4 ms·

My favourite chart for this situation is Everything causes and cures cancer[1]. [1]: https://cdn.vox-cdn.com/uploads/chorus_asset/file/3523382/Medical_studies-

My favourite chart for this situation is Everything causes and cures cancer[1]. [1]: https://cdn.vox-cdn.com/uploads/chorus_asset/file/3523382/Medical_studies-05.0.png https://cdn.vox-cdn.com/uploads/chorus_asset/file/3523382/Me...

rubslopes 3y ago
What's going on with the x-axis?
- iisan7 3y ago
  relative risk in terms of a ratio: <1.0 means less, >1 means increased risk compared to the control group. E.g., one study showed that beef reduced risk of cancer by 50%, another showed that it increased risk by 500%
  - zakki 3y ago
    In the chart is beef causing cancer or preventing it?
    - mdavidn 3y ago
      Either, depending on which study you accept.
      - ruszki 3y ago
        The question is the problem. The answer is not a yes/no, but a point on a scale of multiple dimensions. Most of these studies don’t answer the question asked here, but a completely different question. And also most of these studies don’t answer the same question. Heck, it’s even a good guess that none of these studies answers the question asked here, because it’s rather difficult to make a double blind test about such questions.
    - WheatMillington 3y ago
      Yes.
3cats-in-a-coat 3y ago
This chart is the epitome of modern "science". We need to tweak our process, because this is clearly not working.
- Zetice 3y ago
  What makes you think there are tweaks that would improve "this"? You might be startled to learn "this" (the scientific method) is the best possible way of discovery that humans know of.
  - 3cats-in-a-coat 3y ago
    You may be even more startled to learn the scientific method is clear as an abstract concept, you know, those circle diagrams with "observation -> research -> hypothesis -> experiment -> analysis -> conclusions", but the details are always in flux and vary between countries, universities, publications and in time. And the details are absolutely crucial for the end result. You come in here acting like a religious defender of the scientific method against the evil of rejecting science, but I'm not that guy. I'm not rejecting science, I'm just pointing out the obvious: modern science is producing literally noise, as seen in this chart, because of misaligned incentives and a broken peer review process, among others. Do you even know what the "replication crisis" is? Hints of it in this very chart. And if you do, it's completely disingenuous to come attacking me for even mentioning we have a problem. And if you don't, you're not informed well enough to speak about the scientific method. The "scientific method" should be applied to the "scientific method". Meaning when you see evidence that falsifies it, seek the causes and correct them, don't dig in your heels and go religious.
    - Zetice 3y ago
      Everyone knows about the replication crisis, and everyone knows the flaws in the incentive structures around publishing research, but none of that is what you referenced. What we need are people with level heads making calm decisions, not bombastic polemics demanding the system get blown up.
gymbeaux 3y ago
So it’s obvious how a study would support the notion that X causes cancer, but how would a study support that X prevents cancer? Too many confounding variables methinks.
- SamBam 3y ago
  I'm not sure I see how one is easier than the other. In studies where they find that wine, say, causes cancer, they aren't looking at some molecular chain of events, they're simply doing a large (hopefully) study and looking for correlations, while attempting (hopefully) to factor out confounding variables and incorrect direction of causation. In some of those studies, the wine drinkers get more cancer. Red dot to the right. In some they get less. Red dot to the left.
  - gymbeaux 3y ago
    I would think the effects of confounding variables are reduced the larger the sample size, so you can say "everyone in group A does not drink wine, and everyone in group B does drink wine". Some from both groups will get cancer because of some confounding variable, but they would cancel each other out- a non-related cancer case in Group A would be cancelled out by a non-related cancer case in Group B. Conversely, if you have a similar study aiming to prove that wine prevents cancer, how do you prove that wine is the reason a person did not get cancer? It seems much more difficult, because now you are saying X did NOT happen because of Y rather than Y caused X. I'm struggling to articulate this. Maybe you're right.
    - SamBam 3y ago
      Well, two things: First, a confounding variable doesn't work like that. It's a hidden variable that's linking that independent and dependent variables that you didn't account for. So, for instance, if you look at the correlation between ice cream and sunburns, you might see a strong correlation, and you might naively think that one causes the other if you don't account for the confounding variable of hot summer days. In the case of population-wide studies on food, there is always the danger of confounding variables: if you are just comparing the wine drinkers vs non, who are these non-wine drinkers? What makes them non-wine drinkers? As a whole, do they tend to be more heath-conscious? Is that why they're less likely to get cancer? Etc etc. Second, my point is that in both studies that show foods causing cancer vs those protecting against cancer, it's almost always populations studies. So in an ideal experiment, they have two identical populations, one of whom just happens to eat more chocolate. If that group gets more cancer they say they the chocolate is causing cancer. Similarly, if they get less cancer, they say it's protecting them from cancer. You don't have to prove that individual X would have gotten cancer if it weren't for the chocolate. All you have to show is that the standard, base-line amount of cancer you'd see in any population is reduced in this group.
acidburnNSA 3y ago
Lovely. I wish this had low-dose ionizing radiation on it as well to cover the radiation hormesis hypothesis. https://en.wikipedia.org/wiki/Radiation_hormesis https://en.wikipedia.org/wiki/Radiation_hormesis
kalleboo 3y ago
There used to be a site with a handy database too https://web.archive.org/web/20121115101540/http://kill-or-cure.herokuapp.com/ https://web.archive.org/web/20121115101540/http://kill-or-cu...

rubslopes 3y ago

What's going on with the x-axis?

iisan7 3y ago
relative risk in terms of a ratio: <1.0 means less, >1 means increased risk compared to the control group. E.g., one study showed that beef reduced risk of cancer by 50%, another showed that it increased risk by 500%
- zakki 3y ago
  In the chart is beef causing cancer or preventing it?
  - mdavidn 3y ago
    Either, depending on which study you accept.
    - ruszki 3y ago
      The question is the problem. The answer is not a yes/no, but a point on a scale of multiple dimensions. Most of these studies don’t answer the question asked here, but a completely different question. And also most of these studies don’t answer the same question. Heck, it’s even a good guess that none of these studies answers the question asked here, because it’s rather difficult to make a double blind test about such questions.
  - WheatMillington 3y ago
    Yes.

3cats-in-a-coat 3y ago

This chart is the epitome of modern "science". We need to tweak our process, because this is clearly not working.

Zetice 3y ago
What makes you think there are tweaks that would improve "this"? You might be startled to learn "this" (the scientific method) is the best possible way of discovery that humans know of.
- 3cats-in-a-coat 3y ago
  You may be even more startled to learn the scientific method is clear as an abstract concept, you know, those circle diagrams with "observation -> research -> hypothesis -> experiment -> analysis -> conclusions", but the details are always in flux and vary between countries, universities, publications and in time. And the details are absolutely crucial for the end result. You come in here acting like a religious defender of the scientific method against the evil of rejecting science, but I'm not that guy. I'm not rejecting science, I'm just pointing out the obvious: modern science is producing literally noise, as seen in this chart, because of misaligned incentives and a broken peer review process, among others. Do you even know what the "replication crisis" is? Hints of it in this very chart. And if you do, it's completely disingenuous to come attacking me for even mentioning we have a problem. And if you don't, you're not informed well enough to speak about the scientific method. The "scientific method" should be applied to the "scientific method". Meaning when you see evidence that falsifies it, seek the causes and correct them, don't dig in your heels and go religious.
  - Zetice 3y ago
    Everyone knows about the replication crisis, and everyone knows the flaws in the incentive structures around publishing research, but none of that is what you referenced. What we need are people with level heads making calm decisions, not bombastic polemics demanding the system get blown up.

gymbeaux 3y ago

So it’s obvious how a study would support the notion that X causes cancer, but how would a study support that X prevents cancer? Too many confounding variables methinks.

SamBam 3y ago
I'm not sure I see how one is easier than the other. In studies where they find that wine, say, causes cancer, they aren't looking at some molecular chain of events, they're simply doing a large (hopefully) study and looking for correlations, while attempting (hopefully) to factor out confounding variables and incorrect direction of causation. In some of those studies, the wine drinkers get more cancer. Red dot to the right. In some they get less. Red dot to the left.
- gymbeaux 3y ago
  I would think the effects of confounding variables are reduced the larger the sample size, so you can say "everyone in group A does not drink wine, and everyone in group B does drink wine". Some from both groups will get cancer because of some confounding variable, but they would cancel each other out- a non-related cancer case in Group A would be cancelled out by a non-related cancer case in Group B. Conversely, if you have a similar study aiming to prove that wine prevents cancer, how do you prove that wine is the reason a person did not get cancer? It seems much more difficult, because now you are saying X did NOT happen because of Y rather than Y caused X. I'm struggling to articulate this. Maybe you're right.
  - SamBam 3y ago
    Well, two things: First, a confounding variable doesn't work like that. It's a hidden variable that's linking that independent and dependent variables that you didn't account for. So, for instance, if you look at the correlation between ice cream and sunburns, you might see a strong correlation, and you might naively think that one causes the other if you don't account for the confounding variable of hot summer days. In the case of population-wide studies on food, there is always the danger of confounding variables: if you are just comparing the wine drinkers vs non, who are these non-wine drinkers? What makes them non-wine drinkers? As a whole, do they tend to be more heath-conscious? Is that why they're less likely to get cancer? Etc etc. Second, my point is that in both studies that show foods causing cancer vs those protecting against cancer, it's almost always populations studies. So in an ideal experiment, they have two identical populations, one of whom just happens to eat more chocolate. If that group gets more cancer they say they the chocolate is causing cancer. Similarly, if they get less cancer, they say it's protecting them from cancer. You don't have to prove that individual X would have gotten cancer if it weren't for the chocolate. All you have to show is that the standard, base-line amount of cancer you'd see in any population is reduced in this group.

acidburnNSA 3y ago

Lovely. I wish this had low-dose ionizing radiation on it as well to cover the radiation hormesis hypothesis. https://en.wikipedia.org/wiki/Radiation_hormesis https://en.wikipedia.org/wiki/Radiation_hormesis

kalleboo 3y ago

There used to be a site with a handy database too https://web.archive.org/web/20121115101540/http://kill-or-cure.herokuapp.com/ https://web.archive.org/web/20121115101540/http://kill-or-cu...