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Construction and validation of a prognostic nomogram for predicting the survival of HIV/AIDS adults who received antiretroviral therapy: a cohort between 2003 and 2019 in Nanjing

BACKGROUND: Great achievements have been achieved by free antiretroviral therapy (ART). A rapid and accurate prediction of survival in people living with HIV/AIDS (PLHIV) is needed for effective management. We aimed to establish an effective prognostic model to forecast the survival of PLHIV after A...

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Detalles Bibliográficos
Autores principales: Jiang, Fangfang, Xu, Yuanyuan, Liu, Li, Wang, Kai, Wang, Lu, Fu, Gengfeng, Wang, Liping, Li, Zhongjie, Xu, Junjie, Xing, Hui, Wang, Ning, Zhu, Zhengping, Peng, Zhihang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740442/
https://www.ncbi.nlm.nih.gov/pubmed/34991536
http://dx.doi.org/10.1186/s12889-021-12249-8
Descripción
Sumario:BACKGROUND: Great achievements have been achieved by free antiretroviral therapy (ART). A rapid and accurate prediction of survival in people living with HIV/AIDS (PLHIV) is needed for effective management. We aimed to establish an effective prognostic model to forecast the survival of PLHIV after ART. METHODS: The participants were enrolled from a follow-up cohort over 2003-2019 in Nanjing AIDS Prevention and Control Information System. A nested case-control study was employed with HIV-related death, and a propensity-score matching (PSM) approach was applied in a ratio of 1:4 to allocate the patients. Univariable and multivariable Cox proportional hazards analyses were performed based on the training set to determine the risk factors. The discrimination was qualified using the area under the curve (AUC) and concordance index (C-Index). The nomogram was calibrated using the calibration curve. The clinical benefit of prognostic nomogram was assessed by decision curve analysis (DCA). RESULTS: Predictive factors including CD4 cell count (CD4), body mass index (BMI) and hemoglobin (HB) were determined and incorporated into the nomogram. In the training set, AUC and C-index (95% CI) were 0.831 and 0.798 (0.758, 0.839), respectively. The validation set revealed a good discrimination with an AUC of 0.802 and a C-index (95% CI) of 0.786 (0.681, 0.892). The calibration curve also exhibited a high consistency in the predictive power (especially in the first 3 years after ART initiation) of the nomogram. Moreover, DCA demonstrated that the nomogram was clinically beneficial. CONCLUSION: The nomogram is effective and accurate in forecasting the survival of PLHIV, and beneficial for medical workers in health administration. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-12249-8.