The characteristics of all participants are presented in . The FRAM participants cover a broad age range, a number of races/ethnicities and different HIV-specific risk factors.
Characteristics of the 538 HIV-infected participants
presents the frequency and mean duration of antiretroviral medication use among FRAM participants. Mean duration of treatment among those participants who took a given class of agent was 4.6 years for protease inhibitor, 2.6 years for non-nucleoside reverse transcriptase inhibitors (NNRTIs), and 8.2 years for nucleoside reverse transcriptase inhibitors (NRTIs). Nearly all participants had a history of antiretroviral medication treatment (84% treated with a protease inhibitor, 70% treated with a NNRTI, and 97% treated with a NRTI).
Frequency and mean duration of antiretroviral medication use by HIV-infected participants (n=538)
The posterior probabilities of a variable being selected for a statistical model based on a BMA approach are displayed in . Several traditional risk factors were selected as potential predictors based on a posterior probability of at least 50% (age, race or ethnicity, BP, smoking, and lipid profiles) for at least one cIMT segment (common or internal). The posterior probability of only one HIV-related risk factor exceeded 50%; tenofovir use was inversely associated with common cIMT. All other antiretroviral medications had posterior probabilities far below the 50% selection criterion. When we fit a model substituting the antiretroviral classes for the individual medications, the posterior probabilities for medication classes were all zero for common cIMT. For internal cIMT, only protease inhibitors (1.6%) and NNRTIs (2.5%) had a nonzero posterior probability. Posterior probabilities for the other covariates did not differ appreciably in this alternate model using classes instead of individual agents. None of the inflammatory markers had a posterior probability of greater than 4% in any BMA analysis for either common or internal cIMT.
Posterior probabilities for selection of predictive variables in a model for the association between participant characteristics and increased internal or common carotid intimal–medial thickness using Bayesian model averaging
shows models for both carotid segments containing all variables that had a posterior probability of at least 50% in either segment. There were some noteworthy differences in the estimates of effect for predictive variables between the two cIMT regions (). Smoking, for example, was strongly predictive for internal cIMT but did not appear important for common cIMT. Similarly, BP was strongly predictive for common cIMT but was more weakly associated with internal cIMT in the BMA analysis. Of note, tenofovir was selected for the common carotid with a posterior probability of 51% and was associated with less thick common cIMT. Tenofovir was the only HIV-related factor that was selected for either region of the carotid artery (internal or common). We also observed an inverse association of duration of tenofovir use with internal cIMT (tenofovir association −0.018 mm/year of use) but it did not reach statistical significance, possibly due to the much higher variance in the internal cIMT effect [95% confidence interval (CI) −0.044 to 0.008].
Estimates of the mean difference in common and internal carotid intimal–medial thickness associated with predictors
Tenofovir users were very similar to nonusers with respect to demographic characteristics and most traditional cardiovascular risk factors. However, compared to nonusers, tenofovir users had lower total cholesterol levels (P = 0.04), lower CD4 nadir levels (P < 0.01) and were more likely to have a history of clinical AIDS (P <0.01). There were no statistically significant differences between tenofovir users and nonusers in mean duration of HIV disease (P = 0.10) or in the proportion of participants with a detectable HIV viral load at the follow-up examination (P = 0.92). This low level of confounding by cardiovascular and HIV-related risk factors was supported by noting that the age- and sex-adjusted estimates of the association of tenofovir with common (−0.010 mm/year of use; 95% CI −0.019 to −0.001) and internal (−0.021 mm/year of use; 95% CI −0.046 to −0.0004) cIMT was close to the fully adjusted estimates.
As an additional sensitivity analysis, we added each candidate variable (from ) to the final statistical model for common cIMT () one at a time in order to directly test for any possible confounders that might have been overlooked by our primary modeling strategy. None of the variables, when introduced to the model, resulted in a change of greater than 7% for the point estimate of the association between tenofovir and common cIMT.
We also tested the effect of excluding lipids from the model. In BMA analysis that excluded lipids and diabetes, tenofovir was again selected (posterior probability of 51.2% for common cIMT), whereas no other antiretroviral drug showed greater than 50% posterior probability for internal or common cIMT. All had less than 25% posterior probability. In the multivariable model, excluding lipids and diabetes increased the strength of the association of tenofovir for both common cIMT (ΔcIMT = −0.0100, 95% CI −0.0184 to −0.0017; P = 0.019) and internal cIMT (ΔcIMT =−0.0198, 95% CI −0.0452 to 0.0057; P=0.13).
As an alternative sensitivity analysis, we examined models that defined common and internal cIMT as done in the ARIC study. For common cIMT, only age, African-American race and systolic BP had posterior probabilities greater than 50% (Supplemental Table 1
). For internal cIMT, age, smoking, and systolic BP had posterior probabilities greater than 50%. Multivariable linear regression analysis of ARIC-defined IMT performed as described above showed similar results to our FRAM-defined IMT variables (Supplemental Table 2
For common cIMT, some traditional risk factors were more strongly associated (African-American and smoking), whereas others were not as strongly associated (age, Hispanic, systolic BP, diastolic BP, and HDL) for ARIC-defined cIMT versus FRAM-defined cIMT. The tenofovir association remained protective but lost statistical significance. Likewise, for internal cIMT, results for ARIC-defined cIMT were generally consistent with FRAM-defined cIMT.
In analyses of plaque, as defined by cIMT greater than 1.5 mm, age, smoking and African-American race were selected by BMA (Supplemental Table 1
). In multivariable analysis, age and smoking were associated with plaque, whereas African-American race was protective.