Comment by EA-3167
3 years ago
The key is that the approved treatments are proven to have the requisite efficacy, the risks that come with that are an acceptable tradeoff. The unapproved, often largely untested world of early breakthroughs doesn't have that guarantee of potential efficacy, it often JUST has risks.
It may help to not view the options as a binary choice between drugs approved under the current process and any drug not currently approved.
What constitutes the acceptable tradeoff is the heart of the matter. On the one hand, even the current approval process does not always guarantee efficacy (Aduhelm to mention it by name). Medical trials work with considerable uncertainty, and the risk/benefit tradeoff is always a question of probabilities. Even with the current process, there is no certainty or guarantee.
It is possible to take those probabilities and to talk about the expected number needed to treat (NNT) for a medication, the expected side effect profile, how many people might live and how many might die. Things that may sound cold, but that are already routinely done today.
It is hard to know where the tradeoff should be, how much margin of error is the right amount before something is approved, knowing that there is uncertainty even in large trials, but it's not a choice between the totally unapproved and the status quo. (Better yet, we should not model the choice as a single parameter that goes from more choice & more snake oil to less choice & more safety. It's also often possible to improve one aspect of a bureaucracy without it being a zero-sum game.)
I don’t understand your overall point here as this is pretty much how the current system works.
> It is possible to take those probabilities and to talk about the expected number needed to treat (NNT) for a medication, the expected side effect profile, how many people might live and how many might die.
NNT > NNH = efficacy. To calculate these the trials need to be done, which is not the case for experimental therapies as they have undetermined benefits and harms (hence why they’re in trial).
The choice here is between conventional options that have known benefits/harms, however crappy they may be, with something that has unknown values.
Trials are done in multiple phases, with a progressively wider population. There is a point where we consider a drug to still be unproven, but safe enough for human trials.
I think that situations like TFA make a compelling case for selectively broadening access, for some drugs and some pathologies. The characterization of a choice between something proven and something with unknown values is too coarse and not a good model.
Clinical trials are very expensive, drug development as a field tends to move forward with what it thinks will have a chance of making it through. While most new drugs indeed fail (the large majority of them), in diseases with very poor prognosis like OP's cancer, I think we would benefit from still looking at the tradeoff as a decision under uncertainty, instead of a complete unknown. Even with less data than we would otherwise want.
Looking at experimental therapies as completely undetermined leads to a binary choice. There is supporting evidence that allows those therapies to move forward with experimental trials in the first place. The counterfactual of not treating patients with poor prognosis being what it is, my overall point is that treating experimental drugs as total unknowns with benefits and harms that cannot be quantified until the full process is finished is not consistent with the knowledge that, even after all trials are completed, this is still a uncertain statistical result, only with slightly more data than before.
In other words, we are always working with partial unknowns so when the prognosis is bad a larger unknown may be good overall and save lives, even though it wouldn't be acceptable otherwise.
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