Semi-blinded design in clinical trials

Shu-Mei Wan, Narayanaswamy Balakrishnan, Monica Mayeni Manurung, Kwang-Hwa Chang and Chien-Hua Wu

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 20, 7165-7183

Abstract: The semi-blinded design can be applied for the adaptive design in clinical trials. According the the FDA guidance, an adaptive clinical design study would modify the study design and hypotheses based on the analysis of accrued data. An independent Data Monitoring Committee analyzes the unblinded data in the middle of a clinical trial and makes recommendations to the sponsor if any action is needed. The unblinded interim analysis could potentially introduce bias and put the integrity of the trial at risk. The proposed methodology is technically blinded for the interim analysis. In fact, actual treatment labels are not released. It is based on a treatment re-labeling approach in which the dummy treatments associated with the actual treatments via a pre-specified transition probability matrix are released in the dataset. The semi-blinded test statistic depends on this transition probability matrix. However, it can be evaluated without knowing the transition probability matrix if this matrix is a Latin square. As the stagnation probability approach to 0.5, the more information we will lose. It will lead to obtain a lower power of testing hypothesis, and may not be able to show the utility or efficacy of study treatment if this probability is close to 0.5. The higher the stagnation probability, the higher disclosure risk we have. The randomization codes may be broken as the stagnation probability approach to 1. The sponsor should strike a balance between the statistical power and disclosure risk.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2022.2042024 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:52:y:2023:i:20:p:7165-7183

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2022.2042024

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().