Case Study: Evaluation of a meta-analysis of the association between soy protein and cardiovascular disease

11/29/2021
by   S. Stanley Young, et al.
0

It is well-known that claims coming from observational studies most often fail to replicate. Experimental (randomized) trials, where conditions are under researcher control, have a high reputation and meta-analysis of experimental trials are considered the best possible evidence. Given the irreproducibility crisis, experiments lately are starting to be questioned. There is a need to know the reliability of claims coming from randomized trials. A case study is presented here independently examining a published meta-analysis of randomized trials claiming that soy protein intake improves cardiovascular health. Counting and p-value plotting techniques (standard p-value plot, p-value expectation plot, and volcano plot) are used. Counting (search space) analysis indicates that reported p-values from the meta-analysis could be biased low due to multiple testing and multiple modeling. Plotting techniques used to visualize the behavior of the data set used for meta-analysis suggest that statistics drawn from the base papers do not satisfy key assumptions of a random-effects meta-analysis. These assumptions include using unbiased statistics all drawn from the same population. Also, publication bias is unaddressed in the meta-analysis. The claim that soy protein intake should improve cardiovascular health is not supported by our analysis.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset