Robust meta-analytic-predictive priors in clinical trials with historical control information.

Schmidli, Heinz; Gsteiger, Sandro; Roychoudhury, Satrajit; O'Hagan, Anthony; Spiegelhalter, David; Neuenschwander, Beat (2014). Robust meta-analytic-predictive priors in clinical trials with historical control information. Biometrics, 70(4), pp. 1023-32. The International Biometric Society 10.1111/biom.12242

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Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)

UniBE Contributor:

Gsteiger, Sandro

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services

ISSN:

0006-341X

Publisher:

The International Biometric Society

Language:

English

Submitter:

Doris Kopp Heim

Date Deposited:

10 Nov 2014 10:12

Last Modified:

05 Dec 2022 14:38

Publisher DOI:

10.1111/biom.12242

PubMed ID:

25355546

Uncontrolled Keywords:

Adaptive design, Adaptive randomization, Bayesian inference, Clinical trials, Exponential family, Meta-analysis, Mixture distribution, Robustness

BORIS DOI:

10.7892/boris.59957

URI:

https://boris.unibe.ch/id/eprint/59957

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