Randomized clinical trials have become universally accepted as the standard procedure for comparing treatments. However, there is no guarantee that the subjects allocated to the different treatment groups will be similar in all important characteristics. Can anyone explain, what is the main factor when we got the imbalanced results between the treatment groups? a mistake on the randomization step? and then, what can we do to make it balanced?
Unfortunately a random selection of patients can be associated with a difference in the group just by chance (especially if you have many characteristics that you describe the risk of finding a difference at a type 1 error of 0.05 would increase). Just imagine you flipping a coin 5 times in a row, you could just by chance get the same results and it does not mean that the coin is biased ( if repeating the flipping hundred of times you would get the 0.5 probability of head or tails).This is exactly the same for the patients characteristics you could get just by chance an imbalanced dataset in a random selection of patients.
If it is anticipated that a specific risk factor or characteristic would be critical in the subsequent analysis of your trial (ex tumor stage), you could block patients by this characteristic at inclusion. This would improve the repartitions of patients based on this blocking factor and ensure adequate sample size).
The last option would be to control for this factor in your analysis a posteriori. However, you could be at risk of lacking power in your trial (especially because most of time in RCT sample size is determined a priori not accounting for a specific imbalance of patients on a specific characteristic).
see the paper below for more information on blocking (Efird J. Blocked randomization with randomly selected block sizes. Int J Environ Res Public Health. 2011 Jan;8(1):15-20. doi: 10.3390/ijerph8010015. Epub 2010 Dec 23. PMID: 21318011; PMCID: PMC3037057.)
- Badges
- Science topic
- Similar topics
- Biological Science
- Histology
- Fixatives