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.
Topic summary
[2026 update] How to read a forest plot, properly, from scratch
This is a generated summary. It shows the 8 most-liked posts from a topic of 54, 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.
Narrowing post #8, because the general version has more than one answer.
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.
That is what I would do. It may not be what is correct.
20 likes 20mo
an.zamora, post #1: How to read a forest plot, properly, from scratch — that is the question, and I have not found it answered plainly anywhere I have looked. Reading SURMOUNT-4 ( JAMA , 2024) for the population rather than the effect, which I have not done properly before. The baseline table is more restrictive than the way the trial gets discussed here.… Go to post
Discontinuation handling is the methodological detail that most changes a result and gets the least attention. Read how missing data was imputed before reading the effect size.
This is the version I would want a new member to read first.
m.rasmussen, post #14: Picking up post #12: that is the part I would want checked first. Absolute and relative effects answer different questions. Write down the event rate in each arm and the difference between them; everything quotable is derived from those two numbers. Go to post
Post #14 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.
n.laurent, post #18: Absolute and relative effects answer different questions. Write down the event rate in each arm and the difference between them; everything quotable is derived from those two numbers. I have separated what I observed from what I concluded, which does not always happen. Go to post
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.
m.mwangi, post #26: Where I part company with post #24, and it is a narrow parting. Composite endpoints should be read component by component. A composite driven entirely by its softest component is a different finding from one where the components move together. Go to post
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.
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.
25 likes 19mo
I had written a reply contradicting post #42 and deleted it. Here is what survived.
Absolute and relative effects answer different questions. Write down the event rate in each arm and the difference between them; everything quotable is derived from those two numbers.
29 likes 19mo
Read the full topic (54 posts)
Promoted into the documentation commons. The content of this topic is maintained at STEP-HFpEF — 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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