does SELECT actually matter or is it forum lore at this point
Asking properly rather than in a comment on somebody else’s thread: does SELECT actually matter or is it forum lore at this point.
Compared myself to a trial mean for about six months before realising the trial arm had dietitian contact every fortnight.
On means, which this board treats as targets and which are nothing of the sort.
A reported mean body weight change is the centre of a distribution that in these trials is very wide. Substantial numbers of participants did much better, and substantial numbers did considerably worse while remaining on the drug and in the analysis.
Quoting the mean as an expectation therefore misleads in both directions: it makes ordinary results look like failures and it makes exceptional results look normal. If a paper publishes the distribution — and several do, in the appendix — look at that instead. It is far more informative than the number in the abstract.
Why comparing across trials almost never works, with the specific failure modes.
Different populations: an obesity programme and a diabetes programme enrol different people with different baseline characteristics. Different endpoints: body weight change, glycaemic control and cardiovascular events are not convertible. Different durations: 68 weeks and 72 weeks are not the same, and the curves have not flattened by either.
Different analysis populations: one paper reports intention-to-treat, another emphasises completers. Different support: some trial designs include structured lifestyle contact that no member of this board receives.
Stack those and the "X beats Y" tables that circulate here are comparing five things at once and attributing the difference to the molecule.
Screenshot none of this. Read the whole thread, including the parts where I am told I am wrong.
best — the order this archive was captured in
Cardiovascular outcome trials are powered for events, not for weight, and are typically run in a different population with different inclusion criteria. Reading a weight number out of one is reading a secondary endpoint.
Press-release posts get their own flair here. Nothing wrong with them, they are just a different kind of claim.
Small fix — that was the cardiovascular outcomes trial, so weight was a secondary endpoint and the population was different.
Agreed on comparators. "Superior" means nothing until you know superior to what and at what dose.
Discontinuation rates are a tolerability result. A trial with a strong efficacy number and heavy discontinuation is telling you two things and people only quote one.
How to read one of these papers in fifteen minutes, in the order that actually helps.
Start with the registered protocol and check the primary endpoint against what is reported. Then the methods: who was included, what the comparator was, how long the randomised phase ran. Then the discontinuation numbers, which are a tolerability result and are usually in a supplementary table.
Only then the efficacy figure, and read the interval rather than the point estimate. Finish with the limitations section, which is where the authors say what they actually think.
Fifteen minutes, and you will know more than any thread summarising it.
Relative risk reduction without the baseline rate is uninterpretable. A large relative reduction on a small absolute risk is a small absolute benefit.
Absolute or relative risk reduction?
open-label extensions are not the same evidence as the randomised phase
check who the comparator was before you compare anything
open-label extensions are not the same evidence as the randomised phase
Agreed. And the interval, not the point estimate, is what the trial actually established.
read the endpoint before you read the headline
A confidence interval is the range of effects compatible with the data. Two trials with overlapping intervals have not disagreed, whatever their point estimates look like next to each other.
Read a press release and the publication three months apart. The hedging in the second one was substantial.
Open-label extensions lose their randomisation. Anybody still enrolled at week 104 is a selected group and the numbers describe that group.
That is the 68-week readout, not the 72-week one. Different trial, different duration.
phase 2 finds a dose, phase 3 measures the effect
Intention-to-treat analyses everybody randomised regardless of what they did afterwards. Completer analyses only those who finished. The second is systematically more flattering and both are legitimate if labelled.
What did the confidence interval look like?
The registered protocol is public. Comparing the registered primary endpoint with the reported one is a two-minute check and it is how outcome switching gets caught.
Do you have the publication or the press release?
Yes — the interval is the finding. A point estimate with a wide interval is a hypothesis in a nice font.
Intention-to-treat analyses everybody randomised regardless of what they did afterwards.
Disagreeing with this line: that is a relative reduction and the absolute numbers are considerably less dramatic.
What was the discontinuation rate?
What was the discontinuation rate?
Adding the check nobody runs — the registered protocol is public and takes two minutes to compare.
Correction: SURMOUNT is the obesity programme and SURPASS is the diabetes one. The figure you quoted belongs to the other one.
Argued for a week about a result and then read the limitations section, which conceded most of my opponent’s point.
How long was the randomised phase before any extension?
- 1Intention-to-treat analyses everybody randomised regardless of what they did…9 comments in this branch · started by u/yara_mensah
- 2Relative risk reduction without the baseline rate is uninterpretable. A…8 comments in this branch · started by u/yusuf_ramos