Population Pharmacokinetics (PopPK) is the gold standard method of understanding drug safety and efficacy, particularly as it provides a unique insight into the variation of drug behaviour from person to person. While not a novel methodology—Sheiner, Rosenberg and Marathe first demonstrated the analysis in 1977—techniques and approaches in PopPK have undergone continual improvement in the…
This is the third blog in our trilogy on techniques for population adjustment in network meta-analysis (NMA). Here we will focus on an approach called Multi-Level Network Meta-Regression (ML-NMR), which improves on several aspects of the methods we described in our first two blogs – Matching Adjusted Indirect Comparison (MAIC), and Simulated Treatment Comparison (STC)….
In this blog we will describe an alternative approach to indirect comparison – Simulated Treatment Comparison (STC) – and discuss the key aspects to consider when looking to use the technique. We will discuss the situations when we would recommend using the method instead of a Matching Adjusted Indirect Comparison (MAIC). HTA submissions often involve…
When comparing trial outcomes using standard network meta-analysis (NMA), the assumption is that populations in different trials do not differ in any characteristics that may impact the treatment effect (see this blog for an introduction to the concept of NMA). If this assumption is not true, these study differences then need to be accounted for…
In an ideal world, a single randomized controlled trial (RCT) would be used to compare and evaluate the individual treatment effects for all possible treatments of interest. Of course, this is often not feasible, in which case network meta-analysis (NMA) can be used to link RCTs with common treatment arms and compare treatments across different…
A standard pairwise meta-analysis can compare the efficacy or safety of exactly two treatments that have been directly compared in head-to-head clinical trials. However, in practice, there are often many potential treatments for a single disease. Policy-makers, physicians and patients need to be able to select the best treatment from amongst the many potential options….
In this post we examine the statistical software available for conducting Bayesian network meta-analyses (NMA). The first two sections provide some background information and a review of the available software – we hope this section will be of interest to all of our readers. The final section provides an introduction to conducting NMA in Stan…
Most network meta-analyses will consist of six key stages – developing the protocol, performing the systematic review, conducting the feasibility assessment, preparing the statistical analysis plan, running the analyses and reporting the results. In this post, we give a brief overview of each of these stages, and suggest strategies for ensuring that your network meta-analysis…
Like all statistical analyses, network meta-analysis relies on a specific set of assumptions. Here, we’ll look at the key assumptions of network meta-analysis. In order to draw valid conclusions about the relative efficacy and safety of treatments in a network meta-analysis and facilitate good decision making, it is important to understand and evaluate these assumptions….
Find out about our network meta analysis services Welcome to Quantics’ health technology assessment blog. This blog will explore some of the statistical aspects of health technology assessment, including meta-analysis, network meta-analysis and survival analysis. The aims of this blog are two-fold. Firstly, we want to create a knowledge base to help those who are…