In clinical trials, we sometimes undertake #SensitivityAnalysis alongside the main primary analysis. But when should we use them and to what purpose? 1/8
#MethodologyMonday #80 Sensitivity analyses can assess the impact of key elements/assumptions of a trial on the result eg impact of any baseline imbalance, impact of the choice of analysis approach etc 2/8

I have spoken about “usual care” or “treatment as usual” as a control arm in trials before, but should you ever protocolise usual care or just measure it as is? 1/8
#MethodologyMonday #77 Whilst “usual care” implies a common package of care being applied across sites, there is often a high degree of heterogeneity in care provided - but many would argue that the heterogeneity will increase the external validity of the trial results 2/8

I have spoken about the importance of minimally clinically important differences (#MCID)
before in relation to sample sizes but how do you decide what it should be? There was an interesting paper published this week adding to this literature 1/8
#MethodologyMonday The MCID drives the sample size - it is the minimum clinically important difference you set your trial to detect. Set the MCID too small and the sample size will be much larger than needed; but make the MCID too big & your trial will miss clinically important effects 2/8

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…

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

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

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…

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

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…

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

Having spent the last couple of weeks discussing composite & surrogate outcomes, I was reminded this week of the importance of thoughtful planning on the choice of outcomes in the first place 1/6
#MethodologyMonday In particular I was reminded of the fundamental work of #Donabedian to conceptualise what is important to measure to assess quality of (and improvement in) health care. Although developed decades ago, it remains just as relevant today 2/6
jamanetwork.com/journals/jama/…

Last week I discussed composite endpoints and how while they can be useful, they can also be fraught with difficulty. The same descriptors could equally be applied to #SurrogateOutcomes in clinical trials 1/9
#MethodologyMonday A #SurrogateOutcome is a substitute measure (eg blood pressure) that one might use to stand in for the real outcome of interest (eg stroke) when the real outcomes of interest may take a very long time to measure - to allow trials to be completed more quickly & efficiently 2/9

Choosing the right outcome is key to a clinical trial. Sometimes a #CompositeOutcome
- an outcome that combines more than one dimension into a single measure - is felt to be most appropriate. These can be useful but can be fraught with difficulty 1/8
#MethodologyMonday One of the primary reasons for using a composite outcome is trial efficiency - you can get more events quickly compared to the individual components thus increasing precision and efficiency in sample size calculations 2/8
jamanetwork.com/journals/jama/…

Given the complexity of delivering clinical trials, they are a fertile ground to gain from #interdisciplinary thinking. For example, the field of trial #recruitment has already gained enormously from insights from other disciplinary approaches 1/7
#MethodologyMonday A recent paper highlighted the use of #StatedPreference methods in this space. It showed aspects of trial design can affect recruitment 2/7

bmcmedresmethodol.biomedcentral.com/articles/10.11…

It’s good to start a new year getting the basics right. It’s the same with methods; important not to slip into using common errors.The recent Xmas BMJ paper which showed the most common stats/methods errors is a great place to start 1/7
#MethodologyMonday

bmj.com/content/379/bm… The BMJ stats editors highlighted the top 12 most common stats errors they come across. They are summarised in a neat infographic 2/7

Following the paper noted this week to have just added capital “T”s to a graph to depict standard errors 😱🤯, a short note on the importance of accurate data visualisation in any research report … 1/8
#MethodologyMonday This was the tweet & thread which highlighted T-gate. There are lots of other issues with that paper, but data visualisation is a core element 2/8

https://twitter.com/serifeliciano/status/1597355324008108034?s=46&t=EiTej4apumJRKGTpiq4URw

We are all being rightly encouraged to be #efficient in our trial design & conduct. Efficiency comes primarily through design choices … whether classic or more modern efficient designs … a few reflections below 1/7
#MethodologyMonday A #crossover design can be highly efficient. Each person acts as their own control removing large element of variation, making the design more powerful. The outcome needs to be short term however & the intervention can’t have a long-standing effect 2/7
bmj.com/content/316/71…