alt Hacker News> "This feels off. In medicine, any evidence can also be blinded by confounding factors that are far easier to miss without adding specific controls. Really, in any field this will be the case."
If you have enough data, you can smooth out individual fluctuations due to things like drug interactions, non-compliance, etc. (And indeed you might discover drug interactions!) Observational trials ultimately mirror how drugs are used in the real world.
> "Adding controls and randomizing them, though, has proven to be highly effective at helping progress."
I would argue just the opposite. Demands for increasingly byzantine trials have ballooned the costs associated with drug development, and have slowed things to a crawl. There's a reason the field's golden age was in the 1940s and 1950s, and it's not just "low hanging fruit." Today nobody in their right mind wants to work in drug development when they could work in tech or even finance.
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Right, but you are just relying on a different form of random, there. The whole point of making controls and then building experiments on changing them, is to get more power from fewer observations. No?
Again, it is off to think that one is automatically superior to the other. Certainly to the exclusion of the other. And that is what feels off with the framing of the parent post. I am perfectly fine saying you should use both observational and controlled trials. But I think it is also wrong to think you don't have to build experiments to test interventions.
This is why you put metrics in your service code. So that you can observe them behave and look for things to change. This is also why you do test cases on your code, so that you can specifically target your change.
Now, I fully back the idea that just A/B testing something doesn't automatically mean you learn something true. But neither does observing a strong outcome on uncontrolled data.
How do you get enough data? If, for example, you need a lot of people in the sample, that might not be so easy. In the abstract, should it not come done to what is the best experimental design for each case?
> Demands for increasingly byzantine trials have ballooned the costs associated with drug development,
Even if that is true, is it an intrinsic problem with trials or just bad regulation? If it is the latter then you need to change the regulations? Is the problem global - is every regulator everywhere demanding byzantine trails?
> There's a reason the field's golden age was in the 1940s and 1950s
Yes, that was because of things like
https://en.wikipedia.org/wiki/Tuskegee_syphilis_experiment
https://en.wikipedia.org/wiki/Stateville_Penitentiary_Malari...
https://en.wikipedia.org/wiki/Operation_Sea-Spray
https://en.wikipedia.org/wiki/Nazi_human_experimentation
I understand that certain people are salivating at the thought of a return to those times; I'm not one of them.
> Demands for increasingly byzantine trials
This is silly.
FDA has essentially one requirement: prove that your drug is safe and effective.
The reason trial designs get more and more byzantine is because the drugs themselves work less-and-less well. They're far more nuanced and precise. The experiments have to be extremely well-controlled, and then this has to balance against cost/timeline of the trial, and that's why sponsors choose to use byzantine trial designs.
You are simultaneously arguing for a more complex and nuanced testing approach that demands much higher quantities of data as a result, and also against RCTs, which perhaps rightly you've identified as having suffered from the same kind of cost disease as all other health care in the USA. I can't help but feel like you've identified the wrong root cause here.