Topic summary

Revisiting: Primary endpoint hierarchies and why order matters

Evidence › Trials estimand surrogate endpoints discontinuation & dropout intention to treat open label

This is a generated summary. It shows the 5 most-liked posts from a topic of 26, in their original order, with the accepted answer included where one exists. It is a reading aid and it will miss nuance — the full topic is the record.

a.hartmannTL2 Moderator3 May 2026#1

Posting this under the heading it deserves: Revisiting: Primary endpoint hierarchies and why order matters Everything below is what sits behind that.

Comparing SURMOUNT-4 (JAMA, 2024) with SURPASS-2 (N Engl J Med, 2021) and finding the comparison harder than it looks.

Different populations, different durations, different endpoints defined slightly differently, and in one case a different estimand. People compare the headline percentages anyway, including me until recently.

Is there a defensible way to put these side by side, or is the honest answer that there is not and we should stop?

43 likes 3mo

v.salgadoTL2 Moderator6 May 2026 · edited#6

a.hartmann, post #1: Posting this under the heading it deserves: Revisiting: Primary endpoint hierarchies and why order matters Everything below is what sits behind that. Comparing SURMOUNT-4 ( JAMA , 2024) with SURPASS-2 ( N Engl J Med , 2021) and finding the comparison harder than it looks. Different populations, different durations, different endpoints… Go to post

Worth separating two things that post #2 runs together.

Risk of bias: structured appraisal of internal validity. Key things to assess: randomisation method (was it truly random or could someone predict the next assignment), concealment (could randomisation be subverted), blinding (who was blinded and why or why not), completeness of outcome reporting.

32 likes in reply to #1 3mo

a.stephanopoulosTL3Regular7 May 2026#10

On post #6 — agreed on the reasoning, with one qualification.

Absolute numbers, not just relative: a 30% relative reduction tells you the ratio but not the practical magnitude. The event rate in each arm and the difference between them tells you how many people benefit.

24 likes 3mo

y.adebayoTL2 Moderator8 May 2026#12

Population narrowness: most trials in this class enrolled fairly specific groups. Baseline body mass index ranges, exclusion of renal disease, exclusion of certain comorbidities, all narrow the population. Applying point estimates to someone well outside the range is an extrapolation.

32 likes 3mo

SHermansenTL2Member11 May 2026#21

The estimand: what the trial set out to estimate. Two trials can be identical in structure but estimate different things by using different handling rules for people who stop taking the drug. Treatment-policy and hypothetical approaches are both legitimate but answer different questions.

29 likes 3mo

Read the full topic (26 posts)

Promoted into the documentation commons. The content of this topic is maintained at PIONEER 6 — trial digest, with named maintainers and a review date. The promotion was discussed in doc review. Corrections are best raised against the document, which is the version that gets kept current.

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