Bayesian Statistics in Medical Device Clinical Trials: Design, Analysis and Implementation

Recommended Actions

1. Meet with FDA early to discuss planned use of Bayesian methods and obtain agreement on:
   • Prior information to be used
   • Statistical models and assumptions
   • Trial design and adaptations
   • Success criteria
2. Document in protocol:
   • Justification for using Bayesian approach
   • Sources and validation of prior information
   • Statistical analysis plan including models
   • Operating characteristics through simulation
   • Sample size justification
   • Interim analysis plans if applicable
3. Implement appropriate controls:
   • Verify computational methods and convergence
   • Conduct sensitivity analyses
   • Check model assumptions
   • Document all analyses
4. For submission:
   • Submit data and analysis code electronically
   • Provide clear presentation of results
   • Include sensitivity analyses
   • Justify all modeling choices
   • Present labeling in understandable terms
5. Plan for post-market:
   • Define how Bayesian updating will be used
   • Specify data collection and analysis methods
   • Document process for incorporating new information

Key Considerations

Clinical testing

• Clinical trial design principles remain the same as traditional trials (randomization, blinding, etc.)
• Prior information from previous clinical studies can be incorporated if sufficiently similar
• Minimum sample size should be defined based on safety and effectiveness endpoints
• Operating characteristics (type I and II error rates) should be evaluated

Software

• Software used for Bayesian analysis should be discussed with FDA statisticians
• Program code and data used for simulations should be submitted electronically
• Convergence of computational algorithms should be verified

Labelling

• Results from Bayesian trials should be expressed clearly in device labeling
• Bayesian terminology should be explained in a way that is easy to understand
• Credible intervals should be reported

Safety

• Safety endpoints may require larger sample sizes than effectiveness endpoints
• Prior information on safety should be carefully evaluated
• Sensitivity analyses should be performed for safety claims

Other considerations

• Prior information should be carefully selected and justified
• Adaptive trial designs should be pre-specified
• Model assumptions should be checked and sensitivity analyses performed
• Missing data should be appropriately handled
• Post-market surveillance can utilize Bayesian updating of pre-market data

  Relevant Guidances

• Bayesian Statistics in Medical Device Clinical Trials
• Design Considerations for Medical Device Pivotal Clinical Studies

Related references and norms

• ISO 14155: Clinical investigation of medical devices for human subjects - Good clinical practice

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Original guidance

• Bayesian Statistics in Medical Device Clinical Trials: Design, Analysis and Implementation
• HTML
• Issue date: 2010-02-04
• Last changed date: 2020-01-19
• Status: FINAL
• Official FDA topics: Medical Devices, Biostatistics
• ReguVirta summary file ID: bf385674933d595f298ce2cd3ac8c220