Background
Increasing access to antiretroviral therapy (ART) has ostensibly changed HIV infection in many parts of the world from a fatal diagnosis to a chronic condition requiring lifelong monitoring and treatment. However, this extended life expectancy comes with unique long-term complications. Prior studies, largely from the USA and Europe, have demonstrated that cardiovascular disease (CVD) is a common cause of morbidity and mortality among individuals with HIV, and the second cause of non-AIDS related deaths (1.6 per 1000 person-years) after liver disease [
1,
2]. Causes for the increased CVD risk observed among HIV-infected patients include both traditional risk factors, including aging, higher smoking rates, dyslipidemia, insulin resistance, deposition of body fat; and non-traditional factors, including inflammation, direct effects of HIV on the vasculature, and toxicity from ART [
3,
4].
Several Western studies have demonstrated an increased risk of CVD among HIV-infected patients compared with HIV-negative populations using validated tools such as the Framingham CVD Risk Score (FRS), Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) risk scores and the American College of Cardiology/American Heart Association (ACC/AHA) Atherosclerotic Cardiovascular Disease Risk Score (ASCVD) [
4‐
8]. However, few studies have focused on CVD risk assessment among individuals with HIV in Asia. Two studies from Thailand found the prevalence of predicted cardiovascular risk in HIV-infected Thai patients was relatively low [
9,
10]. In China, the prevalence of risk factors for CVD is high in the general population [
11,
12], and CVD has become the leading cause of morbidity and mortality in recent decades [
13]. No studies to date have assessed the underlying prevalence of CVD risk factors among Chinese individuals with HIV prior to initiation of ART.
To address this gap, we compiled baseline data from two large multicenter studies of individuals with HIV across China from 2009 to 2012, and measured the prevalence of CVD risk factors, 10-year CVD risk, and patterns of CVD risk factor treatment prior to initiation of ART.
Discussion
This is the first multicenter study in China, and one of the largest in Asia, to comprehensively assess CVD risk among adult ART-naïve HIV-infected patients using composite CVD risk scores, and to assess gaps in treatment of key modifiable CVD risk factors. While overall 10-year CVD risk based upon the FRS and D:A:D risk score was low, likely due to the young age of this cohort and comparatively low BMI, we nonetheless found that over 65% of individuals had at least one CVD risk factor, and that few patients with hypertension, diabetes or dyslipidemia were prescribed treatment.
Mortality from CVD has risen dramatically in China over the past two decades and is now the leading cause of death among Chinese men and women [
13]. This is due to increasing prevalence of CVD risk factors (e.g. diabetes, hypertension, and dyslipidemia) driven by aging, dietary change, physical inactivity, increasing BMI, and strikingly high rates of smoking and second hand smoke exposure. Therefore, understanding baseline CVD risk among individuals with HIV in China, and ensuring early intervention for individuals with CVD risk factors is highly important.
For the purposes of this study, we were not able to recruit a comparator group of HIV-negative individuals with similar demographic and HIV risk characteristics. However, data from the general Chinese population provide us with a basis for drawing some comparisons. The China Noncommunicable Disease Surveillance Group carried out a study among a nationally representative sample of over 90,000 Chinese adults over 20 years of age, and found that the prevalence of smoking, overweight and obesity, hypertension, dyslipidemia, and diabetes were 58.16, 36.67, 30.09, 67.43, and 10.61%, respectively, among men; and 3.44, 29.77, 24.79, 63.98, and 8.73%, respectively, among women. [
11]. Another recent study evaluating cardiovascular risk factors among a nationally representative sample of 23,010 Chinese adults aged 18 years and older found the prevalence of smoking, overweight and obesity, hypertension, dyslipidemia, and diabetes were 43.2, 37.2, 27.4, 55.2, and 5.0% respectively among men; and 2.9, 27.6, 21.6, 44.3, and 3.7% respectively among women [
12]. Of note, the former study, which was published in 2012, used slightly different criteria to define these CVD risk factors, but the latter study, published in 2016, utilized the same definitions for CVD risk factors applied in our analysis. Among the treatment-naïve adults with HIV in our study, prevalence of hypertension and overweight/obesity were notably lower that that reported in the general population. This finding likely reflects the catabolic status among our participants in the setting of advanced HIV disease status, as evidenced by the low mean CD4+ T cell count of 229 ± 123 cells/mm
3. However, interestingly, rates of dyslipidemia and diabetes were similar compared to the general population despite the lower mean BMI of this population, perhaps signifying altered lipid and glucose metabolism in the setting of untreated HIV infection. The prevalence of current smoking among patients in our study was lower than found in the two general population studies [
11,
12]. While smoking data was systematically collected for all participants, we cannot exclude the possibility of underreporting of this risk factor.
In terms of other cardiovascular endpoints, our group has previously published echocardiographic data collected in a subgroup of participants from the China AIDS Clinical Trial 0810 [
25]. At baseline, prior to ART initiation, the prevalence of echocardiographic abnormalities, including left ventricular systolic dysfunction and diastolic dysfunction, was significantly higher among 325 ART-naive persons living with HIV compared with 97 age- and sex-matched healthy controls, underscoring again the risk for CVD among individuals with HIV.
The Strategic Timing of Anti-Retroviral Treatment (START) trial, which recruited ART-naïve patients from six continents, found that the proportion of individuals having at least one CVD risk factor varied widely by geographic region (North America:70%; Europe/Australia/Israel: 65.1%; South America:49.4%; Asia: 37%; and Africa: 55.7%) [
10]. Compared to the Asian cohort in the START trial, composed of 154 individuals with HIV from Thailand, participants in our cohort were older [34(28–42) v. 30(24–37) years] and had a notably lower median CD4+ T cell count [235(141–314) v. 604(561–677) cells/mm
3]. While prevalence of hypertension was similar, patients in our cohort had a higher prevalence of diabetes (4.6% v. 1.3%), dyslipidemia (51.7% v. 13.0%) and smoking (23.7% v. 16.9%), but lower prevalence of obesity (1% v. 3.2%).
It is important to note, however, that in the START trial, dyslipidemia was defined by LDL-c ≥ 4.1 mmol/l or use of cholesterol-lowering drugs, which differs from the definition used in our study. Adopting the definition used by the START trial, the prevalence of dyslipidemia in our population decreased to 1.7%, and the prevalence of at least one CVD risk factor decreased from 67.8% to 35%. However, in our cohort, the majority of dyslipidemia was attributable to high TG and low HDL, which is consistent with previous published studies in low- and middle-income countries, including a recent study by Shen et al. focused on prevalence of dyslipidemia among Chinese ART-naïve patients in China [
26‐
30]. This, combined with the significant rate of under-treatment of dyslipidemia in our population, led us to utilize the more comprehensive definition put forth by the NCEP-ATP III Guidelines.
In addition to CVD risk factor prevalence data, our study provides novel information regarding 10-year CVD risk among patients in our cohort. We chose to use the FRS because it has been used widely both internationally and in China to predict CVD risk among HIV-negative patients [
31], and FRS has good predictive accuracy for subclinical carotid atherosclerosis [
32]. The D:A:D risk equations were specifically constructed for use in HIV-infected populations [
4]. Given the younger age of populations with HIV in China (68.4% of patients in our cohort were less than 40 years), the FRS and D:A:D risk equations are more widely applicable compared with tools such as the ACC/AHA ASCVD Risk Score, which applies to individuals ≥40 years of age. The prevalence of patients with 10-year CVD risk ≥10% in our cohort was 4.5% based upon the FRS, which is on par with that reported previously among other studies among Asian (6.5%) and African HIV-positive patients (3.6%) [
10,
33] and lower compared with rates observed among individuals with HIV in Western countries (19.6–21.1%) [
10]. The lower CVD risk in Asia and Africa in the START trial may reflect younger age and lower hypertension and obesity rates for the former, and higher proportion of women and low smoking and dyslipidemia rates in the latter. Consistent with these findings, patients in our study had lower rates of hypertension and obesity, but also more advanced HIV disease contributing to lower overall risk for CVD risk.
Among patients ≥40 years of age, lower overall CVD risk was attributed to the ART-naïve HIV-infected patients using the ASCVD model and the D:A:D risk score compared with the FRS. Prior studies have also suggested that the FRS overestimates CVD risk among individuals with HIV [
34], however other studies have raised concerns about underestimation of CVD risk among individuals with HIV using the FRS as well [
11]. In our cohort, the FRS and ASCVD Risk Scores both identified age and smoking as correlates of 10-year CVD risk ≥10%, which is not surprising given they are factored into the risk models themselves. However after adjusting for traditional risk factors no associations were observed between HIV-related factors and 10-year CVD risk ≥10%, irrespective of the risk algorithm used, similar to previous findings [
35]. The D:A:D CVD Risk Score was developed and validated in a cohort of patients with HIV for the prediction of 5-year CVD risk, however the cohort used to develop the tool was largely European and American, and all patients were on ART. While it has been applied previously to study 10-year CVD risk in both treated and treatment-naïve patients with HIV [
9,
10], the direct applicability of this algorithm to a relatively young treatment-naïve population in a low- and middle-income setting still requires formal validation, and findings should be interpreted with this caveat in mind.
Finally, prior studies from Western countries have highlighted the problem of underdiagnosis and undertreatment of CVD risk factors among ART-naïve HIV-infected patients [
33]. One study from Italy demonstrated approximately 50% patients with HIV meeting criteria for statin therapy were not being treated [
36]. Another study from France found HIV-infected patients treated with statins after acute coronary syndrome had less of an improvement in lipid profiles when compared with HIV-negative controls, in the setting of less potent statins and potential drug-drug interactions with antiretroviral drugs [
37]. De Socio et al. found that one- to two-thirds of hypertensive HIV-infected patients in their study were unaware of their condition, and were not on antihypertensive therapy [
38]. Furthermore, Zanni et al. found that compared with 2004 ATP III guidelines, under the 2013 ACC/AHA guidelines a higher percentage of patients met criteria for statin therapy, however, when patients were evaluated with contrast-enhanced coronary computed tomography angiography, significant discordance was observed between those initiated on statins and those found to have high risk morphology (HRM) coronary plaques. In fact the authors found that 74% of those with subclinical HRM coronary plaque would not be recommended statin therapy based upon the 2013 ACC/AHA guidelines alone [
39]. Therefore, in addition to addressing underdiagnosis and undertreatment of CVD risk factors among individuals with HIV, future studies are also needed to evaluate the appropriateness of applying treatment guidelines developed for the general population to this population.
Few studies, however, have addressed this issue in resource-limited settings. In our cohort, we found significant under-treatment of dyslipidemia, hypertension and diabetes. Approximately 68% of individuals in our study had at least one risk factor for CVD. National clinical guidelines for HIV/AIDS care dictate that blood pressure is measured, and fasting lipid profile and glucose are checked prior to initiation of ART. However, care providers may be less well versed in the nuances of actual management of these primary care issues, particularly thresholds for initiating lipid lowering therapy. Furthermore, smoking cessation should be a cornerstone of primary CVD prevention, but is inadequately addressed in most HIV care settings in China. Further research is necessary to identify the prevention strategies that are most feasible and effective for reducing CVD risk within our population, and should combine both life-style modification strategies with pharmacologic management of hypertension, diabetes, and dyslipidemia [
5,
14]. Although the currently existing CVD risk scores may not have been designed with our population in mind, they nevertheless provide a starting point for care providers to evaluate key CVD risk factors and identify individuals at highest-risk who may need close evaluation and management.
Our study has several limitations. First, our data are cross-sectional and therefore do not provide information regarding longitudinal change in CVD risk over time after initiation of ART, or regarding CVD events. Second, patients with CD4+ cell count ≥500 cells/mm
3 were not enrolled in our study, which may explain why we did not see an association between CD4+ cell count and CVD risk. However, lack of correlation between CD4+ cell count and CVD risk has also been reported by Sabin et al. [
40]. Third, the original studies from which these data are drawn were not designed with CVD risk assessment as their primary endpoints, therefore our analysis focuses on the subset of 973 patients who had complete CVD risk factor data available, which may influence the generalizability of our results. However, there is no known systematic bias influencing collection of risk factor data, and risk factor prevalence in the overall group was similar to that of the subset analyzed. Finally, in our study we did not have data on actual CVD clinical outcomes such as stroke or ischemic heart disease which would have enabled us to assess the ability of the FRS and ASCVD Risk Score to predict CVD in our cohort.