Zobraziť v EDS

Establishment and evaluation of a predictive model for immune reconstitution in people living with HIV after antiretroviral therapy.

Uložené v:
Podrobná bibliografia
Názov: Establishment and evaluation of a predictive model for immune reconstitution in people living with HIV after antiretroviral therapy.
Autori: Li, Na, Li, Rui, Zheng, Hong-Yi, He, Wen-Qiang, Duan, Ru-Fei, Li, Xia, Tian, Ren-Rong, Li, Hui-Qin, Dong, Xing-Qi, Shen, Zhi-Qiang, Zheng, Yong-Tang
Zdroj: BMC Infectious Diseases; 2/24/2025, Vol. 25 Issue 1, p1-13, 13p
Predmety: AIDS, HIV, RECEIVER operating characteristic curves, HIV-positive persons, DECISION making
Abstrakt: Background: Achieving complete immune reconstitution (CIR) in people living with human immunodeficiency virus (PLWH) following antiretroviral therapy (ART) is essential for preventing acquired immunodeficiency syndrome (AIDS) progression and improving survival. However, there is a paucity of robust prediction models for determining the likelihood of CIR in PLWH after ART. We aimed to develop and validate a CIR prediction model utilizing baseline data. Methods: Baseline data including demographic information, immunological profiles, and routine laboratory test results, were collected from PLWH in Yunnan, China. Baseline referred to the first recorded results after HIV diagnosis but before initiating ART, and these initial measurements served as the baseline data for analysis. The participants were divided into training and validation sets (7:3 ratio). To construct the model and accompanying nomogram, univariable and multivariable Cox regression analyses were performed. The model was evaluated using the C-index, time-dependent receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curves to assess discrimination, calibration, and clinical applicability. Results: Five thousand four hundred eight PLWH were included, with a CIR of 38.52%. Cox regression analysis revealed various independent factors associated with CIR, including infection route, baseline CD4+T cell count, baseline CD4/CD8 ratio, interval from HIV diagnosis to ART initiation, and the level of PLT, Glu, Crea, HGB, ALT. A nomogram was formulated to predict the probability of achieving CIR at years 4, 5, and 6. The model demonstrated good performance, as evidenced by an AUC of 0.8 for both sets. Calibration curve analysis demonstrated a high level of agreement, and decision curve analysis revealed a significant positive yield. Conclusions: This study successfully developed a prediction model with robust performance. This model has considerable potential to aid clinicians in tailoring treatment strategies, which could enhance outcomes and quality of life for PLWH. [ABSTRACT FROM AUTHOR]
Copyright of BMC Infectious Diseases is the property of BioMed Central and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáza: Complementary Index
Popis
Abstrakt:Background: Achieving complete immune reconstitution (CIR) in people living with human immunodeficiency virus (PLWH) following antiretroviral therapy (ART) is essential for preventing acquired immunodeficiency syndrome (AIDS) progression and improving survival. However, there is a paucity of robust prediction models for determining the likelihood of CIR in PLWH after ART. We aimed to develop and validate a CIR prediction model utilizing baseline data. Methods: Baseline data including demographic information, immunological profiles, and routine laboratory test results, were collected from PLWH in Yunnan, China. Baseline referred to the first recorded results after HIV diagnosis but before initiating ART, and these initial measurements served as the baseline data for analysis. The participants were divided into training and validation sets (7:3 ratio). To construct the model and accompanying nomogram, univariable and multivariable Cox regression analyses were performed. The model was evaluated using the C-index, time-dependent receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curves to assess discrimination, calibration, and clinical applicability. Results: Five thousand four hundred eight PLWH were included, with a CIR of 38.52%. Cox regression analysis revealed various independent factors associated with CIR, including infection route, baseline CD4<sup>+</sup>T cell count, baseline CD4/CD8 ratio, interval from HIV diagnosis to ART initiation, and the level of PLT, Glu, Crea, HGB, ALT. A nomogram was formulated to predict the probability of achieving CIR at years 4, 5, and 6. The model demonstrated good performance, as evidenced by an AUC of 0.8 for both sets. Calibration curve analysis demonstrated a high level of agreement, and decision curve analysis revealed a significant positive yield. Conclusions: This study successfully developed a prediction model with robust performance. This model has considerable potential to aid clinicians in tailoring treatment strategies, which could enhance outcomes and quality of life for PLWH. [ABSTRACT FROM AUTHOR]
ISSN:14712334
DOI:10.1186/s12879-025-10673-4