The strengths and limitations of randomized controlled trials

[@KeyserTheRedBeard]

Impressive video, Peter Attia MD. Looking forward to seeing your next upload from you. I hit the thumbs up button on your content. Keep up the fantastic work! Your insights into the limitations of randomized control trials are crucial. How do you envision integrating emerging biomarkers into clinical practice to enhance our understanding of age-related diseases?

[@jaymckoskey25]

What about N=1 experiments? They can offer useful insights with high control and phenotype specificity. I would think that a metanalysis of a thousand such studies would be powerful.

[@nichtsistkostenlos6565]

They're effectively useless. The problem is that there is no counter factual and there are literally thousands of variables that are likely being unaccounted for. You cannot derive correlation or causation from the study, so what is the goal?

[@jaymckoskey25]

@@nichtsistkostenlos6565 Proof of concept in the case where you predict an outcome directly contradicting a widely accepted paradigm. If something that absolutely shouldn't happen does happen then it's interesting and instructive, even if it's just one of one, at least for the truly curious.

[@HeatherQ333]

Well, let's go already. I heard a lot of limitations, but no strengths. Such is the mind of a brilliant and conditioned academic... ? I'm thinking about getting in to research because I feel like a lot of time, resources, (etcetera) is being wasted, and opportunities and out of the box thinking underutilized. Not you specifically, Peter. In general. Thanks. 🙂❤

[@davidferry8455]

Blinding is desirable but not necessary to draw clear inferences. Take the time when a belief that high dose chemo in adjuvant breast cancer was beneficial took hold. Many argued it was unethical etc not to randomize against low dose chemo the standard of care. Three RCTs, not blinded showed huge harm done by high dose chemo, a huge shock to the majority of believers. Thus although RCTs are often not perfect in every way they allow robust inferences and do so much good. Biomarkers are always going to be surrogates and the false belief they can be discovered without RCTs will be enormously harmful to medical progress.

[@yunggolem4687]

How did they come up with the idea it's "not ethical" to study people who are already going to do the thing that's bad for them? For instance, smokers. What are the mental gymnastics that make it unethical to study people who are already smokers? Sure if you encouraged them to be smokers or continue smoking, which would provide less noisy data, but you'd need to contort your ethical obligations outside of feasibility to make a valid claim that you have a duty to intervene & stop someone from harming themselves from smoking & therefore it is unethical to even OBSERVE a smoker smoke & measure the effects. Accepting that idea as a principle & acting consistently with it would turn you into the nanny of everyone in the world & one of the worst people on earth. If anything, by measuring the harm a vice does & sharing that information, you ARE intervening in a way that could help them at a deep psychological level, rather than the brute force chemical methods often used which fail very often. The argument that this kind of study using existing vice indulgers is "unethical" is so paper thin I have trouble coming up with one that doesn't sound ridiculous. Perhaps it is more to do with legal liability than actual ethics... or maybe some other factor.

[@xiaoyang4571]

No one is saying it is unethical to study the effects of smoking in smokers. What he is saying is that it would be unethical to randomize a non-smoker to a smoking intervention. Ie, let’s take 1000 non-smoking 70 year olds and randomly assign half of them to smoke for 3 years to see if it increases risk for dementia.

[@ember9747]

He said it's unethical to make people start smoking. There's no problem in studying smokers when the researchers haven't caused them to smoke for the sake of an RCT, you study them with observational studies instead.

[@nichtsistkostenlos6565]

The "Randomized" part of Randomized Controlled Trial is the issue with these types of interventions

[@Dr_Boult]

You did not really cover the strengths which mighe be useful other to understand. For limitations agree with 3 out of 5. Binary is definitely not a requirement of RCT, and even a pill is not really binary. Many good RCTs have used dosage as a part of the design and dose-dependent response curves can themselves be very useful in helping to understand causality. Blindedness is not required, though I agree its helpful. If the effect size is so small that a placebo effect, and hence blinding, is of comparable size then one has a pretty minimal intervention. But I think you also missed what I consider a (or the) major limitation of RCT for causality testing -- the huge variation in human responses makes it only a partial indicator -- if an intervention has an outcome for a fraction of the population but not for all, then the RCT cannot separate if the intervention was the true cause, or just a contributing factor where something else is causal but the impact/effect size is impacted by the intervention. Something that is necessary, but not sufficient is not causal, even if it may be in the causal chain of events. Protein is necessary for the development of arterial plaque, that does not make it causal.

[@nichtsistkostenlos6565]

The main strength is that if you get a statistically significant positive result in a well-designed, appropriately powered RCT, you can be pretty sure that there's something causally inherent to the intervention, at least in the population that you're testing. You get an answer that's likely not just a fluke, especially if it can be repeated, which advances our knowledge of a topic forward. There are only a few modes of study that can get anywhere close to showing a causal relationship between an intervention and an outcome and RCTs are one of them.

[@luisfer14240]

❤

[@winingtheday]

Yes more baby

[@neilcollins5930]

Sorry you lost me