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What did the placebo arm of SURMOUNT-4 report for early satiety?

Asked 7 Apr 2025Modified 12 months agoViewed 47k times
37

What I have: SURMOUNT-4 · early satiety.

This is presented as though it settles something, and I am not convinced it does.

I have two documents that appear to disagree, which is what prompted this.

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

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askedsample_id17k277 Apr 2025

5 Answers

Accepted answer first, then by votes
29

Accepted answer

Start with the population. The inclusion criteria of the trial determine what its result can be extrapolated to, and the extrapolation people want is usually to a population the trial excluded.

Absolute risk reduction, worked: if the control-arm event rate is 8.0 per cent over the follow-up period and the hazard ratio is 0.80, the treated rate is approximately 6.4 per cent, the absolute risk reduction is 1.6 percentage points, and the number needed to treat is 1 ÷ 0.016 ≈ 63 over that period. A 20 per cent relative reduction and a number needed to treat of 63 are the same finding stated two ways, and only one of them sounds impressive.

Relative to absolute, worked

QuantityValueDerivation
Control-arm event rate8.0 %From the trial table, not the abstract
Hazard ratio0.80Reported
Treated event rate6.4 %8.0 × 0.80
Absolute risk reduction1.6 pp8.0 − 6.4
Number needed to treat631 ÷ 0.016
Relative risk reduction20 %1 − 0.80

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

ApoB and LDL-C disagree because they measure different things: LDL-C is the cholesterol mass carried in the LDL fraction, ApoB is a count of atherogenic particles. Small dense particles carry less cholesterol each, so a person with many small particles has a concordantly higher ApoB than their LDL-C suggests. When they disagree, ApoB is the better risk marker.

STEP 1 reported a mean weight change of approximately −14.9 per cent with semaglutide 2.4 mg versus −2.4 per cent with placebo at 68 weeks[1]; the difference between the figures quoted from this trial in different places is an estimand difference.

Read the confidence interval, read the estimand, and compute the absolute effect yourself. It takes two minutes and it changes how the result feels.

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CM
answered · acceptedcarys_meredith17k2828 Jun 2025
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20

In practice, a single laboratory value is a point on a noisy curve. What you want is a trend across at least three draws under comparable conditions, and "comparable" is doing a lot of work in that sentence.

Creatinine is a muscle-derived metabolite, so a substantial loss of lean mass lowers serum creatinine and mathematically raises estimated GFR without anything happening to the kidney. If you have lost twenty kilograms, your creatinine-based eGFR is flattering you. Cystatin C is not muscle-dependent and is the measure to use when the two disagree.

The underlying point is that liver enzymes are a poor surrogate for hepatic histology in both directions: substantial steatohepatitis with normal transaminases is common, and modest enzyme elevation with minimal fibrosis is common. If the question is fibrosis, the answer comes from a non-invasive score such as FIB-4 or a stiffness measurement, not from ALT.

The caveat is the population. Trial participants were screened, monitored and supported; the effect size in an unmonitored setting is not the trial effect size, and it is not obvious in which direction the difference runs.

The papers are readable. Read the paper rather than the summary of the paper, especially where the summary is enthusiastic.

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DB
answeredDr_Fatima_Belkacem52k13826 May 2025
2I have seen exactly this failure mode twice and both times it was the diluent. – Dr_Wren_Halliday 8 months ago
3The distinction between purity and content cannot be repeated often enough here. – vialroom 10 months ago
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13

Put another way, the hazard ratio is the relative effect. What changes decisions is the absolute effect, and converting between them requires the event rate in the control arm, which is usually in the same table and rarely in the abstract.

The rodent thyroid C-cell findings that generated the labelled warning appear to be species-specific: rodent C-cells express GLP-1 receptors at high density, human C-cells at very low density, and human calcitonin data across large trial populations has not reproduced the signal. A family history of medullary thyroid carcinoma or MEN2 is nonetheless a genuine contraindication rather than a theoretical one.

A fasting lipid panel drawn during rapid weight loss reads oddly for a mechanical reason: mobilised adipose tissue delivers free fatty acids to the liver, and hepatic triglyceride export rises. Triglycerides can transiently increase while the person is doing exactly the right thing. Draw the panel when weight has been stable for a few weeks if you want an interpretable number.

FLOW tested a composite renal endpoint — kidney failure, sustained 50 per cent eGFR decline, or renal or cardiovascular death — in type 2 diabetes with chronic kidney disease, and was stopped early for efficacy[1].

Worth being explicit that this is interpretation of published data and not medical advice. Laboratory results belong in a conversation with whoever ordered them.

If the trend across three draws is flat, the difference between draws one and two was noise. Most of what people react to is noise.

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DF
answeredDr_Colm_Fitzhenry85k24817 Jun 2025
8

In practice, the confidence interval is the informative part. A point estimate with an interval spanning no effect is a different object from the same point estimate with a tight interval, and the abstract presents them identically.

Estimated average glucose from HbA1c: eAG in mg/dL = 28.7 × A1c − 46.7, or in mmol/L, 1.59 × A1c − 2.59. An A1c of 6.5 per cent is therefore about 140 mg/dL or 7.8 mmol/L. The relationship is a population regression, so an individual can sit well off the line.

None of this replaces a clinician who can see the whole picture, and the whole picture is usually where the answer is.

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AM
answeredaine_mulcahy35k3821 Jul 2025
6The placebo-arm figure is the part everyone omits. – Dr_Yusuf_Adeyemi 3 months ago
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-2

Mechanically, read the estimand before the effect size. Almost every apparent contradiction between two published figures from the same trial resolves once you notice that one is a trial-product estimand and the other is a treatment-policy estimand.

A network meta-analysis can rank agents that were never compared directly, but only under a transitivity assumption — that the trials being linked are similar enough in population, duration and endpoint definition for the indirect comparison to hold. In this field that assumption is often visibly violated, which is why indirect rankings should be read as hypotheses.

SURMOUNT-4 randomised participants after an open-label lead-in to continued tirzepatide or placebo, and the withdrawal arm regained a substantial proportion of the lost weight over the following year[1].

Convert everything to an absolute effect before you compare two interventions. Relative effects are not comparable across different baseline risks.

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TM
answeredtobias_maartens94k2586 Jun 2025
2Related: the same reasoning applies to the counter-ion question. – sian_llewellyn 5 months ago
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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.

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