>To be clear, all of these conclusions can be true, and in some cases we know they are true, at least in part. For some cancers, treatments have improved, and for some, additional screening would save lives. But to support these conclusions, we need other methods and metrics – notably randomized controlled trials that compare mortality.
the economist put out a piece a few months ago providing just that. Specifically it compares overall cancer mortality rates (and more interestingly, mortality rates adjusted for age) and shows that cancer deaths have been dropping.
https://www.economist.com/briefing/2025/07/17/the-world-is-m...
> notably randomized controlled trials that compare mortality.
Putting people into a control group so you can observe the effects of not treating them might not make it past the ethics committee.
You don't not treat the control group. You give the control group the current standard treatment, and you give the experimental group the new trial treatment.
In some cases, the "current standard treatment" is no treatment.
In some studies, although not cancer, I've seen treatment offered to both groups, someone in the control at any time can opt into the same treatment the other group receives if they want to. Some people will make the informed decision to not take the treatment, and they are your control.
No longer randomized though, so it brings in confounding factors. Which one then has to try to control for.
Doesn't really change your point, but I should clarify that what I said was wrong, it was anyone in the study could choose not to take the blinded pill that could be placebo or active, they were removed from the study, and were provided with the active experimental drug + compensation as to not punish them for giving or not giving their consent after being sufficiently informed of the risks of either choice.
Really? That sounds dumb and unethical. Is the standard treatment for a cut a bandage or leaving you to bleed?
If there is no treatment available, then yes, the standard treatment may be nothing, or possibly just trying to make the patient more comfortable until they die.
Now everyones agree with you and there are no more cases like https://en.wikipedia.org/wiki/Tuskegee_Syphilis_Study (hopefuly).
In the current trials a part of the subjects get the new experimental drug and the control group get the current state of the art treatment.
Yes, but when you compare treatments A vs B for trial 1, and then B vs C for trial 2, and then C, vs D for trail 3, you might not get the same results as comparing A vs D, especially when there may have been other changes in between the three trials (different ages, lifestyles etc).
This is a real problem when the Minister wants to know if it’s worth spending money on treatments, because all you have is a disjointed set of trials, none of which are necessarily representative of the population at large, or the population wide incidence of the disease (assuming there is even data on that (notifiable illnesses are the exception).
> Yes, but when you compare treatments A vs B for trial 1, and then B vs C for trial 2, and then C, vs D for trail 3, you might not get the same results as comparing A vs D, especially when there may have been other changes in between the three trials (different ages, lifestyles etc).
That's not what happens.
Is this just a hypothetical?
Everything will be compared to one standard of care, or perhaps two which will have been compared to each other. If a new treatment is much better, then it will become standard of care.
Trials cost a lot of money, so they are conducted rationally.
That is what happens if C is developed after B becomes the standard treatment, D after C etc.
Suppose D is only slightly less effective than C, but more effective than A, and B, but 100x cheaper, and/or has less bad side effects. If you only compare with C, all you know is it's not as good as C.
> That is what happens if C is developed after B becomes the standard treatment, D after C etc.
Can you point to particular drugs or are you also making up examples?
I admittedly do not know of every trial that happens everywhere but this is exactly the sort of thing that a layman expects would occur but which does not happen.
Stem cell treatments come to mind. Outrageously expensive (or outright unavailable locally), in many areas and for select purposes.
> Stem cell treatments come to mind. Outrageously expensive (or outright unavailable locally), in many areas and for select purposes.
I don't see how stem cells relate to the idea of trials for successive standard-of-care treatments. Can you explain your thinking?
Randomized controlled trials are a bummer of a 'gold standard'. Extremely expensive, extremely slow and in many cases absolutely impossible. I'm not an AI true believer, but I do hope it offers an alternative or at least enables some desperately needed efficiencies.
"Parachute use to prevent death and major trauma when jumping from aircraft: randomized controlled trial"
https://www.bmj.com/content/363/bmj.k5094
But seriously: this is a recognized problem in medicine and there's already a widely used solution. Whenever you're doing trials of an intervention for a condition which already has an accepted treatment, you run a trial to compare your new intervention to that, and see if your test group has better outcomes. After all, the question shouldn't be whether your treatment is effective; it's whether it's better than existing treatments.
Trials against a placebo have a purpose, but they aren't the only way to run a trial.
It also helps to actually go back and look at in terms of "rejecting the null hypothesis".
If you're talking about a treatment for The Common Cold, the null hypothesis is "the subject got better after awhile because people get better after awhile", and you can't disprove that's what's happening without a very rigorous study with a well designed control.
If you're talking about "here's some robot eyes that cure blindness", you don't really need a control group to test if it works. The null hypothesis is they're blind; you just need to demonstrate they can see to disprove the null hypothesis and prove efficacy.
Ok, suppose the current standard treatment is A. You have a new treatment B that is 100x cheaper than B, and doesn't trigger allergic reactions that some people have to A. You test against A, and the B group has slightly worse outcomes overall than A. Does that mean that B is useless? What if it is almost as effective, but it's lower cost means more people would be able to use it?
"better" is not a total order, one treatment may be better in some ways and worse in other ways. Especially if you include things like cost and availability.
Even if that's the case, the metric you're interested in isn't "is Treatment B better than doing nothing"; it's "how effective is Treatment B relative to Treatment A". And the most effective way to determine that will be to trial them against each other, not against a placebo.
Ideally, for getting good information, you compare to both. Because you also want to know if your treatment is more effective than a placebo.
You just discovered the entire scientific field of cost-effectiveness.
Wouldn’t those factors be detected and reported on in the trial?
And years later we may have some useful data, if a study can be conducted ethically in the first place. Meanwhile, the environment around us continues to change at a pace the likes of which humans have never experienced. Whatever this era of LLMs does (or does not) do to improve the situation, I am firmly confident that years-to-decades-long human testing is not the endgame of medical science, but rather a long and inconvenient pitstop. There's a lot of those in the history of medicine.
RCTs aren't always necessary to change the medical standard of care. Sometimes lower quality studies plus a theoretical understanding of the physiologic is good enough.
There has never been an RCT to show that smoking causes lung cancer but doctors now all recommend that their patients not smoke.