I just got back from one of the world’s largest stroke meetings, the European Stroke Organisation Conference (ESOC), held this year in Gothenburg, Sweden. The overwhelming focus of the conference is on groundbreaking large clinical trials, reports of which dominate the plenary-like sessions of the schedule. One thing I’ve noticed about talks on clinical trials is how, every year, the speakers go to great lengths to emphasize some (positive) ethical, methodological, or statistical aspect of their study.
This is the result of something that I like to call the RRRR cyle (pronounced “ARRARRARRARR” or “rrrr” or “quadruple R” or whichever way won’t scare/excite those in your immediate vicinity at that moment in time). It usually starts with loud opposition (reprimand) to some aspect of how clinical trials are run or reported. This usually comes from statisticians, ethicists, or more methodologically inclined researchers. Eventually, a small scandal ensues, and clinical researchers yield (usually after some resistance). They change their ways (repentance) and, in doing so, become fairly vocal about what they’re now doing better (representation)*.
Examples that I’ve experienced in my career as a stroke researcher thus far are:
- Treating polytomous variables as such instead of binarizing them (the term “shift analysis” – in the context of outcome variables – is now an indispensable part of the clinical stroke researcher’s lexicon).
- Pre-specifying hypotheses, especially when it comes to analyzing subgroups.
- Declaring potential conflicts of interest.
Most of these practices are quite fundamental and may have been standard in other fields before making their way to the clinical trial world (delays might be caused by a lack of communication across fields). Still, it’s undoubtedly a good thing that we learn from our mistakes, change, and give ourselves a subtle pat on the back every time we put what we’ve learned to use.
The reason I bring it up is, maybe soon someone** could start making some noise about one of the following issues that come up way too often in my opinion:
- (Mis-)interpreting p-values that are close to 0.05, and how this is affected by confirmation bias.
- Testing if groups are “balanced” in terms of baseline/demographic variables in trials using “traditional” statistical methods instead of equivalence testing.
As the ESOC meeting keeps reminding me, a lot can be done in a year. So I’m pretty optimistic we can get some of these changes implemented by ESOC 2019 in Milan!
* If you think this particular acronym is unnecessary or a bit of a stretch, I fully agree. I also urge you to take a look at this paper for a list of truly ridiculous acronyms (all from clinical trials of course).
** I would, but I’m not really the type – I’d be glad to loudly bang the drums after someone gets the party started, though.