4 replies to this topic

[Michael]

This is clearly additional data coming out of the same "Copenhagen" NR Study (PMID  29992272) that earlier reported that 2 x 100o mg/d NR  had no effect on "Insulin sensitivity, endogenous glucose production, glucose disposal and oxidation ... resting energy expenditure, lipolysis, oxidation of lipids, or body composition" in obese nondiabetic men, and that certain proponents played up a nonsignificant post hoc suggestion of an effect on liver fat in the subgoup with fatty liver. This new report expands those findings to the other half of the syndrome that is diabetes, finding no effect on beta-function either:
 

A 12-week randomized, double-blind, placebo-controlled, and parallel-group trial in 40 obese, insulin-resistant males allocated to NR 1,000 mg twice daily (n = 20) or placebo (n = 20).
 
Methods
2-hour 75 gram oral glucose tolerance tests (OGTT) were performed before and after the intervention ...
 
Results
NR supplementation during 12 weeks neither affected fasting nor post-glucose challenge concentrations of glucose, insulin, C-peptide, glucagon, GLP-1, or GIP, and β-cell function did not respond to the intervention. In addition, no changes in circulating adipsin or bile acids were observed following NR supplementation.
 
Conclusion
The present study does not provide evidence to support that dietary supplementation with the NAD⁺ precursor NR serves to impact glucose tolerance, β-cell secretory capacity, α-cell function, and incretin hormone secretion in obese, non-diabetic males. Moreover, bile acid levels in plasma did not change in response to NR supplementation.

PMID 31390002

Edited by Michael, 13 August 2019 - 09:35 PM.

[bluemoon]

certain proponents played up a nonsignificant post hoc suggestion of an effect on liver fat in the subgoup with fatty liver.

 

 

I don't think Charles Brenner "played up" anything. He simply states that NR reduced fatty liver at the p=.13 level but not at the p=0.05 level.

[Michael]

I don't think Charles Brenner "played up" anything. He simply states that NR reduced fatty liver at the p=.13 level but not at the p=0.05 level.

 

Right — and laetrile cures cancer at the p= 0.5 level, but not the p<.05 level.

 

The whole point of having a standard statistical test for significance is to decide whether the underlying data (nominal effect size, sample size, variability in the data) are sufficiently unlikely to occur by chance as to make it reasonable to reject the null hypothesis. It's true that the cutoff is ultimately arbitrary, but if anything it ought to be tighter, not looser.
 

[Andey]

Right — and laetrile cures cancer at the p= 0.5 level, but not the p<.05 level.

 

The whole point of having a standard statistical test for significance is to decide whether the underlying data (nominal effect size, sample size, variability in the data) are sufficiently unlikely to occur by chance as to make it reasonable to reject the null hypothesis. It's true that the cutoff is ultimately arbitrary, but if anything it ought to be tighter, not looser.
 

 

 To be fair, isnt it more about inappropriately powered study for this outcome? If I were to bet I would put 100 against 13 that given more participants it would reach significance).

 

Yes, its a sloppy science but we are not talking about some personalities careers or marketing products that are not proven properly, we are trying to get a grasp on... truth

Edited by Andey, 14 August 2019 - 07:04 AM.

[bluemoon]

Right — and laetrile cures cancer at the p= 0.5 level, but not the p<.05 level.

 

The whole point of having a standard statistical test for significance is to decide whether the underlying data (nominal effect size, sample size, variability in the data) are sufficiently unlikely to occur by chance as to make it reasonable to reject the null hypothesis. It's true that the cutoff is ultimately arbitrary, but if anything it ought to be tighter, not looser.
 

 

No, the point is that statistical significance can be manipulated and should be abandoned, not be made tighter. 

 

From this past spring:

 

"The current way many researchers apply p-values to draw conclusions on statistical significance is incorrect and unhelpful, three scientists argue in a Nature commentary published yesterday (March 20). The authors urge the research community to drop the concept of statistical significance altogether, and more than 800 statisticians and scientists have signed on to the idea. 

 

Scientists have often misused p-values to make claims about what hypotheses their statistically significant or insignificant results “prove,” leading to hyped claims or artificial conflict between studies, the authors say. Because of the bias in journals towards publishing findings with p-values below 0.05, scientists may ignore interesting results that don’t meet the bar and may pick data or methods to try to surpass the threshold."

 

... .... .... ....The American Statistical Association is also pushing for an end to statistical significance. “Regardless of whether it was ever useful, a declaration of ‘statistical significance’ has today become meaningless,” the statisticians write in an editorial published yesterday in a special issue of The American Statistician devoted to this debate. “[N]o p-value can reveal the plausibility, presence, truth, or importance of an association or effect. Therefore, a label of statistical significance does not mean or imply that an association or effect is highly probable, real, true, or important,” the authors of the editorial explain."

 

https://www.the-scie...tists-say-65635