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Evidence · Trials · continued

Non-inferiority margins: how they are chosen and how they are abused posts 31–47

This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1.

AD
appeals_deskTL3Regular3 Jan 2026#31

Worth separating two things that post #27 runs together.

Two things before anyone answers the substance.

First, the context in the first post is clear and specific. Second, the question is framed so that an answer can actually address it. Both are the norm here and both matter more than they sound.

11 likes 7mo
HL
h.lindqvistTL2 Moderator6 Jan 2026#32

post #31 is right about the mechanism and I think understates the practical bit.

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.

3 likes 7mo
WP
weekly_pinTL2Regular9 Jan 2026#33
Birkeland, post #13: Two things before anyone answers the substance. First, the context in the first post is clear and specific. Second, the question is framed so that an answer can actually address it. Both are the norm here and both matter more than they sound. Go to post

Open-label design: unblinded trials admit expectation effects. For weight-loss trials where one arm loses substantial weight and the other does not, complete blinding is impossible anyway. The unblinded nature is a limitation worth noting.

0 likes in reply to #13 7mo
SA
s.adebayoTL2 Moderator11 Jan 2026#34

Surrogate endpoints: an endpoint that is not the outcome that matters but is measured as a stand-in. HbA1c is a surrogate for long-term glucose control and the short-term complications it prevents. Weight loss is a surrogate for metabolic health and long-term outcomes. Surrogates are useful but not identical to the endpoint that matters.

25 likes 6mo
EF
endo_fellow_rkTL3Endocrinology fellow14 Jan 2026#35

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.

7 likes 6mo
TD
t.dumitruTL2 Moderator17 Jan 2026 · edited#36
c.lundgren, post #22: Two things before anyone answers the substance. First, the context in the first post is clear and specific. Second, the question is framed so that an answer can actually address it. Both are the norm here and both matter more than they sound. Go to post

post #35 answers the question as asked. The question underneath it is different.

Generalisability: the enrolled population was selected in ways that matter. Entry criteria, run-in periods, and the simple fact that people who agree to a multi-year trial differ from people who do not, all narrow the population. That is how internal validity is bought, at the cost of external validity.

1 like in reply to #22 6mo
TH
TL4_HalvorsenTL4Leader · Journal club20 Jan 2026#37
buffer_sheet, post #11: I read post #9 twice before replying, because I had assumed the opposite. Surrogate endpoints: an endpoint that is not the outcome that matters but is measured as a stand-in. HbA1c is a surrogate for long-term glucose control and the short-term complications it prevents. Weight loss is a surrogate for metabolic health and long-term… Go to post

Coming back to post #35, because the follow-up matters more than the original answer.

Intent-to-treat versus per-protocol: ITT includes everyone assigned regardless of whether they took the drug. Per-protocol includes only those who completed it as intended. The two can give substantially different results.

0 likes in reply to #11 6mo
JV
j.vogelTL2 Moderator22 Jan 2026#38

Multiplicity and multiple comparisons: if a trial tests many hypotheses, the chance of a false positive on at least one by random chance increases. This is why pre-specification of the primary endpoint matters and why secondary endpoints are weaker evidence.

18 likes 6mo
SL
s.leclercTL4 Moderator25 Jan 2026#39

Dropout is information: high dropout rates can indicate tolerability problems or lower efficacy than the summary suggests. Where the analysis handled dropouts matters. An intention-to-treat analysis with many dropouts can give a smaller apparent effect than per-protocol analysis.

23 likes 6mo
CR
c.ramosTL2 Moderator28 Jan 2026#40

Confounding in observational data: a third variable can explain an apparent association. In a randomised trial, randomisation balances unknown confounders. In observational data, observed confounders can be adjusted for but unknown ones cannot.

11 likes 6mo
TS
taper_shiftTL3Regular30 Jan 2026#41

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.

15 likes 6mo
HN
h.nwosuTL2 Moderator2 Feb 2026#42
d.oyelaran, post #4: I read post #2 twice before replying, because I had assumed the opposite. Dropout is information: high dropout rates can indicate tolerability problems or lower efficacy than the summary suggests. Where the analysis handled dropouts matters. An intention-to-treat analysis with many dropouts can give a smaller apparent effect than… Go to post

Worth separating two things that post #38 runs together.

Open-label design: unblinded trials admit expectation effects. For weight-loss trials where one arm loses substantial weight and the other does not, complete blinding is impossible anyway. The unblinded nature is a limitation worth noting.

29 likes in reply to #4 6mo
O
OstrowskiTL2Member5 Feb 2026#43

Dropout is information: high dropout rates can indicate tolerability problems or lower efficacy than the summary suggests. Where the analysis handled dropouts matters. An intention-to-treat analysis with many dropouts can give a smaller apparent effect than per-protocol analysis.

0 likes 6mo
JS
j.silvaTL2 Moderator7 Feb 2026#44

Having read the exchange above, I think I was wrong earlier in this topic and I want to say so plainly rather than quietly editing.

The correction was fair and I had been repeating something I had not checked carefully enough.

2 likes 6mo
MS
m.stephanopoulosTL3Regular10 Feb 2026 · edited#45

Multiplicity and multiple comparisons: if a trial tests many hypotheses, the chance of a false positive on at least one by random chance increases. This is why pre-specification of the primary endpoint matters and why secondary endpoints are weaker evidence.

10 likes 6mo
ZI
z.iyerTL2 Moderator13 Feb 2026#46

Intent-to-treat versus per-protocol: ITT includes everyone assigned regardless of whether they took the drug. Per-protocol includes only those who completed it as intended. The two can give substantially different results.

22 likes 5mo
LO
l.oseiTL2 Moderator15 Feb 2026#47
Knowlton, post #9: 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. Go to post

Picking up post #44: that is the part I would want checked first.

For anyone arriving from a search: the marked solution above is the direct answer, and the replies underneath it add the caveats that make it safe to use.

0 likes in reply to #9 5mo
Promoted into the documentation commons. The content of this topic is maintained at STEP 8 — 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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