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Centre for Reviews and Dissemination
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Methodological development

We have a world-leading reputation for evidence synthesis and health technology assessment, underpinned by methodological development and knowledge mobilisation activity.

We have particular interest and expertise in statistical methods including network meta-analysis (NMA), population adjustment in indirect comparisons, Bayesian methods for information sharing, individual participant data (IPD) and diagnostic accuracy synthesis, risk prediction, simulation-based decision modelling, and survival analysis.

We are involved in developing approaches to utilise trial data and information increasingly being released under open data and data sharing initiatives.

Other areas of interest include developing statistical approaches to determine when to update a systematic review, methods of narrative synthesis and defining methods and approaches to “rapid evidence synthesis”.  CRD staff are also active in producing methodological guidance, tools and reporting guidelines.

Methodological projects

Find out more about the range of methodologies that CRD develops and utlises in our research below.

IPD meta-analysis

Individual Participant Data (IPD) reviews assemble study data sets. Access to this individual-level data enables more powerful and flexible analyses than are possible with aggregate or summary data.

Current projects
  • Co-enzyme Q10 for chronic health failure (CHOICE) 
  • Evaluating Progestogen for Prevention of Preterm birth International Collaborative (EPPPIC). More about EPPPIC.
  • Applied Behavioral Analysis interventions for pre-school children with autism (IPD meta-analysis and economic evaluation)
Completed projects
Indirect treatment comparisons and network meta-analysis

Indirect comparisons and network meta-analysis allow comparison of interventions that have not been directly compared in trials.

Current research topics
  • Bias-quantification and adjustment in NMA
  • Modelling time and dose effects
  • Methods for population adjustment and precision medicine
Lastest publications
  1. Phillippo DM, Dias S, Ades AE, Welton NJ. Multilevel network meta-regression for general likelihoods: synthesis of individual and aggregate data with applications to survival analysis. Journal of the Royal Statistical Society Series A: Statistics in Society 2025. 10.1093/jrsssa/qnaf169
  2. Nevitt SJ, Phillippo DM, Hodgson R, Welton NJ, Dias S. Application of Multi-level Network Meta-Regression in the NICE Technology Appraisal of Quizartinib for Induction, Consolidation and Maintenance Treatment of Newly Diagnosed FLT3-ITD-Positive Acute Myeloid Leukaemia: An External Assessment Group Perspective. Pharmacoeconomics 2025;43:243–7. 10.1007/s40273-024-01460-1
  3. Lunny C, Higgins JPT, White IR, Dias S, Hutton B, Wright JM, et al. Risk of Bias in Network Meta-Analysis (RoB NMA) tool. BMJ 2025;388:e079839. 10.1136/bmj-2024-079839
  4. Ades AE, Welton NJ, Dias S, Phillippo DM, Caldwell DM. Twenty years of network meta-analysis: Continuing controversies and recent developments. Research Synthesis Methods 2024;15:702–27. https://doi.org/10.1002/jrsm.1700
Bayesian evidence synthesis

Bayesian methods for meta-analysis allow incorporation of external evidence and estimation of complex data relationships in hierarchical models

Current research topics
  • Use of informative prior distributions and external evidence in Bayesian NMA
  • Incorporation of evidence from different populations
  • Information-sharing models
Recent publications
  1. Singh J, Anwer S, Palmer S, Saramago P, Thomas A, Dias S, et al. Multi-indication Evidence Synthesis in Oncology Health Technology Assessment: Meta-analysis Methods and Their Application to a Case Study of Bevacizumab. Med Decis Making 2025;45:17–33. 10.1177/0272989X241295665
  2. Walker R, Phillips B, Dias S. Comparison of Bayesian methods for incorporating adult clinical trial data to improve certainty of treatment effect estimates in children. PLoS One 2023;18:e0281791. 10.1371/journal.pone.0281791
  3. Hussein H, Abrams KR, Gray LJ, Anwer S, Dias S, Bujkiewicz S. Hierarchical network meta-analysis models for synthesis of evidence from randomised and non-randomised studies. BMC Med Res Methodol 2023;23:97. 10.1186/s12874-023-01925-5
Best practice for evidence synthesis

We are involved in the development of risk of bias tools to assess evidence quality and in providing guidance and standards for the conduct and reporting of systematic reviews.

Latest publications
  1. Lunny C, Higgins JPT, White IR, Dias S, Hutton B, Wright JM, et al. Risk of Bias in Network Meta-Analysis (RoB NMA) tool. BMJ 2025;388:e079839. https://doi.org/10.1136/bmj-2024-079839
  2. Higgins J, Lasserson T, Thomas J, Flemyng E, Churchill R. Methodological Expectations of Cochrane Intervention Reviews (MECIR). Standards for the conduct of new Cochrane Intervention Reviews, and the planning and conduct of updates (Version August 2023). 2023. URL: https://www.cochrane.org/authors/handbooks-and-manuals/mecir-manual (accessed 09/02/2026).
  3. South, E., Rodgers, M. Data visualisation in scoping reviews and evidence maps on health topics: a cross-sectional analysis. Syst Rev 12, 142 (2023). https://doi.org/10.1186/s13643-023-02309-y

Project spotlight

Information sharing using Bayesian evidence synthesis

The CRD team are involved in a series of projects to explore how evidence can be shared across different outcomes, populations, time points, doses or treatment indications within a Bayesian framework.

Watch a video about incorporating adult clinical trial data to improve treatment effect estimates in children. 

Read a paper from our project on sharing information across multiple indications.