September 2022 Sensitivity analysis for evaluating principal surrogate endpoints relaxing the equal early clinical risk assumption
Ying Huang, Yingying Zhuang, Peter Gilbert
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Ann. Appl. Stat. 16(3): 1774-1794 (September 2022). DOI: 10.1214/21-AOAS1566


This article addresses the evaluation of postrandomization immune response biomarkers as principal surrogate endpoints of a vaccine’s protective effect, based on data from randomized vaccine trials. An important metric for quantifying a biomarker’s principal surrogacy in vaccine research is the vaccine efficacy curve, which shows a vaccine’s efficacy as a function of potential biomarker values if receiving vaccine, among an “early-always-at-risk” principal stratum of trial participants who remain disease-free at the time of biomarker measurement whether having received vaccine or placebo. Earlier work in principal surrogate evaluation relied on an “equal-early-clinical-risk” assumption for identifiability of the vaccine curve, based on observed disease status at the time of biomarker measurement. This assumption is violated in the common setting that the vaccine has an early effect on the clinical endpoint before the biomarker is measured. In particular, a vaccine’s early protective effect observed in two phase III dengue vaccine trials (CYD14/CYD15) has motivated our current research development. We relax the “equal-early-clinical-risk” assumption and propose a new sensitivity analysis framework for principal surrogate evaluation allowing for early vaccine efficacy. Under this framework we develop inference procedures for vaccine efficacy curve estimators, based on the estimated maximum likelihood approach. We then use the proposed methodology to assess the surrogacy of postrandomization neutralization titer in the motivating dengue application.


The authors thank the participants, investigators, and sponsors of the CYD14 and CYD15 trials. Research reported in this publication was supported by Sanofi Pasteur and NIH awards R37 AI054165 and R01 GM106177. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or Sanofi Pasteur.


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Ying Huang. Yingying Zhuang. Peter Gilbert. "Sensitivity analysis for evaluating principal surrogate endpoints relaxing the equal early clinical risk assumption." Ann. Appl. Stat. 16 (3) 1774 - 1794, September 2022.


Received: 1 November 2020; Revised: 1 October 2021; Published: September 2022
First available in Project Euclid: 19 July 2022

MathSciNet: MR4455899
zbMATH: 1498.62222
Digital Object Identifier: 10.1214/21-AOAS1566

Keywords: Causal inference , estimated maximum likelihood , Principal stratification , principal surrogate , sensitivity analysis , vaccine efficacy curve

Rights: Copyright © 2022 Institute of Mathematical Statistics


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Vol.16 • No. 3 • September 2022
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