Not sure. Is it the colon cancer one? I read the breast cancer one linked on his post. I dont believe/expect that vit D is going to make an impact for every illness or type of cancer. I expect the relationship will be complex, and will depend heavily on dietary factors and genetics (for example there is strong evidence for various climdate adaptations—far northern peoples need much less vit D, etc.) I picked the breast cancer paper because I have a vague memory of hearing a very convincing talk from a breast cancer doctor about the evidence for the bio mechanisms between the low vit D and breast cancer.
Methods Postmenopausal women (N = 36 282) who were enrolled in a Women’s Health Initiative clinical trial were randomly assigned to 1000 mg of elemental calcium with 400 IU of vitamin D3 daily or placebo for a mean of 7.0 years
Results Invasive breast cancer incidence was similar in the two groups (528 supplement vs 546 placebo; hazard ratio = 0.96; 95% confidence interval = 0.85 to 1.09). In the nested case–control study, no effect of supplement group assignment on breast cancer risk was seen. Baseline 25-hydroxyvitamin D levels were modestly correlated with total vitamin D intake (diet and supplements) (r = 0.19, P < .001) and were higher among women with lower BMI and higher recreational physical activity (both P < .001). Baseline 25-hydroxyvitamin D levels were not associated with breast cancer risk in analyses that were adjusted for BMI and physical activity (Ptrend = .20).
So they used only 400 IU, and even then the breast cancer incidence was 528 vs 546 for 400 IU vs 0 IU. There was no effect only when they “adjusted for BMI”—of course—as some other studies have suggested, vit D has a potential weight loss effect. The 400 IU didn’t make a huge diff on OHD levels.
This study is supportive of vit D potentially having a significant effect on breast cancer, and it is reasonable evidence against the null hypothesis (no effect). Instead here is their conclusion:
Conclusions Calcium and vitamin D supplementation did not reduce invasive breast cancer incidence in postmenopausal women. In addition, 25-hydroxyvitamin D levels were not associated with subsequent breast cancer risk. These findings do not support a relationship between total vitamin D intake and 25-hydroxyvitamin D levels with breast cancer risk.
That is not justifiable, nor is it even an accurate summary of their own data.
Yes I meant the colon cancer paper (I should have stated at the beginning rather than the end), but the breast cancer paper was from the same experiment, and as such also addresses you initial concerns about effects on different subgroups and measuring serum levels.
So they used only 400 IU, and even then the breast cancer incidence was 528 vs 546 for 400 IU vs 0 IU.
The difference in incidence was not statistically significant. Random chance could easily result in this level of variation. Regarding the dosage, yes you can only make conclusions about what you measure. This trial was started in the 90′s, and since then there have been some recommendations for higher doses. However, the authors are not unaware of this and point out that many women in the trial were supplementing with additional Vitamin D, and after analyzing that, there was still no detectable effect:
We cannot assess whether a higher dosage would have changed the outcome of the current study. However, our findings provide some evidence against that hypothesis. Because approximately half of the women were taking an additional 400 IU of nonprotocol vitamin D supplement daily, actual vitamin D supplement intake was greater than 800 IU daily for a substantial number of participants in the supplement group. Nonetheless, no effects on risk of breast cancer overall or in sensitivity analyses that were adjusted for study adherence were observed.
Perhaps a still higher dose is need to see any effect. But this would require positing a very non-linear model. Is it possible? Sure, but this complaint can always be made.
Regarding BMI, the authors are also aware of this argument—see the quote below. I’d like to point out that the BMI numbers were baseline which is not evidence that vitamin D supplementation causes weight loss. It is consistent with the hypothesis that healthier lifestyles result in both higher vitamin D levels (due to sun exposure with exercise) and lower BMI.
Levels of 25-hydroxyvitamin D at baseline were statistically significantly higher among lean women and/or those with more recreational activity than overweight or obese or less active women. Based on the associations of these breast cancer risk factors with 25-hydroxyvitamin D, 25-hydroxyvitamin D could be a potential mediator of lifestyle influence on breast cancer. Alternatively, lifestyle choices could have led to more sunlight exposure, with higher 25-hydroxyvitamin D levels and lower breast cancer risk as independent processes. The finding that analyses adjusted for BMI and physical activity did not identify an association between baseline 25-hydroxyvitamin D levels and breast cancer risk suggests that the association between 25-hydroxyvitamin D and breast cancer seen in some observational studies could be confounded to some degree by such factors.
You can argue that the question isn’t yet settled. I think that is defensible—maybe we really do need much higher doses. But you cannot argue that the researchers haven’t done their homework or that they aren’t aware of what their data is capable or incapable of showing.
So they used only 400 IU, and even then the breast cancer incidence was 528 vs 546 for 400 IU vs 0 IU.
The difference in incidence was not statistically significant.
This is primitive frequentist statistics.
If we could repeat this same experiment with a very similar distribution of patients and other factors (or if the trial was still ongoing), and it came down to a bet on which group would have higher cancer deaths—would you accept an even money bet that the placebo group would have less cancer deaths? ie—would you bet against me?
Whether 3% more deaths in the placebo group is significant or not for a sample size of 1000, and an average supplement level which is only 10% of what the vit D experts believe is required to replace sunlight depends completely on your priors and your statistical model. There is nothing innate or inherently correct about the standard puny little models used to determine ‘statistical significance’.
Thinking in terms of prediction markets helps clarify these issues—the best model is the one that ends up sitting on the big heap pile of money.
Random chance could easily result in this level of variation.
Sure—or maybe not. It is still evidence that favors a vit D effect for breast cancer.
However, the authors are not unaware of this and point out that many women in the trial were supplementing with additional Vitamin D, and after analyzing that, there was still no detectable effect:
Half of the women reported taking an additional 400 IU, which—even with full compliance—only raises the average up to 600 IU.
The main key point is that the range of measured OHD levels was between 30 to 67 ish and didn’t have a strong correlation to the supplement—they failed to raise the OHD levels. That is key. All of the studies which show a health effect also significantly shift the OHD levels. If your supplement isn’t shifting OHD levels much, why would think it would do much of anything?
The general theory predicts health effects in 1.) certain genetic subpopulations, who 2.) have unnaturally low levels (say <30 for caucasians), and 3. then raise those levels up to evolutionary ideal for their genetics (perhaps 50-60 for caucasians). The exact numbers are just hyperparameters—the point of the studies should be to refine them into a predictive model.
But you cannot argue that the researchers haven’t done their homework or that they aren’t aware of what their data is capable or incapable of showing.
The completely honest conclusion for their abstract should have been something like this:
Conclusions Calcium and low doses of vitamin D supplementation did not significantly reduce (> 3%) invasive breast cancer incidence in postmenopausal women. In addition, 25-hydroxyvitamin D levels were not associated with subsequent breast cancer risk after we adjusted for body mass index. It is difficult to make definitive conclusions from these findings.
Compare that to the conclusion they actually wrote. Then the telephone game begins, and people begin quoting this study as one which somehow ‘proves’ vit D supplementation has no effect on breast cancer . …
I’m sorry, I’m really not interested in getting into an ideological debate or whether frequentist or bayesian statistics is “better”—if you think that frequentist methods are worthless, then the inferential gap is too wide to begin to bridge.
Agreed—I do believe that Frequentist methods are primitive compared to modern machine learning.
Also, I don’t even have a strong opinion on whether a few years of vit D supplementation in the elderly is going to make a big difference in many health outcomes like cancer risk—the correct comparison is between a lifetime of adequate vit D levels vs a lifetime of inadequacy. I don’t suspect that correcting it late in life is going to avoid most of the cancer risk.
Not sure. Is it the colon cancer one? I read the breast cancer one linked on his post. I dont believe/expect that vit D is going to make an impact for every illness or type of cancer. I expect the relationship will be complex, and will depend heavily on dietary factors and genetics (for example there is strong evidence for various climdate adaptations—far northern peoples need much less vit D, etc.) I picked the breast cancer paper because I have a vague memory of hearing a very convincing talk from a breast cancer doctor about the evidence for the bio mechanisms between the low vit D and breast cancer.
From the summary of the breast cancer paper yvain linked to:
Methods Postmenopausal women (N = 36 282) who were enrolled in a Women’s Health Initiative clinical trial were randomly assigned to 1000 mg of elemental calcium with 400 IU of vitamin D3 daily or placebo for a mean of 7.0 years
Results Invasive breast cancer incidence was similar in the two groups (528 supplement vs 546 placebo; hazard ratio = 0.96; 95% confidence interval = 0.85 to 1.09). In the nested case–control study, no effect of supplement group assignment on breast cancer risk was seen. Baseline 25-hydroxyvitamin D levels were modestly correlated with total vitamin D intake (diet and supplements) (r = 0.19, P < .001) and were higher among women with lower BMI and higher recreational physical activity (both P < .001). Baseline 25-hydroxyvitamin D levels were not associated with breast cancer risk in analyses that were adjusted for BMI and physical activity (Ptrend = .20).
So they used only 400 IU, and even then the breast cancer incidence was 528 vs 546 for 400 IU vs 0 IU. There was no effect only when they “adjusted for BMI”—of course—as some other studies have suggested, vit D has a potential weight loss effect. The 400 IU didn’t make a huge diff on OHD levels.
This study is supportive of vit D potentially having a significant effect on breast cancer, and it is reasonable evidence against the null hypothesis (no effect). Instead here is their conclusion:
Conclusions Calcium and vitamin D supplementation did not reduce invasive breast cancer incidence in postmenopausal women. In addition, 25-hydroxyvitamin D levels were not associated with subsequent breast cancer risk. These findings do not support a relationship between total vitamin D intake and 25-hydroxyvitamin D levels with breast cancer risk.
That is not justifiable, nor is it even an accurate summary of their own data.
Yes I meant the colon cancer paper (I should have stated at the beginning rather than the end), but the breast cancer paper was from the same experiment, and as such also addresses you initial concerns about effects on different subgroups and measuring serum levels.
The difference in incidence was not statistically significant. Random chance could easily result in this level of variation. Regarding the dosage, yes you can only make conclusions about what you measure. This trial was started in the 90′s, and since then there have been some recommendations for higher doses. However, the authors are not unaware of this and point out that many women in the trial were supplementing with additional Vitamin D, and after analyzing that, there was still no detectable effect:
Perhaps a still higher dose is need to see any effect. But this would require positing a very non-linear model. Is it possible? Sure, but this complaint can always be made.
Regarding BMI, the authors are also aware of this argument—see the quote below. I’d like to point out that the BMI numbers were baseline which is not evidence that vitamin D supplementation causes weight loss. It is consistent with the hypothesis that healthier lifestyles result in both higher vitamin D levels (due to sun exposure with exercise) and lower BMI.
You can argue that the question isn’t yet settled. I think that is defensible—maybe we really do need much higher doses. But you cannot argue that the researchers haven’t done their homework or that they aren’t aware of what their data is capable or incapable of showing.
This is primitive frequentist statistics.
If we could repeat this same experiment with a very similar distribution of patients and other factors (or if the trial was still ongoing), and it came down to a bet on which group would have higher cancer deaths—would you accept an even money bet that the placebo group would have less cancer deaths? ie—would you bet against me?
Whether 3% more deaths in the placebo group is significant or not for a sample size of 1000, and an average supplement level which is only 10% of what the vit D experts believe is required to replace sunlight depends completely on your priors and your statistical model. There is nothing innate or inherently correct about the standard puny little models used to determine ‘statistical significance’.
Thinking in terms of prediction markets helps clarify these issues—the best model is the one that ends up sitting on the big heap pile of money.
Sure—or maybe not. It is still evidence that favors a vit D effect for breast cancer.
Half of the women reported taking an additional 400 IU, which—even with full compliance—only raises the average up to 600 IU.
The main key point is that the range of measured OHD levels was between 30 to 67 ish and didn’t have a strong correlation to the supplement—they failed to raise the OHD levels. That is key. All of the studies which show a health effect also significantly shift the OHD levels. If your supplement isn’t shifting OHD levels much, why would think it would do much of anything?
The general theory predicts health effects in 1.) certain genetic subpopulations, who 2.) have unnaturally low levels (say <30 for caucasians), and 3. then raise those levels up to evolutionary ideal for their genetics (perhaps 50-60 for caucasians). The exact numbers are just hyperparameters—the point of the studies should be to refine them into a predictive model.
The completely honest conclusion for their abstract should have been something like this:
Conclusions Calcium and low doses of vitamin D supplementation did not significantly reduce (> 3%) invasive breast cancer incidence in postmenopausal women. In addition, 25-hydroxyvitamin D levels were not associated with subsequent breast cancer risk after we adjusted for body mass index. It is difficult to make definitive conclusions from these findings.
Compare that to the conclusion they actually wrote. Then the telephone game begins, and people begin quoting this study as one which somehow ‘proves’ vit D supplementation has no effect on breast cancer . …
If you want to bet there the VITAL study going on: http://www.vitalstudy.org/VitalSigns.html 25,000 subjects 2000 UI Vitamin D3 and upcoming mortality data.
I also created a prediction book entry a while ago: http://predictionbook.com/predictions/14426
I’m sorry, I’m really not interested in getting into an ideological debate or whether frequentist or bayesian statistics is “better”—if you think that frequentist methods are worthless, then the inferential gap is too wide to begin to bridge.
Agreed—I do believe that Frequentist methods are primitive compared to modern machine learning.
Also, I don’t even have a strong opinion on whether a few years of vit D supplementation in the elderly is going to make a big difference in many health outcomes like cancer risk—the correct comparison is between a lifetime of adequate vit D levels vs a lifetime of inadequacy. I don’t suspect that correcting it late in life is going to avoid most of the cancer risk.