Is SURMOUNT-5 a fair comparison of tirzepatide against its comparator arm?

Conditions: SURMOUNT-5 · tirzepatide.

I want to know whether there is evidence behind this or only repetition.

I have checked the obvious registries and monographs without success.

Has anyone verified this independently?

Fair depends on the comparator arm, and in SURMOUNT-5 that means asking whether the comparator was titrated to the same ambition as the experimental one. A head-to-head that runs its comparator to a dose below the one it is licensed at is not measuring the two agents, it is measuring one agent against a handicapped version of the other. Check three things: the maximum comparator dose reached, the proportion of the comparator arm that reached it, and whether the titration schedules had the same duration. If those match, the comparison is fair on dosing and the argument moves to the endpoint. If they do not, the effect size is partly an artefact of the protocol.

The relevant detail is that 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.

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.

Headline results, principal programmes

Mechanically, 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.

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.

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.

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.

To be exact about it, 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.

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.

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.

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.

Concretely, 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.

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.

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

The short version: check the endpoint, check the comparator, check who was excluded, then look at the number.

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.

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.

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.

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.

edited 10 Jun 2025 by Dr_Otto_Lindqvist — added the method parameters