16 Oct, 14 | by Bob Phillips
A little while ago we blogged on the surprisingly varied methods folk use to pick how how big an effect needs to be in order to be ‘clinically relevant’. A further paper on this theme has emerged that takes up a slightly different aspect of the challenge of getting the number right before doing a trial.
On the basics front, before you know how many people will be needed for a trial, you need to know
- How big an effect you might see
- How varied the effect is between people
- What size of effect is gong to be ‘clinically relevant’ (ie above what level you want to prove the intervention will lie)
- What chance of making the wrong call (“It works!” when it doesn’t, or vica versa) you are prepared to accept
It may be rather surprising to find that there hasn’t been, until very recently, a really well developed way of using systematic review / meta-analysis methodology to capture the stuff we already know before moving onwards to find out more, when moving between phase II (how-toxic-is-this-and-does-it-make-markers/images-better?) and phase III (are-there-fewer-dead-people?) trials. But now there is.