The particulars: STEP 2 · semaglutide.
I have the document in front of me and I can read the numbers. What I cannot do is interpret them.
I am reasonably comfortable with statistics and completely uncomfortable with chromatography, or vice versa.
Which parts of this are informative and which are decoration?
Whatever its primary endpoint was, at the power it was designed for, in the population it recruited — and nothing else. STEP 2 was sized to answer one question. Every other result in it is a secondary or exploratory endpoint, powered incidentally if at all, and a nominally significant secondary in a programme with twenty of them is what you would expect from chance alone. So the reading order is: primary endpoint, then whether the secondaries were pre-specified and hierarchically tested, then everything else as hypothesis-generating. A trial establishes one thing well and suggests several things badly, and the press coverage inverts that ranking reliably.
Put another way, a trial establishes what happened to a defined group under a defined protocol. Extending it beyond that group is inference, and inference is allowed as long as it is labelled.
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.
Stated carefully, 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.
The caveat is that trial evidence is about licensed product administered under supervision. None of it transfers automatically to research-grade material of unverified content.
Read the protocol and the statistical analysis plan if the result matters to you. Both are usually published alongside.
edited 20 Jun 2025 by Dr_Ilse_Vandenberg — reworded for clarity after a comment
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.
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.
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.
Registry entries at ClinicalTrials.gov carry the pre-specified primary endpoint with a timestamp, which is the cheapest available check on whether an endpoint was changed after the data were seen.
I am not a clinician and this is not medical advice; it is a reading of a published protocol.
Quote the interval alongside the estimate and half the disagreements on this site would not start.
Before comparing two trials, check whether they share an endpoint definition. Frequently they do not, and the numbers then are not comparable in any sense.
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.
The part that matters: 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.
Meta-analyses in this area are dominated by whichever trial contributed the most participants, so read the forest plot rather than the summary estimate.
If a claim cannot be traced to a named trial with a named endpoint, treat it as a claim rather than as evidence.
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.
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.
Be careful about generalising from a trial population to yourself. The exclusion criteria are usually the most informative page in the supplement.
When two sources disagree, the answer is almost always in the methods section of the one you have not read.
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.
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.
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.
The short version: check the endpoint, check the comparator, check who was excluded, then look at the number.
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.