[Stats] relative risk reduction sells papers, absolute risk reduction makes decisions
relative risk reduction sells papers, absolute risk reduction makes decisions. It is the sort of thing everyone half-believes and nobody writes down.
The discontinuation numbers were the most useful thing in the paper for me and they were in a supplementary table.
Argued for a week about a result and then read the limitations section, which conceded most of my opponent’s point.
How to read one of these papers in fifteen minutes, in the order that actually helps.
Start with the registered protocol and check the primary endpoint against what is reported. Then the methods: who was included, what the comparator was, how long the randomised phase ran. Then the discontinuation numbers, which are a tolerability result and are usually in a supplementary table.
Only then the efficacy figure, and read the interval rather than the point estimate. Finish with the limitations section, which is where the authors say what they actually think.
Fifteen minutes, and you will know more than any thread summarising it.
If two or three other people have done the same thing we might actually learn something. Alone it is an anecdote.
best — the order this archive was captured in
Intention-to-treat analyses everybody randomised regardless of what they did afterwards. Completer analyses only those who finished. The second is systematically more flattering and both are legitimate if labelled.
Yes — the interval is the finding. A point estimate with a wide interval is a hypothesis in a nice font.
read the endpoint before you read the headline
Agreed on comparators. "Superior" means nothing until you know superior to what and at what dose.
Went looking for the registered protocol to see whether the endpoint had changed. It had not, which was reassuring and worth checking.
SELECT was cardiovascular outcomes, not weight
open-label extensions are not the same evidence as the randomised phase
open-label extensions are not the same evidence as the randomised phase
customs_seizure_sid is right about the programme names. They are different populations with different endpoints.
Disagree — that figure is from the diabetes programme and you are quoting it as an obesity endpoint.
This. Intention-to-treat versus completer analysis routinely moves the headline by several points.
SURPASS is the diabetes programme and reports glycaemic endpoints
Do you have the publication or the press release?
Correction: SURMOUNT is the obesity programme and SURPASS is the diabetes one. The figure you quoted belongs to the other one.
Small fix — that was the cardiovascular outcomes trial, so weight was a secondary endpoint and the population was different.
Relative risk reduction without the baseline rate is uninterpretable. A large relative reduction on a small absolute risk is a small absolute benefit.
A confidence interval is the range of effects compatible with the data. Two trials with overlapping intervals have not disagreed, whatever their point estimates look like next to each other.
Retitled: the original quoted a diabetes endpoint as an obesity result.
trial populations get support that nobody on this board gets
What was the discontinuation rate?
check who the comparator was before you compare anything
trial populations get support that nobody on this board gets
This is the distinction that would end about half the arguments on this board.
Right — trial participants get structured support. Comparing yourself to a trial mean is comparing across two different interventions.
Cardiovascular outcome trials are powered for events, not for weight, and are typically run in a different population with different inclusion criteria. Reading a weight number out of one is reading a secondary endpoint.
- 1Intention-to-treat analyses everybody randomised regardless of what they did…9 comments in this branch · started by u/oskar_ibarra
- 2This. Intention-to-treat versus completer analysis routinely moves the…7 comments in this branch · started by u/tb500_tangent