3 ms·

but people who are depressed still improve when on SSRIs Does that mean 'over 50%' of them improve, or is it, as is more common with pharmaceuticals, closer to

but people who are depressed still improve when on SSRIs Does that mean 'over 50%' of them improve, or is it, as is more common with pharmaceuticals, closer to a rounding error? There was a deluge of media a couple decades ago about Prozac and its dramatic effects. A few years later, I read some report that the studies testing its efficacy had ambiguous conclusions.

Aurornis 2y ago
> Does that mean 'over 50%' of them improve, or is it, as is more common with pharmaceuticals, closer to a rounding error? This question is more complicated than it appears. One of the biggest challenges with depression studies is that the placebo group always improves dramatically, too. Using your terms, "over 50%" of the placebo group would likely show improvements in their depression inventories. This makes it very complicated to interpret the studies, because now you have to look for how much more the active treatment group improves relative to the placebo group. This is a huge detail that gets abused a lot by anti-pharma people, who write headlines about how SSRIs are "barely better than placebo" and then ignore the actual statistics. Another common tactic is to try to reframe the thresholds in different terms like "effect size" and then pool studies together to try to show that the "effect size" is below some arbitrary threshold. Another challenge is that placebo response has been getting stronger over the years and nobody really knows why. Some antidepressant studies have even been halted because, ironically, the placebo group improved so much that there numerically wasn't much room left for the active group to be statistically better given the sample size. This is less of a problem with very large scale studies where smaller margins can be shown to be more statistically significant, but those are expensive and rare. There isn't really a question about whether or not they are effective for many patients in the world of empirical treatment. However, if you go digging through the internet you can find plenty of commentary trying to convince you they don't work. Sadly, I've had some close friends and family members delay SSRI treatment for years because they read too many of these studies, but when they finally gave in and did a trial it turned their life around. The drugs aren't perfect and don't work for every situation, but they do work for a lot of people.
- nostrebored 2y ago
  Can you explain why low percentage improvement over placebo is not important?
  - Aurornis 2y ago
    Imagine you have a depression inventory (test) with 21 questions, rated from 0-3. The highest score is 3 * 21 = 63 indicating the most severe depression. The lowest score is 0, indicating no depressive symptoms at all. In practice, the average person will fall more in the range of maybe 5-15 due to vague symptoms like "I don't sleep as well as I used to" triggering some of the points. The average depressed person who seeks treatment might fall in the range of 25-35. Now imagine the placebo group goes in with an average score of 35 and improves to a score of 25 by the end of the test. The SSRI group improves to an average of 20 by the end of the test. Is this significant? Well, it depends on how many patients you have in the sample size. That's the problem. There's only so much room in these scales for improvement, so when both groups improve a lot you need to have a larger sample size to get statistical significance. Getting a lot of patients in a study (hundreds) is very expensive, so it's only a small number of studies that can pull this off.
    - nostrebored 2y ago
      Right, but study power is really the responsibility of a pharma company. It's not like this is some new and novel medication, it's been used for decades and has been questionable for _literally the entirety of the time_.
    - ants_everywhere 2y ago
      The problem with being barely measurably better than a placebo is that each study is a coin flip whether it supports your drug or not. And you can just file drawer any study that didn't go your way (as happens with the majority of null results). So the published results are over-sampling studies where the statistics happened to work and under-sampling studies where they didn't.
- deleted 2y ago
  [deleted]

Aurornis 2y ago

> Does that mean 'over 50%' of them improve, or is it, as is more common with pharmaceuticals, closer to a rounding error? This question is more complicated than it appears. One of the biggest challenges with depression studies is that the placebo group always improves dramatically, too. Using your terms, "over 50%" of the placebo group would likely show improvements in their depression inventories. This makes it very complicated to interpret the studies, because now you have to look for how much more the active treatment group improves relative to the placebo group. This is a huge detail that gets abused a lot by anti-pharma people, who write headlines about how SSRIs are "barely better than placebo" and then ignore the actual statistics. Another common tactic is to try to reframe the thresholds in different terms like "effect size" and then pool studies together to try to show that the "effect size" is below some arbitrary threshold. Another challenge is that placebo response has been getting stronger over the years and nobody really knows why. Some antidepressant studies have even been halted because, ironically, the placebo group improved so much that there numerically wasn't much room left for the active group to be statistically better given the sample size. This is less of a problem with very large scale studies where smaller margins can be shown to be more statistically significant, but those are expensive and rare. There isn't really a question about whether or not they are effective for many patients in the world of empirical treatment. However, if you go digging through the internet you can find plenty of commentary trying to convince you they don't work. Sadly, I've had some close friends and family members delay SSRI treatment for years because they read too many of these studies, but when they finally gave in and did a trial it turned their life around. The drugs aren't perfect and don't work for every situation, but they do work for a lot of people.

nostrebored 2y ago
Can you explain why low percentage improvement over placebo is not important?
- Aurornis 2y ago
  Imagine you have a depression inventory (test) with 21 questions, rated from 0-3. The highest score is 3 * 21 = 63 indicating the most severe depression. The lowest score is 0, indicating no depressive symptoms at all. In practice, the average person will fall more in the range of maybe 5-15 due to vague symptoms like "I don't sleep as well as I used to" triggering some of the points. The average depressed person who seeks treatment might fall in the range of 25-35. Now imagine the placebo group goes in with an average score of 35 and improves to a score of 25 by the end of the test. The SSRI group improves to an average of 20 by the end of the test. Is this significant? Well, it depends on how many patients you have in the sample size. That's the problem. There's only so much room in these scales for improvement, so when both groups improve a lot you need to have a larger sample size to get statistical significance. Getting a lot of patients in a study (hundreds) is very expensive, so it's only a small number of studies that can pull this off.
  - nostrebored 2y ago
    Right, but study power is really the responsibility of a pharma company. It's not like this is some new and novel medication, it's been used for decades and has been questionable for _literally the entirety of the time_.
  - ants_everywhere 2y ago
    The problem with being barely measurably better than a placebo is that each study is a coin flip whether it supports your drug or not. And you can just file drawer any study that didn't go your way (as happens with the majority of null results). So the published results are over-sampling studies where the statistics happened to work and under-sampling studies where they didn't.
deleted 2y ago
[deleted]