The case in front of me: headache · semaglutide · STEP 3.
I would like to know the limits of what can be inferred from this.
What I am trying to avoid is over-reading a single result, which I have done before.
What would I need in addition before this supported a decision?
Take it from the STEP 3 adverse-event table by arm, and check the unit before you use it. An incidence can be the proportion of participants who reported the event at least once, or the count of events divided by exposure time, and the two differ by however many people had it repeatedly. Then subtract the placebo arm, because the untreated rate is not zero. And read the discontinuation column beside it: an event that made people leave the trial is under-counted at every later visit, so a low late-timepoint incidence can mean the event was severe rather than rare.
In practice, the trial answers a narrower question than the headline suggests, and the narrowing is where the useful information is.
Placebo arms in this class are not nothing. Lifestyle-intervention placebo arms in the major obesity trials commonly lose two to three per cent of body weight, so an active-arm figure quoted without its comparator overstates the drug effect by roughly that much.
The underlying point is that a composite endpoint is only as informative as its least serious component. Where a cardiovascular composite combines death, infarction and stroke, ask which component moved, because they are not interchangeable outcomes.
Where a result is quoted from a conference abstract rather than a peer-reviewed publication, the numbers routinely move between the two. It is worth checking which one you are reading.
The short version: check the endpoint, check the comparator, check who was excluded, then look at the number.
Analytical standards and reagents with traceable certificates. Every quantitative result you read inherits the accuracy of the standard behind it.
Shop standardsThe honest answer here is that the published evidence supports part of the claim and is silent on the rest, and it is worth being precise about which part is which.
Confidence intervals matter more than point estimates when two trials disagree. Two studies reporting fifteen and twenty per cent whose intervals overlap heavily have not disagreed about anything.
Non-inferiority and superiority designs are not interchangeable. A non-inferiority result says the new agent is not meaningfully worse against a pre-specified margin — it does not say it is as good, and it certainly does not say it is better.
The cardiovascular outcome programme in this class runs to several large randomised trials — LEADER for liraglutide, SUSTAIN-6 and SELECT for semaglutide, REWIND for dulaglutide — and they are the reason the class is discussed as more than a weight intervention.
Be careful about generalising from a trial population to yourself. The exclusion criteria are usually the most informative page in the supplement.
Read the protocol and the statistical analysis plan if the result matters to you. Both are usually published alongside.
edited 27 Jul 2026 by dmitri_savchuk — added the placebo-arm figures
Answer first: read the primary endpoint, the comparator and the population before you read the effect size. Almost every argument on this site about a trial is really an argument about one of those three.
Duration decides what can be seen. A 68-week trial can measure weight and glycaemia; it cannot measure anything whose event rate is one per cent per year without enrolling tens of thousands.
Mechanically, intention-to-treat and per-protocol analyses answer different questions. ITT asks what happens if you offer the treatment; per-protocol asks what happens if it is taken as directed. The gap between the two is a measure of how tolerable the protocol was.
Meta-analyses in this area are dominated by whichever trial contributed the most participants, so read the forest plot rather than the summary estimate.
One qualification: absence of a signal in a trial of this size is not evidence of absence for a rare event. It is evidence that the event is rarer than the trial could detect.
When two sources disagree, the answer is almost always in the methods section of the one you have not read.
Ask PeptideStack is a static archive. Posting is closed, but the norms are worth stating: answer the question that was asked, show your working, cite the trial or the certificate, and say plainly where the evidence runs out.