Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology

Abstract

Introduction: Clinical trial designs based on the assumption of independent observations are well established. Clustered clinical trial designs, where all observational units belong to a cluster and outcomes within clusters are expected to be correlated, have also received considerable attention. However, many clinical trials involve partially clustered data, where only some observational units belong to a cluster. Examples of such trials occur in neonatology, where participants include infants from both singleton and multiple births, and ophthalmology, where one or two eyes per participant may need treatment. Partial clustering can also arise in trials of group-based treatments (e.g. group education or counselling sessions) or treatments administered individually by a discrete number of health care professionals (e.g. surgeons or physical therapists), when this is compared to an unclustered control arm. Trials involving partially clustered data have received limited attention in the literature and the current lack of standardised terminology may be hampering the development and dissemination of methods for designing and analysing these trials. Methods and examples: In this article, we present an overarching definition of partially clustered trials, bringing together several existing trial designs including those for group-based treatments, clustering due to facilitator effects and the re-randomisation design. We define and describe four types of partially clustered trial designs, characterised by whether the clustering occurs pre-randomisation or post-randomisation and, in the case of pre-randomisation clustering, by the method of randomisation that is used for the clustered observations (individual randomisation, cluster randomisation or balanced randomisation within clusters). Real life examples are provided to highlight the occurrence of partially clustered trials across a variety of fields. To assess how partially clustered trials are currently reported, we review published reports of partially clustered trials. Discussion: Our findings demonstrate that the description of these trials is often incomplete and the terminology used to describe the trial designs is inconsistent, restricting the ability to identify these trials in the literature. By adopting the definitions and terminology presented in this article, the reporting of partially clustered trials can be substantially improved, and we present several recommendations for reporting these trial designs in practice. Greater awareness of partially clustered trials will facilitate more methodological research into their design and analysis, ultimately improving the quality of these trials.

Sample size for partially nested designs and other nested or crossed designs with a continuous outcome when adjusted for baseline

“…This is also known as the therapist effect 2 . In both cases, the correlation is induced by the treatment; such trials are also called individually randomized group therapy trials, and more recently have been referred to as individual randomized trials with post‐randomization clustering 3 …”

“…2 In both cases, the correlation is induced by the treatment; such trials are also called individually randomized group therapy trials, and more recently have been referred to as individual randomized trials with post-randomization clustering. 3 An example where the correlation arises from treatment in a group setting is a cluster randomized trial. In this case, outcomes of participants are nested within clusters.…”

Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations

“…Individually randomized group treatment (IRGT) trials (also referred to as individually randomized trials with post-randomization clustering which can involve differential clustering in different trial arms) are becoming increasingly popular in public health research and biomedical studies. [1][2][3] In an IRGT trial, although individuals are randomized to different trial arms, clustering of outcomes arises in one or both conditions due to the nature of the treatment being either group-based (eg, a group-based psychological treatment) or delivered to multiple participants by the same individual (eg, surgeon). In some IRGT trials, no clustering of outcomes occurs in the control or usual care condition.…”

Designing multicenter individually randomized group treatment trials

“…Roberts and Roberts (2005) derived an explicit sample size formula to simultaneously adjust for such complexities in planning IRGT trials; Teerenstra et al (2023) extended their formula to allow for a baseline measurement of the outcome in both IRGTs and other nested or crossed designs. In the special case where active group-based treatment is compared with ungrouped standard care, IRGT trials are also known as partially clustered designs (Bauer et al, 2008;Lange et al, 2023), in which only the ICC of outcome in the active treatment group is nonzero. Systematic reviews suggested that clustering induced by treatment delivery has often been overlooked at both the design and analytical stages in randomized trials (Pals et al, 2008(Pals et al, , 2011, which may have led to overoptimistic findings in published trial reports.…”