BSU Virtual Seminar: “Estimating treatment effects from adaptive clinical trials”

Add to your list(s) Download to your calendar using vCal

• Prof Ian Marschner, University of Sydney
• Tuesday 14 September 2021, 09:30-10:30
• Virtual Seminar .

If you have a question about this talk, please contact Alison Quenault.

If you would like to join this virtual seminar, please email alison.quenault@mrc-bsu.cam.ac.uk for more information.

Adaptive clinical trials have design features that adapt to the accumulating data, meaning that the design itself is informative about the treatment effect. Consequently, the overall information from an adaptive clinical trial is a combination of information from two sources, the realised design and the observed outcomes. I will present a general framework for the analysis of adaptive clinical trials, based on the decomposition of overall information into design information and outcome information. The framework provides transparent delineation and comparison of unconditional and conditional approaches to treatment effect estimation. Conditional estimation involves conditioning on the observed design so that the treatment effect is interpreted with reference to the particular design that actually occurred. Unconditional estimation involves interpreting the treatment effect with reference to all designs that could possibly have occurred. Unconditional estimation may be more efficient because it uses more information, but it is potentially subject to bias for some designs. Identifying such bias in a given clinical trial is a motivation of the proposed framework and we show that this is most likely to occur when the outcome information and the design information are inconsistent. Thus, we can detect the presence of bias by assessing heterogeneity between the information provided by the design and the information provided by the outcomes. When such heterogeneity is detected, conditional inference may be more appropriate. Various examples will be considered including response-adaptive randomization, multi-stage phase II studies, multi-arm treatment selection and Bayesian adaptive trials.

This talk is part of the MRC Biostatistics Unit Seminars series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• BHRU Annual Lecture 2015
• BHRU Annual Lecture 2016
• Biology
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Immunology
• Cambridge talks
• Cardiovascular Epidemiology Unit Special Seminars
• Chris Davis' list
• Department of Public Health and Primary Care
• Graduate-Seminars
• Interested Talks
• Life Sciences
• Life Sciences
• ME Seminar
• MRC Biostatistics Unit Seminars
• Primary Care
• PublicHealth@Cambridge
• Trust & Technology Initiative - interesting events
• Virtual Seminar
• bld31
• my_list
• ndk22's list
• ob366-ai4er
• other talks
• primary care
• rp587

Note that ex-directory lists are not shown.