Daniel Lee, M.D., of UC San Diego Owen Clinic, presents "Update from the 15th International Workshop on Co-Morbidities and Adverse Drug Reactions in HIV"
Top Rated Hyderabad Call Girls Chintal ⟟ 9332606886 ⟟ Call Me For Genuine Se...
Update from the 15th International Workshop on Co-Morbidities and Adverse Drug Reactions in HIV
1. AIDS CLINICAL ROUNDS
The UC San Diego AntiViral Research Center sponsors weekly
presentations by infectious disease clinicians, physicians and
researchers. The goal of these presentations is to provide the most
current research, clinical practices and trends in HIV, HBV, HCV, TB
and other infectious diseases of global significance.
The slides from the AIDS Clinical Rounds presentation that you are
about to view are intended for the educational purposes of our
audience. They may not be used for other purposes without the
presenter’s express permission.
2. Daniel Lee, MD
Clinical Professor of Medicine
UCSD Medical Center – Owen Clinic
December 6th, 2013
3. BLACK BOX WARNING/DISCLAIMER
This talk represents my opinion based upon
my interpretation of the data and my clinical
observations and experience from seeing
patients in the Owen Clinic for the past 15+
years
4. Outline
• Aging
• Bone Disease
• Cardiovascular Disease
• Lipids
• Bonus
– 2013 ACC/AHA Guideline on Treatment of
Cholesterol to Reduce ASCVD Risk
7. Inflamm-ageing
• Inflammaging is a
multifactorial and
systemic process,
characterized by
complex interactions
• It is associated with the
progressive increase of
the inflammatory tone
with age, fostered by
“garbaging”
Franceschi C. 15th IWCADR in HIV. October 2013. Plenary 1.
Cevenini E, et al. Curr Opin Clin Nutr Metab Care 2013; 16: 14-20.
8. Inflamm-ageing
• Inflammaging is the pathological side of a physiological
phenomenon/program crucial for survival
• Inflammaging is triggered by “Garbaging”
• Garbaging includes a variety of “danger signals”
– Exogenous (viruses, bacteria including the gut microbiota)
– Endogenous (senescent cells, damaged organelles,
altered/modified proteins and N-glycans, mtDNA, ATP, ROS,
AGE, ceramides)
• Two fundamental and unavoidable activities (ie. eating
and moving) can generate danger signals
– Exercise may induce inflammation
Franceschi C. 15th IWCADR in HIV. October 2013. Plenary 1.
9. Gut Microbiota, Health, Disease, & Aging
• Gut microbiota is required for development of immunity
– Microbiota changes with age (early changes in life can
increase risk for immunological diseases later in life)
– Microbiota depends on diet diversity (changes in microbiota
seen in institutionalized elderly vs. community-based elderly)
Shanahan F. 15th IWCADR in HIV. October 2013. Plenary 2.
10. Effect of ARV Penetration into CNS on Incidence
of AIDS-Defining Neurologic Conditions
• Objective: to estimate the effect of the CPE score on
incidence of 4 AIDS-defining neurologic conditions
– HIV dementia, Toxoplasmosis, Cryptomeningitis, PML
• HIV-Causal Collaboration: prospective cohort from 6
European countries and the US
– ARV naïve at baseline
– No history of AIDS
– 55,814 individuals followed for a median of 31 months
•
35,402 – low CPE (4-7), 15,089 – medium CPE (8-9), 5,323 – high
CPE (10-16)
Caniglia EC. 15th IWCADR in HIV. October 2013. Oral 3.
CPE = CNS Penetrating Effectiveness
11. Effect of ARV Penetration into CNS on Incidence
of AIDS-Defining Neurologic Conditions
Caniglia EC. 15th IWCADR in HIV. October 2013. Oral 3.
CPE = CNS Penetrating Effectiveness
12. Effect of ARV Penetration into CNS on Incidence
of AIDS-Defining Neurologic Conditions
• Conclusions
– The incidence of HIV dementia (but not of other neuroAIDS
conditions) increases by more than 50% after initiating an
ARV regimen with a high CPE score compared with a low
score
• Limitations
– Incomplete adherence, confounding by indication, few
events, average followup <3 years, may not be generalizable
to resource-limited settings or to other health care systems,
diagnostic procedures reflect standard clinical practice rather
than standardized research criteria
Caniglia EC. 15th IWCADR in HIV. October 2013. Oral 3.
CPE = CNS Penetrating Effectiveness
13. Question #1
• Is aging a normal or an abnormal process (ie. disease) of life?
• 1.
Normal process
• 2.
Abnormal process
14. Question #2
• In regards to the concept of aging, what do you think is most
likely to cause aging
• 1.
Inflammation
• 2. Genetics (accumulation of damage to DNA, telomere
shortening, etc.)
• 3.
Mental Stress
• 4.
Other
15. Current State of Aging Research
• Multiple theories including biological and genetic theories
• Focused on evaluating the (distal) effects of aging on the
development of disease
– Brain (cognitive function)
– Physical body (physical function)
• Current thinking – for example, we can develop medications or
treatments to reduce inflammation associated with aging
• Does inflammation cause aging or is it just an association?
Inflammation
Aging or ??
Inflammation/Aging
• Are we thinking too distally?
• What causes aging to occur more proximally?
16. Mental Stress and Aging
• Mental stress can have a proximal effect on the brain and the
physical body
• Mental stress (in response to external or internal stimuli) in the form of
chronic negative thoughts and emotion (conscious and unconscious) may
trigger a cascade of physiologic changes in the brain and body, including
chronic activation of the stress response (↑cortisol/epinephrine), eventually
leading to a chronically overstimulated/inflammatory state which is cumulative
over one’s lifetime, and may lead to epigenetic changes, thus making a
person more susceptible to disease over time
17. HIV and Aging
• Many of our patients have had to deal with mental
stress from an early age
– Physical, mental, and/or sexual abuse by others
• Many of our patients have had difficulty coping with
these multiple stressors including their HIV dx
– Maladaptive coping strategies to escape from pain of life
•
Substance abuse (illicit drugs, EtOH, prescription drugs), sexual
addiction, overeating, etc.
•
Poor decision making
– Result in cumulatively high levels of stress, anxiety,
depression
• Is it surprising that HIV+ age quicker than HIV-?
20. ART and Loss of BMD – 1st Line ART
Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
21. ART and Loss of BMD – 2nd Line ART
Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
22. ART and Loss of BMD – Switching ART
Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
23. ART and Loss of BMD
Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
24. Pathogenesis of HIV and Low BMD
Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
25. Pathogenesis of HIV and Low BMD
Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
26. HIV Associated with High Bone Turnover
• All bone turnover markers (BTM) are increased in
HIV+ compared to HIV– Bone Formation
•
Osteocalcin
•
Procollagen type 1, N-terminal (P1NP)
– Bone Resorption
•
Collagen type 1 cross-linked C-telopeptide (CTX-1)
• Higher BTM correlate with lower BMD
• However, differences in BTM do not explain all of the
effect of HIV on BMD
Cotter AG, et al. IAS 2013. Abstract MOPE077.
27. HIV, Bone Turnover and ART Initiation
Adapted from Mallon PW. 15th IWCADR in HIV. Plenary 5.
28. ART Impact on Bone Mineral Density (BMD)
• In the 2 years after ART initiation, BMD decreases by 2-6%,
regardless of the ART regimen used1
•
•
•
Similar to the 2-year decline in BMD among women age 50-59 years in the
general population1
Associated with rapid increases in bone turnover markers, including markers of
bone resorption (eg. CTx) and markers of bone formation (eg. OC, P1NP)3,4
Markers of bone resorption increase earlier and to a greater extent than
markers of bone formation, creating a “catabolic window”4
• Some specific ART agents have independent effects on BMD
with ART initiation
•
Tenofovir DF (TDF) has been associated with independent decreases in BMD
with ART initiation and greater increases in bone turnover markers3,4
• It is unclear whether early changes in bone turnover markers
predict bone loss following ART initiation in treatment-naïve
patients
•
In the RADAR study, increases in bone turnover markers at 16 weeks were
associated with decreases in total BMD (tBMD) at 48 weeks in HIV+, ARTnaïve persons initiating TDF/FTC/DRV/r or TDF/FTC/RAL5
1. Clin Infect Dis. 2010; 51:937-46. 2. Antivir Ther. 2011; 16(7):1063-72. 3. Clin Infect Dis. 2010; 51(8):963-72. 4. 18th CROI.
2011. Abstract 833. 5. IAS 2013. Abstract WEPE512.
Adapted from Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
29. Changes in Bone Turnover Markers and
Association with Decreased Total BMD
• PROGRESS study: Randomized, open-label, multicenter trial
comparing the safety, tolerability, and antiviral activity of LPV/r +
RAL or LVP/r + TDF/FTC in HIV-infected ART-naïve subjects
– 206 patients were randomized and received LPV/r 400/100 mg BID with
RAL 400 mg BID or TDF/FTC 300/200 mg QD
• Objectives:
– To evaluate changes in bone turnover markers (BTM) in subjects
initiating LPV/r + RAL or LPV/r + TDF/FTC
•
Osteocalcin (OC), Type 1 C-terminus telopeptide (CTx), Procollagen type 1 propeptide
(P1NP), Bone-specific alkaline phosphatase (BSAP)
– To test whether there is an association between baseline BTM levels and
early changes from baseline (Wk 4 & 16), and clinically significant bone
loss at Wk 96 (ie. ≥5% decline in BMD)
Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
BMD = Bone Mineral Density
30. Changes in Total BMD Through 96 Weeks in
the PROGRESS Study
Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
tBMD = Total Bone Mineral Density
31. Mean (±SD) Absolute Changes from Baseline
in Bone Turnover Markers
Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
32. Proportion of Subjects with ≥5% Decrease
from Baseline in Total BMD at Week 96
Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
tBMD = Total Bone Mineral Density
33. Factors Associated with a ≥5% Decrease from
Baseline in Total BMD at Week 96
• Baseline factors independently associated (P<0.05) with reduced incidence
of a ≥5% decrease from baseline in total BMD at Week 96 were:
•
age <40 years
•
male gender
•
greater absolute change from baseline to Wk4 in P1NP
• Baseline factors independently associated (P<0.05) with increased incidence
of a ≥5% decrease from baseline in total BMD at Week 96 were:
•
White race
•
Baseline CD4+ T-cell count <200 cells/mm3
•
Higher baseline CTx
•
Greater absolute change from baseline to Wk4 in CTx (bone resorption)
•
Greater absolute change from baseline to Wk16 in P1NP and OC (bone
formation)
Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
tBMD = Total Bone Mineral Density
34. Changes in Bone Turnover Markers and
Association with Decreased Total BMD
• Conclusions
– In the setting of LPV/r, TDF/FTC had a greater effect on bone turnover with ART
initiation and was associated with a higher incidence of clinically significant bone
loss, compared to RAL
– Changes in bone turnover occurred very early after ART initiation
– Early increases in bone resorption markers with ART initiation predicted clinically
significant bone loss at 96 wks
– Early increases in bone formation markers (4 wks) protected against clinically
significant bone loss at 96 wks
– Taken together, these data provide evidence supporting the hypothesis that early
relative changes in markers of bone resorption and bone formation (i.e., the
catabolic window) are important predictors of bone loss in HIV-infected persons
initiating ART
– The mechanisms underlying this effect and the specific effects of the ART
components on bone turnover deserve further investigation
Brown, TT, et al. 15th IWCADR in HIV. October 2013. Oral 17.
BMD = Bone Mineral Density
35. BMD in AGEhIV Cohort Study
• Objectives:
– To assess the prevalence of osteopenia/osteoporosis in comparable cohorts of
HIV+ and HIV- individuals, aged ≥45 years
– To investigate associations between HIV and HIV-related characteristics and BMD
• AGEhIV Cohort in Amsterdam
– 597 HIV+ ≥45 years (Academic Medical Center, Amsterdam) - 75.2% MSM
– 551 HIV- ≥45 years (STD clinic of Municipal Health Service, Amsterdam)
– 2 yearly study visits, baseline measurement 2010-2012
• Demographics – several differences seen at baseline
– HIV+ group had more blacks, lower body weight, slightly lower BMI, more likely to
be current smokers with higher pack year history, more likely to be IDU, less
physical activity than HIV- group
– HIV+: median duration of HIV = 12.1 years, CD4 nadir 170, CD4 count = 570,
91.3% VL undetectable, 95% on ART, duration of ART use = 10.4 years
Kooij, KW, et al. 15th IWCADR in HIV. October 2013. Oral 18.
BMD = Bone Mineral Density
36. BMD in AGEhIV Cohort Study
Kooij, KW, et al. 15th IWCADR in HIV. October 2013. Oral 18.
BMD = Bone Mineral Density
37. BMD in AGEhIV Cohort Study
• Results/Summary:
– Prevalence of osteoporosis or low BMD for age was higher in HIV+ (14.4%) vs.
HIV- (8.1%), P=0.001
– After adjustment for age, gender, menopausal status, ethnicity, DXA software
changes, HIV infection remained significantly associated with lower femoral neck
(-0.020 g/cm2, P=0.02) and total hip BMD (-0.030 g/cm2, P=0.001)
•
Upon further adjustment for body weight and smoking, HIV+ status was no
longer independently associated with lower BMD in this largely MSM
population
– A strong interaction was observed between age and being MSM
•
In non-MSM, older age was associated with lower BMD
•
In MSM, younger MSM had lower BMD compared to older MSM and nonMSM of any age, irrespective of HIV status
– This could not be explained by any differences in behavior (including drug
use or Vit D)
– Reduced BMD was not independently associated with TDF use
Kooij, KW, et al. 15th IWCADR in HIV. October 2013. Oral 18.
BMD = Bone Mineral Density
38. Question #3
• In regards to the osteoporosis screening, what do you think is
most reflective of your clinical practice
• 1. I screen the majority of my patients for osteoporosis, but
only above the age of 50
• 2. I screen the majority of my patients for osteoporosis
regardless of age
• 3. I screen patients who I feel are at risk for osteoporosis, but
only if they are above the age of 50
• 4. I screen patients who I feel are at risk for osteoporosis,
regardless of the age of the patient
• 5.
I rarely screen patients for osteoporosis
• 6.
Insurance issues/costs prevent me from screening
39. Recommendations for BMD Screening:
HIV+ vs. HIV- Patient Populations
HIV+ Patient Population1
• All postmenopausal HIV+ women
(any age)
• All HIV+ men ≥50 years old
• Any HIV+ patient with a history
of fracture
HIV- Patient Population2
• Those with a history of fragility fracture
• Women ≥ 65 yrs, Men ≥ 70
• Women in the menopausal transition,
younger postmenopausal women, and
men 50-69, who have clinical risk factors
for low BMD/fracture
• Adults >50 who have experienced
a fracture
• Adults with a condition or taking a
medication associated with low bone
mass or bone loss
• Anyone being considered for or treated
for osteoporosis
1. McComsey GA, et al. Clin Infect Dis. 2010;51(8):937-46
2. NOF. Clinician’s Guide to Prevention and Treatment of Osteoporosis. 2010
40. Clinical Approach to Managing
Bone Disease in HIV (1)
Initial approach
HIV infected individual
Assess risk factors
Age
Sex
Weight/Height
History Of Fractures
Secondary causes
Indications for DXA
Lifestyle advice
Smoking cessation
Vitamin D and Calcium intake
Weight bearing exercise
Sun exposure
< 50 years ♂
PREmenopausal ♀
AND NO history of
fracture?
≥ 50 years ♂
POSTmenopausal ♀
AND/OR history of
fracture?
WAIT
Measure BMD by
DXA
McComsey GA, et al. Clin Infect Dis. 2010;51(8):937-46
41. Clinical Approach to Managing
Bone Disease in HIV (2)
Work-up
T-Score ≤ -2.5
OR fragility fracture
Evaluate potential
secondary
causes identified in
history
(Table 2)
Secondary cause
Treatment
Yes
Treat secondary cause
T-Score > -2.5 and ≤ -1
NO fragility fracture
T-Score > -1
NO fragility fracture
Consider
Calculate FRAX score
10 year fracture risk
(USA)
≥ 20% major
osteoporotic
AND/OR
≥ 3% hip
No
Yes
Lifestyle advice
Continue ART
No
Lifestyle advice
Continue ART
Consider
Biphosphonate
or other treatment
Follow-up
McComsey GA, et al. Clin Infect Dis. 2010;51(8):937-46
Monitor DXA in 1-2
years
Monitor DXA in 2-5
years
44. Clinical Impact of New Data From ICAAC, IDWeek, and EACS 2013
clinicaloptions.com/hiv
D:A:D Updated Models of Global CVD
Risk/Comparison With Framingham
Retrospective analysis of 32,663 HIV+ persons from
20 countries in Europe and Australia with
– No CVD disease at entry to study, and
– Data on CVD risk factors
1010 CVD events in 186,364.5 PY → overall rate of 5.42/1000 PY
(95% CI: 5.09-5.76)
Prior study – overall rate was 3.3/1000 PY
– Includes MI (n = 493); stroke (n = 295); angioplasty (n = 129); bypass
(n = 44); other CVD death (n = 36); carotid endarterectomy (n = 13)
– 2 D:A:D models used (1 including exposure to certain ARV agents)
and compared with Framingham model
Friis-Møller N, et al. EACS 2013. Abstract PS1/3.
45. Clinical Impact of New Data From ICAAC, IDWeek, and EACS 2013
clinicaloptions.com/hiv
D:A:D HRs of CVD Risk Using 3 Models
Risk Factor
Unit
D:A:D
+ ARVs
D:A:D
-ARVs
Framingham
(Males Only)
Age
Linear
22.0
24.0
21.4
Sex
M/F
1.37
1.41
N/A
Diabetes
Y/N
1.96
2.08
1.78
Smoking
Current
Former
2.25
1.24
2.26
1.27
1.92
TC
HDL-C
Linear
2.58
0.61
2.98
0.59
3.08
0.39
Systolic BP
Linear
4.59
4.56
6.91
7.38*
Family hx CVD
Y/N
1.37
1.39
CD4+ cell count
2-fold higher
0.89
0.89
ABC, current
Y/N
1.47
PI, cumulative
Yrs
1.05
NRTI, cumulative
Yrs
1.03
Friis-Møller N, et al. EACS 2013. Abstract PS1/3. Reproduced with permission.
*If treated.
46. Clinical Impact of New Data From ICAAC, IDWeek, and EACS 2013
clinicaloptions.com/hiv
D:A:D Summary of Key Conclusions
Classic CVD risk factors
important in HIV+ pts
5-Yr CVD Risk by
Age and Diabetes Status
Framingham model
D:A:D reduced model
D:A:D full model
Observed Kaplan-Meier
Risk related to current use of
ABC lower than previous
estimates
– HR: 1.47 vs no current ABC
use
Estimated 5-Yr Risk, %
Framingham appears to
underestimate risk compared
with D:A:D models
12
10
8
6
4
2
0
Prior study – HR was 1.63
Friis-Møller N, et al. EACS 2013. Abstract PS1/3. Reproduced with permission.
49. Metabolic Substudy of iPrEx
• iPrEx Study – international randomized, double-blind,
placebo controlled trial of FTC/TDF in MSM
– 2499 participants enrolled at 11 clinical sites
– ITT analysis: randomization to FTC/TDF decreased HIV
acquisition by 44% (P=0.005)
– Plasma or intracellular drug was detected in 51% on FTC/TDF
• Metabolic substudy: opt-in substudy at 7 sites in 5 cities
– Target enrollment = 500 (~20% of parent study)
– Assessments at study entry and q6months
•
Fasting lipids
•
DXA
Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
50. No Differences in Baseline Lipids - iPrEx
Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
51. Metabolic Substudy of iPrEx - Results
Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
53. Metabolic Substudy of iPrEx
• Conclusions:
– In HIV-seronegative men taking FTC/TDF for PrEP, there were
small but statistically significant across-the-board decreases in
cholesterol
– Changes were most pronounced at week 24 and tended to
rebound by week 72
– Among those randomized to active drug, the changes were
evident only in those with detectable drug levels
– TG tended to increase over time in all groups but differences
among groups were not significant
– These changes could not be explained by baseline weight or
changes in weight or fat or GI symptoms during treatment
Mulligan K. 15th IWCADR in HIV. October 2013. Oral 5.
54. STaR Study: Single Tablet Regimen
Rilpivirine/Emtricitabine/Tenofovir DF Maintains NonInferiority to Efavirenz/Emtricitabine/Tenofovir DF and Has
Minimal Impact on Fasting Lipids in ART-Naïve Adults
Week 96 Results
Calvin Cohen1, David Wohl2, Jose Arribas3, Keith Henry4, Jan van Lunzen5,
Mark Bloch6, William Towner7, Edmund Wilkins8, Ramin Ebrahimi9,
Danielle Porter9, Shampa De-Oertel9, Todd Fralich9, Kathy Melbourne9
1Community
Research Initiative of New England, Boston, Massachusetts USA; 2University of North Carolina at Chapel Hill, Chapel
Hill, North Carolina USA; 3Hospital Universitario, La Paz, Madrid, Spain; 4 HIV Program Hennepin County Medical Center,
Minneapolis, Minnesota, USA; 5University Medical Center Hamburg-Eppendorf, Hamburg, Germany; 6Holdsworth House Medical
Practice, Darlinghurst, NSW Australia; 7Department of Infectious Disease Kaiser Los Angeles Medical Center, Los Angeles,
California, USA; 8North Manchester General Hospital, Manchester, United Kingdom; 9Gilead Sciences, Foster City, California, USA
15th International Workshop on Co-morbidities and
Adverse Drug Reactions in HIV
Brussels, Belgium
15 October 2013
Clinical trial number: GS-US-264-0110 Clinical Trials.gov: NCT01309243
55. STaR
Study Design
Multicenter, international, randomized, open-label, Phase 3b, 96-week study
n=394
ARV-naive
HIV-1 RNA ≥2500 c/mL
Sensitivity to EFV, FTC, RPV, TDF
(N=786)
Stratified by HIV RNA (≤ or >100,000 c/mL)
RPV/FTC/TDF
STR
1:1
n=392
EFV/FTC/TDF
STR
48 Weeks
Primary Endpoint
Primary endpoint:
Secondary endpoints:
Cohen C, et al. 15th IWCADR in HIV.
October 2013. Oral Presentation O6.
96 Weeks
Efficacy of the 2 STRs by proportion with HIV-1 RNA <50 c/mL at
Week 48 (Snapshot analysis); non-inferiority margin of 12%
Safety and efficacy of the 2 STRs by proportion with
HIV-1 RNA <50 c/mL at Week 96 (Snapshot analysis)
Change in CD4 cell count at Weeks 48 and 96
Genotype/phenotype resistance at time of virologic failure
56. STaR
Changes from Baseline at Week 96
in Fasting Lipids
Change in mean from baseline,
mmol/L (mg/dL)
TC
LDL
TG
HDL
■ RPV/FTC/TDF
■ EFV/FTC/TDF
(+25)
(+15)
(+9)
(+3)
(+8)
(+2)
(+2)
(-5)
Mean Baseline
Values, mmol/L
Change in TC:HDL at
Week 96, -0.2 in both arms
For comparisons between groups using ANOVA: p<0.001 for TC, LDL, HDL and p=0.09 for TG
4.24
4.22
2.69
2.66
1.37
1.46
1.14 1.14
Changes to lipid lowering therapy* from baseline through Week 96:
RPV/FTC/TDF 2.3%, EFV/FTC/TDF 4.1%
Baseline lipid lowering therapy, n (%): RPV/FTC/TDF, 4 (1%) and EFV/FTC/TDF, 1 (0.3%)
TC - total cholesterol, LDL - low-density lipoprotein, TG - triglycerides, HDL - high-density lipoprotein
*Changes to lipid lowering therapy includes starting and any dose modifications of a lipid lowering therapy per the Investigator
57. STaR
Conclusions
• Overall, RPV/TDF/FTC was non-inferior to EFV/FTC/TDF through
Week 96 for virologic suppression
– Statistically significant difference favouring RPV/FTC/TDF for baseline HIV-1
RNA ≤100,000 copies/mL
– Non-inferior for baseline HIV-1 RNA >100,000 copies/mL
• Lipid parameter changes through Week 96
– Significant differences in mean change and categorical change in TC and
LDL favoring RPV/FTC/TDF
– Significant differences in mean change and categorical change in HDL
favoring EFV/FTC/TDF
• TC:HDL ratio change -0.2 in both arms
• RPV/FTC/TDF is better tolerated than EFV/FTC/TDF
– Fewer nervous system and psychiatric adverse events
– Fewer discontinuations due to adverse events
Cohen C, et al. 15th IWCADR in HIV. October 2013. Oral Presentation O6.
58. Question #4
• Have you heard about the new updated guidelines for starting
statin therapy to reduce atherosclerotic CVD risk?
• 1.
Yes
• 2.
No
59. Question #5
• Which statement is false regarding the 2013 ACC/AHA
guideline on treatment of cholesterol to reduce atherosclerotic
CVD risk?
• 1.
HIV was not specifically addressed in the guidelines
• 2.
Treatment to specific LDL goals was eliminated
• 3.
A new risk calculator was developed
• 4. At least 1 new surrogate marker (such as hs-CRP) was
added to the risk calculation
• 5. The risk calculator takes into account the race and sex of
an individual
60. 2013 ACC/AHA Guideline on Treatment of
Cholesterol to Reduce ASCVD Risk
ASCVD =
Atherosclerotic
Cardiovascular
Disease
Stone NJ, et al. Circulation. doi:10.1161/01.cir.0000437738.63853.7a.
61. 2013 ACC/AHA Guideline on Treatment of
Cholesterol to Reduce ASCVD Risk (2)
ASCVD =
Atherosclerotic
Cardiovascular
Disease
Stone NJ, et al. Circulation. doi:10.1161/01.cir.0000437738.63853.7a.
63. High-, Moderate-, and Low-Intensity
Statin Therapy
Adapted from Bilazarian S. Theheart.org & Medscape; November 2013.
64. Implications of New 2013 ACC/AHA
Guidelines to Reduce ASCVD Risk
• Of 101 million people in US w/o CVD and aged 40-79 years
– 33 million are expected to have a 10-year predicted risk of CVD ≥ 7.5%
and high-intensity statins would be recommended
– Another 13 million are expected to have a predicted risk of between 5%
and 7.5% and statins should be considered
• Criticisms
– New risk score was developed for informing US populations
– May overpredict risk
– Despite a plethora of candidate emerging predictors of CV risk, the
model ended up selecting risk factors known since the 1960s
– HDL was selected to be in the model even though it is clearly
noncausally related to CAD
– Conflict of interest still remain with 8 of 15 panelists with industry ties
Ioannidis JP. JAMA. 2013 Dec 2. doi:10.1001/jama.2013.284657. [Epub ahead of print]