Statistical learning methods to determine immune correlates of herpes zoster in vaccine efficacy trials
PB Gilbert, AR Luedtke - The Journal of Infectious Diseases, 2018 - academic.oup.com
The Journal of Infectious Diseases, 2018•academic.oup.com
Abstract Using Super Learner, a machine learning statistical method, we assessed varicella
zoster virus-specific glycoprotein-based enzyme-linked immunosorbent assay (gpELISA)
antibody titer as an individual-level signature of herpes zoster (HZ) risk in the Zostavax
Efficacy and Safety Trial. Gender and pre-and postvaccination gpELISA titers had moderate
ability to predict whether a 50–59 year old experienced HZ over 1–2 years of follow-up, with
equal classification accuracy (cross-validated area under the receiver operator curve= 0.65) …
zoster virus-specific glycoprotein-based enzyme-linked immunosorbent assay (gpELISA)
antibody titer as an individual-level signature of herpes zoster (HZ) risk in the Zostavax
Efficacy and Safety Trial. Gender and pre-and postvaccination gpELISA titers had moderate
ability to predict whether a 50–59 year old experienced HZ over 1–2 years of follow-up, with
equal classification accuracy (cross-validated area under the receiver operator curve= 0.65) …
Abstract
Using Super Learner, a machine learning statistical method, we assessed varicella zoster virus-specific glycoprotein-based enzyme-linked immunosorbent assay (gpELISA) antibody titer as an individual-level signature of herpes zoster (HZ) risk in the Zostavax Efficacy and Safety Trial. Gender and pre- and postvaccination gpELISA titers had moderate ability to predict whether a 50–59 year old experienced HZ over 1–2 years of follow-up, with equal classification accuracy (cross-validated area under the receiver operator curve = 0.65) for vaccine and placebo recipients. Previous analyses suggested that fold-rise gpELISA titer is a statistical correlate of protection and supported the hypothesis that it is not a mechanistic correlate of protection. Our results also support this hypothesis.
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