An international investigation confirms that beta-blockers, prescribed routinely for four decades, do not provide benefits to most patients recovering from a myocardial infarction
I got to say, I’m not convinced. All this really shows is that bisoprolol does not trigger the primary outcome (85% use), which is a composite of 3 things - death from any cause, reinfarction and hospitalization for heart failure. I don’t think I’ve used bisoprolol a single time in my career.
Also, I need to recalculate the power, because they say themselves the event rate wasn’t any where near what they thought it would be. So this study was severely underpowered, which is ironic since the primary event rate was 7.4% and 7.2%. So yes, maybe you don’t want to have a power to distinguish between a 7.4 and 7.2% event rate, but it’s also very possible that actual mortality is getting lost in the noise with the composite primary end point.
Power is a function of the size of the difference you’re testing for. Idk how to really calculate it accurately, but this site would suggest to discriminate between 7.2% and 7.4% you’d need over 300,000 participants
I’m kind of skeptical of that, but I don’t know enough about clinical trials to know that.
I got to say, I’m not convinced. All this really shows is that bisoprolol does not trigger the primary outcome (85% use), which is a composite of 3 things - death from any cause, reinfarction and hospitalization for heart failure. I don’t think I’ve used bisoprolol a single time in my career.
Also, I need to recalculate the power, because they say themselves the event rate wasn’t any where near what they thought it would be. So this study was severely underpowered, which is ironic since the primary event rate was 7.4% and 7.2%. So yes, maybe you don’t want to have a power to distinguish between a 7.4 and 7.2% event rate, but it’s also very possible that actual mortality is getting lost in the noise with the composite primary end point.
how is 18,000 underpowered.
8,400 were assigned
Power is a function of the size of the difference you’re testing for. Idk how to really calculate it accurately, but this site would suggest to discriminate between 7.2% and 7.4% you’d need over 300,000 participants
I’m kind of skeptical of that, but I don’t know enough about clinical trials to know that.