Bayesian multi-response nonlinear mixed-effect model: application of two recent HIV infection biomarkers.
Int J Biostat
; 18(2): 455-471, 2022 11 01.
Article
em En
| MEDLINE
| ID: mdl-34391216
ABSTRACT
Since the discovery of the human immunodeficiency virus (HIV) 35 years ago, the epidemic is still ongoing in France. To monitor the dynamics of HIV transmission and assess the impact of prevention campaigns, the main indicator is the incidence. One method to estimate the HIV incidence is based on biomarker values at diagnosis and their dynamics over time. Estimating the HIV incidence from biomarkers first requires modeling their dynamics since infection using external longitudinal data. The objective of the work presented here is to estimate the joint dynamics of two biomarkers from the PRIMO cohort. We thus jointly modeled the dynamics of two biomarkers (TM and V3) using a multi-response nonlinear mixed-effect model. The parameters were estimated using Bayesian Hamiltonian Monte Carlo inference. This procedure was first applied to the real data of the PRIMO cohort. In a simulation study, we then evaluated the performance of the Bayesian procedure for estimating the parameters of multi-response nonlinear mixed-effect models.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Infecções por HIV
Tipo de estudo:
Diagnostic_studies
/
Health_economic_evaluation
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article