Survival analysis and construction of predictive model for HIV/AIDS patients receiving antiviral treatment in Tongchuan City,Shaanxi
Objective To analyze the risk factors for HIV/AIDS mortality after receiving antiviral treatment in Tongchuan City,and to provide a scientific basis for implementing precision treatment in Tongchuan City.Methods A retrospective cohort study was conducted to collect general demographic characteristics and survival-related information of HIV/AIDS individuals who received antiviral treatment in Tongchuan City from 2005 to 2023.Mortality table analysis was used to assess the cumulative survival rate,Cox regression model was used to analyze survival influencing factors,and a nomogram was constructed to predict the prognosis of antiviral treatment.Results A total of 410 HIV/AIDS patients underwent antiviral treatment,with the shortest observation period being 0 months and the longest 222 months,and the median survival time was 71 months(QR:64-106);among the 362 cases followed up,there were 39 AIDS-related deaths.The cumulative survival rates after 1,5,and 10 years of antiretroviral therapy were 96.2%,91.3%,and 83.0%,respectively.Multivariate Cox analysis showed that patients with a higher level of education(college degree or above)(HR=0.349,95%CI:0.159-0.769)and without clinical symptoms(HR=0.357,95%CI:0.178-0.715)had a lower risk of death after antiretroviral treatment,whereas patients with a CD4 cell count＜200 cells/μL group(HR=9.383,95%CI:2.879-30.578)had a higher risk of death.Based on the above three influencing factors,a nomogram model was constructed.Internal validation showed that the model's discriminative ability with a C-index of 0.859(95%CI:0.762-0.956),and the calibration curve indicated good consistency,demonstrating the model's good predictive ability.Conclusions Tongchuan City should expand health education on AIDS prevention and control,strengthen HIV monitoring,carry out education on compliance with antiviral treatment among HIV/AIDS individuals,conduct timely CD4 cell count detection,and use the constructed nomogram model to assist in precise diagnosis and treatment in clinical practice.
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