Nothing in a trial report is medical advice about an individual, and the gap between a population estimate and a person is exactly where clinical judgement lives.
If anyone has run this properly I would rather read that than my own guess.
This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1 · go to the accepted answer.
Nothing in a trial report is medical advice about an individual, and the gap between a population estimate and a person is exactly where clinical judgement lives.
If anyone has run this properly I would rather read that than my own guess.
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.
Not a conclusion. A place to stand while looking for one.
On post #60 — agreed on the reasoning, with one qualification.
Genuine question rather than a rhetorical one: has anyone here actually observed Comparators chosen for regulatory reasons, as opposed to read about it? The thread is long and I cannot tell.
Picking up post #63: that is the part I would want checked first.
Practical answer on Comparators chosen for regulatory reasons, since the theoretical one is upthread: do the simplest check first, write down the result, and only then decide whether the complicated explanation is needed. It usually is not.
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.
Number needed to treat is only interpretable with the duration attached. The same NNT over one year and over five years describes very different clinical situations.
Comparators chosen for regulatory reasons is a question about a distribution, not about a value, and treating it as a value is what produces the confident wrong answers.
Two people in this thread mean different things by Comparators chosen for regulatory reasons and are disagreeing about the definition while believing they are disagreeing about the facts. Worth pausing to define it.
Post #68 answers the question as asked. The question underneath it is different.
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.
Worth one more sentence than it usually gets.
Taking post #70 at face value and following it one step further.
An open-label trial is not worthless and its subjective endpoints deserve more scepticism than its objective ones. That is a graded judgement rather than a verdict.
Second-hand, so weight it accordingly.
Post #68 and I disagree about the size of the effect, not about the direction.
Non-inferiority margins are chosen, and the choice is an argument rather than a fact. A wide margin can make a worse treatment look acceptable.
Posting it because the silence on this was starting to look like agreement.
Practical note on Comparators chosen for regulatory reasons: write down what you expect before you look. The number of times I have found what I went looking for is higher than chance would allow.
Comparators chosen for regulatory reasons is one of those subjects where the general answer and the answer for a specific case diverge, and the thread will go in circles until someone says which one is being asked for.
This follows post #74 rather than contradicting it.
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.
Reading it again, the caveat matters more than the finding.
That is consistent with mine, for whatever one more account is worth.
Two things can be true about Comparators chosen for regulatory reasons at once: the mechanism is plausible and the evidence for the size of the effect is thin. Most of the argument here is people defending the first against attacks on the second.
Coming back to post #75, because the follow-up matters more than the original answer.
Before the thread moves on from Comparators chosen for regulatory reasons — what is the sample size behind the claim? I am not being difficult; I have seen the same figure quoted from an n of four and from an n of four hundred.
A treatment-policy estimand asks what happens to people assigned to a strategy, including those who abandon it. A hypothetical estimand asks what would have happened had everyone continued. Both are legitimate and they give different numbers.
Two claims get bundled together under Comparators chosen for regulatory reasons and they need separating. The descriptive one — this is what was observed — is usually well supported. The causal one — this is why — usually is not.
Almost every disagreement in threads like this one dissolves once you say which of the two you are making.
I had written a reply contradicting post #78 and deleted it. Here is what survived.
I would call the community position on Comparators chosen for regulatory reasons likely rather than established, and I would be comfortable defending that hedge.
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.
Correct me on the arithmetic if it is wrong; I would rather know.
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.
I would call that likely rather than established.
A treatment-policy estimand asks what happens to people assigned to a strategy, including those who abandon it. A hypothetical estimand asks what would have happened had everyone continued. Both are legitimate and they give different numbers.
If anyone can point at the primary source I would be grateful.
The arithmetic in post #85 is right; the assumption feeding it is the part to check.
The failure mode on Comparators chosen for regulatory reasons is boring rather than dramatic. It is almost always the step everyone assumes was done correctly because it is too simple to get wrong.
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