This forum is about wrong numbers in science, politics and the media. It respects good science and good English.
That's interesting and prompts a few questions, more about the Vioxx side of things than the efficacies of 'lifestyle choice' recreational treatments.
Is there any attempt (assuming it could be done ethically) to assess for common circumstances (DNA or previous health events come to mind but there may well be more factors) for those who are adversely affected by drugs in the way that the Vioxx trial identified?
If there is and a regular pattern could be confidently elicited from the results, notably for the early negative outcomes, it would suggest that individuals could be pre-screened for unsuitable treatments. Maybe.
On that basis the moral clouds of health risk during trals could be more tolerated ("for the greater good") and pre-treatment testing to identify and exclude from treatment those who are thought to be at risk could be implemented. Those not thought to be at risk might then progress to a successful treatment.
Presumably at some point the risk factor associated with long term use, beyond any previous controlled trials, would have to be considered but in the meantime the many would have had access to a presumably effective (for them) treatment and the few with an anticipated high RR would have been protected from the risk.
Assuming that whatever information could be gathered from those that succumbed to the risk was both relatively conclusive and cost effective (and I appreciate that might be a big IF) thus making the idea a practical proposition, what other factors, moral or scientific, would kick such an approach onto the sidelines?
Some of that is done, for example with tumour genotypes or expression profiles for oncology drugs.
Of course most of this work is speculative and experimental and in the context of clinical trials these are rarely statistically powered to be informative in terms of "these patients are more/less likely to respond to treatment".
Of course, faced with 10 potential treatments for whatever disease you'd like to know which one the patient is most likely to respond to. That's the holy grail if you like, not treating someone with a drug they won't respond to anyway but going straight to the one that will work for them.
To the extent that that is down to individual physiology rather than random, it's largely something for the future when you can genetically profile everyone cheaply, with the compounding problems being that you are then looking for probably small differences in response between potentially hundreds of thousands of subgroups, plus all genetic stuff is multifactorial anyway, so correlating genetic background with response in some set of people is unlikely to apply to some other set. Not to mention we are entirely neglecting phenotype here.
So tailor-made treatment is theoretically very nice, but is likely to remain as much art as science for a long time.