The FDA has issued a guidance on Bayesian statistical methods in the design and analysis of medical device clinical trials, which could result in less costly and more efficient patient studies.

The Bayesian statistical method applies an algorithm that makes it possible for companies to combine data collected in previous studies with data collected in a current trial. The combined data may provide sufficient justification for smaller or shorter clinical studies.

The FDA has approved a number of medical devices whose approval applications submitted to the agency included clinical studies that used these statistical methods.

The final guidance, titled ‘Guidance for the Use of Bayesian Statistics in Medical Device Clinical Trials,’ describes use of Bayesian methods, design and analysis of medical device clinical trials. Also, the benefits and difficulties with the Bayesian approach and comparisons with standard statistical methods are described. The guidance also presents ideas for using Bayesian methods in post-market studies.

Reportedly, in June 2009 public meeting, the Medicare Evidence Development and Coverage Advisory Committee encouraged Medicare policymakers to consider Bayesian approaches when reviewing trials or technology assessments during the national coverage analysis process.

Margaret Hamburg, commissioner of FDA, said: “This final guidance on the use of Bayesian statistics is consistent with the FDA’s commitment to streamline clinical trials, when possible, in order to get safe and effective products to market faster. This is an example of regulatory science in practice at FDA.”