Summary paragraphAn outbreak of acute hepatitis of unknown aetiology in children was first reported in Scotland in April 2022.1 Cases aged <16 years have since been identified in 35 countries.2 Here we report a detailed investigation of 9 early cases and 58 control subjects. Using next-generation sequencing and real-time PCR, adeno-associated virus 2 (AAV2), was detected in the plasma of 9/9 and liver of 4/4 patients but in 0/13 sera/plasma of age-matched healthy controls, 0/12 children with adenovirus (HAdV) infection and normal liver function and 0/33 children admitted to hospital with hepatitis of other aetiology. AAV2 typically requires a coinfecting ‘helper’ virus to replicate, usually HAdV or a herpesvirus. HAdV (species C and F) and human herpesvirus 6B (HHV6B) were detected in 6/9 and 3/9 affected cases, including 3/4 and 2/4 liver biopsies, respectively. The class II HLA-DRB1*04:01 allele was identified in 8/9 cases (89%), compared with a background frequency of 15.6% in Scottish blood donors, suggestive of increased susceptibility in affected cases. Acute non-A-E paediatric hepatitis is associated with the presence of AAV2 infection, which could represent a primary pathogen or a useful biomarker of recent HAdV or HHV6B infection. Population and mechanistic studies are required to explore these findings further.

Sample size derivation is a crucial element of planning any confirmatory trial. The required sample size is typically derived based on constraints on the maximal acceptable Type I error rate and minimal desired power. Power depends on the unknown true effect and tends to be calculated either for the smallest relevant effect or a likely point alternative. The former might be problematic if the minimal relevant effect is close to the null, thus requiring an excessively large sample size, while the latter is dubious since it does not account for the a priori uncertainty about the likely alternative effect. A Bayesian perspective on sample size derivation for a frequentist trial can reconcile arguments about the relative a priori plausibility of alternative effects with ideas based on the relevance of effect sizes. Many suggestions as to how such "hybrid" approaches could be implemented in practice have been put forward. However, key quantities are often defined in subtly different ways in the literature. Starting from the traditional entirely frequentist approach to sample size derivation, we derive consistent definitions for the most commonly used hybrid quantities and highlight connections, before discussing and demonstrating their use in sample size derivation for clinical trials.

Summary Multi-arm trials are an efficient way of simultaneously testing several experimental treatments against a shared control group. As well as reducing the sample size required compared to running each trial separately, they have important administrative and logistical advantages. There has been debate over whether multi-arm trials should correct for the fact that multiple null hypotheses are tested within the same experiment. Previous opinions have ranged from no correction is required, to a stringent correction (controlling the probability of making at least one type I error) being needed, with regulators arguing the latter for confirmatory settings. In this article, we propose that controlling the false-discovery rate (FDR) is a suitable compromise, with an appealing interpretation in multi-arm clinical trials. We investigate the properties of the different correction methods in terms of the positive and negative predictive value (respectively how confident we are that a recommended treatment is effective and that a non-recommended treatment is ineffective). The number of arms and proportion of treatments that are truly effective is varied. Controlling the FDR provides good properties. It retains the high positive predictive value of FWER correction in situations where a low proportion of treatments is effective. It also has a good negative predictive value in situations where a high proportion of treatments is effective. In a multi-arm trial testing distinct treatment arms, we recommend that sponsors and trialists consider use of the FDR.