A structured framework for adaptively incorporating external evidence in sequentially monitored clinical trials. Issue 3 (4th May 2022)
- Record Type:
- Journal Article
- Title:
- A structured framework for adaptively incorporating external evidence in sequentially monitored clinical trials. Issue 3 (4th May 2022)
- Main Title:
- A structured framework for adaptively incorporating external evidence in sequentially monitored clinical trials
- Authors:
- Kwiatkowski, Evan
Andraca-Carrera, Eugenio
Soukup, Mat
Psioda, Matthew A. - Abstract:
- ABSTRACT: We present a Bayesian framework for sequential monitoring that allows for use of external data, and that can be applied in a wide range of clinical trial applications. The basis for this framework is the idea that, in many cases, specification of priors used for sequential monitoring and the stopping criteria can be semi-algorithmic byproducts of the trial hypotheses and relevant external data, simplifying the process of prior elicitation. Monitoring priors are defined using the family of generalized normal distributions, which comprise a flexible class of priors, naturally allowing one to construct a prior that is peaked or flat about the parameter values thought to be most likely. External data are incorporated into the monitoring process through mixing an a priori skeptical prior with an enthusiastic prior using a weight that can be fixed or adaptively estimated. In particular, we introduce an adaptive monitoring prior for efficacy evaluation that dynamically weighs skeptical and enthusiastic prior components based on the degree to which observed data are consistent with an enthusiastic perspective. The proposed approach allows for prospective and pre-specified use of external data in the monitoring procedure. We illustrate the method for both single-arm and two-arm randomized controlled trials. For the latter case, we also include a retrospective analysis of actual trial data using the proposed adaptive sequential monitoring procedure. Both examples areABSTRACT: We present a Bayesian framework for sequential monitoring that allows for use of external data, and that can be applied in a wide range of clinical trial applications. The basis for this framework is the idea that, in many cases, specification of priors used for sequential monitoring and the stopping criteria can be semi-algorithmic byproducts of the trial hypotheses and relevant external data, simplifying the process of prior elicitation. Monitoring priors are defined using the family of generalized normal distributions, which comprise a flexible class of priors, naturally allowing one to construct a prior that is peaked or flat about the parameter values thought to be most likely. External data are incorporated into the monitoring process through mixing an a priori skeptical prior with an enthusiastic prior using a weight that can be fixed or adaptively estimated. In particular, we introduce an adaptive monitoring prior for efficacy evaluation that dynamically weighs skeptical and enthusiastic prior components based on the degree to which observed data are consistent with an enthusiastic perspective. The proposed approach allows for prospective and pre-specified use of external data in the monitoring procedure. We illustrate the method for both single-arm and two-arm randomized controlled trials. For the latter case, we also include a retrospective analysis of actual trial data using the proposed adaptive sequential monitoring procedure. Both examples are motivated by completed pediatric trials, and the designs incorporate information from adult trials to varying degrees. Preposterior analysis and frequentist operating characteristics of each trial design are discussed. … (more)
- Is Part Of:
- Journal of biopharmaceutical statistics. Volume 32:Issue 3(2022)
- Journal:
- Journal of biopharmaceutical statistics
- Issue:
- Volume 32:Issue 3(2022)
- Issue Display:
- Volume 32, Issue 3 (2022)
- Year:
- 2022
- Volume:
- 32
- Issue:
- 3
- Issue Sort Value:
- 2022-0032-0003-0000
- Page Start:
- 474
- Page End:
- 495
- Publication Date:
- 2022-05-04
- Subjects:
- Adaptive trial design -- bayesian sequential monitoring -- information borrowing -- pediatric trials -- skeptical prior
Pharmacy -- Statistical methods -- Periodicals
Drugs -- Testing -- Statistical methods -- Periodicals
Biometry -- Periodicals
Biopharmaceutics -- Periodicals
Pharmacokinetics -- Periodicals
615.19 - Journal URLs:
- http://www.tandfonline.com/toc/lbps20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/10543406.2022.2078346 ↗
- Languages:
- English
- ISSNs:
- 1054-3406
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4953.910000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 23260.xml