What does STEP 2 tell me about injection-site erythema at the 60 mg dose?

The case in front of me: STEP 2 · injection-site erythema · 60 mg.

The figures are clear enough; the question is what they mean and what they do not.

I can supply the numbers if the specifics change the answer.

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

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.

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.

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.

SURMOUNT-OSA reported reductions in the apnoea-hypopnoea index with tirzepatide in adults with obesity and moderate-to-severe obstructive sleep apnoea, both with and without concurrent positive airway pressure therapy[1].

The limitation is that surrogate endpoints and hard endpoints have come apart before in metabolic medicine, so a favourable biomarker is a reason for optimism rather than a conclusion.

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

Stated carefully, this is a question about what the trial was designed to answer, and the honest response is that it was not designed to answer this.

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.

Worth being precise here: 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 PIONEER programme established oral semaglutide’s efficacy and the constraints on its administration, and the bioavailability figure of roughly one per cent is what drives the fasting and water-volume requirements[1].

I would resist reading a subgroup finding as a result. Subgroups in these trials were not powered, and a striking subgroup in a large trial is the expected consequence of multiplicity.

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.

The underlying point is that 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.

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.

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.

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

edited 26 Jul 2024 by w_okoye — added the method parameters

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.

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.

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

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