| I think the author makes a fair point, but the analogies and examples in this piece offended my aesthetic sensibilities to the point that I find myself wanting to disagree with him purely out of spite. > Some of these exclusion criteria are pretty straightforward. […] you’d want to avoid any participants with conditions that make them predisposed to gain or lose weight, as that would make an apples-to-apples comparison across groups more difficult. Absolutely! > However, there are other exclusion criteria that I don’t understand at all. Why no oral contraceptive use? Why no smoking? Why no diabetes[…]? Smoking makes you lose weight. Diabetes is literally characterized by abnormal metabolism. > There might well be good reasons for these exclusions that I’m not aware of. […] However, those reasons are not outlined here. Agreed. There should at least be a sentence in a supplement somewhere. One things about trials and extrapolation is that trails are tightly controlled and will never reflect real world conditions in terms of the patient population, the intervention, or the context in which the intervention is performed. This is a double edged sword. It’s good because you can get “cleaner” measurements and data by getting rid of cofounders and such. But it’s bad because your trial scenario may be unrealistic and your results may not translate into the clinic. If anything good has come out of Surveillance capitalism and those shitty EPIC / Cerner EHR systems that everybody (except for hospital quality people) hates, it is a drastic improvement in capabilities for post market data collection (i.e. real world data). RWD is increasingly a thing at FDA. I think the big issue there which needs public discussion is the extent to which post market data collection should either replace or augment clinical trials. If you replace clinical trials with RWD then you are essentially running mass experiments on sick people with untested drugs, which is monstrous. If you purely augment, then it is basically like a tax and you are driving up the cost and complexity of drug development. |