Last week I have written about trial quality over time, I have tried to convince the ICECReamers that one of the biggest causes of publication of low quality trials is bad editorial policies or bad editorial management (which involves editors and reviewers opinions/decisions).
At the moment, we have quite strong evidence that there are some critical points that must be taken into consideration while designing and conducting a trial such as proper randomisation, concealed allocation, blinding (if possible) and intention-to-treat analysis… so in theory if authors could perform at least these steps properly, the world of science would be a much better place 🙂
Having said that, most of researchers (including me) think that there are other issues that influence the internal validity of a trial. My good friend Chris Lin mentioned on a comment last week that although sample size influences trial results and interpretation, this item is not considered a quality item in any risk of bias assessment tools! In other words we could have a “100% internally valid” trial with 9 patients randomised into 3 groups! Some people would argue that sample size is more related with generalizability rather than internal validity, but I tend to agree with Chris with this point.
Here in Brazil (in which most of researchers that I know do basic research) there is a big criticism regarding the research question per se in clinical trials (every day I listen to comments like: “if the research question does not make sense, I don’t care if the study is good or bad… I just ignore the study!”)… in my opinion (like Steve Kamper said on his WCPT post), these guys are probably more disappointed with the trial results than with the study itself and then react by smashing the trial… I wouldn’t be surprised that you guys have already listened to something similar…
Coming back to the point of trial quality, Nick Henschke and colleagues from the Netherlands are working on a study about “fatal flaws in randomised controlled trials”. I was invited to answer their questions, and it seems to me that by the end of this study the conclusions will be the same: blinding, randomisation, excluding patients, ITT analysis and baseline data imbalance will be the main issues that can destroy (or save) a trial.
I would like to invite you to insert a comment on this. What do you think that could be also related to trial quality?
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