A reflection on the possibility of finding a good surrogate. Issue 3 (4th May 2019)

• Record Type: Journal Article
• Authors: Alonso, Ariel; Meyvisch, Paul; Van der Elst, Wim; Molenberghs, Geert; Verbeke, Geert
• Is Part Of: Journal of biopharmaceutical statistics. Volume 29:Issue 3(2019)
• Page Start: 468
• Page End: 477
• Publication Date: 2019-05-04
• Subjects: Causal inference -- Fano's inequality -- surrogate endpoints; Pharmacy -- Statistical methods -- Periodicals; Drugs -- Testing -- Statistical methods -- Periodicals; Biometry -- Periodicals; Biopharmaceutics -- Periodicals; Pharmacokinetics -- Periodicals; 615.19
• DOI: 10.1080/10543406.2018.1559854
• Languages: English
• ISSNs: 1054-3406

Abstract

ABSTRACT: Surrogate endpoints need to be statistically evaluated before they can be used as substitutes of true endpoints in clinical studies. However, even though several evaluation methods have been introduced over the last decades, the identification of good surrogate endpoints remains practically and conceptually challenging. In the present work, the question regarding the existence of a good surrogate is addressed using information-theoretic concepts, within a causal-inference framework. The methodology can help practitioners to assess, given a clinically relevant true endpoint and a treatment of interest, the chances of finding a good surrogate endpoint in the first place. The methodology focuses on binary outcomes and is illustrated using data from the Initial Glaucoma Treatment Study. Furthermore, a newly developed and user friendly R package Surrogate is provided to carry out the necessary calculations.