Related Experiment Video
Updated: Aug 18, 2026

Rapid In Vivo Assessment of Adjuvant's Cytotoxic T Lymphocytes Generation Capabilities for Vaccine Development
Published on: June 19, 2018
Comparison of competing risks failure time methods and time-independent methods for assessing strain variations in
1Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, Massachusetts 02115, USA. pgilbert@hsph.harvard.edu
Abstract:
In a preventive vaccine efficacy trial of a vaccine for a genotypically and phenotypically diverse pathogen, it is important to assess if and how vaccine protection against infection or disease varies with characteristics of the exposing pathogen. Gilbert, Self and Ashby developed statistical methods for this problem when the outcome data are counts of the number of vaccinated and unvaccinated trial participants infected by each pathogen strain. However, in many vaccine trials time-to-case information is available, and the extent to which this information improves investigation of differential vaccine protection is unclear. We describe how cause-specific proportional hazards models and other popular competing risks failure time techniques can be applied to this problem. This includes new results on the assumptions required for these methods to give valid inferences about strain-specific vaccine efficacy, and a comparison of theoretical and finite-sample properties between these methods and the time-independent methods. Theoretical considerations, a cholera vaccine trial example, and an extensive simulation study of a human immunodeficiency virus type 1 (HIV-1) vaccine trial show that information about failure times does not appreciably improve estimation or testing unless the pathogen has a high attack rate and the relative prevalence of pathogen strains shifts substantially during the trial follow-up period. An important implication is that practically optimal evaluation of strain-specific vaccine efficacy in HIV-1 vaccine trials will not require knowledge of infection times.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Relative Risk
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Assumptions of Survival Analysis
Comparing the Survival Analysis of Two or More Groups
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...

