Xin Li

Ms. Xin Li

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 January 2022 in BMC Public Health
Verified
Journal Article
Open access
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FJFangfang Jiang
Fangfang Jiang
YXYuanyuan Xu
Yuanyuan Xu
XLXin Li
Xin Li
KWKai Wang
Kai Wang
LWLu Wang
Lu Wang
ZPZhihang Peng
Zhihang Peng
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.