Welcome to the Bayesian Statistical Science Section

The Bayesian Statistical Science Section of the ASA provides a forum for statisticians and people who have interest in the Bayesian paradigm. The broad objectives of the Section are: to encourage research on theory and methods of statistical inference and decisionmaking associated with Bayes' theorem and to encourage the application and proper use of Bayesian procedures in the behavioral, biological, managerial, engineering, environmental, legal, medical, pharmaceutical, physical, and social sciences.



Current Affairs 

Upcoming Web-Based Lectures


Title: Modeling and Simulation Approach to Optimize the Assessment of the Potential for QT Prolongation
Presenter: Daniel Weiner, SrVP & GM, Certara
Date and Time: Thursday, September 18, 2014, 12:00 p.m. - 2:00 p.m. Eastern time
Sponsor: Biopharmaceutical Section

Registration Deadline: Tuesday, September 16, at 12:00 p.m. Eastern time

Description:
Regulatory authorities require that all drugs be assessed for the potential for drug-induced QT interval prolongation, which is a biomarker for Torsades de Pointes, which can sometimes result in sudden death. Since 1988, there have been at least 14 drugs withdrawn from market as a result of QT prolongation (Stockbridge et al. Drug Safety 2013;36: 167-182). There are currently two Regulatory Requirements regarding this safety assessment: ICH E14 and S7B, which cover clinical and nonclinical evaluations, respectively.

The main topics of this webinar are
1) Review of the E14 Guidance and the concept of a Thorough QT (TQT) Study, including a discussion of how such studies should be analyzed
2) Discussion of what data to collect, on an ongoing basis, to assess the potential for QT prolongation
3) Discuss methods to determine if there is an emerging signal regarding the relationship between drug exposure and QT prolongation, and how to use that information for dose selection in the TQT and other subsequent clinical trials

Concepts will be illustrated with case studies. 

*** More information and registration at the webinar page.



Title: Coordinating Collection, Analysis and Submission of Clinical Trials Data with Metadata Standards - Focus on Tabulations Deliverables (Part 1 of 2)
Presenter: Steve Kirby, Mario Widel and Luke Reinbolt
Date and Time: Tuesday, October 21, 2014, 12 p.m. - 1:30 p.m. Eastern time
Sponsor: Section for Statistical Programmers and Analysts

Registration Deadline: Friday, October 17, at 12:00 p.m. Eastern time

Description:
Starting with a diagram that links key submission deliverables and associated metadata, the authors will share how companies can plan to have key content needed to support study planning and generation of CDISC data, TFLs and associated documentation available as metadata and will discuss how that metadata can support operational efficiency and a transparent, traceable path from study planning to regulatory submission.

For each deliverable, the authors will explore the use case for a metadata driven approach, share a specific, concrete process example and investigate how the content is related to other aspects of the clinical trials process.

Part 1 will focus on tabulations deliverables and associated metadata. Analysis metadata will be included as needed to ensure that the tabulations content will support analysis objectives and study endpoints. Key content areas will be: Protocol/SAP metadata and SDTM Trial Design domains; and SDTM metadata, SDTM mapping code and associated submission documentation (blankcrf.pdf, define.xml, Reviewer's Guide).

*** More information and registration at the webinar page.




Title: Design and Analysis of Biomarkers Studies for Risk Prediction
Presenter: Tianxi Cai, Department of Biostatistics, Harvard School of Public Health
Date and Time: Wednesday, October 22, 2014, 12:00 p.m. - 2:00 p.m. Eastern time
Sponsor: Biopharmaceutical Section

Registration Deadline: Monday, October 20, at 12:00 p.m. Eastern time

Description:
An accurate and individualized outcome prediction promises to dramatically change clinical decision making in many branches of medicine, for example in early diagnosis of cancer and in selecting patient-specific treatments. But translating the promise into reality is not easy. Clinical evaluations, while remaining an essential basis for risk assessment, may not be sufficient for complex diseases. Improved prediction may be achieved by combining information from multiple markers based on emerging new technology such as gene expression profiling, protein mass spectrometry and proton emission tomography. Most marker tests are imperfect, and incorporate test results can have enormous consequences in both financial and human terms. Prior to incorporating a biomarker into standard clinical care, rigorous evaluation is required. Designing an rigorous study that efficiently uses available biologic specimens is critical. Compared to classical statistical methods for evaluating medical diagnostic test, there is relatively little literature devoted to statistical methods for marker development carried out in a prospective cohort study with censored failure time outcome. This webinar will introduce recent statistical development for constructing and evaluating risk prediction model (markers) with censored data. While providing some mathematical details, we will emphasize the concepts, methods and their real world applications with the aim of both offering an overview of the rapid developing area of risk prediction and biomarker evaluation; and discussions on efficient design of biomarker and risk prediction studies.

*** More information and registration at the webinar page.



 

From the SBSS Mixer at JSM 2013