Conditional borrowing external data to establish a hybrid control arm in randomized clinical trials

References

• Chen, M.-H., and J. Ibrahim. 2000. Power prior distributions for regression models. Statistical Science 15 (1):46–60. doi:10.1214/ss/1009212673.
   Web of Science ®Google Scholar
• Food and Drug Administration. 2019. Demonstrating Substantial Evidence of Effectiveness for Human Drug and Biological Products Guidance for Industry. https://www.federalregister.gov/d/2019-27524
   Google Scholar
• Gamalo, M., R. Tiwari, and L. LaVange. 2014. Bayesian approach to the design and analysis of non-inferiority trials for anti-infective products. Pharmaceutical Statistics 13 (1):25–40. doi:10.1002/pst.1588.
   PubMed Web of Science ®Google Scholar
• Hobbs, B., D. Sargent, and B. Carlin. 2012. Commensurate priors for incorporating historical information in clinical trials using general and generalized linear models. Bayesian Analysis 7 (3):639–674. doi:10.1214/12-BA722.
   PubMed Web of Science ®Google Scholar
• Johnson, M., H. Tolley, M. Bryson, and A. Goldman. 1982. Covariate analysis of survival data: A small-sample study of Cox’s model. Biometrics 38 (3):685–698. doi:10.2307/2530049.
   PubMed Web of Science ®Google Scholar
• Li, H., V. Mukhi, N. Lu, Y. Xu, and L. Yue. 2016. A note on good practice of objective propensity score design for premarket nonrandomized medical device studies with an example. Statistics in Biopharmaceutical Research 8 (3):282–286. doi:10.1080/19466315.2016.1148071.
   Web of Science ®Google Scholar
• Li, W., F. Liu, and D. Snavely. 2020. Revisit of test‐then‐pool methods and some practical considerations. Pharmaceutical Statistics 19 (5):498–517. doi:10.1002/pst.2009.
   PubMed Web of Science ®Google Scholar
• Lin, J., M. Gamalo-Siebers, and R. Tiwari. 2018. Propensity score matched augmented controls in randomized clinical trials: A case study. Pharmaceutical Statistics 17 (5):629–647. doi:10.1002/pst.1879.
   PubMed Web of Science ®Google Scholar
• Neuenschwander, B., G. Capkun-Niggli, M. Branson, and D. Spiegelhalter. 2010. Summarizing historical information on controls in clinical trials. Clinical Trials 7 (1):5–18. doi:10.1177/1740774509356002.
   PubMed Web of Science ®Google Scholar
• Rosenbaum, P., and D. Rubin. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70 (1):41–55. doi:10.1093/biomet/70.1.41.
   Web of Science ®Google Scholar
• Rosenbaum, P., and D. Rubin. 1984. Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association 79 (387):516–524. doi:10.1080/01621459.1984.10478078.
   Web of Science ®Google Scholar
• Rosenbaum, P. 1987. Model‐based direct adjustment. Journal of the American Statistical Association 82 (398):387–394. doi:10.1080/01621459.1987.10478441.
   Web of Science ®Google Scholar
• van Rosmalen, J., D. Dejardin, Y. van Norden, B. Löwenberg, and E. Lesaffre. 2017. Including historical data in the analysis of clinical trials: Is it worth the effort?. Statistical Methods in Medical Research 27 (10):3167–3182. doi:10.1177/0962280217694506.
   PubMed Web of Science ®Google Scholar
• Viele, K., S. Berry, B. Neuenschwander, B. Amzal, F. Chen, N. Enas, B. Hobbs, J. G. Ibrahim, N. Kinnersley, S. Lindborg, et al. 2014. Use of historical control data for assessing treatment effects in clinical trials. Pharmaceutical Statistics 13(1):41–54. doi:10.1002/pst.1589.
   PubMed Web of Science ®Google Scholar
• Wang, C., H. Li, W. Chen, N. Lu, R. Tiwari, Y. Xu, and L. Yue. 2019. Propensity score-integrated power prior approach for incorporating real-world evidence in single-arm clinical studies. Journal of Biopharmaceutical Statistics 29 (5):731–748. doi:10.1080/10543406.2019.1657133.
   PubMed Web of Science ®Google Scholar
• Xu, R. 2017. Methods for survival analysis in small samples. Publicly Accessible Penn Dissertations 2649. https://repository.upenn.edu/edissertations/2649.
   Google Scholar
• Yue, L., N. Lu, and Y. Xu. 2014. Designing premarket observational comparative studies using existing data as controls: Challenges and opportunities. Journal of Biopharmaceutical Statistics 24 (5):994–1010. doi:10.1080/10543406.2014.926367.
   PubMed Web of Science ®Google Scholar