Competing Effects of Indirect Protection and Clustering on the Power of Cluster-Randomized Controlled Vaccine Trials

Abstract

Power considerations for trials evaluating vaccines against infectious diseases are complicated by indirect protective effects of vaccination. While cluster-randomized trials (cRCTs) are less statistically efficient than individually randomized trials (iRCT), a cRCT's ability to measure direct and indirect vaccine effects may mitigate the loss of efficiency due to clustering. Within cRCTs, the number and size of clusters affects three determinants of power: the effect size being measured, disease incidence, and intra-cluster correlation. We simulate trials conducted in a collection of small communities to assess how indirect protection and clustering affect the power of cRCTs and iRCTs during an emerging epidemic. Across diverse parameters, we find that within the same trial population, cRCTs are never more powerful than iRCTs, although the difference can be small. We also identify two effects that attenuate the loss of cRCT power traditionally associated with increased cluster size. First, if enrollment of fewer, larger clusters is performed to achieve higher vaccine coverage within vaccinated communities, this increases the effect to be measured and, consequently, power. Second, the greater rate of imported transmission in larger communities may increase the attack rate and similarly mitigate loss of power relative to a trial in many, smaller communities. Cluster-randomized controlled trials (cRCTs) have become an increasingly common method for evaluating interventions for infectious diseases, including vaccines. Compared to individually randomized controlled trials (iRCTs), cRCTs may offer logistical, operational, and acceptability advantages (1), and allow the measurement of direct and indirect effects of vaccination, which are often relevant for policy-makers (2). The statistical theory of cRCT design has largely focused on the effect of clustering, commonly measured by intracluster correlation, on power (3-5). Intracluster correlation arises because outcomes of members of the same cluster are more similar than those from different clusters. Therefore, increasing the number of individuals within a cluster provides less information than would adding the same number of individuals in a new cluster.When the trial outcome is an infectious disease, correlation arises also because each case in a cluster can transmit infection to other cluster members. Thus, trials of vaccines against infectious diseases exhibit a more complicated relationship between statistical power and sample size than in trials for non-infectious outcomes (6, 7); in particular, the total or overall vaccine effect measured by a cRCT is generally larger than the direct effect measured by an iRCT. In principle, this increased effect size in a cRCT might partially or fully offset the loss of power due to within-cluster correlation. Understanding these complexities can aid in vaccine trial design for emerging epidemics. While an important consideration in any clinical trial, maximizing efficiency is particularly crucial in trials during ...

Novel methods for the analysis of stepped wedge cluster randomized trials

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Choices in vaccine trial design in epidemics of emerging infections

“…In order to further prepare in advance for epidemics, future work should characterize choices for specific pathogen characteristics and contexts. Mathematical modeling and simulation are useful tools for addressing choices beyond the four discussed here, e.g., sample size, trial location, duration, or end point [ 33 , 50 – 52 ]. Rigorous ethical analysis, as well as inclusive and transparent debate by different stakeholders, would help to illuminate the underlying moral questions.…”

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The required size of cluster randomized trials of nonpharmaceutical interventions in epidemic settings

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