131–140 of 172 posts
Earlier quoted context omitted.
If I were facing a 75-90% chance of dying, I think I’d be pretty happy to reduce that to 6-30%.
But I wouldn’t call the disease “cured”.
Although if I were to die from it I wouldn't probably be able to call it anything.
There is no news I enjoy reading more than that a clinical trial had to be ended early because the treatment was so effective that it would be unethical to continue with alternative treatments (or a placebo).
Actually, it's quite terrifying when you remember that stopping a clinical trial early is a great way to create statistical fraud. https://blogs.sciencemag.org/pipeline/archives/2019/08/08/st... cites an example of a drug whose clinical trial was stopped early due to obviously effective success... only to discover later on that the "obviously effective" was a statistically spurious event, and the drug did not confer…
There are 6 possibilities:
1- stop early, effective
2- stop early, ineffective
3- passed all trials, effective
4- passed all trials, ineffective
5- failed trials, effective
6- failed trials, ineffective
Assign a utility value (lives saved, risks, cost,...) and a probability to each situation and do the maths.
P(1) = P(3) + P(5)
P(2) = P(4) + P(6)
So, if (P(3) + P(5))U(1) + (P(4) + P(6))U(2) > P(3)U(3) + P(4)U(4) + P(5)U(5) + P(6)U(6) it is better to stop early.
The risk of fraud can be taken into account.
There is no news I enjoy reading more than that a clinical trial had to be ended early because the treatment was so effective that it would be unethical to continue with alternative treatments (or a placebo).
Actually, it's quite terrifying when you remember that stopping a clinical trial early is a great way to create statistical fraud. https://blogs.sciencemag.org/pipeline/archives/2019/08/08/st... cites an example of a drug whose clinical trial was stopped early due to obviously effective success... only to discover later on that the "obviously effective" was a statistically spurious event, and the drug did not confer…
Earlier quoted context omitted.
That trial wasn't a "statistically spurious event", it was a flawed trial > the reason the first trial came to an exaggerated impression seemed to be the number of patients who might not have fully progressed to SPMS Stopping early can lead to statistical fraud, which is why the bar is so high on doing so. But it has to be balanced with the recognition that, if the interim results are correct, continuing the trial wi…
Having worked in clinical trialling, what I saw made me realise that the final stats may be worth much less because of mismanagement of data. I can give some hare-raising examples[0] but for obvious reasons... The one I can give is it was known that docs who prescribed this to multiple patients and saw an apparent improvement the attributed to the new drug, would switch the patients on the old drug to the new and not…
In general it’s worth remembering that RCTs are estimating the effect of an intention to treat ( the randomisation) not the treatment itself.
Earlier quoted context omitted.
Having worked in clinical trialling, what I saw made me realise that the final stats may be worth much less because of mismanagement of data. I can give some hare-raising examples[0] but for obvious reasons... The one I can give is it was known that docs who prescribed this to multiple patients and saw an apparent improvement the attributed to the new drug, would switch the patients on the old drug to the new and not…
Switching extra patients to a new drug would make the trial more conservative though... so perhaps don’t worry so much. In general it’s worth remembering that RCTs are estimating the effect of an intention to treat ( the randomisation) not the treatment itself.
If the doc correctly divines that the drug is improving things, yes, but there is noise in the signal so it may be just noise causing the few apparent improvements the doc sees. If so, doc's action may be smothering a less-then-obvious signal.
There's too much at stake for that to be acceptable.
> ...are estimating the effect of an intention to treat ( the randomisation) not the treatment itself.
I don't understand - the protocol applies the drug (aka the treatment) and results are measured. I don't understand 'intention to treat'. What is 'intention' here, so tech term I am not familiar with?
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Just as a point of comparison: Toxic epidermal necrolysis, a severe form of Stevens-Johnson Syndrome, has about a 30% mortality rate. I understand it to be a first world problem typically caused by taking certain strong medications. It's a severe and often deadly allergic reaction. (I'm not going to provide links because both Wikipedia entries have disturbing photos. I've verified that I'm spelling both correctly so…
Unpacking the name totally is even more brutal! "necro" -- "death" "lysis" -- "busting open" "epidermal" -- "skin" "syndrome" -- "no known cause" However, it's a little unclear why TEN is a point of comparison to Ebola, as one is a transmissible disease and one is something that happens to unlucky people typically in response to common small-molecule drugs. I guess TEN sounds like a probable side effect of antiviral…
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The comparison is to show that even in technologically advanced societies, there are diseases with 30% survival rates.
A doctor once told me that so much of our higher survival rate is based on a few key drugs and supportive care to keep us alive while the body heals itself. We seem to possess remarkably few cures for the majority of diseases out there, we are mostly able to treat symptoms to buy time for our bodies to self-repair.
This is awesome that we've seen another horrendous disease go from incurable to curable in my lifetime. While ebola hasn't touched my community like AIDS/HIV has, reading this cracked my RBF and I smiled.
A 6% to 30% fatality rate depending on how early the treatment is not what I would call a cure. However, at best 6% fatality rate is still huge progress.