An alternative measure of vaccine effect based on Aalen’s additive survival model framework

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F24%3A00588195" target="_blank" >RIV/67985807:_____/24:00588195 - isvavai.cz</a>

Výsledek na webu

<a href="https://convin.gr/assets/files/misc/ISCB2024Program_AbstractBook.pdf" target="_blank" >https://convin.gr/assets/files/misc/ISCB2024Program_AbstractBook.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

An alternative measure of vaccine effect based on Aalen’s additive survival model framework

Popis výsledku v původním jazyce

ZÁKLADNÍ ÚDAJE: ISCB 45 - Final Programme & Book of Abstracts. Thessaloniki: ISCB, 2024. s. 293-293. [ISCB 2024: Annual Conference of the International Society for Clinical Biostatistics /45./. 21.07.2024-25.07.2024, Thessaloniki]. ABSTRAKT: BACKGROUND: The protective effect of a vaccine is typically evaluated as vaccine efficacy in randomized controlled clinical trials. Efficacy is defined as a proportional reduction in risk of disease among vaccinated subjects relative to a placebo control. Previous work considered immune response biomarker values (immunogenicity) for assessing vaccine efficacy in the context of cross-sectional and time-to-event data, using logistic regression and Cox proportional hazards (PH) or Fine-Gray regression models, respectively. METHODS: In this novel approach, we employ flexible properties of Aalen’s additive survival model framework and define an alternative measure of vaccine effect as “relative survival” (RS) of vaccinated versus control subjects. RS compares estimated probabilities of not contracting the disease in vaccinated and control population. Given time-dependent covariates and/or time-varying effects, this measure can vary with respect to time. It extends well to models involving interactions. In this metric, better survival (here meaning lower risk of disease) among vaccinated subjects leads to an RS value greater than 1. RESULTS: This work studies data on the effect of live attenuated tetravalent dengue vaccine (Dengue Tetravalent Vaccine, Live, CYD-TDV, Sanofi Pasteur, Inc.) on the incidence of DENV2 virologically confirmed dengue disease. We estimate the RS, its standard error and confidence limits based on Aalen’s additive model. The best-fitting Aalen’s additive model involves time-dependent DENV2-specific immunogenicity baseline dengue serostatus, vaccination status, and an interaction between baseline dengue serostatus and vaccination status, in this model the effects of the two categorical predictors and their interaction change over time, while the immunogenicity effect is constant with respect to time. When fitting the main effects model only, the effect of vaccination status and dengue serostatus were insignificant while the protectiv effect appeared to be mediated solely by time-dependent immunogenicity values. When employing the Cox PH model in estimating time-invariant (i.e., averaged) main effects of dengue serostatus, vaccination status and time-dependent immunogenicity, addition of an interaction term resulted in convergence failure. CONCLUSIONS: This work extends the time-to-event data analysis approach to situations where either the assumption of proportional hazards is violated, or the estimation based on the Cox PH multiplicative survival framework fails. Understanding the time-varying effects of vaccination status, immunogenicity and baseline covariates can elucidate persistence (durability) of vaccine-induced protection and its potential heterogeneity. This knowledge is essential to decisions on vaccine recommendations, design of immunization schedules and revaccination strategies

Název v anglickém jazyce

An alternative measure of vaccine effect based on Aalen’s additive survival model framework

Popis výsledku anglicky

ZÁKLADNÍ ÚDAJE: ISCB 45 - Final Programme & Book of Abstracts. Thessaloniki: ISCB, 2024. s. 293-293. [ISCB 2024: Annual Conference of the International Society for Clinical Biostatistics /45./. 21.07.2024-25.07.2024, Thessaloniki]. ABSTRAKT: BACKGROUND: The protective effect of a vaccine is typically evaluated as vaccine efficacy in randomized controlled clinical trials. Efficacy is defined as a proportional reduction in risk of disease among vaccinated subjects relative to a placebo control. Previous work considered immune response biomarker values (immunogenicity) for assessing vaccine efficacy in the context of cross-sectional and time-to-event data, using logistic regression and Cox proportional hazards (PH) or Fine-Gray regression models, respectively. METHODS: In this novel approach, we employ flexible properties of Aalen’s additive survival model framework and define an alternative measure of vaccine effect as “relative survival” (RS) of vaccinated versus control subjects. RS compares estimated probabilities of not contracting the disease in vaccinated and control population. Given time-dependent covariates and/or time-varying effects, this measure can vary with respect to time. It extends well to models involving interactions. In this metric, better survival (here meaning lower risk of disease) among vaccinated subjects leads to an RS value greater than 1. RESULTS: This work studies data on the effect of live attenuated tetravalent dengue vaccine (Dengue Tetravalent Vaccine, Live, CYD-TDV, Sanofi Pasteur, Inc.) on the incidence of DENV2 virologically confirmed dengue disease. We estimate the RS, its standard error and confidence limits based on Aalen’s additive model. The best-fitting Aalen’s additive model involves time-dependent DENV2-specific immunogenicity baseline dengue serostatus, vaccination status, and an interaction between baseline dengue serostatus and vaccination status, in this model the effects of the two categorical predictors and their interaction change over time, while the immunogenicity effect is constant with respect to time. When fitting the main effects model only, the effect of vaccination status and dengue serostatus were insignificant while the protectiv effect appeared to be mediated solely by time-dependent immunogenicity values. When employing the Cox PH model in estimating time-invariant (i.e., averaged) main effects of dengue serostatus, vaccination status and time-dependent immunogenicity, addition of an interaction term resulted in convergence failure. CONCLUSIONS: This work extends the time-to-event data analysis approach to situations where either the assumption of proportional hazards is violated, or the estimation based on the Cox PH multiplicative survival framework fails. Understanding the time-varying effects of vaccination status, immunogenicity and baseline covariates can elucidate persistence (durability) of vaccine-induced protection and its potential heterogeneity. This knowledge is essential to decisions on vaccine recommendations, design of immunization schedules and revaccination strategies

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

30303 - Infectious Diseases

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů