The case in front of me: TRIUMPH-3 · retatrutide.
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.
How should I read this, and where are the traps?
Check the TRIUMPH-3 inclusion criteria against yourself in that order: entry BMI band, diabetes status, prior weight-loss attempts, and what the run-in excluded. Registration programmes recruit a population selected to show an effect if one exists, which is the right design and a poor basis for generalising. The run-in is the part that is easiest to miss: a programme that drops people during a placebo lead-in has already removed those least likely to tolerate or comply, and the published arms describe the survivors. External validity is not a property of the trial; it is a property of the distance between its population and yours, and that distance is yours to measure.
This is answerable from the published record, but only if you take the placebo arm seriously rather than reading the active arm alone.
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 underlying point is that 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.
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.
Aggregated, published test results and vendor ratings built from submitted batches. Methodology stated, dataset browsable, no listing fees.
Browse resultsLook 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.
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.
When two sources disagree, the answer is almost always in the methods section of the one you have not read.
In practice, the trial answers a narrower question than the headline suggests, and the narrowing is where the useful information is.
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.
The underlying point is that 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.
Quote the interval alongside the estimate and half the disagreements on this site would not start.
edited 26 Oct 2025 by Dr_Priya_Raghunathan — added the citation requested in comments
The short version: the effect is real, the magnitude depends on the population, and the population is usually the part that gets dropped when a result is quoted second-hand.
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.
If a claim cannot be traced to a named trial with a named endpoint, treat it as a claim rather than as evidence.
The 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.
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.
Read the protocol and the statistical analysis plan if the result matters to you. Both are usually published alongside.
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.