Increasing efficiency of preclinical research by group sequential designs: a new paper in PLOS biology

We have another paper published in PLOS Biology. The theme is in the same area as the first paper I published in that journal, which had the wonderful title “where have all the rodents gone”, but this time we did not focus on threats to internal validity, but we explored whether sequential study designs can be useful in preclinical research.

Sequential designs, what are those? It is a family of study designs (perhaps you could call it the “adaptive study size design” family) where one takes a quick peek at the results before the total number of subject is enrolled. But, this peek comes at a cost: it should be taken into account in the statistical analyses, as it has direct consequence for the interpretation of the final result of the experiment. But the bottom line is this: with the information you get half way through can decide to continue with the experiment or to stop because of efficacy or futility reasons. If this sounds familiar to those familiar with interim analyses in clinical trials, it is because it is the sam concept. however, we explored its impact when applied to animal experiments.

Figure from our publication in PLOS Biology describing sequential study designs in or computer simulations

Old wine in new bottles” one might say, and some of the reviewers for this paper published rightfully pointed out that our paper was not novel in terms of showing how sequential designs are more efficient compared to non sequential designs. But there is not where the novelty lies. Up untill now, we have not seen people applying this approach to preclinical research in a formal way. However, our experience is that a lot of preclinical studies are done with some kind of informal sequential aspect. No p<0.05? Just add another mouse/cell culture/synapse/MRI scan to the mix! The problem here is that there is no formal framework in which this is done, leading to cherry picking, p-hacking and other nasty stuff that you can’t grasp from the methods and results section.

Should all preclinical studies from now on half sequential designs? My guess would be NO, and there are two major reasons why. First of all, sequential data analyses have their ideosyncrasies and might not be for everyone. Second, the logistics of sequential study designs are complex, especially if you are affraid to introduce batch effects. We only wanted to show preclinical researchers that the sequential approach has their benefits: the same information with on average less costs. If you translate “costs” into animals the obvious conclusion is: apply sequential designs where you can, and the decrease in animals can “re-invested” in more animals per study to obtain higher power in preclinical research. But I hope that the side effect of this paper (or perhaps its main effect!) will be that the readers just think about their current practices and whether thise involve those ‘informal sequential designs’ that really hurt science.

The paper, this time with aless exotic title, “Increasing efficiency of preclinical research by group sequential designs” can be found on the website of PLOS biology.

Advertisements