Contents
What is Frequentist network meta-analysis?
Network meta-analysis is used to compare three or more treatments for the same condition. Within a Bayesian framework, for each treatment the probability of being best, or, more general, the probability that it has a certain rank can be derived from the posterior distributions of all treatments.
What is the difference between a meta-analysis and a network meta-analysis?
A fundamental difference between a conventional pair-wise meta-analysis and network meta-analysis is that a conventional pair-wise meta-analysis yields only one pooled effect estimate whereas a network meta-analysis yields more than one pooled effect estimate.
What is a Bayesian meta-analysis?
In a Bayesian analysis, initial uncertainty is expressed through a prior distribution about the quantities of interest. In the context of a meta-analysis, the prior distribution will describe uncertainty regarding the particular effect measure being analysed, such as the odds ratio or the mean difference.
What is sucra curve?
The surface under the cumulative ranking curve (SUCRA) is a numeric presentation of the overall ranking and presents a single number associated with each treatment. SUCRA values range from 0 to 100%.
What does sucra stand for?
How to rank treatments in frequentist network meta-analysis?
Using case studies of network meta-analysis in diabetes and depression, we demonstrate that the numerical values of SUCRA and P-Score are nearly identical. Ranking treatments in frequentist network meta-analysis works without resampling.
When do you use a network meta-analysis?
An increasing number of systematic reviews use network meta-analysis to compare three or more treatments to each other even if they have never been compared directly in a clinical trial [ 1 – 4 ]. The methodology of network meta-analysis has developed quickly and continues to be refined using both Bayesian and frequentist approaches.
How are P-scores calculated in the frequentist network?
P-scores are based solely on the point estimates and standard errors of the frequentist network meta-analysis estimates under normality assumption and can easily be calculated as means of one-sided p-values. They measure the mean extent of certainty that a treatment is better than the competing treatments.
What is the AUC of the frequentist network?
The large difference in variances is reflected by the asymmetric appearance of the curve. Moreover, the curve cuts the dotted line, which is due to the above-mentioned region to the left of Fig. 1 where we observe more unfavorable effects occurring under A. The AUC is 59 %.