#HIERARCHICAL SEQUENTIAL TESTING TRIAL#

The proposed two-stage monitoring model has an excellent accuracy of detecting and flagging a potential safety signal at stage 1, and with the most important feature that further action at stage 2 could confirm the safety issue. The two-stage Bayesian safety procedure in this paper provides a statistical view to monitor safety during the clinical trials. Operating characteristics describing the performance of this proposed workflow are investigated using simulations based on the different scenarios.

#HIERARCHICAL SEQUENTIAL TESTING TRIAL#

The proposed safety monitoring process starts once 53 subjects have been enrolled into an eight-arm phase II clinical trial for the first interim analysis. ResultsĪny interim safety monitoring analysis is usually scheduled via negotiation between the trial sponsor and the Data and Safety Monitoring Board. At stage 1, a hierarchical blinded model uses blinded safety data to detect a potential safety signal and at stage 2, a hierarchical logistic model is applied to confirm the signal with unblinded safety data. In this paper, two-stage Bayesian hierarchical models are proposed for safety signal detection following a pre-specified set of interim analyses that are applied to efficacy. This paper investigates the potential impact of the process of the blinded investigator identifying a potential safety signal, which should be further investigated by the Data and Safety Monitoring Board with an unblinded safety data analysis.

More recent attention to drug safety has encouraged statistical methods development for monitoring and detecting potential safety signals. Monitoring and reporting of drug safety during a clinical trial is essential to its success.

Hierarchical sequential testing