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Activity Number: 9 - Impact of Using Surrogate Endpoints on Drug Development
Type: Invited
Date/Time: Sunday, July 28, 2019 : 2:00 PM to 3:50 PM
Sponsor: WNAR
Abstract #300444 Presentation
Title: An Information-Theoretic Approach for the Evaluation of Surrogate Endpoints Based on Causal Inference
Author(s): Ariel Alonso Abad*
Companies: KUleuven
Keywords: Causal inference; Information theory; Surrogate endpoints

In this work a new metric of surrogacy, the so-called individual causal association (ICA), is introduced using information-theoretic concepts and a causal inference model for a binary surrogate and true endpoint. The ICA has a simple and appealing interpretation in terms of uncertainty reduction and, in some scenarios, it seems to provide a more coherent assessment of the validity of a surrogate than existing measures. The identifiability issues are tackled using a two-step procedure. In the first step, the region of the parametric space of the distribution of the potential outcomes, compatible with the data at hand, is geometrically characterized. Further, in a second step, a Monte Carlo approach is proposed to study the behavior of the ICA on the previous region. The method is illustrated using data from the Collaborative Initial Glaucoma Treatment Study.

Authors who are presenting talks have a * after their name.

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