What does SURMOUNT-OSA report at the 5 mg dose level?

For reference: SURMOUNT-OSA · 5 mg.

I have the document in front of me and I can read the numbers. What I cannot do is interpret them.

I am reasonably comfortable with statistics and completely uncomfortable with chromatography, or vice versa.

What is the correct interpretation, and what is the common misreading?

Read the 5 mg row, not the pooled one. A programme that randomised more than one dose level reports each arm separately, and the figure that circulates afterwards is usually either the top-dose arm or an average across arms nobody was randomised to. If SURMOUNT-OSA ran a 5 mg arm, that row carries its own sample size and its own confidence interval, and both are narrower than the trial-level ones by roughly the square root of however many arms there were. Take the primary publication rather than the press release: one reports by arm, the other reports whichever number is largest. A dose level inside a trial is a protocol decision made under supervision, not a recommendation, and nothing here is medical advice.

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.

Relative to absolute, worked

The last two rows describe the same finding. Only one of them is used in headlines.

The part that matters: 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.

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

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.

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.

It helps to be literal here: 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.

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.

edited 9 Jul 2024 by Dr_Tomas_Kral — clarified the distinction between purity and content

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.

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.

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.

To be exact about it, the trial answers a narrower question than the headline suggests, and the narrowing is where the useful information is.

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.

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

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

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.

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.

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