Network Meta-Analysis: A Statistical Physics Perspective

TL;DR

This paper introduces network meta-analysis (NMA) to statistical physicists, highlighting how physics tools like complex networks and stochastic models can enhance evidence synthesis in medical research.

Contribution

It presents NMA concepts and approaches in an accessible way for physicists, fostering interdisciplinary collaboration and future research opportunities.

Findings

Identifies connections between NMA and complex network theory

Suggests physics-based models can improve NMA methods

Encourages physicists to contribute to medical evidence synthesis

Abstract

Network meta-analysis (NMA) is a technique used in medical statistics to combine evidence from multiple medical trials. NMA defines an inference and information processing problem on a network of treatment options and trials connecting the treatments. We believe that statistical physics can offer useful ideas and tools for this area, including from the theory of complex networks, stochastic modelling and simulation techniques. The lack of a unique source that would allow physicists to learn about NMA effectively is a barrier to this. In this article we aim to present the `NMA problem' and existing approaches to it coherently and in a language accessible to statistical physicists. We also summarise existing points of contact between statistical physics and NMA, and describe our ideas of how physics might make a difference for NMA in the future. The overall goal of the article is to attract physicists to this interesting, timely and worthwhile field of research.