Sample size calculations, read backwards from the published number

Sample size calculations, read backwards from the published number Writing it up because I had to work it out twice and would rather nobody else did.

Session topic: SUSTAIN 6 (N Engl J Med, 2016). Please read it before posting; the discussion is much better when everyone has.

The question I would like us to start with is what the trial set out to estimate, rather than what it found. Once that is on the table we can talk about whether the design could have answered it, and only then about the numbers.

Specific things I would like covered: the population and how far it generalises, how discontinuation was handled, whether the comparator was a fair one, and what the absolute rather than relative effect looks like.

I will summarise at the end and the summary will feed the relevant digest page.

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.

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.