It seems to me like claim (2) could easily make sense if you interpret it more charitably as “the mortality effects are too small for the studies to detect”.
Bingo, partially, it’s likely that at least in the Indian study the mortality was too low over that period to be accurately represented … which is the same argument I’d have for 100% of the kidney donation studies, follow-up is not lengthy enough, and the longer you followup and the stronger your controls the worse things get.
Death is a bad endpoint for evaluating things and thus we should not be using it.
I would have a longer claim (in the linked article) that in some cases it is worth using, given that e.g. our views around why modern medicine is good and worthwhile ultimately root themselves in preventing mortality and such things are as of yet on shaky grounds.
But when doing risk estimates we should try looking at proxies for mortality and QAL downgrades as opposed to mortality, especially when we don’t have life-long studies or studies following people into old age when most of them start dying.
Bingo, partially, it’s likely that at least in the Indian study the mortality was too low over that period to be accurately represented … which is the same argument I’d have for 100% of the kidney donation studies, follow-up is not lengthy enough, and the longer you followup and the stronger your controls the worse things get.
Death is a bad endpoint for evaluating things and thus we should not be using it.
I would have a longer claim (in the linked article) that in some cases it is worth using, given that e.g. our views around why modern medicine is good and worthwhile ultimately root themselves in preventing mortality and such things are as of yet on shaky grounds.
But when doing risk estimates we should try looking at proxies for mortality and QAL downgrades as opposed to mortality, especially when we don’t have life-long studies or studies following people into old age when most of them start dying.