-event endpoints is not easily handled by the standard theory. We analyze current methods that allow design modifications to be based on the full interim data, i.e., not only the observed event times but also secondary endpoint and safety data from patients who are yet to have an event. We show that the final test statistic may ignore a substantial subset of the observed event times. Since it is the data corresponding to the earliest recruited patients that is ignored, this neglect becomes egregious when there is specific interest in learning about long-term survival. An alternative test incorporating all event times is proposed, where a conservative assumption is made in order to guarantee type I error control. We examine the properties of our proposed approach using the example of a clinical trial comparing two cancer therapies.Comment: 22 pages, 7 figure

Terms in Popular Science Communication: The Case of TV Documentaries

Science documentaries on television aim to provide easy and entertaining access to research findings. To do so, producers need to know how to explain complex content for non-expert audiences in a comprehensible way. At the same time, they have to decide what aspects of a subject might be relevant for viewers, or how the subject matter could be rendered more interesting by employing strategies such as personalisation or emotionalisation. One specific decision concerns the use of terms. Both existing research and journalistic handbooks suggest that terms should be or are, in fact, avoided in popular science contexts. However, there is only little empirical research on the topic. This contribution seeks to test several pre-existing hypotheses on terms in documentaries for adults and show how often terms are used and whether/how they are explained when they appear. Examining terms in four English and four German science documentaries, the analysis points out which communicative resources are used to facilitate the comprehension of terms, and where an explanation seems to focus primarily on entertainment rather than ease of comprehension. The results challenge some of the previous views on terms in popular science communication and reveal that documentaries display highly idiosyncratic strategies when it comes to the use of terms