What does SURMOUNT-1 actually establish about tirzepatide?

Setup, so nobody has to ask: SURMOUNT-1 · tirzepatide.

I would like help reading this properly rather than being told what conclusion to reach.

I have the full report including the method section, so I can quote specifics if that helps.

What would I need in addition before this supported a decision?

Whatever its primary endpoint was, at the power it was designed for, in the population it recruited — and nothing else. SURMOUNT-1 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.

Stated carefully, the trial answers a narrower question than the headline suggests, and the narrowing is where the useful information is.

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.

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.

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

edited 12 Jul 2024 by grainne_ahearn — expanded the table to cover the lower concentration

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.

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.

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.

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 caveat is that trial evidence is about licensed product administered under supervision. None of it transfers automatically to research-grade material of unverified content.

Quote the interval alongside the estimate and half the disagreements on this site would not start.

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.

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.

Worth being precise here: 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.

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

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.

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

Read the protocol and the statistical analysis plan if the result matters to you. Both are usually published alongside.

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.

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.

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.

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.