When recruitment into a clinical trial is limited due to rarity of the disease of interest, or when recruitment to the control arm is limited due to ethical reasons (eg, pediatric studies or important unmet medical need), exploiting historical controls to augment the prospectively collected database can be an attractive option. Statistical methods for combining historical data with randomized data, while accounting for the incompatibility between the two, have been recently proposed and remain an active field of research. The current literature is lacking a rigorous comparison between methods but also guidelines about their use in practice. In this paper, we compare the existing methods based on a confirmatory phase III study design exercise done for a new antibacterial therapy with a binary endpoint and a single historical dataset. A procedure to assess the relative performance of the different methods for borrowing information from historical control data is proposed, and practical questions related to the selection and implementation of methods are discussed. Based on our examination, we found that the methods have a comparable performance, but we recommend the robust mixture prior for its ease of implementation.

Additional Metadata
Keywords Bayesian analysis, commensurate prior, historical control, power prior, robust mixture prior
Persistent URL dx.doi.org/10.1002/pst.1843, hdl.handle.net/1765/111347
Journal Pharmaceutical Statistics
Citation
Dejardin, D, Delmar, P. (Paul), Warne, C. (Charles), Patel, K. (Katie), van Rosmalen, J.M, & Lesaffre, E.M.E.H. (2018). Use of a historical control group in a noninferiority trial assessing a new antibacterial treatment: A case study and discussion of practical implementation aspects. Pharmaceutical Statistics, 17(2), 169–181. doi:10.1002/pst.1843