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This course will introduce participants to the fundamental statistical methods and principles for evidence synthesis and meta-analysis when IPD (Individual Participant/Patient Data) are available from multiple related studies. The course will consider continuous, binary and time-to-event outcomes, and both fixed-effect and random-effects meta-analysis models. Day 1 will focus mainly on the general rationale and advantages of IPD meta-analysis. Day 2 will focus on the synthesis of IPD from randomised trials of interventions, where the aim is to quantify a treatment effect (usually in the presence of between-study heterogeneity) or to identify treatment effect modifiers (interactions) for stratified medicine. Day 3 will focus on key differences and potential objectives of IPD meta-analysis of observational studies, where the aim is to identify prognostic factors or to develop/validate a risk prediction (prognostic) model. Day 4 will focus on statistical methods for developing and validating risk prediction models in IPD meta-analysis. On Day 5, students will prepare a protocol for a case study and discuss this with their peers.

The key messages will be illustrated with real examples throughout, and participants will conduct a variety of IPD analyses within R, to practise the key methods and reinforce the learning points. By the end of the course, you should be able to:

  • Explain the rationale for performing an individual participant data meta-analysis (IPD-MA)
  • Understand the advantages, limitations and key characteristics of IPD-MA in intervention, diagnostic and prognostic research
  • Understand the relevance of between-study heterogeneity, and be familiar with statistical methods for investigating and reporting this
  • Be familiar with statistical methods for summarizing relative treatment effects and exploring the presence of treatment-covariate interaction
  • Be familiar with statistical methods for developing and validating clinical prediction models using IPD from multiple studies or settings
  • Be familiar with statistical methods for investigating and comparing diagnostic test accuracy using IPD
  • Interpret and critically appraise the results from an IPD-MA

We expect participants to have a basic knowledge about the principles of intervention research, diagnostic research, prognostic research, systematic reviews and meta-analysis. Some basic knowledge of R is helpful (but not required).