how much of what we believe about endpoint actually comes from TRIUMPH threads
how much of what we believe about endpoint actually comes from TRIUMPH threads. I would rather ask a basic question now than get this wrong quietly for two months.
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.
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.
Open-label extensions lose their randomisation. Anybody still enrolled at week 104 is a selected group and the numbers describe that group.
Please do not ask me what dose you should be on. I genuinely do not know and neither does anyone else here.
best — the order this archive was captured in
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.
How to read one of these papers in fifteen minutes, in the order that actually helps.
Agreed. And the interval, not the point estimate, is what the trial actually established.
Agreed.
hub_ops is right about the programme names. They are different populations with different endpoints.
hub_ops is right about the programme names.
Disagreeing with this line: that is a relative reduction and the absolute numbers are considerably less dramatic.
Absolute or relative risk reduction?
What did the confidence interval look like?
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.
What was the comparator?
intention to treat versus completers changes the number substantially
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.
Argued for a week about a result and then read the limitations section, which conceded most of my opponent’s point.
Compared myself to a trial mean for about six months before realising the trial arm had dietitian contact every fortnight.
Relative risk reduction without the baseline rate is uninterpretable. A large relative reduction on a small absolute risk is a small absolute benefit.
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.
trial populations get support that nobody on this board gets
STEP is semaglutide obesity, SURMOUNT is tirzepatide obesity, they are not interchangeable
The registered protocol is public. Comparing the registered primary endpoint with the reported one is a two-minute check and it is how outcome switching gets caught.
That is the 68-week readout, not the 72-week one. Different trial, different duration.
The discontinuation numbers were the most useful thing in the paper for me and they were in a supplementary table.
Right — trial participants get structured support. Comparing yourself to a trial mean is comparing across two different interventions.
Right — trial participants get structured support.
Adding the check nobody runs — the registered protocol is public and takes two minutes to compare.
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.
How long was the randomised phase before any extension?
discontinuation rate is a result, not a footnote
Started keeping the trial identifiers straight in a note file because I kept mixing up two programmes in the same sentence.
The press release said that; the publication says something more hedged. Worth reading both.
check who the comparator was before you compare anything
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