Statistical Methods to Evaluate Surrogate Markers.
Journal
Medical care
ISSN: 1537-1948
Titre abrégé: Med Care
Pays: United States
ID NLM: 0230027
Informations de publication
Date de publication:
11 Dec 2023
11 Dec 2023
Historique:
medline:
11
12
2023
pubmed:
11
12
2023
entrez:
11
12
2023
Statut:
aheadofprint
Résumé
There is tremendous interest in evaluating surrogate markers given their potential to decrease study time, costs, and patient burden. The purpose of this statistical workshop article is to describe and illustrate how to evaluate a surrogate marker of interest using the proportion of treatment effect (PTE) explained as a measure of the quality of the surrogate marker for (1) a setting with a general fully observed primary outcome (eg, biopsy score) and (2) a setting with a time-to-event primary outcome which may be censored due to study termination or early drop out (eg, time to diabetes). The methods are motivated by 2 randomized trials, one among children with nonalcoholic fatty liver disease where the primary outcome was a change in biopsy score (general outcome) and another study among adults at high risk for Type 2 diabetes where the primary outcome was time to diabetes (time-to-event outcome). The methods are illustrated using the Rsurrogate package with a detailed R code provided. In the biopsy score outcome setting, the estimated PTE of the examined surrogate marker was 0.182 (95% confidence interval [CI]: 0.121, 0.240), that is, the surrogate explained only 18.2% of the treatment effect on the biopsy score. In the diabetes setting, the estimated PTE of the surrogate marker was 0.596 (95% CI: 0.404, 0.760), that is, the surrogate explained 59.6% of the treatment effect on diabetes incidence. This statistical workshop provides tools that will support future researchers in the evaluation of surrogate markers.
Sections du résumé
BACKGROUND
BACKGROUND
There is tremendous interest in evaluating surrogate markers given their potential to decrease study time, costs, and patient burden.
OBJECTIVES
OBJECTIVE
The purpose of this statistical workshop article is to describe and illustrate how to evaluate a surrogate marker of interest using the proportion of treatment effect (PTE) explained as a measure of the quality of the surrogate marker for (1) a setting with a general fully observed primary outcome (eg, biopsy score) and (2) a setting with a time-to-event primary outcome which may be censored due to study termination or early drop out (eg, time to diabetes).
METHODS
METHODS
The methods are motivated by 2 randomized trials, one among children with nonalcoholic fatty liver disease where the primary outcome was a change in biopsy score (general outcome) and another study among adults at high risk for Type 2 diabetes where the primary outcome was time to diabetes (time-to-event outcome). The methods are illustrated using the Rsurrogate package with a detailed R code provided.
RESULTS
RESULTS
In the biopsy score outcome setting, the estimated PTE of the examined surrogate marker was 0.182 (95% confidence interval [CI]: 0.121, 0.240), that is, the surrogate explained only 18.2% of the treatment effect on the biopsy score. In the diabetes setting, the estimated PTE of the surrogate marker was 0.596 (95% CI: 0.404, 0.760), that is, the surrogate explained 59.6% of the treatment effect on diabetes incidence.
CONCLUSIONS
CONCLUSIONS
This statistical workshop provides tools that will support future researchers in the evaluation of surrogate markers.
Identifiants
pubmed: 38079232
doi: 10.1097/MLR.0000000000001956
pii: 00005650-990000000-00191
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
The authors have no conflicts of interest to disclose.
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