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What does SURMOUNT-3 actually establish about a GLP-1 receptor agonist?

Asked 23 May 2024Modified 22 months agoViewed 23k times
2

What I am working with: SURMOUNT-3 · a GLP-1 receptor agonist.

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.

How should I read this, and where are the traps?

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askedanouk_desmet16k3823 May 2024
Worth saying whether you want relative or absolute risk. They read very differently. – stopper_core 8 months ago
Same question, and the two papers I found disagree, which is why I am watching. – juliette_farnese 10 months ago
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5 Answers

Accepted answer first, then by votes
-3

Accepted answer

Whatever its primary endpoint was, at the power it was designed for, in the population it recruited — and nothing else. SURMOUNT-3 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.

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

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.

Concretely, 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.

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.

I am not a clinician and this is not medical advice; it is a reading of a published protocol.

When two sources disagree, the answer is almost always in the methods section of the one you have not read.

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answered · acceptedDr_Tomas_Kral53k3831 Jul 2024
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23

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.

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.

More usefully, 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.

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

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DA
answeredDr_Rosalind_Achebe69k14711 Aug 2024
20

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.

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.

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

edited 16 Sept 2024 by Dr_Rosalind_Achebe — added a caveat about sampling

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DA
answeredDr_Rosalind_Achebe69k14722 Aug 2024
8Is the open-label extension included in that figure, or just the randomised phase? – day_seven_trough 35 days ago
This should be linked from the help pages. – tabular_nums 3 months ago
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15

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.

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.

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.

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DV
answeredDr_Ilse_Vandenberg113k2482 Sept 2024
8Thank you for separating the surrogate from the outcome. That distinction gets lost constantly. – sian_llewellyn 3 months ago
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10

On the detail: 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.

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.

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.

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EH
answeredeighty_six_hours20k2713 Sept 2024
7This matches what I was told by a clinician, for whatever that is worth. – assay_blank 4 months ago
8Adding a vote because this deserves more of them. – sian_llewellyn 6 months ago
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Your answer

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.

Not medical advice. Research-use-only compounds are not approved for human use.