A Bayesian Framework Allowing Incorporation of Retrospective Information in Prospective Diagnostic Biomarker-Validation Designs. (3rd July 2019)
- Record Type:
- Journal Article
- Title:
- A Bayesian Framework Allowing Incorporation of Retrospective Information in Prospective Diagnostic Biomarker-Validation Designs. (3rd July 2019)
- Main Title:
- A Bayesian Framework Allowing Incorporation of Retrospective Information in Prospective Diagnostic Biomarker-Validation Designs
- Authors:
- Barrado, Leandro García
Coart, Els
Burzykowski, Tomasz - Abstract:
- Abstract: The sample size of a prospective clinical study aimed at validation of a diagnostic biomarker-based test may be prohibitively large. We present a Bayesian framework that allows incorporating available development-study information about the performance of the test. As a result, the framework allows reducing the sample size required in the validation study, which may render the latter study feasible. The validation is based on the Bayesian testing of a hypothesis regarding possible values of AUC. Toward this end, first, available information is translated into a prior distribution. Next, this prior distribution is used in a Bayesian design to evaluate the performance of the diagnostic-test. We perform a simulation study to compare the power of the proposed Bayesian design to the approach ignoring development-study information. For each scenario, 1000 studies of sample size 100, 400, and 800 are simulated. Overall, the proposed Bayesian design leads to a substantially higher power than the flat-prior design. In some of the considered simulation settings, the Bayesian design requires as little as 50% of the flat-prior traditional design's sample size to reach approximately the same power. Moreover, a simulation-based application strategy is proposed and presented with respect to a case-study involving the development of a biomarker-based diagnostic-test for Alzheimer's disease.
- Is Part Of:
- Statistics in biopharmaceutical research. Volume 11:Number 3(2019)
- Journal:
- Statistics in biopharmaceutical research
- Issue:
- Volume 11:Number 3(2019)
- Issue Display:
- Volume 11, Issue 3 (2019)
- Year:
- 2019
- Volume:
- 11
- Issue:
- 3
- Issue Sort Value:
- 2019-0011-0003-0000
- Page Start:
- 311
- Page End:
- 323
- Publication Date:
- 2019-07-03
- Subjects:
- Bayesian hypothesis testing -- Bayesian statistics -- Biomarkers -- Diagnostic index -- Historical priors -- Latent class mixture models -- Validation
Pharmacy -- Statistical methods -- Periodicals
Pharmaceutical biotechnology -- Statistical methods -- Periodicals
Biopharmaceutics -- Periodicals
Biometry -- Periodicals
Pharmacy -- Statistical methods
Periodicals
615.190727 - Journal URLs:
- http://www.tandfonline.com/toc/usbr20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/19466315.2019.1574489 ↗
- Languages:
- English
- ISSNs:
- 1946-6315
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14199.xml