Why do two papers on TRIUMPH-1 report different headline figures?

This is a question about interpretation, not about whether to act — I will take action questions elsewhere.

I want to know whether this is a real physical effect or an artefact of how it is measured.

What prompted the question is an inconsistency between two sources I otherwise trust.

Is the standard explanation correct, and if so, what is the evidence for it?

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.

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.

Stated carefully, 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 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.

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.

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.

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.

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.

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.

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.

Meta-analyses in this area are dominated by whichever trial contributed the most participants, so read the forest plot rather than the summary estimate.

Be careful about generalising from a trial population to yourself. The exclusion criteria are usually the most informative page in the supplement.

If a claim cannot be traced to a named trial with a named endpoint, treat it as a claim rather than as evidence.

edited 4 May 2026 by u100_marks — tightened the wording; no substantive change

This is answerable from the published record, but only if you take the placebo arm seriously rather than reading the active arm alone.

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.

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.