NDLI: Causal Measures of the Treatment Effect Captured by Candidate Surrogate Endpoints

Content Provider	Springer Nature Link
Author	Kobayashi, Fumiaki Kuroki, Manabu
Copyright Year	2015
Abstract	In randomized clinical trials, true clinical endpoints that are rare or difficult to measure can be costly and time consuming. Therefore, there is an increasing need to substitute true clinical endpoints with surrogate endpoints. However, candidate surrogate endpoints require appropriate validation. To evaluate the extent of a treatment effect (TE) captured by candidate surrogate endpoints, various surrogacy measures have been proposed by biostatisticians and medical professionals. Although many researchers stated that it is desirable that surrogacy measures should take values between zero to one, those often fall outside a range [0, 1] without suitable assumptions. To overcome this problem, we propose two types of surrogacy measures based on the causal association (CA) paradigm and the causal effect (CE) paradigm. These operate by decomposing the TE into those parts that are and are not captured by candidate surrogate endpoints. The surrogacy measures based on the CA paradigm mainly consider how much of the TE of the treatment on the true clinical endpoint can be predicted through the TE on the candidate surrogate endpoints, while the surrogacy measures based on the CE paradigm are concerned with how much of the TE on the true clinical endpoint is a result of the candidate surrogate endpoints. In addition, we demonstrate some properties of the proposed surrogacy measures, and show that they always fall inside the range [0, 1]. Furthermore, they can be considered as improved and extended versions of existing surrogacy measures. Based on simulation experiments and applications of the proposed surrogacy measures to a case study of the Olmesartan Reducing Incidence of End-stage Renal Disease in Diabetic Nephropathy Trial, we show that the proposed surrogacy measures solve the problems encountered by the existing surrogacy measures. This paper presents new quantitative surrogacy measures that reliably evaluate the proportion of the TE captured by candidate surrogate endpoints.Supplementary materials accompanying this paper appear online.
Starting Page	409
Ending Page	430
Page Count	22
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	20
Issue Number	3
e-ISSN	15372693
Language	English
Publisher	Springer US
Publisher Date	2015-08-27
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Mediation proportion Potential outcome approach Proportion indirect Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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