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Changes in Cardiovascular Disease Risk Factors With Immediate Versus Deferred Antiretroviral Therapy Initiation Among HIV‐Positive Participants in the START (Strategic Timing of Antiretroviral Treatment) Trial


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Introduction HIV infection and certain antiretroviral therapy (ART) medications increase atherosclerotic cardiovascular disease risk, mediated, in part, through traditional cardiovascular disease risk factors. Methods and Results We studied cardiovascular disease risk factor changes in the START (Strategic Timing of Antiretroviral Treatment) trial, a randomized study of immediate versus deferred ART initiation among HIV‐positive persons with CD4+ cell counts >500 cells/mm3. Mean change from baseline in risk factors and the incidence of comorbid conditions were compared between groups. The characteristics among 4685 HIV‐positive START trial participants include a median age of 36 years, a CD4 cell count of 651 cells/mm3, an HIV viral load of 12 759 copies/mL, a current smoking status of 32%, a median systolic/diastolic blood pressure of 120/76 mm Hg, and median levels of total cholesterol of 168 mg/dL, low‐density lipoprotein cholesterol of 102 mg/dL, and high‐density lipoprotein cholesterol of 41 mg/dL. Mean follow‐up was 3.0 years. The immediate and deferred ART groups spent 94% and 28% of follow‐up time taking ART, respectively. Compared with patients in the deferral group, patients in the immediate ART group had increased total cholesterol and low‐density lipoprotein cholesterol and higher use of lipid‐lowering therapy (1.2%; 95% CI, 0.1–2.2). Concurrent increases in high‐density lipoprotein cholesterol with immediate ART resulted in a 0.1 lower total cholesterol to high‐density lipoprotein cholesterol ratio (95% CI, 0.1–0.2). Immediate ART resulted in 2.3% less BP‐lowering therapy use (95% CI, 0.9–3.6), but there were no differences in new‐onset hypertension or diabetes mellitus. Conclusions Among HIV‐positive persons with preserved immunity, immediate ART led to increases in total cholesterol and low‐density lipoprotein cholesterol but also concurrent increases in high‐density lipoprotein cholesterol and decreased use of blood pressure medications. These opposing effects suggest that, in the short term, the net effect of early ART on traditional cardiovascular disease risk factors may be clinically insignificant."
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Changes in Cardiovascular Disease Risk Factors With Immediate
Versus Deferred Antiretroviral Therapy Initiation Among HIV-Positive
Participants in the START (Strategic Timing of Antiretroviral
Treatment) Trial
Jason V. Baker, MD, MS; Shweta Sharma, MS; Amit C. Achhra, MD, PhD, MPH; Jose Ignacio Bernardino, MD; Johannes R. Bogner, MD;
Daniel Duprez, MD, PhD; Sean Emery, PhD; Brian Gazzard, MD; Jonathan Gordin, MD; Greg Grandits, MS; Andrew N. Phillips, PhD; Siegfried
Schwarze, Dipl Bio; Elsayed Z. Soliman, MD, PhD; Stephen A. Spector, MD; Giuseppe Tambussi, MD; Jens Lundgren, MD for the INSIGHT
(International Network for Strategic Initiatives in Global HIV Trials) START (Strategic Timing of Antiretroviral Treatment) Study Group*
Introduction-HIV infection and certain antiretroviral therapy (ART) medications increase atherosclerotic cardiovascular disease
risk, mediated, in part, through traditional cardiovascular disease risk factors.
Methods and Results-We studied cardiovascular disease risk factor changes in the START (Strategic Timing of Antiretroviral
Treatment) trial, a randomized study of immediate versus deferred ART initiation among HIV-positive persons with CD4
cell counts
>500 cells/mm
. Mean change from baseline in risk factors and the incidence of comorbid conditions were compared between
groups. The characteristics among 4685 HIV-positive START trial participants include a median age of 36 years, a CD4 cell count of
651 cells/mm
, an HIV viral load of 12 759 copies/mL, a current smoking status of 32%, a median systolic/diastolic blood
pressure of 120/76 mm Hg, and median levels of total cholesterol of 168 mg/dL, low-density lipoprotein cholesterol of 102 mg/
dL, and high-density lipoprotein cholesterol of 41 mg/dL. Mean follow-up was 3.0 years. The immediate and deferred ART groups
spent 94% and 28% of follow-up time taking ART, respectively. Compared with patients in the deferral group, patients in the
immediate ART group had increased total cholesterol and low-density lipoprotein cholesterol and higher use of lipid-lowering
therapy (1.2%; 95% CI, 0.12.2). Concurrent increases in high-density lipoprotein cholesterol with immediate ART resulted in a 0.1
lower total cholesterol to high-density lipoprotein cholesterol ratio (95% CI, 0.10.2). Immediate ART resulted in 2.3% less
BP-lowering therapy use (95% CI, 0.93.6), but there were no differences in new-onset hypertension or diabetes mellitus.
Conclusions-Among HIV-positive persons with preserved immunity, immediate ART led to increases in total cholesterol and low-
density lipoprotein cholesterol but also concurrent increases in high-density lipoprotein cholesterol and decreased use of blood
pressure medications. These opposing effects suggest that, in the short term, the net effect of early ART on traditional
cardiovascular disease risk factors may be clinically insignicant."
Clinical Trial Registration-URL: Unique identier: NCT00867048. (J Am Heart Assoc. 2017;6:
e004987. DOI: 10.1161/JAHA.116.004987.)
Key Words: antiretroviral therapy cholesterol HIV risk factor
From the Department of Medicine (J.V.B., D.D.) and Division of Biostatistics, School of Public Health (S. Sharma, G.G.), University of Minnesota, Minneapolis, MN;
Division of Infectious Diseases, Hennepin County Medical Center, Minneapolis, MN (J.V.B.); Kirby Institute, University of New South Wales, Sydney, Australia (A.C.A.,
S.E.); Department of Medicine, Hospital La Paz, IdiPAZ, Madrid, Spain (J.I.B.); Division of Infectious Diseases, MedIV, University Hospital of Munich, Germany (J.R.B.);
Chelsea and Westminster Hospital, London, United Kingdom (B.G.); Division of Cardiology, David Geffen School of Medicine at University of California, Los Angeles, CA
(J.G.); HIV Epidemiology & Biostatistics Group, University College London, London, United Kingdom (A.N.P.); European AIDS Treatment Group, Berlin, Germany (S.
Schwarze); Epidemiological Cardiology Research Center, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.); Division of Pediatric Infectious Diseases,
University of California San Diego and Rady Childrens Hospital, San Diego, CA (S.A.S.); San Raffaele Scientic Institute, Milano, Italy (G.T.); CHIP, Department of
Infectious Diseases, Rigshospitalet, University of Copenhagen, Denmark (J.L.).
Accompanying Table S1, Figure S1, and Appendix S1 are available at
*A complete list of the INSIGHT (International Network for Strategic Initiatives in Global HIV Trials) START (Strategic Timing of Antiretroviral Treatment) Study Group
members are given in Appendix S1.
Data were presented as a research abstract at the 24th Conference on Retroviruses and Opportunistic Infections, February 2225, 2016, in Boston, MA.
Correspondence to: Jason V. Baker, MD, MS, 701 Park Avenue, MC G5, Minneapolis, MN 55417. E-mail:
Received November 22, 2016; accepted March 30, 2017.
ª2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the Creative Commons
Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-
commercial and no modications or adaptations are made.
DOI: 10.1161/JAHA.116.004987 Journal of the American Heart Association 1
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HIV-positive persons are at increased risk for premature
cardiovascular disease (CVD),
which is currently a
leading cause of morbidity and mortality.
disease accounts for a substantial proportion of HIV-related
CVD among contemporary patients. This atherosclerotic dis-
ease manifests as excess risk for coronary heart disease (CHD;
eg, myocardial infarction)
and stroke,
and may also contribute
to excess risk for heart failure
and sudden cardiac death.
It is well established that features of both HIV infection and
certain antiretroviral medications increase the risk for CVD.
Some of this excess CVD risk may be caused by long-term
systemic inammation that is mitigated, in part, via antiretroviral
therapy (ART)associated viral suppression,
whereas some
may be caused by exposure to specic antiretrovirals (eg,
certain protease inhibitors [PIs] and abacavir)
with potential
for adverse changes in blood cholesterol, platelet dysfunction,
and/or endothelial dysfunction.
Despite unique features of
HIV disease, traditional risk factors are highly predictive for CVD
among HIV-positive patients
and can be adversely affected
by HIV infection and ART treatment (eg, dyslipidemia).
Given the potential for ART to both increase (via drug toxicity
and low-density lipoprotein cholesterol [LDL-C] increases) and
decrease (via viral suppression and reduced inammation)
atherosclerosis, it is important to study this pathophysiology in
the context of randomized comparisons. The START (Strategic
Timing of Antiretroviral Treatment) trial is a randomized
controlled study of immediate initiation of ART (immediate
group) versus deferral of ART initiation until CD4
cell counts
decline to <350 cells/mm
or clinical symptoms develop
(deferredgroup) among participants naive to ART with CD4
cell counts >500 cells/mm
at entry.
The START trial used an
ideal design to compare CVD risk factors between ART-treated
and untreated HIV infection in a controlled fashion among
persons at low risk for AIDS. CVD events were a component of
the composite end point in the START trial, and participants with
a recent CVD event (<6 months from entry) were not eligible.
The START trial did not have sufcient power to specically
assess CVD event risk (12 and 14 CVD events in the immediate
and deferred groups, respectively).
In this study, we charac-
terized the inuence of immediate versus deferred ART on CVD
risk factor changes and incidence of CVD-related comorbidities.
Study Design and Data Collection
The design and primary ndings from the START trial have
been described.
The START protocol was approved by the
human subjects institutional review committee at the Univer-
sity of Minnesota and at all international coordinating centers
and participating clinical sites. After informed consent was
obtained, data collection occurred at baseline, months 1 and
4, and every 4 months thereafter. Participants were
instructed to fast (minimum of 8 hours) for annual blood
draws. Laboratory measures were performed using standard-
ized clinical assays at the sites. HIV RNA level, CD4
count, weight, and blood pressure (BP) were ascertained at
every study visit. The BP values used in the analyses were the
average of 2 measurements separated by a brief rest. Glucose
and serum lipid levels (total cholesterol, high-density lipopro-
tein cholesterol [HDL-C], LDL-C, and triglycerides) and
concomitant medication use were obtained at baseline and
annually. At screening, clinicians together with participants
prespecied the intended ART regimen a participant would
initiate if randomized to the immediate group. This regimen
was required to include 2 background nucleoside reverse
transcriptase inhibitors plus either a non-nucleoside reverse
transcriptase inhibitor (NNRTI) or a ritonavir-boosted PI, or an
integrase strand transfer inhibitor (INSTI). Dening subgroups
by the prespecied ART regimen allowed a randomized
comparison between the immediate and deferred groups
among those who were designated to start the same
antiretroviral medication. Data for this report included visits
up to the START trial unblinding date of May 26, 2015.
Clinical Comorbidities and Risk Factor Scores
Dyslipidemia was dened as an LDL-C level 160 mg/dL or
use of lipid-lowering therapy. Hypertension was dened as a
systolic BP 140 mm Hg, a diastolic BP 90 mm Hg, or use
of BP-lowering therapy. Diabetes mellitus was dened as a
fasting glucose level >126 mg/dL, use of medication for
diabetes mellitus, or a clinical diagnosis of diabetes mellitus
(adjudicated as conrmed or probable). Body mass index
(BMI) was computed using visit-specic weight and baseline
height. Ten-year risk scores were calculated at baseline and
updated during follow-up for the following
: (1) Framing-
ham Risk Score for a CVD or CHD event; (2) D:A:D (Data
Collection on Adverse Events of Anti-HIV Drugs) risk score for
a CVD or CHD event; and (3) the pooled cohort risk
assessment for an atherosclerotic CVD event.
Statistical Methods
The mean changes from baseline between the immediate and
deferred groups for continuous measures were compared
using longitudinal mixed models with random intercepts,
including treatment group, visit, and baseline value in the
model. The differences between groups for the prevalence of
binary measures were compared using generalized estimating
equations (binomial regression) with treatment group, visit,
and baseline prevalence in the model. Histograms showed
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that total cholesterol, LDL-C, HDL-C, and BP were approxi-
mately normally distributed and were analyzed untrans-
formed. The proportional hazards assumption was tested
using log-time as a covariate in the model. Comparisons
within subgroups dened by prespecied ART drug or class
(efavirenz [EFV], PI, or INSTI) are reported. EFV-based ART was
included as a subgroup in analyses by ART class, given that
EFV represented 95% of the NNRTI use in the START trial.
Incidence for binary risk factors was determined in partici-
pants without that condition at baseline using a single factor
for treatment in Cox regression models. To directly compare
treated versus untreated HIV infection we repeated the
analyses by excluding immediate group participants who
never started ART (n=39) and censoring the deferred group at
the time of ART initiation. Analyses were performed using SAS
software version 9.3 (SAS Institute Inc) and R software
version 3.2.3 (R Foundation for Statistical Computing).
Participant Characteristics
A total of 4685 HIV-positive individuals from 215 sites in 35
countries were enrolled into the START trial. The median age
of participants was 36 years and 27% were female
(Table 1).
Self-reported race/ethnicity reected global
enrollment from the United States (11%), South America
and Mexico (25%), Europe, Israel and Australia (35%), Africa
(21%), and Asia (8%). The CD4
cell count at entry was 651
, and the median time since HIV diagnosis was
1 year. Mean (SD) and median [interquartile range] follow-up
time was 3.0 (1.2) and 2.8 [2.13.9] years, respectively, with
no difference in follow-up time between the immediate and
deferred groups. Baseline characteristics did not differ
between groups (Table 1). In addition to a high smoking
prevalence, START trial participants were at low risk for CVD
based on the median values for BMI, BP, cholesterol, and
CVD/CHD risk scores.
The percentage of participants taking ART during follow-
up is presented in Figure 1; 98% of the immediate group and
48% of the deferred group initiated ART, with a median time
to initiation of 36 months in the deferred group. The
percentage of follow-up time spent taking ART was 94%
and 28% for the immediate and deferred groups, respec-
tively. The frequency of specic antiretrovirals in the initial
ART regimen reects contemporary clinical practice
(Table S1). Among the 2287 immediate group participants
who initiated therapy, ART included tenofovir disoproxil
fumarate in 89%, an NNRTI in 77% (73% EFV), a ritonavir-
boosted PI in 19% (10% atazanavir and 7% darunavir), and an
INSTI in 5% (4% raltegravir); corresponding values for the
1134 deferred group participants who initiated therapy
included tenofovir disoproxil fumarate in 89%, an NNRTI in
64% (51% EFV), a PI in 22% (11% darunavir), and an INSTI in
14% (8% raltegravir).
Changes in Serum Cholesterol Levels and Lipid-
Lowering Therapy
Mean changes in lipid levels (Figure 2) and the incidence of
dyslipidemia (Figure 3) are presented for each group.
Compared with the ART deferral group, the immediate ART
group had 11 mg/dL higher total cholesterol (95% CI, 10
13), 6 mg/dL higher LDL-C (95% CI, 47), and 5 mg/dL
higher HDL-C (95% CI, 45) levels. The rise in total
cholesterol and LDL-C in the immediate group was associ-
ated with a 1.2% greater use of lipid-lowering therapy (95%
CI, 0.22.2) and a higher incidence rate of dyslipidemia
(hazard ratio, 1.7; 95% CI, 1.42.02). Among the 346
participants taking lipid-lowering therapy at entry or during
follow-up, 68% were taking a statin. Increases in HDL-C
levels resulted in a marginally lower total cholesterol to HDL-
C ratio in the immediate versus the deferred group (0.1;
95% CI, 0.2 to 0.1). When HDL <40 mg/dL was included
in the criteria for dyslipidemia, 49% (2283) of participants
had dyslipidemia at study entry. When including low HDL in
the denition, the incidence rate for dyslipidemia was lower
in the immediate ART group compared with the deferred ART
group (hazard ratio, 0.7; 95% CI, 0.60.8) (Figure 3).
Immediate ART also resulted in higher triglyceride (8 mg/
dL; 95% CI, 312) and nonHDL-C (7 mg/dL; 95% CI, 58)
levels than deferred ART. Participants were fasting for 91%
of blood draw visits and the ndings were similar when
analyses were restricted to fasting specimens. In analyses of
treated versus untreated HIV infection, the treatment
differences in lipid changes from baseline were of higher
magnitude but similar.
Table 2 presents analyses of subgroups dened by
prespecied ART, with comparisons for EFV-, PI-, and INSTI-
based ART. These data represent the effect of starting a
specic antiretroviral when compared with a group random-
ized to defer ART but who intended to start the same
antiretroviral medication or class. Time spent during follow-up
taking the prespecied ART varied between 75% and 80% for
the immediate group and 15% and 20% for the deferred group.
There was a signicant interaction between the prespecied
ART regimen and the treatment difference for several
cholesterol measures. Specically, participants who prespec-
ied EFV use had a greater difference in both total cholesterol
and HDL-C level between the immediate and deferred groups,
when compared with those who prespecied PI use. Similarly,
when compared with those who prespecied an INSTI, the
EFV subgroup had greater differences in total cholesterol,
LDL-C, and HDL-C levels between the immediate and deferred
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groups. Notably, there was no difference in any lipid
parameters between immediate and deferred ART among
the subgroup that prespecied INSTI use. In analyses of
treated versus untreated HIV infection, the magnitude of the
treatment differences in lipid changes from baseline was
higher for EFV- and PI-based ART.
Changes in BP
When compared with patients who underwent ART deferral,
those who took immediate ART demonstrated no difference
in systolic BP, a lower diastolic BP that was not signicant
(Figure 2), and a lower prevalence of BP-lowering therapy
(2.2%; 95% CI, 3.6 to 0.93). At entry, 19% of
participants had hypertension (per our denition), and when
new-onset hypertension rates were compared between the
immediate and deferred groups, the hazard ratio for reduced
incidence of hypertension did not reach signicance (0.87;
95% CI, 0.741.02; [P=0.10]) (Figure 3). After analyses of
treated versus untreated HIV infection, there remained no
difference in use of BP-lowering therapy or incident hyper-
tension between the groups, whereas diastolic BP was
signicantly lower in the immediate ART group (0.4; 95%
CI, 0.1 to 0.7 [P=0.02]).
Changes in Metabolic Parameters
Patients in the immediate group had a higher mean glucose
level of 2 mg/dL (95% CI, 13) than patients in the deferred
group (Figure S1), but there was no difference in the incidence
Table 1. Baseline Characteristics of Patients in the START
Trial (n=4685)
Median [IQR] or % (No.)
Age, y 36 [2944]
Female sex 26.8 (1257)
Asian 8.3 (388)
Black 30.1 (1410)
Latino/Hispanic 13.6 (638)
White 44.5 (2086)
Other 3.5 (163)
HIV history and laboratory
Time known to be HIV positive, y 1.0 [0.43.1]
CD4, cells/mm
* 651 [584765]
Nadir CD4, cells/mm
553 [488654]
HIV RNA, copies/mL 12 759 [301943 391]
Clinical measures
BMI, kg/m
24.6 [22.127.9]
Systolic BP, mm Hg 120 [111130]
Diastolic BP, mm Hg 76 [7083]
Risk factors
Current smoker 31.9 (1496)
Diabetes mellitus 3.3 (156)
Prior CVD diagnosis
0.8 (36)
Hypertension 19.2 (898)
BP-lowering drugs 8.1 (281)
Dyslipidemia 8.2 (386)
Lipid-lowering drugs 3.5 (163)
Glucose and lipids
Glucose, mg/dL 85 [7992]
Total cholesterol, mg/dL 168 [144195]
LDL-C, mg/dL 102 [82124]
HDL-C, mg/dL 41 [3550]
Triglycerides, mg/dL 97 [71142]
Total cholesterol to HDL-C ratio 4.0 [3.25.0]
NonHDL-C, mg/dL 124 [102150]
10-year predicted risk scores
2.3 [0.76.5]
1.9 [0.55.0]
CVD D:A:D, %
1.8 [0.93.5]
CHD D:A:D, %
1.4 [0.72.9]
Pooled cohort ASCVD, %
2.2 [1.04.4]
Lifetime ASCVD risk score, %
31.2 [15.639.6]
Table 1. Continued
Median [IQR] or % (No.)
Prespecified ART regimen
EFV 75.1 (3516)
PI 17.4 (815)
INSTI 3.9 (183)
Non-EFV NNRTI 3.7 (171)
ART indicates antiretroviral therapy; BMI, body mass index; BP, blood pressure; CHD,
coronary heart disease; CVD, cardiovascular disease; EFV, efavirenz; HDL-C, high-density
lipoprotein cholesterol; INSTI, integrase strand transfer inhibitor; IQR, interquartile range;
LDL-C, low-density lipoprotein cholesterol; NNRTI, non-nucleoside reverse tra nscriptase
inhibitor; PI, protease inhibitor; START, Strategic Timing of Antiretroviral Treatment.
*Average of 2 screening values.
Documented in participant record.
Diagnosis of any of the following prior to randomization: myocardial infarction, stroke,
coronary heart disease requiring drug treatment, coronary revascularization, congestive
heart failure, or peripheral arterial disease.
Framingham Risk Score (FRS) equations in Anderson et al.
Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) score equations in Friis-
Møller et al.
Atherosclerotic cardiovascular disease (ASCVD) risk equation in Goff et al.
Lifetime ASCVD risk score in Berry et al.
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of type 2 diabetes mellitus (Figure 3). In contrast, BMI was
signicantly lower among patients in the immediate versus
deferred groups (0.2 kg/m
; 95% CI, 0.3 to 0.1), although
the magnitude of this effect is of unclear clinical signicance
(Figure S1). The treatment effect on BMI appeared greatest
early after randomization (P<0.001 for interaction of treatment
group by follow-up time). When comparing subgroups dened
by prespecied ART regimen, BMI showed a signicantly
greater decline (with immediate versus deferred ART) among
patients in the EFV (0.3 kg/m
; 95% CI, 0.4 to 0.2) versus
PI (0.1 kg/m
; 95% CI, 0.2 to 0.1) subgroups. Finally, there
was no evidence of an interaction between prespecied ART
regimen and a treatment effect for serum glucose or incident
diabetes mellitus.
Differences in Risk Factor Prole and Predicted
Risk Scores
We studied the effect of immediate ART on CVD and CHD
predicted risk scores. Smoking contributed the most to
predicted risk, but rates did not differ between treatment
groups during follow-up (Figure S1). The mean difference
between groups was not signicant for the atherosclerotic
CVD pooled cohort 10-year risk score (0.1; 95% CI, 0.2 to
0.1), the Framingham Risk Score 10-year CVD (0.1; 95%
CI, 0.3 to 0.0), or the Framingham Risk Score 10-year
CHD (0.1; 95% CI 0.3 to 0.0), but was slightly higher in
the immediate group for the D:A:D 10-year CVD (0.2; 95% CI,
0.10.3) and CHD (0.1; 95% CI, 0.10.2) estimates. Differ-
ences in the D:A:D scores were caused primarily by the fact
that this score considers exposure to certain antiretrovirals
(eg, abacavir, lopinavir); there were no differences when
censoring participants after initiation of these antiretrovirals.
After analyses of patients with treated versus untreated HIV
infection, the treatment differences in the Framingham Risk
Score estimates were of a similar low magnitude but reached
statistical signicance.
The START trial is the rst randomized clinical investigation to
study the impact of immediate ART initiation, when compared
with deferral, on CVD risk factors among a large global HIV-
positive cohort with high CD4
cell counts. It is in this context
that understanding and mitigating risk for CVD becomes a
high priority in clinical practice. When compared with ART
deferral, ART initiation increased total cholesterol and LDL-C
levels and use of lipid-lowering therapy, but also increased
HDL-C level and resulted in a decline in total cholesterol to
HDL-C ratio. Changes in CVD or CHD prediction scores
with immediate versus deferred ART were minimal or
A well-described consequence of untreated HIV infection is
a decline in most serum lipids levels (the primary exception
being an elevation in triglycerides), with ART initiation then
leading to a compensatory increase in total cholesterol and
LDL-C levels to a degree that often varies by regimen.
We present novel randomized data quantifying the absolute
effect of ART initiation on serum lipids, when compared with
initially untreated HIV disease. Increases in total cholesterol
were greatest among the subgroups that prespecied EFV.
Prior studies have lacked a comparison group of untreated
persons, but have reported greater within-participant
increases in total cholesterol (mean 19 and 55 mg/dL) and
LDL-C (mean 4 and 23 mg/dL) levels 1 year after starting
NNRTI- (eg, EFV) or PI-based ART, when compared with the
changes reported in the START trial.
It is unclear
whether the greater increases in LDL-C level with EFV-based
ART reects greater CVD risk, given that increases in HDL-C
level were also greater with EFV and that epidemiologic data
demonstrate that exposure to certain PIs, but not to NNRTIs
(eg, EFV), are associated with greater risk for myocardial
Data from comparative antiretroviral trials have shown
the greatest rises in HDL-C level after starting EFV (73% in
the START trial) or tenofovir (89% in the START trial), with
the effect from INSTIs (5% in the START trial) being
Months from Randomization
Patients, %
No. of Participants:
2326 2287 1809 1040 551
2359 2303 1837 1055 546
362412 48
Figure 1. Antiretroviral therapy (ART) use by treatment
group in the START (Strategic Timing of Antiretroviral
Treatment) trial (n=4685). Shown is the percentage of
participants taking ART by follow-up month in the immedi-
ate and deferred ART groups. Data were previously reported
but the results shown here are truncated at month 48.
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20 A Total Cholesterol, mg/dL
I−D diff.: 11.4 (95% CI, 10.0–12.9): P<0.001 −5
10 B LDL-C, mg/dL
I−D diff.: 5.5 (95% CI, 4.2-6.8): P<0.001
8C HDL−C (mg/dL)
I−D diff.: 4.8 (95% CI, 4.3–5.4): P<0.001 −0.3
0.1 D Total−C:HDL−C Ratio
I−D diff.: −0.1 (95% CI, –0.2 to –0.1): P<0.001
1.5 E Systolic BP, mm Hg
I−D diff.: −0.1 (95% CI, –0.6 to –0.3) P=0.58 −1.5
1.5 F Diastolic BP, mm Hg
I−D diff.: −0.3 (95% CI, –0.6 to –0.0) P=0.07
14 G Use of BP-Lowering Drugs
I−D diff.: −2.3 (95% CI, –3.6 to –0.9): P<0.001
10 H Use of Lipid-Lowering Drugs
I−D diff.: 1.2 (95% CI, 0.1–2.2) P=0.03
Change From BaselinePrevalence, %
Months From Randomization
Immediate Deferred
0 12 24 36 48 0 12 24 36 48
Figure 2. Cardiovascular risk factor changes by treatment group. Shown in the rst 3 rows are the
unadjusted mean changesfrom baseline at annual visits for participants in the immediate (I) and deferred (D)
antiretroviral therapy (ART) groups for the following measures: total cholesterol (A), low-density lipoprotein
cholesterol (LDL-C; B), high-density lipoprotein cholesterol (HDL-C; C), total cholesterol to HDL-C ratio (D),
systolic blood pressure (BP; E), and diastolic BP (F). Presented within (A through F) are the estimated mean
differences (with 95% CIs and Pvalues) during follow-up between the 2 groups (I minus D), adjusting for the
baseline value and visit from longitudinal mixed models. Shown in the last row is the unadjusted prevalence
(percentage) at baseline and follow-up annual visits for participants in both ARTgroups for use of BP-lowering
drugs (G) and lipid-lowering drugs (H). Presented within (G and H) are the overall estimated differences in
prevalence during follow-up (with 95% CIs and Pvalues) between the 2 groups (I minus D), adjusting for the
baseline prevalence and visit from generalized estimating equations. Figures are truncated at month 48.
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Our ndings support that ART initiation with
EFV-based ART led to the greatest increases in HDL-C level.
Furthermore, the degree of HDL-C level increase attributable
to initiating EFV-based ART was large enough to result in a
concurrent decline in the ratio of total cholesterol to HDL-C,
which was not observed for PI- or INSTI-based ART. The
differential effect on HDL-C level by ART regimen and lack of
signicant INSTI effects on any blood lipids suggests that
cholesterol changes may, in part, be mediated via effects
other than those related to HIV viral suppression.
Multiple factors contribute to dyslipidemia among ART-
treated HIV-positive patients, including altered hepatic syn-
thesis, inammation, oxidative stress, direct drug toxicity (eg,
PI binding of the LDL-C receptor protein), and possibly genetic
The modest degree of ART-associated
increases in total cholesterol and LDL-C levels described in
the START trial was surprising, although, as noted, may be
caused by the fact that previous estimates cannot isolate the
net effect of ART versus no ART. One important caveat to the
increase in dyslipidemia with immediate ART in the START trial
was that if low HDL level was included as criteria, then
dyslipidemia was less with immediate ART. Another important
difference between ndings from the START trial and most
prior ART trials is the health of the study population, raising
the question of whether ART-related effects on serum lipids
may be decreased when initiating treatment earlier in HIV
disease. Still, the effect of ART treatment on blood lipid levels
in the START trial emphasizes that cholesterol should remain
a key target for CVD risk factor modication within this
30 A Dyslipidemia (no HDL)
I/D HR: 1.66 (95% CI, 1.36–2.02): P<0.001
80 B Dyslipidemia (with HDL)
I/D HR: 0.70 (95% CI, 0.61–0.8): P<0.001
30 C Hypertension
I/D HR: 0.87 (95% CI, 0.74–1.02) P=0.10
6D Diabetes
I/D HR: 1.13 (95% CI, 0.75–1.72) P=0.56
Cumulative Percent With Event
Months From Randomization
Immediate Deferred
0 12243648 0 12243648
Figure 3. Cumulative incidence of comorbid conditions by treatment group. Shown are KaplanMeier
estimates of the cumulative incidence of participants with dyslipidemia, excluding high-density lipoprotein
(HDL) in the denition (A), dyslipidemia, including HDL <40 mg/dL in the denition* (B), hypertension
and diabetes mellitus (D) during follow-up for participants in the immediate (I) and deferred (D) antiretroviral
therapy (ART) groups. Presented within the gures are the estimated hazard ratios (HRs) for the immediate
(I) vs deferred (D) groups (with 95% CIs and Pvalues) from Cox proportional hazards regression models.
Figures are truncated at month 48. The cumulative incidence plots have jumps annually because
measurements were obtained only at annual visits. *A total of 2203 (49%) START (Strategic Timing of
Antiretroviral Treatment) trial participants had dyslipidemia at baseline when including the criteria of HDL
<40 mg/dL. The incidence computation during follow-up for this denition is limited to the 2402
participants without baseline dyslipidemia.
For the incidence computation, an individual was dened as
being hypertensive at the rst visit when systolic blood pressure (BP) was 140 mm Hg, diastolic BP was
90 mm Hg, or BP medication use was reported. In some individuals classied as hypertensive based on
BP alone, the BP may be lower at subsequent visits. This denition leads to a higher incidence.
DOI: 10.1161/JAHA.116.004987 Journal of the American Heart Association 7
Cardiovascular Disease Risk Factors in the START Trial Baker et al
by guest on May 23, 2017 from
Although immediate ART initiation did not lead to signicant
changes in BP or incident hypertension, the use of BP-lowering
therapy and the prevalence of hypertension were less with
immediate ART. Reasons for this discrepancy are unclear, but
incident hypertension does not reect inuences on the use of
BP-lowering therapy among patients with known hypertension
at entry. Associations between inammatory cytokines and
vascular stiffness provide some biologic pretense for why
suppressing HIV replication may reduce the need for BP
However, if a true ART-treatment effect on
absolute BP was present but not detected in this study (eg,
type 2 error), it is unlikely to be clinically signicant.
ART is well known to be associated with body composition
changes, although contemporary ART regimens are less toxic
than early-era antiretrovirals.
In the START trial, imme-
diate ART initiation led to a clinically insignicant increase in
serum glucose (ie, with no change in incidence of diabetes
mellitus), but was also associated with a marginally lower BMI.
The BMI ndings are counter to prior observations of ART
increases in abdominal fat, but, importantly, BMI assessments
do not delineate between changes in visceral and subcuta-
neous fat.
In addition, the relative immune preservation in
the START trial may be important in that toxicity from a given
antiretroviral medication may be more pronounced among
patients with more severe immune depletion. This hypothesis
was suggested by notable ndings from HOPS (the HIV
Outpatient Study), in which starting ART at higher (versus
lower) CD4
cell counts reduced the incidence of peripheral
neuropathy, even when using antiretrovirals well known to
cause neuropathy.
Ultimately, the net effect of early ART initiation on
traditional risk factors appeared to have a clinically insignif-
icant effect on CVD and CHD risk algorithms. While 10-year
CVD/CHD predicted risk remained low in absolute terms, the
estimated lifetime atherosclerotic CVD risk at study entry
among this younger population was still >30%,
that traditional risk factor management remains an important
strategy to mitigate the cumulative effects of HIV, ART, and
advancing age over time. However, it does remain unclear
how well the atherosclerotic CVD lifetime risk estimation
reects true clinical risk in this context as it has not been
validated among HIV-positive persons.
Study Limitations
These analyses have several limitations. We did not directly
assess or characterize other potentially important CVD risk
mechanisms (eg, HIV-related systemic inammation) or
potential mechanisms of ART toxicity. There was potential
for confounding in terms of baseline lipid levels inuencing
the choice of ART regimen; however, we did not see evidence
for this, as the prevalence of prespecied PI (17%) was the
same for persons with and without hyperlipidemia at baseline.
Also, analyses focused on the INSTI subgroup were limited by
small numbers. Finally, we are not able to characterize
whether the ART-related changes in CVD risk factors will
translate to differences in clinical event risk caused by the
limited number of events in the START trial, although ndings
to date have not detected a signicant effect of immediate
versus deferred ART on risk for CVD events (HR, 0.84; 95% CI,
These data, among a diverse global population of HIV-positive
persons with high CD4 cell counts, suggest that immediate
ART initiation has both positive and negative inuences on
CVD risk factors. Ultimately, long-term follow-up in the START
trial is needed to determine the net effect of ART treatment
initiation for CVD event risk among HIV-positive individuals
with preserved immunity.
Table 2. Overall Treatment Difference (ID) in Metabolic Parameters by Subgroups Dened by Prespecied ART Regimen at
Prespecied ART
EFV (n=3516) PI (n=815) INSTI (n=183)
Mean Difference* (95% CI)
Mean Difference* (95% CI)
Mean Difference* (95% CI)
Total cholesterol, mg/dL 13.2 (11.514.9) 8.7 (5.212.1) 2.4 (10.1 to 5.3) <0.001
LDL-C, mg/dL 6.5 (5.07.9) 3.7 (0.76.7) 1.1 (7.8 to 5.7) 0.036
HDL-C, mg/dL 5.8 (5.26.4) 2.2 (0.93.5) 0.4 (2.5 to 3.4) <0.001
Total cholesterol to HDL-C ratio 0.2 (0.2 to 0.1) 0.0 (0.2 to 0.1) 0.2 (0.5 to 0.2) 0.13
EFV indicates efavirenz; HDL-C, high-density lipoprotein cholesterol; INSTI, integrase strand transfer inhibitor; LDL-C, low-density lipoprotein cholesterol; PI, protease inhibitor.
*Mean differences (immediate [I] minus deferred [D]) during all follow-up using longitudinal mixed models adjusting for baseline level and visit.
2df P value for interaction between treatment group and 3 prespecied antiretroviral therapy (ART) regimens comparing the ID treatment difference among subgroups.
DOI: 10.1161/JAHA.116.004987 Journal of the American Heart Association 8
Cardiovascular Disease Risk Factors in the START Trial Baker et al
by guest on May 23, 2017 from
The authors would like to specically thank the participants in the
START trial. See supplemental material for the complete listing of the
INSIGHT (International Network for Strategic Initiatives in Global HIV
Trials) START (Strategic Timing of Antiretroviral Treatment) Study
Group (also published in N Engl J Med. 2015;373:795807).
Sources of Funding
The START trial (NCT00867048) is registered at clinicaltrials.-
gov. The START trial is primarily funded by the National Institute
of Allergy and Infectious Diseases (NIAID) of the National
Institutes of Health (NIH) under award numbers UM1-AI068641
and UMN1-AI120197, with additional support from the NIH
Clinical Center; National Cancer Institute; National Heart, Lung,
and Blood Institute; Eunice Kennedy Shriver National Institute
of Child Health and Human Development; National Institute of
Mental Health; National Institute of Neurological Disorders and
Stroke; National Institute of Arthritis and Musculoskeletal and
Skin Diseases; Agence Nationale de Recherches sur le SIDA et
les H
epatites Virales (France); National Health and Medical
Research Council (Australia); National Research Foundation
(Denmark); Bundesministerium f
ur Bildung und Forschung
(Germany); European AIDS Treatment Network; Medical
Research Council (United Kingdom); National Institute for
Health Research; National Health Service (United Kingdom);
and University of Minnesota. Antiretroviral drugs are donated to
the central drug repository by AbbVie, Bristol-Myers Squibb,
Gilead Sciences, GlaxoSmithKline/ViiV Healthcare, Janssen
Scientic Affairs, and Merck. Dr Gordin is supported by the NIH
Cardiovascular Scientist Training Program under award number
T32 HL007895.
The content is solely the responsibility of the authors and
does not necessarily represent the ofcial views of the NIH.
Dr Phillips received fees for speaking at 2 meetings sponsored
by Gilead Sciences, for consulting from GSK Biologicals, and
for attendance at an advisory board membership from AbbVie.
The remaining authors declare no relevant nancial interests.
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Cardiovascular Disease Risk Factors in the START Trial Baker et al
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Table S1. Distribution (number and percent) of specific ART used for the first regimen
and total follow-up time spent taking a specific ART (Person Years, percent of follow-up).
Follow-up Time
on Drug
PY(% time)
Follow-up Time
on Drug
PY(% time)
No. of participants
6582 (93.9)
1954 (27.7)
344 (4.9)
154 (2.2)
5794 (82.7)
1724 (24.4)
5821 (83.1)
1735 (24.6)
779 (11.1)
225 (3.2)
411 (5.9)
63 (0.9)
0 (0.0)
0 (0.0)
4524 (64.6)
1122 (15.9)
4097 (58.5)
855 (12.1)
360 (5.1)
237 (3.4)
68 (1.0)
31 (0.4)
Any PI
1653 (23.6)
553 (7.8)
887 (12.7)
220 (3.1)
611 (8.7)
290 (4.1)
33 (0.5)
13 (0.2)
121 (1.7)
30 (0.4)
1630 (23.3)
547 (7.8)
0 (0.0)
0 (0.0)
448 (6.4)
288 (4.1)
10 (0.1)
21 (0.3)
25 (0.4)
63 (0.9)
413 (5.9)
205 (2.9)
0 (0.0)
0 (0.0)
Other ART
2 (0.0)
0 (0.0)
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Not on any ART
400 (5.7)
5094 (72.2)
N number; PY Person years; ART Antiretroviral therapy; NRTI nucleoside reverse transcriptase inhibitor; NNRTI non-
nucleoside reverse transcriptase inhibitor; PI protease inhibitor; INSTI integrase strand transfer inhibitor
* Denominator is all participants in the randomization group.
Person years includes switches and accounts for stops and therefore includes time spent on drug for participant who did not
initiate ART with the given
drug. Denominator is over all follow-up time accumulated within the randomization group.
1 participant started a blinded study and the type of ART taken is unknown.
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Figure S1. Changes in the Prevalence of Selected CVD Risk Factors by Treatment Group
Shown in panels A-C is the unadjusted prevalence (%) at baseline and follow-up annual visits
for participants in the immediate (I, solid line) and deferred (D, dashed line) ART groups for
CVD (cardiovascular disease) risk factor, including hypertension (panel A), dyslipidemia (panel
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B), and current smoking (panel C). Presented within panels A-C are overall estimated
differences in prevalence (with 95% confidence interval and p-value) over follow-up between the
two groups (immediate minus deferred), adjusting for the baseline prevalence and visit from
generalized estimating equations. Shown in panels D-E are the unadjusted mean changes from
baseline at annual visits for participants in both ART groups for the following measures: body
mass index (BMI, panel D) and glucose (panel E). Presented within panels D-E is the estimated
mean difference (with 95% confidence interval and p-value) over follow-up between the two
groups (immediate minus deferred), adjusting for the baseline value and visit from longitudinal
mixed models. Figures are truncated at Month 48.
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Appendix: The INSIGHT START (Strategic Timing of AntiRetroviral Treatment) Study
In addition to writing group, the following committee members contributed to the conduct of the START
Community Advisory Board: C. Rappoport (INSIGHT community liaison), P.D. Aagaard, S. Collins,
G.M. Corbelli, N. Geffen, C. Kittitrakul, T. Maynard, M. Meulbroek, D. Munroe, M.S. Nsubuga, D.
Peavey, S. Schwarze, M. Valdez.
Substudy Chairs: J.V. Baker, D. Duprez (arterial elasticity); A. Carr, J. Hoy (bone mineral density); M.
Dolan, A. Telenti (genomics); C. Grady (informed consent); G. Matthews, J. Rockstroh (liver fibrosis
progression); W.H. Belloso, J.M. Kagan (monitoring); E. Wright, B. Brew, R.W. Price, K. Robertson, L.
Cysique (neurology); K.M. Kunisaki, J.E. Connett, D.E. Niewoehner (pulmonary). Endpoint Review
Committee: A. Lifson (chair), W.H. Belloso, R.T. Davey Jr., D. Duprez, J.M. Gatell, J. Hoy, C. Pedersen,
R.W. Price, R. Prineas, J. Worley.
Central Drug Repository and Drug Distribution: K. Brekke, S. Meger, B. Baugh, J. Eckstrand, C.
Gallagher, J. Myers, J. Rooney, J. Van Wyk.
Network Laboratory Group: J. Baxter, C. Carey, A. DuChene, E.B. Finley, M. George, J. Grarup, M.
Hoover, R. Pedersen, C. Russell, B. Standridge.
Specimen Repositories: E. Flowers, M. Hoover, K. Smith (Advanced BioMedical Laboratories, LLC,
Cinnaminson, NJ, United States); M. McGrath, S. Silver (AIDS and Cancer Specimen Resource,
University of California, San Francisco, San Francisco, CA, United States).
Wake Forest ECG Reading Center, Winston-Salem, NC, United States: E.Z. Soliman, M. Barr, C.
Campbell, S. Hensley, J. Hu, L. Keasler, Y. Li, T. Taylor, Z.M. Zhang.
Division of AIDS, National Institute of Allergy and Infectious Diseases, Bethesda, MD, United States: B.
AlstonSmith, E. DeCarlo, K. Klingman, M. Proschan.
Data and Safety Monitoring Board: S. Bangdiwala (chair), R. Chaisson, A.R. Fleischman, C. Hill, J.
Hilton, O.H.M. Leite, V.I. Mathan, B. Pick, C. Seas, P. Suwangool, G. Thimothe, F. Venter, I. Weller, P.
by guest on May 23, 2017 from
Minnesota Coordinating Center, University of Minnesota, Minneapolis, MN, United States: J.D. Neaton,
K. Brekke, G. Collins, E.T. Denning, A. DuChene, N.W. Engen, M. George, B. Grund, M. Harrison, K.H.
Hullsiek, L.H. Klemme, E. Krum, G. Larson, S. Meger, R. Nelson, J. Neuhaus Nordwall, K. Quan, S.F.
Quan, T. Schultz, S. Sharma, G. Thompson.
International Coordinating Centers: Copenhagen HIV Programme, Rigshospitalet, University of
Copenhagen, Denmark: J.D. Lundgren, B. Aagaard, A.H.D. Borges, M. Eid, J. Grarup, P. Jansson, Z.
Joensen, B. Nielsen, M. Page 3 Pearson, R. Pedersen, A.N. Phillips; The Kirby Institute, University of
New South Wales, Sydney, Australia: S. Emery, N. Berthon-Jones, C. Carey, L. Cassar, M. Clewett, D.
Courtney-Rodgers, P. Findlay, S. Hough, S. Jacoby, J. Levitt, S.L. Pett, R. Robson, V. Shahamat, A.
Shambrook; Medical Research Council Clinical Trials Unit at UCL, London, United Kingdom: A.G.
Babiker, B. Angus, A. Arenas-Pinto, R. Bennett, N. Braimah, E. Dennis, N. Doyle, M. Gabriel, F.
Hudson, B. Jackson, A. Palfreeman, N. Paton, C. Purvis, C. Russell; Veterans Affairs Medical Center,
Washington, DC, United States: F. Gordin, D. Conwell, H. Elvis, E.B. Finley, V. Kan, L. Lynch, J.
Royal, A. Sánchez, B. Standridge, D. Thomas, M. Turner, M.J. Vjecha.
The following investigators participated in the START study, listed by country (country lead, numbers of
participants enrolled) and clinical site:
Argentina (M.H. Losso, n=216): CAICI (Instituto Centralizado de Assistencia e Investigación Clínica
Integral), Rosario Santa Fe: S. Lupo, L. Marconi, D. Aguila; FUNCEI, Buenos Aires: G. Lopardo, E.
Bissio, D. Fridman; Fundación IDEAA, Buenos Aires: H. Mingrone, E. Loiza, V. Mingrone; Hospital
General de Agudos JM Ramos Mejia, Buenos Aires: M. Losso, J.M. Bruguera, P. Burgoa; Hospital
Interzonal General de Agudos Dr. Diego Paroissien, Buenos Aires: E. Warley, S. Tavella; Hospital
Italiano de Buenos Aires, Buenos Aires: W. Belloso, M. Sanchez; Hospital Nacional Profesor Alejandro
Posadas, Buenos Aires: H. Laplumé, L. Daciuk; Hospital Rawson, Cordoba: D. David, A. Crinejo;
Argentinean SCC, Fundación IBIS, Buenos Aires: G. Rodriguez-Loria, L. Doldan, A. Moricz, I. Otegui,
I. Lanusse.
Australia (J. Hoy, n=109): Burwood Road General Practice, Burwood, VIC: N. Doong, S. Hewitt; Centre
Clinic, St Kilda, VIC: B.K. Tee; East Sydney Doctors, Darlinghurst, NSW: D. Baker, E. Odgers;
Holdsworth House Medical Practice, Darlinghurst, NSW: S. Agrawal, M. Bloch; Melbourne Sexual
Health Centre, Carlton, VIC: T.R.H. Read, S.J. Kent; Prahran Market Clinic, Prahran, VIC: H. Lau, N.
Roth; Royal Adelaide Hospital, Adelaide, SA: L. Daly, D. Shaw; Royal Perth Hospital, Perth, WA: M.
French, J. Robinson; Sexual Health & HIV Service - Clinic 2, Brisbane, QLD: M. Kelly, D. Rowling; St
Vincent's Hospital, Fitzroy, VIC: D.A. Cooper, A. J. Kelleher; Taylor Square Private Clinic, Surry Hills,
NSW: C. Pell, S. Dinning; The Alfred Hospital, Melbourne, VIC: J. Hoy, J. Costa; Westmead Hospital,
Westmead, NSW: D.E. Dwyer, P. King.
by guest on May 23, 2017 from
Austria (A. Rieger, n=7): Otto-Wagner-Spital SMZ /Baumgartner Hoehe, Vienna: N. Vetter; B. Schmied;
University Vienna General Hospital, Vienna: A. Rieger, V.R. Touzeau.
Belgium (S. de Witt, n=102): Centre Hospitalier Universitaire St. Pierre (C.H.U. St. Pierre), Brussels: S.
de Witt, N. Clumeck, K. Kabeya; Institute of Tropical Medicine, Antwerp: E. Cleve, E. Florence, L. van
Petersen; Universitair Ziekenhuis Gasthuisberg, Leuven: H. Ceunen, E.H. van Wijngaerden; Universitaire
Ziekenhuizen Gent, Gent: T. James, L. Vandekerckhove.
Brazil (L.C. Pereira Jr., M. Schechter, n=619): Ambulatório de Imunodeficiências (LIM-56), Sao Paulo,
SP: J. Casseb, E. Constantinov, M.A. Monteiro; Center for ID at UFES, Vitoria, ES: L.N. Passos, T.
Reuter; Centro de Referência e Treinamento DST/AIDS, Sao Paulo, SP: S.T. Leme, J.V.R. Madruga, R.S.
Nogueira; Hospital Page 4 Escola Sao Francisco de Assis, Rio de Janeiro, RJ: M. Barbosa Souza, C.
Beppu Yoshida, M. Dias Costa; Instituto de Infectologia Emilio Ribas, Sao Paulo, SP: R. Castro, R.Cruz,
S. Ito, T.N. Lobato Souza; Instituto FIOCRUZ, Rio de Janeiro, RJ: B. Grinsztejn, V.G. Veloso, S.
Wagner Cardoso; SEI Serviços Especializados em Infectología LTDA, Salvador, Bahia: F. Bahia, C.
Brites, J. Correia.
Chile (M.J. Wolff, n=76): Fundación Arriarán, Santiago: M. Wolff, R. Northland, C. Cortés.
Czech Republic (D. Sedlacek, n=13): Faculty Hospital Na Bulovce, Prague: D. Jilich; University Hospital
Plzen, Plzen: D. Sedlacek.
Denmark (J. Gerstoft, n=33): Hvidovre University Hospital, Hvidovre: P. Collins, L. Mathiesen; Odense
University Hospital, Odense: L. Hergens, C. Pedersen; Rigshospitalet, Copenhagen: J. Gerstoft, L.P.
Jensen; Århus Universitetshospital, Skejby, Århus: I.R. Lofthiem, L. Østergaard.
Estonia (K. Zilmer, n=8): West Tallinn Central Hospital Infectious Diseases, Tallinn: K. Zilmer.
Finland (M. Ristola, n=23): Helsinki University Central Hospital, Helsinki: M. Ristola, O. Debnam.
France (B. Hoen, n=111): CHU Côte de Nacre Caen, Caen: R. Verdon, S. Dargere; CHU de Besançon -
Hôpital Jean-Minjoz, Besancon: B. Hoen, C. Chirouze; Groupe Hospitalier Pitié-Salpêtrière, Paris: C.
Katlama, M-A. Valantin; Hôpital Antoine Béclère, Clamart: F. Boue, I. Kansau; Hôpital de Bicêtre, Le
Kremlin-Bicetre: C. Goujard, C. Chakvetadze; Hôpital Européen Georges Pompidou, Paris: L. Weiss, M
Karmochkine; Hôpital Foch, Suresnes: D. Zucman, C. Majerholc; Hôpital Gustava Dron, Tourcoing:
O.Robineau, R. Biekre; Hôpital Henri Mondor, Creteil: Y. Levy, J.D. Lelievre; Hôpital Hôtel Dieu, Paris:
J.P. Viard, J Ghosn; Hôpital Saint-Antoine, Paris: J. Pacanowski, B. Lefebvre; Hôpital Saint-Louis, Paris:
by guest on May 23, 2017 from
J.-M. Molina, L. Niedbalski, M. Previlon; French SCC, ANRS-Inserm SC10, Paris: J.P. Aboulker, C.
Capitant, B. Lebas, N. Leturque, L. Meyer, E. Netzer.
Germany (G. Fätkenheuer, n=312): EPIMED, Berlin: K. Arastéh, T. Meier; Gemeinschaftspraxis Jessen-
JessenStein, Berlin: C. Zedlack, H. Jessen; ICH Study Center, Hamburg: S. Heesch, C. Hoffmann; Ifi -
Studien und Projekte GmbH, Hamburg: A. Plettenberg, A. Stoehr; Johann Wolfgang Goethe - University
Hospital, Frankfurt: G. Sarrach, C. Stephan; Klinik I für Innere Medizin der Universität zu Köln,
Cologne: G. Fätkenheuer, E. Thomas; Klinikum der Universität München, Munich: J.R. Bogner, I. Ott;
Klinikum Dortmund GmbH, Dortmund: M. Hower, C. Bachmann; Medizinische Hochschule Hannover,
Hannover: M. Stoll, R. Bieder; Medizinische Universitätsklinik - Bonn, Bonn: J. Rockstroh, B. Becker;
Universitätsklinikum Düsseldorf, Düsseldorf: B. Jensen, C. Feind; Universitätsklinikum Erlangen,
Erlangen: E. Harrer, T. Harrer; Universitätsklinikum Essen, Essen: S. Esser, H. Wiehler;
Universitätsklinikum Heidelberg, Heidelberg: M. Hartmann, R. Röger; Universitätsklinikum Regensburg,
Regensburg: B. Salzberger, E. Jäger; Universitätsklinikum Würzburg, Würzburg: H. Klinker, G. Mark;
Universitätsklinikum, Hamburg-Eppendorf: J. van Lunzen, N. Zerche; German SSC, Johann Wolfgang
Goethe - University Hospital, Frankfurt: V. Müller, K. Tillman.
Greece (G. Touloumi, n=101): AHEPA University Hospital, Thessaloniki Central Macedonia: S.
Metallidis, O. Tsachouridou; Attikon University General Hospital, Athens: A. Papadopoulos, K.
Protopapas; Evangelismos General Hospital, Athens: A. Skoutelis, V. Papastamopoulos; Hippokration
University General Hospital of Athens, Athens: H. Sambatakou, I. Mariolis; Korgialenio-Benakio
Hellenic Red Cross, Athens: M. K. Lazanas, M. Chini; Syngros Hospital, Athens: S. Kourkounti, V.
Paparizos; Greek SCC, National Kapodistrian University of Athens, Athens: G. Touloumi, V. Gioukari,
O. Anagnostou.
India (n=91): Institute of Infectious Diseases, Pune Maharashtra: A. Chitalikar, S. Pujari; YRGCARE
Medical Centre VHS, Chennai CRS: F. Beulah, N. Kumarasamy, S. Poongulali.
Ireland (P. Mallon, n=7): Mater Misericordiae University Hospital, Dublin: P. Mallon, P. McGettrick.
Israel (E. Kedem, n=28): Rambam Medical Center, Haifa: E. Kedem, S. Pollack; Tel Aviv Sourasky
Medical Center, Tel Aviv: D. Turner.
Italy (G. Tambussi, n=33): Lazzaro Spallanzani IRCSS, Rome: A. Antinori, R. Libertone; Ospedale San
Raffaele S.r.l., Milan: G. Tambussi, S. Nozza, M.R. Parisi.
Luxembourg (T. Staub, n=5): Centre Hospitalier de Luxembourg, Luxembourg: T. Staub, C. Lieunard.
by guest on May 23, 2017 from
Malaysia (n=18): University Malaya Medical Centre, Kuala Lumpur: R.I.S.R. Azwa.
Mali (S. Dao, n=41): SEREFO/ CESAC Mali, Bamako, Bamako: B. Baya, M. Cissé, D. Goita.
Mexico (n=48): INCMNSZ (Instituto Nacional de Ciencias Médicas y Nutrición), Tlalpan D.F.: J. Sierra-
Madero, M.E. Zghaib.
Morocco (K.M. El Filali, n=44): University Hospital Centre Ibn Rochd, Casablanca: K.M. El Filali, I.
Erradey, H. Himmich.
Nigeria (n=50): Institute of Human Virology-Nigeria (IHVN), Garki, Abuja FCT: E. Ekong, N. Eriobu.
Norway (V. Ormaasen, n=15): Oslo University Hospital, Ulleval, Oslo: V. Ormaasen, L. Skeie.
Peru (A. La Rosa, n=215): Hospital Nacional Edgardo Rebagliati Martins, Lima, Lima: M. Espichan
Gambirazzio, F. Mendo Urbina; Hospital Nacional Guillermo Almenara Irigoyen, Lima, Lima: R. Salazar
Castro, J. Vega Bazalar; IMPACTA Salud y Educación, Lima, Lima: M.E. Guevara, R. Infante, J.
Sanchez, M. Sanchez; IMPACTA San Miguel, Lima, Lima: R. Chinchay, J.R. Lama, M. Sanchez; Via
Libre, Lima, Lima: E.C. Agurto, R. Ayarza, J.A. Hidalgo.
Poland (A.J. Horban, n=68): EMC Instytut Medyczny SA, Wroclaw: B. Knysz, A. Szymczak;
Uniwersytecki Szpital Kliniczny, Bialystok: R. Flisiak, A. Grzeszczuk; Wojewodzki Szpital Zakazny,
Warsaw: A.J. Horban, E. Bakowska, A. Ignatowska.
Portugal (L. Caldeira, n=67): Hospital Curry Cabral, Lisbon: F. Maltez, S. Lino; Hospital de Egas Moniz,
Lisbon: K. Mansinho, T. Bapista; Hospital de Santa Maria, Lisbon: M. Doroana, A. Sequeira, L. Caldeira;
Hospital Joaquim Urbano, Oporto: J. Mendez, R.S.E. Castro.
South Africa (R. Wood, n=518): 1 Military Hospital, Pretoria Gauteng: S.A. Pitsi; Desmond Tutu HIV
Centre - Cape Town, Cape Town, Western Province: R. Kaplan, N. Killa, C. Orrell, M. Rattley; Durban
International Clinical Research Site, Durban, KwaZulu Natal: U.G. Lalloo, R. Mngqibisa, S. Pillay;
Durban International Clinical Research Site WWH, Durban, KwaZulu Natal: J. Govender, M. John;
University of Witwatersrand, Johannesburg, Gauteng: S. Badal-Faesen, N. Mwelase, M. Rassool.
by guest on May 23, 2017 from
Spain (J.R. Arribas, n=234): Complejo Hospitalario Xeral Cies, Vigo Pontevedra: A.O. Hermida, F.
Warncke; Hospital Clínic de Barcelona, Barcelona: J.M. Gatell, A. Gonzalez; Hospital Clínico San
Carlos, Madrid: V. Estrada, M. Rodrigo; Hospital de la Santa Creu i Sant Pau, Barcelona: P. Domingo,
M. Gutierrez; Hospital del Mar, Barcelona: H.J. Knobel, A. Gonzalez; Hospital La Paz, Madrid: J.R.
Arribas, M. Montes Ramirez; Hospital La Princesa, Internal Medicine and Infectious Disease Service
CRS, Madrid: I. de los Santo Gil, J. Sanz Sanz; Hospital Universitari Germans Trias i Pujol, Badalona: B.
Clotet, J.M. Llibre, P. Cobarsi; Hospital Universitari Mutua Terrassa, Terrassa Barcelona: D. Dalmau, C.
Badia; Hospital Universitario Doce de Octubre, Madrid: R. Rubio, M.M. del Amo; Hospital Universitario
Príncipe de Asturias, Alcala de Henares Madrid: J. Sanz Moreno; Hospital Universitario y Politécnico La
Fe, Valencia: J. López Aldeguer, S. Cuellar; Spanish SSC, Acoiba, Madrid: P. López, B. Portas, P.
Sweden (M. Gisslén, n=2): Sahlgrenska University Hospital, Sweden: M. Gisslén, L. Johansson; Skåne
University Hospital, Malmö: C. Håkangård, K. Törqvist.
Switzerland (H. Furrer, n=31): Bern University Hospital, Bern: H. Furrer, A. Rauch; Unite VIH/SIDA
Genèva, Genèva: A.L. Calmy, B. Hirschel (retd), T Lecompte; University Hospital Basel, Basel: M.
Stoeckle; University Hospital Zurich, Zürich: N. Muller, M. Rizo-Oberholzer; Swiss SCC, Bern
University Hospital, Bern: H. Furrer, C. Bruelisauer, A. Christen, M. Lacalamita.
Thailand (K. Ruxrungtham, n=248): Bamrasnaradura Infections Diseases Institute, Nonthaburi: W.
Prasithsirikul, S. Thongyen; Chiangrai Prachanukroh Hospital, Chiang Rai: P. Kantipong, S. Khusuwan;
Chonburi Regional Hospital, Chonburi: C. Bowonwatanuwong, U. Ampunpong; Chulalongkorn
University Hospital, Bangkok: K. Ruxrungtham, A. Avihingsanon, W. Thiansanguankul; Khon Kaen
University, Srinagarind Hospital, Khon Kaen: P. Chetchotisakd, P. Motsikapun, S. Anunnatsari;
Ramathibodi Hospital, Bangkok: S. Kiertiburanakul, N. Sanmeema; Research Institute for Health
Sciences (RIHES), Chiang Mai: K. Supparatpinyo, P. Sugandhavesa; Sanpatong Hospital, Chiang Mai:
V. Klinbuayaem, Y. Siriwarothai; Siriraj Hospital, Bangkok Noi: W. Ratanasuwan, T Anekthananon;
Thai SCC, The HIV Netherlands Australia Thailand Research Collaboration (HIV-NAT), Bangkok: W.
Harnnapachewin, T. Jupimai, P. Rerksirikul.
Uganda (P. Mugyenyi, n=349): Joint Clinical Research Center (JCRC), Kampala: P. Mugyenyi, C. Kityo,
H. Mugerwa; MRC/UVRI Research Unit on AIDS, Entebbe: P. Munderi, B. Kikaire, J. Lutaakome;
MRC/UVRI Research Unit on AIDS, Masaka satellite site: Z. Anywaine.
United Kingdom (M.A. Johnson, n=339): Barts Health NHS Trust, London: C. Orkin, J. Hand; Belfast
Health and Social Care Trust (RVH), Belfast Northern Ireland: C. Emerson, S. McKernan; Birmingham
Heartlands Hospital, Birmingham West Midlands: D. White, C. Stretton; Brighton and Sussex University
Hospitals NHS Trust, Brighton East Sussex: M. Fisher, A. Clarke, A. Bexley; Chelsea and Westminster
Hospital, London: B. Gazzard, C. Higgs, A. Jackson; Coventry and Warwickshire NHS partnership Trust,
Coventry West Midlands: S. Das, A. Sahota; Gloucestershire Royal Hospital, Gloucester: A. de Burgh-
by guest on May 23, 2017 from
Thomas, I. Karunaratne; Guy's and St.Thomas' NHS Foundation Trust, London: J. Fox, J.M. Tiraboschi;
Imperial College Healthcare NHS Trust, London: A. Winston, B. Mora-Peris; Leicester Royal Infirmary,
Leicester Leicestershire: M.J. Wiselka, L. Mashonganyika; Lewisham and Greenwich NHS Trust,
London: S. Kegg, T. Moussaoui; North Manchester General Hospital, Manchester: E. Wilkins, Y.
Clowes; Queen Elizabeth Hospital Birmingham, Birmingham West Midlands: J. Ross, J. Harding; Royal
Berkshire Hospital, Reading Berkshire: F. Chen, S. Lynch; Royal Bournemouth Hospital, Bournemouth
Dorset: E. Herieka, J. Ablorde; Royal Free London NHS Foundation Trust, London: M.A. Johnson, M.
Tyrer, M. Youle; Sheffield Teaching Hospital NHS Foundation Trust, Sheffield South Yorkshire: D.
Dockrell, C. Bowman; Southmead Hospital, Bristol: M. Gompels, L. Jennings; St. George's Healthcare
NHS Trust, London: P. Hay, O. Okolo; The James Cook University Hospital, Middlesbrough Cleveland:
D.R. Chadwick, P. Lambert; University College London Medical School, London: I. Williams, A. Ashraf.
United States (K. Henry, n=507): Adult Clinical Research Center, Newark, NJ: M. Paez-Quinde, S.
Swaminathan; Boston University Medical Center, Boston, MA: I. Bica, M. Sullivan; Bronx-Lebanon
Hospital Center, Bronx, NY: R.B. Cindrich, L.M. Vasco; Community Research Initiative of New
England, Boston, MA: J. Green, H.B. Olivet; Cooper University Hospital, Camden, NJ: J. Baxter, Y.
Smith; Cornell CRS, New York, NY: V. Hughes, T. Wilkin; Denver Public Health, Denver, CO: E.M.
Gardner, J. Scott; Duke University, Durham, NC: J. Granholm, N. Thielman; Florida Department of
Health in Orange/Sunshine Care Center, Orlando, FL: W.M. Carter, N.D. Desai; George Washington
University Medical Center, Washington, DC: D.M. Parenti, G.L. Simon; Georgetown University Medical
Center, Washington, DC: P. Kumar, M. Menna; Hennepin County Medical Center, Minneapolis, MN: J.
Baker, R. Givot; Henry Ford Hospital, Detroit, MI: L.H. Makohon, N.P. Markowitz; Hillsborough
County Health Department, Tampa, FL: M. Chow, C. Somboonwit; Infectious Disease Associates of
Northwest Florida, Pensacola, FL: A.B. Brown, B.H. Wade; Lurie Children's Hospital, Chicago, IL: J.
Jensen, A. Talsky; Maternal, Child and Adolescent Center for ID/Virology USC, Alhambra, CA: A.
Kovacs, L. Spencer; Mayo Clinic, Rochester, MN: S. Rizza, Z. Temesgen; Medical College of Wisconsin,
Milwaukee, WI: M. Frank, S. Parker; Montefiore Medical Center, Bronx, NY: C. Rosario, J. Shuter; Mt
Sinai Hospital, Chicago, IL: K. Rohit, R. Yogev; National Military Medical Center, Bethesda, MD: I.
Barahona, A. Ganesan; Naval Medical Center Portsmouth NMCP, Portsmouth, VA: S. Banks, T. Lalani;
Naval Medical Center San Diego NMCSD, San Diego, CA: M.F. Bavaro, S. Echols; NICE, Southfield,
MI: M. Farrough, R.D. MacArthur; NIH, Bethesda, MD: R.T. Page 8 Davey Jr., R. McConnell; Ohio
State University, Columbus, OH: H. Harber, S.L. Koletar; Orlando Immunology Center, Orlando, FL: E.
DeJesus, A.F. Garcia; Regional Center for Infectious Disease, Greensboro, NC: K. Epperson, C.N. Van
Dam; San Antonio Military Health System, JBSA Fort Sam Houston, TX: J.F. Okulicz, T.J. Sjoberg; San
Juan Hospital, San Juan, PR: M. Acevedo, L. Angeli; St. Jude Children's Research Hospital, Memphis,
TN: P.M. Flynn, N. Patel; Temple University, Philadelphia, PA: C. Geisler, E. Tedaldi; Texas Children's
Hospital- Baylor College of Medicine, Houston, TX: C. McMullen-Jackson, W.T. Shearer; The Research
& Education Group, Portland, OR: M.D. Murphy, S.M. Sweek; Tulane University Health Sciences
Center, New Orleans, LA: D. Mushatt, C. Scott; UCLA CARE 4 Families, Los Angeles, CA: M. Carter,
J. Deville; UCSD Mother-Child-Adolescent HIV Program, San Diego, CA: S.A. Spector, L. Stangl;
University of Florida, Department of Pediatrics, Jacksonville, FL: M.H. Rathore, K. Thoma; University of
Florida, Jacksonville, FL: M. Sands, N. Wilson; University of Illinois at Chicago, Chicago, IL: R.M.
Novak, T. Pearson; University of Miami, Miami, FL: M.A. Kolber, T. Tanner; University of North
Carolina, Chapel Hill, NC: M. Chicurel-Bayard, E. Hoffman; University of North Texas Health Science
Center, Fort Worth, TX: I. Vecino, S.E. Weis; University of Puerto Rico, San Juan, PR: I. Boneta, J.
Santana; University of Texas Southwestern Medical Center, Dallas, TX: M.K. Jain, M. Santos; Veterans
by guest on May 23, 2017 from
Affairs Greater LA Healthcare System, Los Angeles, CA: M.B. Goetz, W.L. Rossen; Virginia
Commonwealth University, Richmond, VA: D. Nixon, V. Watson; Wake County Human Services,
Raleigh, NC: D. Currin, C. Kronk; Wake Forest University Health Sciences, Winston-Salem, NC: L.
Mosley, A. Wilkin; Washington DC Veterans Administration, Washington, DC: A.M. Labriola, D.W.
Thomas; Yale University School of Medicine, New Haven, CT: D. Chodkowski, G. Friedland.
by guest on May 23, 2017 from
Timing of Antiretroviral Treatment) Study Group (Strategicthe INSIGHT (International Network for Strategic Initiatives in Global HIV Trials) START
Siegfried Schwarze, Elsayed Z. Soliman, Stephen A. Spector, Giuseppe Tambussi, Jens Lundgren and
Daniel Duprez, Sean Emery, Brian Gazzard, Jonathan Gordin, Greg Grandits, Andrew N. Phillips,
Jason V. Baker, Shweta Sharma, Amit C. Achhra, Jose Ignacio Bernardino, Johannes R. Bogner,
Timing of Antiretroviral Treatment) Trial
Positive Participants in the START (StrategicAntiretroviral Therapy Initiation Among HIV Changes in Cardiovascular Disease Risk Factors With Immediate Versus Deferred
Online ISSN: 2047-9980
Dallas, TX 75231
is published by the American Heart Association, 7272 Greenville Avenue,Journal of the American Heart AssociationThe doi: 10.1161/JAHA.116.004987
2017;6:e004987; originally published May 22, 2017;J Am Heart Assoc.
World Wide Web at:
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by guest on May 23, 2017 from
... Für die Beantwortung dieser beispielhaften Frage gibt es verschiedene Ansätze: 1. Ein RCT kann die verschiedenen dynamischen Behandlungsstrategien vergleichen [1]. Bei absoluter Therapie-Compliance und ohne "loss to follow-up" ist die Analyse von RCT ...
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Background Treatment decisions that are dependent on if–then rules on disease status or prior treatment information are dynamic treatment decisions. The effectiveness of dynamic treatment strategies is often investigated with real-world data (RWD). As many different therapy strategies can be observed in routine practice, RWD offer great potential. However, RWD are always associated with risks for several biases including immortal time and selection bias.Objectives This article shows how to adequately compare dynamic treatment strategies and identify the optimal strategy. A case study is used to illustrate the causal approach described above.Materials and methodsWe describe how the combination of three counterfactual approaches allows causal interpretation of results. We describe causal diagrams, target trial emulation, and g-methods. The described causal approach is illustrated by a case study examining when antiviral therapy should be initiated in treatment-naïve patients with human immunodeficiency virus (HIV) infection.ResultsCausal diagrams visualize underlying causal processes. They help to identify parameters that need to be considered in the analysis. Target trial emulation simulates a randomized clinical trial by defining all possible dynamic strategies, copying (“cloning”) patient data, and assigning each patient to each treatment arm. In a causal per protocol analysis, all patients violating the protocol of a given treatment strategy are censored. Informative censoring is adjusted by g-methods. The expected outcomes of each treatment strategy are simulated and compared.Conclusions Dynamic treatment strategies can be adequately compared using RWD when three causal approaches are combined, and the necessary data are available. These approaches are (1) causal diagrams, (2) target trial emulation, and (3) statistical g-methods.
... Furthermore, there have been changes in the characteristics of pregnant WLWH, including increasing maternal age, a growing number with vertically acquired HIV and a decreasing proportion born in sub-Saharan Africa [11,12]. The implications of lifelong treatment for non-pregnant populations may include increased risk of diabetes [13,14] and cardiovascular disease [15,16], but findings on the effect of treatment in pregnancy, particularly protease inhibitors (PIs), on GD risk have been inconsistent [17][18][19][20]. Using population-based data from the UK and Ireland from 2010 to 2020, our aim was to describe the prevalence of GD in WLWH, assess associated maternal risk factors and examine specific birth outcomes of pregnancies affected by GD. ...
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Introduction: The prevalence of gestational diabetes (GD) is increasing globally. While universal risk factors for GD are reasonably well understood, questions remain regarding risks for women living with HIV (WLWH). We aimed to describe GD prevalence, evaluate associated maternal risk factors and assess specific birth outcomes in WLWH in the UK and Ireland. Methods: We analysed all pregnancies (≥24 weeks' gestation) in women diagnosed with HIV before delivery, reported to the UK-based Integrated Screening Outcomes Surveillance Service between 2010 and 2020. Every report of GD was considered as a case. A multivariable logistic regression model, adjusted for women with more than one pregnancy fitted with generalized estimating equations (GEE) assessed the effect of independent risk factors. Results: There were 10,553 pregnancies in 7916 women, of which 460 (4.72%) pregnancies had reported GD. Overall, the median maternal age was 33 years (Q1:29-Q3:37), and 73% of pregnancies were in Black African women. WLWH with GD (WLWH-GD) were older (61% vs. 41% aged ≥35 years, p < 0.001) and more likely to be on treatment at conception (74% vs. 64%, p < 0.001) than women without GD. WLWH-GD were more likely to have a stillbirth (odds ratio [OR]: 5.38, 95% CI: 2.14-13.5), preterm delivery (OR: 2.54, 95% CI: 1.95-3.32) and fetal macrosomia (OR: 1.14, 95% CI: 1.04-1.24). Independent risk factors for GD included estimated year of delivery (GEE-adjusted odds ratio [GEE-aOR]: 1.14, 95% CI: 1.10-1.18), advanced maternal age (≥35 years) (GEE-aOR: 2.87, 95% CI: 1.54-5.34), Asian (GEE-aOR: 2.63, 95% CI: 1.40-4.63) and Black African (GEE-aOR: 1.55, 95% CI: 1.13-2.12) ethnicity. Timing and type of antiretroviral therapy showed no evidence of a relationship with GD in multivariable analyses; however, women with a CD4 count ≤350 cells/μl were 27% less likely to have GD than women with CD4 counts >350 cells/μl (GEE-aOR: 0.73, 95% CI: 0.50-0.96). Conclusions: GD prevalence increased over time among WLWH but was not significantly different from the general population. Maternal age, ethnicity and CD4 count were risk factors based on available data. Stillbirth and preterm delivery were more common in WLWH-GD than other WLWH over the study period. Further studies are required to build upon these results.
... The analysis of 3 large international HIV treatment trials suggested that higher interleukin 6 and D-dimer levels reflecting inflammation and coagulation associated with HIV are also associated with an increased risk of fatal CVD and a greater risk of death following a nonfatal CVD event [3]. Recent publications linked CVD with inflammation and antiretroviral treatment associated with HIV [4,5]. Furthermore, risk factors of coronary heart disease (eg, smoking, diet) as well as nontraditional risk factors (eg, hepatitis C, substance use) should also be considered in persons with HIV [5,6]. ...
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Background: Approximately every 36 seconds someone in the United States dies of cardiovascular disease (CVD). It has emerged as an important contributor to morbidity among persons with HIV. Black and Latinx sexual minority men are at higher risk of both HIV and CVD when compared to heterosexual, non-ethnic/minority men. Persons with HIV have a 1.5-to-2-time risk of CVD than HIV-negative persons. Data suggests that by the year 2030, an estimated 78% of persons with HIV will have cardiovascular disease. The relationship between HIV and CVD, in marginalized populations, is not well understood because overall awareness of HIV and CVD, as comorbid conditions, is low, which further heightens risk. This has created a critically pressing issue affecting underrepresented ethnic and racial populations with HIV and requires immediate efforts to mitigate risk. Objective: The purpose of this formative, mixed methods study is to use a community-engaged approach to map a behavioral intervention for cardiovascular disease prevention in Black and Latinx sexual minority men with HIV in New York City. Methods: Literature reviews focused on behavioral prevention studies using intervention mapping. In Aim 1, we will use qualitative interviews with HIV program managers and community members to understand facilitators and barriers to CVD prevention, chronic illnesses of concern, and early design elements needed for a web-based CVD prevention intervention. In Aim 2, we will conduct qualitative interviews and administer cross-sectional validated surveys with 30 Black and Latinx sexual minority men with HIV. We will assess illness perceptions of chronic conditions, such as HIV, hypertension, and diabetes. A total of 40 participants (program managers and community members) for Aims 1 and 2 will be enrolled to participate. To develop the protocol, we will follow steps 1 through 3 (needs assessment, change objectives, implementation strategy) of intervention mapping, using mixed methods. Results: The study was approved by New York University Institutional Review Board in February 2021 (IRB-FY2021-4772) and also by the Yale University Institutional Review Board in June 2022 (2000031577). Data collection is ongoing. We anticipate completing data collection on or before December 2022. Early analyses suggested concerns about illnesses outside of HIV and associate comorbid conditions, such as COVID-19 and Monkeypox. Additionally, we noted a strong interest in using a web-based platform for CVD prevention education. Conclusions: Web-based, behavioral, CVD prevention interventions may be promising modalities to closing the cardiovascular health disparities gap in Black and Latinx sexual minority men with HIV by extending the reach of prevention interventions using community informed approaches and technological modalities that have been underutilized in this population. Clinicaltrial:
... Our work also showed increased levels of markers of endothelial activation, especially VCAM-1 and ICAM-1, in HICs. These proteins are cellular adhesion molecules expressed in response to endothelial activation, and their increase was associated with HIV infection in other studies [28][29][30][31]92,93 . Here, we observed similar levels for both molecules between cART and VC, in contrast to studies that observed reduced levels in response to ART 30,92,93 , although similar to a recent study that observed only a slight alteration in individuals with viremia < 3000 copies/mL submitted for treatment 29 . ...
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HIV controllers (HICs) are models of HIV functional cure, although some studies have shown persistent inflammation and increased rates of atherosclerosis in HICs. Since immune activation/inflammation contributes to the pathogenesis of cardiovascular diseases (CVD), we evaluated clinical data and inflammation markers in HIV-1 viremic controllers (VC), elite controllers (EC), and control groups (HIV positive individuals with virological suppression by antiretroviral therapy—cART; HIV negative individuals—HIVneg) to assess whether they presented elevated levels of inflammation markers also associated with CVD. We observed the highest frequencies of activated CD8+ T cells in VCs, while EC and cART groups presented similar but slightly altered frequencies of this marker when compared to the HIVneg group. Regarding platelet activation, both HICs groups presented higher expression of P-selectin in platelets when compared to control groups. Monocyte subset analyses revealed lower frequencies of classical monocytes and increased frequencies of non-classical and intermediate monocytes among cART individuals and in EC when compared to HIV negative individuals, but none of the differences were significant. For VC, however, significant decreases in frequencies of classical monocytes and increases in the frequency of intermediate monocytes were observed in comparison to HIV negative individuals. The frequency of monocytes expressing tissue factor was similar among the groups on all subsets. In terms of plasma markers, VC had higher levels of many inflammatory markers, while EC had higher levels of VCAM-1 and ICAM-1 compared to control groups. Our data showed that VCs display increased levels of inflammation markers that have been associated with CVD risk. Meanwhile, ECs show signals of lower but persistent inflammation, comparable to the cART group, indicating the potential benefits of alternative therapies to decrease inflammation in this group.
... Analyses from selected populations and small cohorts have reported a higher risk of hypertension or elevated blood pressure (BP) in people living with HIV using INSTIs [21][22][23] despite evidence linking INSTI use with favourable lipid profiles [24][25][26] and lower levels of vascular disease markers [27]. Randomized controlled trials have also not reported a higher risk of hypertension in people living with HIV receiving INSTIs [28,29], although this has been investigated in few studies. In addition, the results from clinical trials may be inconclusive because of the highly selected participants and brief durations of follow-up. ...
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Objective: To compare the incidence of hypertension in people living with HIV receiving integrase strand transfer inhibitor (INSTI)-based antiretroviral therapy (ART) versus non-nucleoside reverse transcriptase inhibitors (NNRTIs) or boosted protease inhibitors (PIs) in the RESPOND consortium of HIV cohorts. Methods: Eligible people with HIV were aged ≥18 years who initiated a new three-drug ART regimen for the first time (baseline), did not have hypertension, and had at least two follow-up blood pressure (BP) measurements. Hypertension was defined as two consecutive systolic BP measurements ≥140 mmHg and/or diastolic BP ≥90 mmHg or initiation of antihypertensives. Multivariable Poisson regression was used to determine adjusted incidence rate ratios (aIRRs) of hypertension, overall and in those who were ART naïve or experienced at baseline. Results: Overall, 4606 people living with HIV were eligible (INSTIs 3164, NNRTIs 807, PIs 635). The median baseline systolic BP, diastolic BP, and age were 120 (interquartile range [IQR] 113-130) mmHg, 78 (70-82) mmHg, and 43 (34-50) years, respectively. Over 8380.4 person-years (median follow-up 1.5 [IQR 1.0-2.7] years), 1058 (23.0%) participants developed hypertension (incidence rate 126.2/1000 person-years, 95% confidence interval [CI] 118.9-134.1). Participants receiving INSTIs had a higher incidence of hypertension than those receiving NNRTIs (aIRR 1.76; 95% CI 1.47-2.11), whereas the incidence was no different in those receiving PIs (aIRR 1.07; 95% CI 0.89-1.29). The results were similar when the analysis was stratified by ART status at baseline. Conclusion: Although unmeasured confounding and channelling bias cannot be excluded, INSTIs were associated with a higher incidence of hypertension than were NNRTIs, but rates were similar to those of PIs overall, in ART-naïve and ART-experienced participants within RESPOND.
Modern antiretroviral therapy safely, potently, and durably suppresses human immunodeficiency virus (HIV) that, if left untreated, predictably causes acquired immunodeficiency syndrome (AIDS), which has been responsible for tens of millions of deaths globally since it was described in 1981. In one of the most extraordinary medical success stories in modern times, a combination of pioneering basic science, innovative drug development, and ambitious public health programming resulted in access to lifesaving, safe drugs, taken as an oral tablet daily, for most of the world. However, substantial challenges remain in the fields of prevention, timely access to diagnosis, and treatment, especially in pediatric and adolescent patients. As HIV-positive adults age, treating their comorbidities will require understanding the course of different chronic diseases complicated by HIV-related and antiretroviral toxicities and finding potential treatments. Finally, new long-acting antiretrovirals on the horizon promise exciting new options in both the prevention and treatment fields.
Human immunodeficiency virus (HIV) infection represents a major cardiovascular risk factor and the cumulative cardiovascular disease (CVD) burden among ageing people living with HIV (PLWH) constitutes a leading cause of morbidity and mortality. To date, CVD risk assessment in PLWH still remains challenging. Therefore, it is necessary to evaluate and stratify the cardiovascular risk in PLWH with appropriate screening and risk assessment tools and protocols, in order to correctly identify which patients are at a higher risk for CVD and will benefit most from prevention measures and timely management. This review aims to accumulate the current evidence on the association between HIV infection and CVD, as well as the risk factors contributing to CVD in PLWH. Furthermore, considering the need for cardiovascular risk assessment in daily clinical practice, the purpose of this review is also to report the current practices and novel perspectives in cardiovascular risk assessment of PLWH and provide further insights in the development and implementation of appropriate CVD risk stratification and treatment strategies, especially in countries with high HIV burden and limited resources.
Background HIV induces several metabolic derangements that contribute to cardiovascular disease, but it is unclear if HIV increases diabetes or hypertension risk. Refining longitudinal relationships between HIV-specific factors and cardiovascular disease risk factors across different care settings may help inform cardiovascular disease prevention among people with HIV (PWH). Methods We tested the hypothesis that long-term higher cumulative viral load (viremia-copy-year) is associated with higher risk of diabetes and hypertension by analyzing electronic records of PWH from 2 distinct health systems in Chicago (Northwestern Medicine and Howard Brown Health Care) receiving care in 2004 to 2019. We used joint longitudinal-survival models to assess multivariable-adjusted associations. Subgroup analyses per site were also conducted. Results We observed 230 (3.0%) incident diabetes cases in 7628 PWH without baseline diabetes and 496 (6.7%) hypertension cases in 7450 PWH without baseline hypertension. Pooled analysis showed a direct association of viremia-copy-year with incident hypertension (hazards ratio, 1.20 [95% CI, 1.14–1.26]) but not with diabetes (hazards ratio, 1.03 [95% CI, 0.96–1.10]). However, site-specific differences existed whereby the Northwestern-only analysis demonstrated a significant association of viremia-copy-year with hypertension (hazards ratio, 1.29 [95% CI, 1.08–1.32]). Additionally, higher social deprivation index (both sites) and diagnosis of mental health disorder (Howard Brown Health only) was associated with higher diabetes and hypertension risk. Conclusions Cumulative viral load may be associated with incident hypertension among PWH. Associations of HIV control with cardiovascular disease risk factors among PWH may differ by health care system context.
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Tissue factor (TF) is a procoagulant protein released from activated host cells, such as monocytes, and tumor cells on extracellular vesicles (EVs). TF + EVs are observed in the circulation of patients with various types of diseases. In this review, we will summarize the association between TF + EVs and activation of coagulation and survival in different types of diseases, including cancer, sepsis, and infections with different viruses, such as human immunodeficiency virus (HIV), influenza A virus (IAV), and severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). We will also discuss the source of TF + EVs in various diseases. EVTF activity is associated with thrombosis in pancreatic cancer patients and coronavirus disease 2019 patients (COVID‐19) and with disseminated intravascular coagulation in cancer patients. EVTF activity is also associated with worse survival in patients with cancer and COVID‐19. Monocytes are the major sources of TF + EVs in sepsis, and viral infections, such as HIV, Ebola virus, and SARS‐CoV‐2. In contrast, alveolar epithelial cells are the major source of TF + EVs in bronchoalveolar lavage fluid in COVID‐19 and influenza A patients. These studies indicate that EVTF activity could be used as a biomarker to identify patients that have an increased risk of coagulopathy and mortality.
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Background. Efavirenz (EFV), an antiretroviral medication used to treat human immunodeficiency virus (HIV) infection, can increase lipid levels. Because hyperlipidemia is associated with increased risk for cardiovascular (CV) events, this study compared the risk of CV events in patients initiating EFV-containing vs EFV-free antiretroviral regimens. Methods. Antiretroviral-naive HIV-positive (HIV+) patients ages 18–64 were selected from commercial and Medicaid insurance claims databases. Patients with ≥1 claim for antiretroviral medications between January 1, 2007 and December 31, 2013 were classified into 2 cohorts: EFV-containing or EFV-free regimens. Patients were required to have 6 months of continuous enrollment before initiation, with no evidence of a CV event during this time. Patients were observed from initiation until the occurrence of a CV event, disenrollment, or study end. Cardiovascular events were identified through diagnosis or procedure codes for myocardial infarction, stroke, percutaneous coronary intervention, or coronary artery bypass graft. We calculated unadjusted incidence rates (IRs) and fit propensity-score-weighted Cox proportional hazards models. Results. There were 22 212 patients (11 978 EFV-containing and 10 234 EFV-free) identified in the commercial database and 7400 patients identified (2943 EFV-containing and 4457 EFV-free) in the Medicaid database. Cardiovascular events were rare (commercial IR = 396 per 100 000 person-years; Medicaid IR = 973 per 100 000 person-years). In propensity-score-weighted models, hazards of CV events were significantly lower for EFV-containing regimens in the commercial database (hazard ratio [HR] = 0.68; 95% confidence interval [CI], .49–.93) No significant difference was found in the Medicaid database (HR = 0.83; 95% CI, .58–1.19). Conclusions. This analysis found no evidence of increased risk of CV events among HIV+ patients initiating EFV-containing regimens.
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Background: Fat gain after antiretroviral therapy (ART) occurs, and its association with protease inhibitors (PIs) has been questioned. Methods: Peripheral and central fat depots, and lean mass were measured using standardized and centrally read CT scan of abdomen and whole body DXA scan over 96 weeks in HIV-infected treatment-naive participants randomized to tenofovir-emtricitabine (TDF/FTC) plus atazanavir-ritonavir (ATV/r), darunavir-ritonavir (DRV/r), or raltegravir (RAL) in ACTG A5260s, a substudy of A5257. Within arm changes were assessed with signed-rank tests. The 96-week percentage changes in fat and lean mass in the two PI arms were not different, thus outcomes for the PI arms were combined and compared to the RAL arm. Associations between baseline biomarkers and changes in body composition were assessed. All analyses used linear regression models. Results: 328 were randomized; 90% were male and 44% white non-Hispanic; at entry, median age was 36 years, HIV-1 RNA 4.6 log10 copies/mL, and CD4 349 cells/μL. Overall, at week 96, increases in limb fat (13.4%), subcutaneous (19.9%) and visceral abdominal fat (25.8%), trunk fat (18%), and lean mass (1.8%) were apparent (p<0.001 for changes within each arm). Changes for all fat and lean outcomes were not different between the PI arms, or between the RAL and the combined PI arms. Higher baseline HIV-1 RNA levels were associated with greater gains in peripheral and central fat. Conclusions: In treatment-naïve participants initiating ART with TDF/FTC, no differences in lean mass, and regional fat were found with RAL when compared to ATV/r or DRV/r over 96 weeks.
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Background: Data from randomized trials are lacking on the benefits and risks of initiating antiretroviral therapy in patients with asymptomatic human immunodeficiency virus (HIV) infection who have a CD4+ count of more than 350 cells per cubic millimeter. Methods: We randomly assigned HIV-positive adults who had a CD4+ count of more than 500 cells per cubic millimeter to start antiretroviral therapy immediately (immediate-initiation group) or to defer it until the CD4+ count decreased to 350 cells per cubic millimeter or until the development of the acquired immunodeficiency syndrome (AIDS) or another condition that dictated the use of antiretroviral therapy (deferred-initiation group). The primary composite end point was any serious AIDS-related event, serious non-AIDS-related event, or death from any cause. Results: A total of 4685 patients were followed for a mean of 3.0 years. At study entry, the median HIV viral load was 12,759 copies per milliliter, and the median CD4+ count was 651 cells per cubic millimeter. On May 15, 2015, on the basis of an interim analysis, the data and safety monitoring board determined that the study question had been answered and recommended that patients in the deferred-initiation group be offered antiretroviral therapy. The primary end point occurred in 42 patients in the immediate-initiation group (1.8%; 0.60 events per 100 person-years), as compared with 96 patients in the deferred-initiation group (4.1%; 1.38 events per 100 person-years), for a hazard ratio of 0.43 (95% confidence interval [CI], 0.30 to 0.62; P<0.001). Hazard ratios for serious AIDS-related and serious non-AIDS-related events were 0.28 (95% CI, 0.15 to 0.50; P<0.001) and 0.61 (95% CI, 0.38 to 0.97; P=0.04), respectively. More than two thirds of the primary end points (68%) occurred in patients with a CD4+ count of more than 500 cells per cubic millimeter. The risks of a grade 4 event were similar in the two groups, as were the risks of unscheduled hospital admissions. Conclusions: The initiation of antiretroviral therapy in HIV-positive adults with a CD4+ count of more than 500 cells per cubic millimeter provided net benefits over starting such therapy in patients after the CD4+ count had declined to 350 cells per cubic millimeter. (Funded by the National Institute of Allergy and Infectious Diseases and others; START number, NCT00867048.).
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Background. Metabolic effects following combination antiretroviral therapy (cART) vary by regimen type. Changes in metabolic effects were assessed following cART in the AIDS Clinical Trials Group (ACTG) A5257 study, and correlated with plasma ritonavir trough concentrations (C24). Methods. Treatment-naive adult subjects were randomized to ritonavir-boosted atazanavir or darunavir, or raltegravir-based cART. Changes in lipids and other metabolic outcomes over time were estimated. Differences between arms were estimated with 97.5% confidence intervals and compared using pairwise Student t tests. Associations between ritonavir C24 and lipid changes at week 48 were evaluated via linear regression. Results. Analyses included 1797 subjects with baseline fasting data. Baseline lipid profiles and metabolic syndrome rates (approximately 21%) were similar across arms. Comparable increases occurred in total cholesterol, triglycerides, and low-density lipoprotein cholesterol with the boosted protease inhibitors (PIs); each PI had greater increases relative to raltegravir (all P ≤ .001 at week 96). Metabolic syndrome incident rates by week 96 (approximately 22%) were not different across arms. Ritonavir C24 was not different by arm (P = .89) (median, 69 ng/mL and 74 ng/mL in the atazanavir and darunavir arms, respectively) and were not associated with changes in lipid measures (all P > .1). Conclusions. Raltegravir produced the most favorable lipid profile. Metabolic syndrome rates were high at baseline and increased to the same degree in all arms. Ritonavir C24 was not different in the PI arms and had no relationship with the modest but comparable increases in lipids observed with either atazanavir or darunavir. The long-term clinical significance of the lipid changes noted with the PIs relative to raltegravir deserves further evaluation. Clinical Trials Registration. NCT 00811954.
Context Three major coronary risk factors—serum cholesterol level, blood pressure, and smoking—increase incidence of coronary heart disease (CHD) and related end points. In previous investigations, risks for low-risk reference groups were estimated statistically because samples contained too few such people to measure risk.Objective To measure long-term mortality rates for individuals with favorable levels for all 3 major risk factors, compared with others.Design Two prospective studies, involving 5 cohorts based on age and sex, that enrolled persons with a range of risk factors. Low risk was defined as serum cholesterol level less than 5.17 mmol/L (<200 mg/dL), blood pressure less than or equal to120/80 mm Hg, and no current cigarette smoking. All persons with a history of diabetes, myocardial infarction (MI), or, in 3 of 5 cohorts, electrocardiogram (ECG) abnormalities, were excluded.Setting and Participants In 18 US cities, a total of 72,144 men aged 35 through 39 years and 270,671 men aged 40 through 57 years screened (1973-1975) for the Multiple Risk Factor Intervention Trial (MRFIT); in Chicago, a total of 10,025 men aged 18 through 39 years, 7490 men aged 40 through 59 years, and 6229 women aged 40 through 59 years screened (1967-1973) for the Chicago Heart Association Detection Project in Industry (CHA) (N = 366,559).Main Outcome Measures Cause-specific mortality during 16 (MRFIT) and 22 (CHA) years, relative risks (RRs) of death, and estimated greater life expectancy, comparing low-risk subcohorts vs others by age strata.Results Low-risk persons comprised only 4.8% to 9.9% of the cohorts. All 5 low-risk groups experienced significantly and markedly lower CHD and cardiovascular disease death rates than those who had elevated cholesterol level, or blood pressure, or smoked. For example, age-adjusted RRs of CHD mortality ranged from 0.08 for CHA men aged 18 to 39 years to 0.23 for CHA men aged 40 through 59 years. The age-adjusted relative risks (RRs) for all cardiovascular disease mortality ranged from 0.15 for MRFIT men aged 35 through 39 years to 0.28 for CHA men aged 40 through 59 years. The age-adjusted RR for all-cause mortality rate ranged from 0.42 for CHA men aged 40 through 59 years to 0.60 for CHA women aged 40 through 59 years. Estimated greater life expectancy for low-risk groups ranged from 5.8 years for CHA women aged 40 through 59 years to 9.5 years for CHA men aged 18 through 39 years.Conclusions Based on these very large cohort studies, for individuals with favorable levels of cholesterol and blood pressure who do not smoke and do not have diabetes, MI, or ECG abnormalities, long-term mortality is much lower and longevity is much greater. A substantial increase in the proportion of the population at lifetime low risk could contribute decisively to ending the CHD epidemic.
BACKGROUND: Despite declines in morbidity and mortality with the use of combination antiretroviral therapy, its effectiveness is limited by adverse events, problems with adherence, and resistance of the human immunodeficiency virus (HIV). METHODS: We randomly assigned persons infected with HIV who had a CD4+ cell count of more than 350 per cubic millimeter to the continuous use of antiretroviral therapy (the viral suppression group) or the episodic use of antiretroviral therapy (the drug conservation group). Episodic use involved the deferral of therapy until the CD4+ count decreased to less than 250 per cubic millimeter and then the use of therapy until the CD4+ count increased to more than 350 per cubic millimeter. The primary end point was the development of an opportunistic disease or death from any cause. An important secondary end point was major cardiovascular, renal, or hepatic disease. RESULTS: A total of 5472 participants (2720 assigned to drug conservation and 2752 to viral suppression) were followed for an average of 16 months before the protocol was modified for the drug conservation group. At baseline, the median and nadir CD4+ counts were 597 per cubic millimeter and 250 per cubic millimeter, respectively, and 71.7% of participants had plasma HIV RNA levels of 400 copies or less per milliliter. Opportunistic disease or death from any cause occurred in 120 participants (3.3 events per 100 person-years) in the drug conservation group and 47 participants (1.3 per 100 person-years) in the viral suppression group (hazard ratio for the drug conservation group vs. the viral suppression group, 2.6; 95% confidence interval [CI], 1.9 to 3.7; P<0.001). Hazard ratios for death from any cause and for major cardiovascular, renal, and hepatic disease were 1.8 (95% CI, 1.2 to 2.9; P=0.007) and 1.7 (95% CI, 1.1 to 2.5; P=0.009), respectively. Adjustment for the latest CD4+ count and HIV RNA level (as time-updated covariates) reduced the hazard ratio for the primary end point from 2.6 to 1.5 (95% CI, 1.0 to 2.1). CONCLUSIONS: Episodic antiretroviral therapy guided by the CD4+ count, as used in our study, significantly increased the risk of opportunistic disease or death from any cause, as compared with continuous antiretroviral therapy, largely as a consequence of lowering the CD4+ cell count and increasing the viral load. Episodic antiretroviral therapy does not reduce the risk of adverse events that have been associated with antiretroviral therapy.
Background: Limited data compare once-daily options for initial therapy for HIV-1. Objective: To compare time to virologic failure; first grade-3 or -4 sign, symptom, or laboratory abnormality (safety); and change or discontinuation of regimen (tolerability) for atazanavir plus ritonavir with efavirenz-containing initial therapy for HIV-1. Design: A randomized equivalence trial accrued from September 2005 to November 2007, with median follow-up of 138 weeks. Regimens were assigned by using a central computer, stratified by screening HIV-1 RNA level less than 100 000 copies/mL or 100 000 copies/mL or greater; blinding was known only to the site pharmacist. ( registration number: NCT00118898) Setting: 59 AIDS Clinical Trials Group sites in the United States and Puerto Rico. Patients: Antiretroviral-naive patients. Intervention: Open-label atazanavir plus ritonavir or efavirenz, each given with with placebo-controlled abacavir-lamivudine or tenofovir disoproxil fumarate (DF)-emtricitabine. Measurements: Primary outcomes were time to virologic failure, safety, and tolerability events. Secondary end points included proportion of patients with HIV-1 RNA level less than 50 copies/mL, emergence of drug resistance, changes in CD4 cell counts, calculated creatinine clearance, and lipid levels. Results: 463 eligible patients were randomly assigned to receive atazanavir plus ritonavir and 465 were assigned to receive efavirenz, both with abacavir-lamivudine; 322 (70%) and 324 (70%), respectively, completed follow-up. The respective numbers of participants in each group who received tenofovir DF-emtricitabine were 465 and 464; 342 (74%) and 343 (74%) completed follow-up. Primary efficacy was similar in the group that received atazanavir plus ritonavir and and the group that received efavirenz and did not differ according to whether abacavir-lamivudine or tenofovir DF-emtricitabine was also given. Hazard ratios for time to virologic failure were 1.13 (95% CI, 0.82 to 1.56) and 1.01 (CI, 0.70 to 1.46), respectively, although CIs did not meet prespecified criteria for equivalence. The time to safety (P = 0.048) and tolerability (P < 0.001) events was longer in persons given atazanavir plus ritonavir than in those given efavirenz with abacavir-lamivudine but not with tenofovir DF-emtricitabine. Limitations: Neither HLA-B*5701 nor resistance testing was the standard of care when A5202 enrolled patients. The third drugs, atazanavir plus ritonavir and efavirenz, were open-label; the nucleoside reverse transcriptase inhibitors were prematurely unblinded in the high viral load stratum; and 32% of patients modified or discontinued treatment with their third drug. Conclusion: Atazanavir plus ritonavir and efavirenz have similar antiviral activity when used with abacavir-lamivudine or tenofovir DF-emtricitabine. Primary funding source: National Institutes of Health.
Given conflicting data regarding the association of HIV infection and ischemic stroke risk, we sought to determine whether HIV infection conferred an increased ischemic stroke risk among male veterans. The Veterans Aging Cohort Study-Virtual Cohort consists of HIV-infected and uninfected veterans in care matched (1:2) for age, sex, race/ethnicity, and clinical site. We analyzed data on 76,835 male participants in the Veterans Aging Cohort Study-Virtual Cohort who were free of baseline cardiovascular disease. We assessed demographics, ischemic stroke risk factors, comorbid diseases, substance use, HIV biomarkers, and incidence of ischemic stroke from October 1, 2003, to December 31, 2009. During a median follow-up period of 5.9 (interquartile range 3.5-6.6) years, there were 910 stroke events (37.4% HIV-infected). Ischemic stroke rates per 1,000 person-years were higher for HIV-infected (2.79, 95% confidence interval 2.51-3.10) than for uninfected veterans (2.24 [2.06-2.43]) (incidence rate ratio 1.25 [1.09-1.43]; p < 0.01). After adjusting for demographics, ischemic stroke risk factors, comorbid diseases, and substance use, the risk of ischemic stroke was higher among male veterans with HIV infection compared with uninfected veterans (hazard ratio 1.17 [1.01-1.36]; p = 0.04). HIV infection is associated with an increased ischemic stroke risk among HIV-infected compared with demographically and behaviorally similar uninfected male veterans. © 2015 American Academy of Neurology.