Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/30157
Title: A reflection on the causal interpretation of individual-level surrogacy
Authors: ALONSO ABAD, Ariel 
VAN DER ELST, Wim 
MOLENBERGHS, Geert 
Florez, Alvaro J.
Issue Date: 2019
Publisher: TAYLOR & FRANCIS INC
Source: JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 29(3), p. 529-540
Abstract: At the beginning of the 21st century, a new paradigm was introduced for the evaluation of surrogate endpoints based on meta-analysis. In this paradigm, the putative surrogate is assessed at two different levels, the so-called, trial and individual level. Trial level surrogacy is defined as the association between the expected causal treatment effects across different trials populations, whereas the individual level is defined as the association between the surrogate and true endpoints, after adjusting by trial and treatment. It has been argued that the individual level surrogacy does not have a causal interpretation and, consequently, it is a poor metric of surrogacy. In the present work, an alternative definition of individual level surrogacy is introduced based on individual causal treatment effects. In addition, using the maximum entropy principle, a direct link between the individual level surrogacy, as defined in the meta-analytic approach, and the newly proposed definition is established. This new perspective sets the individual level surrogacy in a more coherent framework with respect to the trial level and bridges the two main schools of thought in this domain, namely, the causal inference and meta-analytic schools.
Notes: [Alonso, Ariel; Florez, Alvaro J.] Katholieke Univ Leuven, I BioStat, Kapucijnenvoer 35, B-3000 Leuven, Belgium. [Van der Elst, Wim] Janssen Pharmaceut Co Johnson & Johnson, Quantitat Sci, Beerse, Belgium. [Molenberghs, Geert] Univ Hasselt, I BioStat, Diepenbeek, Belgium.
Keywords: Causal inference;meta-analytic approach;maximum entropy;surrogate endpoints
Document URI: http://hdl.handle.net/1942/30157
ISSN: 1054-3406
e-ISSN: 1520-5711
DOI: 10.1080/10543406.2019.1579221
ISI #: 000469139500009
Category: A1
Type: Journal Contribution
Validations: ecoom 2020
Appears in Collections:Research publications

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