Often, perhaps usually, a treatment will make some people better, do nothing for others, and make some people worse.
When a treatment makes about as many people worse as it makes better, then meta-analysts say it doesn’t work.
But often it *does* work - for *some* people. Indeed, it might work very well indeed for them.
The other people - those for whom it makes no difference or makes worse - just need to stop using it - then everyone benefits.
It is just a matter of using patient response as a feedback loop.
Is that really so difficult to understand? - yet I can never get this point across to bio-statisticians/ epidemiologists, meta-analysts and the like…
