how much of what we believe about endpoint actually comes from SURMOUNT threads
how much of what we believe about endpoint actually comes from SURMOUNT threads. I am not trying to be the "source?" guy. I would just like a source.
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.
Why comparing across trials almost never works, with the specific failure modes.
Different populations: an obesity programme and a diabetes programme enrol different people with different baseline characteristics. Different endpoints: body weight change, glycaemic control and cardiovascular events are not convertible. Different durations: 68 weeks and 72 weeks are not the same, and the curves have not flattened by either.
Different analysis populations: one paper reports intention-to-treat, another emphasises completers. Different support: some trial designs include structured lifestyle contact that no member of this board receives.
Stack those and the "X beats Y" tables that circulate here are comparing five things at once and attributing the difference to the molecule.
On means, which this board treats as targets and which are nothing of the sort.
A reported mean body weight change is the centre of a distribution that in these trials is very wide. Substantial numbers of participants did much better, and substantial numbers did considerably worse while remaining on the drug and in the analysis.
Quoting the mean as an expectation therefore misleads in both directions: it makes ordinary results look like failures and it makes exceptional results look normal. If a paper publishes the distribution — and several do, in the appendix — look at that instead. It is far more informative than the number in the abstract.
I will update this if the picture changes rather than quietly leaving it up.
best — the order this archive was captured in
STEP is semaglutide obesity, SURMOUNT is tirzepatide obesity, they are not interchangeable
Absolute or relative risk reduction?
Open-label extensions lose their randomisation. Anybody still enrolled at week 104 is a selected group and the numbers describe that group.
the appendix is where the interesting tables live
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.
Compared myself to a trial mean for about six months before realising the trial arm had dietitian contact every fortnight.
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The discontinuation numbers were the most useful thing in the paper for me and they were in a supplementary table.
Read a press release and the publication three months apart. The hedging in the second one was substantial.
This. Intention-to-treat versus completer analysis routinely moves the headline by several points.
Spent an evening with the appendix tables and found the subgroup detail that the entire thread had been speculating about.
SELECT was cardiovascular outcomes, not weight
Yes — the interval is the finding. A point estimate with a wide interval is a hypothesis in a nice font.
Went looking for the registered protocol to see whether the endpoint had changed. It had not, which was reassuring and worth checking.
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.
Agreed. Half the arguments on this site are two people quoting different trials at each other without noticing.
Careful with that mean. The distribution around it was wide enough that it describes very few individual participants.
Same. A press release is a claim about a result; the publication is the result.
Agreed.
Agreed. And the interval, not the point estimate, is what the trial actually established.
discontinuation rate is a result, not a footnote
check who the comparator was before you compare anything
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.
How long was the randomised phase before any extension?
What was the discontinuation rate?
Discontinuation rates are a tolerability result. A trial with a strong efficacy number and heavy discontinuation is telling you two things and people only quote one.
trial populations get support that nobody on this board gets
Not convinced. Cross-trial comparison between two programmes with different populations and designs is not a comparison.
registry entry, protocol, publication — three different documents
SURPASS is the diabetes programme and reports glycaemic endpoints
- 1Intention-to-treat analyses everybody randomised regardless of what they did…15 comments in this branch · started by u/cesar_ivaturi
- 2Open-label extensions lose their randomisation. Anybody still enrolled at…8 comments in this branch · started by u/laila_almeida