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Why do two papers on SURPASS-2 report different headline figures?

Asked 14 Jul 2026Modified 1 min agoViewed 6.4k times
This question was marked as a duplicate of Why do two papers on STEP 8 report different headline figures?Closed 28 Jul 2026. It remains here because the answers below are specific to how it was asked.
20

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

This is one of those things that everyone repeats and nobody derives.

This matters practically, not just academically, because it changes what I would do next.

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

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CD
askedcolm_dunphy8.2k1414 Jul 2026
2Is that the primary endpoint or a secondary one? They get quoted interchangeably. – tandem_gradient 4 months ago
Do you have the population it was measured in? The figure moves a lot between them. – halvard_ness 2 months ago
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5 Answers

Accepted answer first, then by votes
46

Accepted answer

Because two papers on SURPASS-2 are usually reporting two different estimands from the same randomisation. The treatment-policy estimand asks what happened to everyone assigned, including those who stopped; the trial-product estimand asks what happens if you keep taking it. The second is always the larger number, and both are legitimate answers to different questions. Then there is the analysis population — randomised, treated, or completers — and the handling of missing data, where a last-observation-carried-forward and a multiple imputation can differ by a point or more. Neither paper is wrong. Read the statistical methods section and you will find both figures defined in it.

The relevant detail is that this is answerable from the published record, but only if you take the placebo arm seriously rather than reading the active arm alone.

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 underlying point is that 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.

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

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CR
answered · acceptedcoring_risk27k2715 Jul 2026
The placebo-arm figure is the part everyone omits. – plate_count_9k 6 months ago
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40

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.

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.

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.

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.

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RM
answeredrosa_mendieta8k1628 Jul 2026
19

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.

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.

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.

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

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

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DB
answeredDr_Ingrid_Baumgartner73k5821 Jul 2026
7Adding a vote because this deserves more of them. – Dr_Idris_Coulibaly 8 months ago
6Good answer, but the confidence interval in the cited trial is wider than implied. – Dr_Ilse_Vandenberg 6 months ago
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15

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.

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.

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.

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

edited 5 Aug 2026 by j_wierzbicki — fixed an arithmetic slip in the third paragraph

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JW
answeredj_wierzbicki69k14815 Jul 2026
6Minor: the trial name is hyphenated in the original publication. – t_oyelaran 4 months ago
7Worth flagging that this changed with the 2025 publication, so older answers are out of date. – Dr_Colm_Fitzhenry 6 months ago
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15

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

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DK
answeredDr_Sara_Kuusela28k3725 Jul 2026

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.