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Marion Campbell Profile picture
@MarionKCampbell
May 29 • 9 tweets • 4 min read Twitter logo Read on Twitter
While 1:1 randomisation to interventions is most common in clinical trials, sometimes #UnequalRandomisation is used. There are a number of factors that influence which randomisation ratio to use 1/9
#MethodologyMonday
One justification for unequal randomisation is when there is a substantial difference in cost of treatments. In this scenario, randomising unequally with fewer to the very expensive arm maximises efficiency when a trial has set resources 2/9
bmj.com/content/321/72… Image
Another is if you are undertaking an early investigation of a new treatment and need to have greater insights into its underlying safety/benefit profile. Here, increasing allocation to the new treatment will provide greater precision around these estimates 3/9
However, moving away from 1:1 randomisation has consequences for trial power. Even moving from 1:1 to a 2:1 randomisation will require approx 12.5% more patients to retain the same statistical power and the % increases the greater the ratio adopted 4/9
A couple of reviews have highlighted the different rationales given by triallists for use of unequal randomisation 5/9
Review 1/ sciencedirect.com/science/articl…
Review 2/jclinepi.com/article/S0895-… ImageImage
Unequal randomisation raises ethical issues, however, especially as more patients will need to be recruited to achieve equivalent power. Hey et al outline some of the issues and provides insights on when it may or may not be ethically justified 6/9
ncbi.nlm.nih.gov/pmc/articles/P… Image
The growth of adaptive trials has seen more use of “response adaptive randomisation”which adapts the randomisation ratio over time in response to emerging data & weights the ratio in favour of the emerging better treatment. @remap_cap is a good example 7/9
remapcap.org/protocol-docum… Image
The aim of response adaptive randomisation is that more patients get the likely better trt. This could theoretically break the blind though causing problems with the overall trial integrity. Effects may also oscillate esp early in a trial. Mitigations need to be in place 8/9
In any event, when any form of unequal randomisation ratio is used, it is essential that the rationale for the selected ratio is outlined in trial protocols & reports. The reviews flagged above show this is rarely done and needs improvement 9/9

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More from @MarionKCampbell

Marion Campbell Profile picture
Apr 24
One phenomenon that can affect clinical trials is the #HawthorneEffect. This is when purely being involved in a trial can improve performance. 1/9
#MethodologyMonday
The #HawthorneEffect was named after a famous set of experiments at the Hawthorne Western Electric plant, Illinois in the 1920/30s. 2/9
In one experiment lighting levels were repeatedly changed & with each change, productivity increased .. even when reverting to poorer lighting. This was attributed to workers knowing their work was being observed. Productivity returned to normal after the experiments ended 3/9
Read 9 tweets
Marion Campbell Profile picture
Apr 17
This week some of my discussions have centred on #ClusterTrials. Cluster trials involve the randomisation of intact units (wards, hospitals, GP practices etc) rather than individuals. They have a number of key elements that must be accounted for 1/11
#MethodologyMonday
There are very good reasons for cluster/group randomisation eg when evaluating interventions like clinical guidelines or educational interventions which apply at practice/hospital level; or when there is potential of contamination of the intervention across trial groups 2/11
However, cluster randomisation has some major impacts for design & analysis primarily because observations within a cluster are not independent (outcomes are likely to be more similar within a cluster) 3/11
Read 11 tweets
Marion Campbell Profile picture
Apr 3
The first step in a clinical trial is deciding the #ResearchQuestion. Knowing which question is most important to focus on may not be clear cut. An interesting paper was recently published which developed a tool to rank the importance of research questions 1/7
#MethodologyMonday
This tool was developed for the musculo-skeletal field (ANZMUSC-RQIT), but the concepts are highly likely to be transferable to other fields 2/7
journals.plos.org/plosone/articl…
The tool identified 5 domains to be ranked:1) extent of stakeholder consensus, 2) social burden of health condition, 3) patient burden of health condition, 4) anticipated effectiveness of proposed intervention, and 5) extent to which health equity is addressed by the research 3/7
Read 7 tweets
Marion Campbell Profile picture
Mar 27
There was an interesting paper this week on different stakeholders understanding of the concept of #equipoise. Equipoise is an essential concept in clinical trials but is often not well understood 1/8
#MethodologyMonday
For it to be ethical to randomise in a trial, it is important that there is uncertainty which treatment is best 2/8
Originally uncertainty (equipoise) had to be at the level of the individual clinician but was refined to uncertainty at the professional community level by Freedman in the 1980s 3/8
nejm.org/doi/full/10.10…
Read 8 tweets
Marion Campbell Profile picture
Mar 20
The #FactorialTrial design is one of the very original efficient trial designs yet its potential often remains underused 1/7
#MethodologyMonday
In a #FactorialTrial you can evaluate the effectiveness of more than one treatment simultaneously and for the same sample size requirements as doing a single trial 2/7
bmcmedresmethodol.biomedcentral.com/articles/10.11…
For a factorial trial of say 2 treatments, patients are allocated to 1 of 4 groups: Gp1 receives both treatments A and B; Gp2 receives only A; Gp3 receives only B; and Gp4 receives neither A nor B (the control) 3/7
cambridge.org/core/services/…
Read 7 tweets
Marion Campbell Profile picture
Mar 13
A clinical trial design that is often misunderstood is the #NonInferiority clinical trial design. 1/8
#MethodologyMonday
Mostly we set up trials to test if a new treatment is better than another (ie we test for superiority) but in a #NonInferiority design we wish to test if a treatment is not unacceptably worse than a comparator. 2/8
The main reasons why we might look for non-inferiority is when an alternative treatment is say much cheaper, or has fewer side effects … but we would only wish to use it if the benefits of the standard treatment are not significantly compromised. 3/8
onlinelibrary.wiley.com/doi/full/10.10…
Read 8 tweets

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