Bayesian Evaluation of Time-To-Event and Reliability (for vaccine surveillance) (BETTER)

Study identification

• EU PAS number:
  EUPAS48616
• Study ID:
  48617
• Official title and acronym:
  Bayesian Evaluation of Time-To-Event and Reliability (for vaccine surveillance) (BETTER)
• DARWIN EU® study:
  No
• Study countries:
  United States
• Study description:
  As various approved COVID-19 vaccines are rolled out globally, safety signals have been identified from spontaneous reports and other data sources. The current standard method of safety surveillance adopted by the FDA is MaxSPRT, which suffers from the inflexibility of a pre-specified sequential analysis schedule. We hope to develop and implement a more flexible Bayesian surveillance framework and compare its performance with MaxSPRT in real-world data. To compare the real-data performance (testing errors, timeliness, precision and bias) of Bayesian and frequentist sequential analysis methods for the study of comparative vaccine safety. We will also produce a reference table of Type I and II error rates and signal detection times for all combinations of design and threshold choices, as exploration of the operating characteristics of Bayesian sequential methods.
• Study status:
  Ongoing

Research institutions and networks

Institutions

Observational Health Data Sciences and Informatics (OHDSI)

Networks

Observational Health Data Sciences and Informatics (OHDSI) Network

Study timelines

Date when funding contract was signed

Actual:28/08/2021

Study start date

Actual:01/01/2022

Data analysis start date

Actual:01/02/2022

Date of final study report

Planned:30/09/2022

Sources of funding

Pharmaceutical company and other private sector 

Other

More details on funding

Johnson & Johnson, US Food & Drug Administration, US Department of Veterans Affairs, US National Institutes of Health

Regulatory

• Was the study required by a regulatory body?:
  Yes
• Is the study required by a Risk Management Plan (RMP)?:
  Not applicable