This paper describes a tool explaining the 5 attributes of an estimand, accessibly referred to as the 5 pillars of the research question. This was co-developed for researchers and public partners to use to facilitate the involvement of public partners in devising estimands.

This paper proposes using the posterior probability of noninferiority to demonstrate the value of undertaking an NI trial using a credible NI margin. A five-part Bayesian framework is described: the data generation/analysis model; maximum feasible sample size; different potential outcomes; primary NI margin; and plausible priors.

A review of original research protocols submitted to the United Kingdom’s Health Research Authority, which oversees ethical review of clinical trials, to identify how the use of estimands has changed over time, whether trials are using estimands correctly (i.e. correctly defining the five attributes of an estimand), and which strategies are being used to handle intercurrent events.

Patient and Public Involvement (PPI) is well-established in applied health research but remains under utilised in statistical methodology research due to perceived irrelevance and communication challenges. This paper summarises a one-day workshop held in February 2024 in Leicester, organised by the University of Leicester and the NIHR Statistics Group, aimed at addressing barriers to meaningful PPI in statistical methodology.

In a special series, Trials invited submissions that related to the collection, analysis and reporting of adverse events in clinical trials. To date twelve articles have been published in the series. In this editorial, we summarise each of these submissions and briefly discuss the implications on applied clinical trials and future methodological research.

Many trials are affected by unforeseen events after recruitment has commenced. The aim of this study is to explore a hypothetical strategy for dealing with an intercurrent event that occurred during trial follow-up; COVID-19 restrictions. Analysis was conducted using multiple imputation.

This article conducted a secondary analysis of the VANISH RCT, which compared the early use of vasopressin with norepinephrine on renal failure-free survival for patients with septic shock at 28 days. This was done using classical (separate tests for interaction with Bonferroni correction), data-adaptive (hierarchical lasso regression), and non-parametric causal machine learning (causal forest) methods to analyse HTEs for the primary outcome of being alive at 28 days. The modal initial (root) splits of the causal forest were extracted, and the mean value was used as a threshold to partition the population into subgroups with different treatment effects.

This paper formulates and describes two algorithms for implementing reference-based multiple imputation for longitudinal binary outcome data using: (i) joint modeling with the multivariate normal distribution and an adaptive rounding algorithm and (ii) joint modeling with a latent multivariate normal model. A simulation study was performed to compare the properties of the two methods.

Five years on from the publication of the ICH E9 (R1), this fun but informative article uses a trial conducted by Santa Clause to explain the importance of estimands to clearly specifying the precise research targeted in a trial.

This paper provides an overview of the evolution of Phase 3 vaccine trial design and statistical analysis methods from traditional to more innovative contemporary methods.