For reference: PIONEER-1 · headache · 25 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?
Only what the 25 mg arm reported, and the denominator is that arm rather than the trial. Adverse-event tables are published per arm, so the 25 mg incidence of headache has its own numerator and its own denominator, and pooling it with the other arms produces a figure that describes nobody. Two further deductions before you use it. Subtract the placebo arm — headache occurs in people who received nothing, and the difference is the part attributable to the drug. And check whether PIONEER-1 counted events or counted participants: one participant with six episodes is one row in a participant count and six in an event count, and the two get quoted interchangeably. Nothing here is medical advice.
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.
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.
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.
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.
Read the protocol and the statistical analysis plan if the result matters to you. Both are usually published alongside.
Analytical standards and reagents with traceable certificates. Every quantitative result you read inherits the accuracy of the standard behind it.
Shop standardsThe 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.
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.
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.
When two sources disagree, the answer is almost always in the methods section of the one you have not read.
edited 1 Nov 2024 by Dr_Bram_Verhoeven — corrected a unit error in the worked example
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.