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  "path": "/t/generalizability-vs-transportability-in-trials/28551?page=3#post_44",
  "publishedAt": "2026-02-23T20:27:00.000Z",
  "site": "https://discourse.datamethods.org",
  "textContent": "Thanks for the links to the Matthews articles. We can learn so much from studying the history of science. It’s particularly valuable to identify the historical roots of common scientific/statistical misconceptions.\n\nThere’s no question that Sackett understood the value of randomization. But, as Matthews pointed out, even prominent proponents of randomization (like Hill) didn’t necessarily appreciate _all_ the reasons why it’s so valuable (specifically, the fact that it allows us to estimate the _uncertainty_ that accompanies a study result).\n\nI don’t see that any of the patient cases in your paper undermine Sackett’s main point. He seems to be saying that _qualitative_ interactions tend to be such rare clinical phenomena that physicians, in general, shouldn’t let a nebulous _fear_ of this type of interaction drive treatment decisions in the postmarket setting. Of course, physicians should always ensure that their patient’s disease shares the biological mechanism that will drive the therapeutic effect (Sackett makes this point nicely). Your cases mainly highlight the importance of considering the impact of _quantitative_ interaction (risk magnification) when advising specific patients about whether to take a therapy.\n\nA clinical scenario that _would_ satisfy Dr.Sackett’s challenge is the patient with a rare/idiosyncratic physiologic feature (metabolic/immunologic/genetic) that renders him, and perhaps only a very small number of other patients in the world, susceptible to a particular adverse reaction (e.g., a severe hypersensitivity reaction) when exposed to a particular therapy. This type of patient-by-treatment _qualitative_ interaction is often (?usually) so rare as to not be identifiable during typically-sized clinical trials. In the postmarket setting, this patients might appear “similar” to clinical trial subjects with regard to the biologic mechanism driving his disease. But, if offered the therapy, he will react _adversely_ to it, even though the trial showed a _beneficial_ effect, on average, at the group level. These types of qualitative interactions (idiosyncratic vulnerability of certain patients to ADRs) tend to be so rare, and their mechanisms so rarely understood, that they are almost never predictable in clinical settings. Therefore, clinical decision-making at the level of an individual patient will almost never be affected by knowledge that an adverse qualitative interaction like this can occur.",
  "title": "Generalizability vs. Transportability in Trials"
}