METHODS: Analyses were based on patients recruited to the TREAT Asia HIV Observational Database (TAHOD), consisting of 21 sites in 12 countries. Patients on triple antiretroviral therapy (ART) were included if they were alive, without previous CVD, and had data on CVD risk factors. Annual new CVD events for 2019-2028 were estimated with the D:A:D equation, accounting for age- and sex-adjusted mortality. Modelled intervention scenarios were treatment of high total cholesterol, low high-density lipoprotein cholesterol (HDL) or high blood pressure, abacavir or lopinavir substitution, and smoking cessation.
RESULTS: Of 3703 included patients, 69% were male, median age was 46 (IQR 40-53) years, and median time since ART initiation was 9.8 years (IQR 7.5-14.1). Cohort incidence rates of CVD were projected to increase from 730 per 100,000 person-years (pys) in 2019 to 1432 per 100,000 pys in 2028. In the modelled intervention scenarios, most events can be avoided by smoking cessation, abacavir substitution, lopinavir substitution, decreasing total cholesterol, treating high blood pressure, and increasing HDL.
CONCLUSIONS: Our projections suggest a doubling of CVD incidence rates in Asian HIV-positive adults in our cohort. An increase in CVD can be expected in any aging population, however, according to our models, this can be close to averted by interventions. Thus, there is an urgent need for risk screening and integration of HIV and CVD programmes to reduce the future CVD burden.
METHODS: HIV-infected adults enrolled in the TREAT Asia HIV Observational Database were eligible if they had an HIV RNA measurement documented at the time of ART initiation. The dataset was randomly split into a derivation data set (75% of patients) and a validation data set (25%). Factors associated with pre-treatment HIV RNA <100,000 copies/mL were evaluated by logistic regression adjusted for study site. A prediction model and prediction scores were created.
RESULTS: A total of 2592 patients were enrolled for the analysis. Median [interquartile range (IQR)] age was 35.8 (29.9-42.5) years; CD4 count was 147 (50-248) cells/mm3; and pre-treatment HIV RNA was 100,000 (34,045-301,075) copies/mL. Factors associated with pre-treatment HIV RNA <100,000 copies/mL were age <30 years [OR 1.40 vs. 41-50 years; 95% confidence interval (CI) 1.10-1.80, p = 0.01], body mass index >30 kg/m2(OR 2.4 vs. <18.5 kg/m2; 95% CI 1.1-5.1, p = 0.02), anemia (OR 1.70; 95% CI 1.40-2.10, p 350 cells/mm3(OR 3.9 vs. <100 cells/mm3; 95% CI 2.0-4.1, p 2000 cells/mm3(OR 1.7 vs. <1000 cells/mm3; 95% CI 1.3-2.3, p 25 yielded the sensitivity of 46.7%, specificity of 79.1%, positive predictive value of 67.7%, and negative predictive value of 61.2% for prediction of pre-treatment HIV RNA <100,000 copies/mL among derivation patients.
CONCLUSION: A model prediction for pre-treatment HIV RNA <100,000 copies/mL produced an area under the ROC curve of 0.70. A larger sample size for prediction model development as well as for model validation is warranted.