Completed Psychology & Behaviour Brain & Nervous System

Method Meta-analysis

In plain English

AI plain-English summary

Clinical trial results are being pooled and re-analysed to find out which treatments actually work, and for whom. This matters because doctors and policymakers rely on systematic reviews and meta-analyses to decide which drugs to prescribe or which treatments to fund. But the statistical methods behind these reviews are often outdated or too crude to detect whether a treatment works better for certain patient groups—older people, women, or those with other health conditions. Without better methods, patients may receive treatments that are less effective for them, or effective treatments may be wrongly dismissed. The researchers are developing new statistical techniques for all types of meta-analysis, including network meta-analysis, which compares multiple treatments at once. They are also collecting more detailed patient-level data to explore why some people respond differently. To make these methods usable, they are writing open-source software, producing guidance documents, and running training courses. If successful, this work will not change daily life directly. Instead, it will quietly improve the infrastructure of medical decision-making—making clinical guidelines more reliable, drug approvals more precise, and treatment recommendations more tailored to individual patients.

View original technical description
Systematic reviews are a way of bringing together similar clinical trials. Meta-analysis is a way of putting results or data from these trials together to work out whether treatments work, and network meta-analysis helps us decide which treatments work best. Working alongside trial teams, we are developing new and improved ways of planning and doing these systematic reviews and meta-analyses, so that we can find out which treatments are best for patients quickly and reliably. Sometimes, treatments work better in some patients than in others, so we are also collecting more detailed data and developing reliable methods to explore this. We are developing better statistical techniques for doing all types of meta-analysis and network meta-analysis. To help others to use our new methods of doing things, we are writing user-friendly software, preparing guidance, and giving tutorials and training courses.

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Researchers

Claire Louise Vale (Co-Investigator)Ian White (Principal Investigator)Jayne Tierney (Principal Investigator)Rebecca Turner (Co-Investigator)

Related Research

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Meta-analysis, complexity and heterogeneity (MACH): methodological review and development of guidance
Evidence synthesis of diagnostic test performance from a decision-making perspective

Original classification

Intramural

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