Trial registration and comparing the protocol with the paper

The honest answer on trial registration is that it depends, and the useful part is the list of what it depends on. Four items, in rough order of how much they matter.

Most people get the first two right and then argue about the fourth.

Seconded. It reads as careful rather than confident, which is the right register.

Coming back to post #14, because the follow-up matters more than the original answer.

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.

I would rather be precise about what I do not know than vague about what I do.

Narrowing post #16, because the general version has more than one answer.

The bit of trial registration that nobody enjoys is that the answer changes depending on what you are trying to decide with it. Say what the decision is and the thread will converge.

Everything in post #18 holds. The case it does not cover is the one I have.

Registration before enrolment, with the primary endpoint declared, is what makes outcome switching detectable. Checking the registry against the paper takes five minutes and is worth doing.

That is all I can say without guessing.

Post #19 and I disagree about the size of the effect, not about the direction.

Adding a small correction to the trial registration summary above rather than a disagreement with it. The substance holds; one of the figures is out by a factor that matters.

Reading rather than answering, but this is the post I would point somebody at.

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.

Post #23 put the caveat in the right place and I want to underline it.

Trial registration: I have looked for the primary source twice and failed twice. Either it does not exist or it is somewhere I do not know to look, and I would like to know which.

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 would want a second opinion before relying on that.

Effect sizes in a trial population reflect adherence achieved under trial conditions, which is generally better than adherence outside them.

The arithmetic in post #27 is right; the assumption feeding it is the part to check.

Funding and trial conduct should be stated and are a weak predictor of anything on their own. Design quality is the stronger signal and it is checkable.

Worth checking against a second source before it gets quoted onward.

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.

Somebody will have a better source than mine, and I hope they post it.

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.