Concretely: SURPASS-3 · injection-site erythema · 15 mg.
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 can I legitimately conclude from this figure?
Only what the 15 mg arm reported, and the denominator is that arm rather than the trial. Adverse-event tables are published per arm, so the 15 mg incidence of injection-site erythema has its own numerator and its own denominator, and pooling it with the other arms produces a figure that describes nobody. Two further deductions before you use it. Subtract the placebo arm — injection-site erythema occurs in people who received nothing, and the difference is the part attributable to the drug. And check whether SURPASS-3 counted events or counted participants: one participant with six episodes is one row in a participant count and six in an event count, and the two get quoted interchangeably. Nothing here is medical advice.
More usefully, the trial answers a narrower question than the headline suggests, and the narrowing is where the useful information is.
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.
It helps to be literal here: 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.
Meta-analyses in this area are dominated by whichever trial contributed the most participants, so read the forest plot rather than the summary estimate.
Quote the interval alongside the estimate and half the disagreements on this site would not start.
edited 21 Jun 2025 by Dr_Ilse_Vandenberg — added a caveat about sampling
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Browse resultsBefore comparing two trials, check whether they share an endpoint definition. Frequently they do not, and the numbers then are not comparable in any sense.
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.
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.
Read the protocol and the statistical analysis plan if the result matters to you. Both are usually published alongside.
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.
Open-label extensions are not the same evidence as the randomised phase. Once everyone knows what they are taking, the reported outcomes acquire a bias that no analysis fully removes.
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 short version: check the endpoint, check the comparator, check who was excluded, then look at the number.
Look at the discontinuation rate alongside the efficacy figure. A large effect in the two thirds who stayed is a different result from a large effect in everyone.
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.
If a claim cannot be traced to a named trial with a named endpoint, treat it as a claim rather than as evidence.
Start with what the trial was powered for. Everything else in the publication is secondary, exploratory, or a subgroup, and those three words mean three different things.
Trial populations are selected. Exclusion criteria in this class routinely remove people with significant renal impairment, prior pancreatitis and unstable psychiatric illness, which is exactly the population the results are then quoted for.
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.
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.