Great suggestion, particularly as you say for trials with a super expensive treatment relative to control.
In defense of current practice, I’d like to add that a major difficulty when running medical trials for new therapeutics is simply recruiting patients to the trial. Many patients enroll on the trial with the aim of getting the experimental treatment, so it’s a lot easier to recruit people when your trial has a 50% or 75% chance of assignment to therapeutic arm.
Some other important strategies that are currently hot right now: Platform trials: One giant trial that has one control arm and maybe three to four treatment arms. Hard to do as it requires a lot of people to work together but amazing when you pull them off (e.g. we did many of these for COVID) Use of historical or shared control data: Why recruit as many controls if you can integrate existing data in a statistically principled, unbiased way (easier said than done of course).
Great suggestion, particularly as you say for trials with a super expensive treatment relative to control.
In defense of current practice, I’d like to add that a major difficulty when running medical trials for new therapeutics is simply recruiting patients to the trial. Many patients enroll on the trial with the aim of getting the experimental treatment, so it’s a lot easier to recruit people when your trial has a 50% or 75% chance of assignment to therapeutic arm.
Some other important strategies that are currently hot right now:
Platform trials: One giant trial that has one control arm and maybe three to four treatment arms. Hard to do as it requires a lot of people to work together but amazing when you pull them off (e.g. we did many of these for COVID)
Use of historical or shared control data: Why recruit as many controls if you can integrate existing data in a statistically principled, unbiased way (easier said than done of course).