Transcript to this slideshow

INTRODUCTORY TALK
D Costagliola
Chapter 1
THE CURRENT DEBATE ON
ABACAVIR
Summary of studies on the association between
exposure to abacavir the risk of myocardial infarction
Study
Design
CV Events
Effect of ABC?
D:A:D[1] (N of MI = 580)
Observational cohort
Prospective, predefined
Yes
FHDH[2] (N of MI = 289)
Case control study
Prospective, MI retrospectively
validated
SMART[3] (N of MI = 19)
RCT, observational
analyses
Prospective, predefined
Yes
STEAL[4] (N of MI = 3 )
RCT
Prospective
Yes
GSK analysis[5]
(N of MI = 11 )
12 RCTs
Retrospective database search
No
ALLRT ACTG A5001[6]
(N of MI = 27 )
5 RCTs
Retrospective by
2 independent reviewers
No
RCT
Prospective
No
HEAT[7]
(N of MI = 0 )
1st
Yes
yr of exposure
All or majority of patients antiretroviral-experienced at ABC initiation
All or majority of patients antiretroviral naive at ABC inclusion
Can we extrapolate the results to naive patients?
Adapted from: 1. Lundgren JD, et al. CROI 2009. Abstract 44LB; 2. Lang S, et al. CROI 2009. Abstract 43LB; 3. SMART. AIDS. 2008;22:F17F24; 4. Carr A, et al. CROI 2009. Abstract 576; 5. Cutrell A, et al. IAC 2008. Abstract WEAB0106; 6. Benson C, et al. CROI 2009. Abstract 721;
7. McComsey G, et al. CROI 2009. Abstract 732.
Exposure to abacavir and other NRTIs
and risk of MI, FHDH Study
N
exposed
N
exposed
cases
Univariate model
Model 1: cumulative
exposure only
OR [ 95% CI ]
OR [ 95% CI ]
Abacavir, cumul expo
410
127
1.05 (0.96 - 1.15)
0.97 (0.86 - 1.10)
Didanosine, cumul expo
691
186
1.02 (0.95 – 1.09)
0.91 (0.82 – 1.01)
Lamivudine, cumul expo
1043
269
1.06 (1.00 – 1.13)
0.96 (0.86 – 1.08)
Stavudine, cumul expo
718
199
1.09 (1.02 – 1.16)
1.11 (0.99 – 1.24)
Tenofovir, cumul expo
238
65
1.19 (0.99 – 1.44)
1.01 (0.79 – 1.30)
Zalcitabine, cumul expo
314
92
1.08 (0.94 – 1.24)
0.99 (0.82 – 1.21)
Zidovudine, cumul expo
998
256
1.03 (0.98 – 1.08)
1.09 (1.00 – 1.19)
This is different from D:A:D
Without D:A:D, we would have found no association
Adjusted for hypertension, smoking, family history of premature CAD, use of cocaine and/or IV drug
use, plasma HIV-1 RNA level, CD4/CD8 cells ratio, exposure to emtricitabine, atazanavir, ritonavir and
tipranavir
Exposure to abacavir and other NRTIs
and risk of MI, FHDH Study
N
exposed
N
exposed
cases
Univariate model
Model 1: cumulative
exposure only
OR [ 95% CI ]
OR [ 95% CI ]
Abacavir, cumul expo
410
127
1.05 (0.96 - 1.15)
0.97 (0.86 - 1.10)
Didanosine, cumul expo
691
186
1.02 (0.95 – 1.09)
0.91 (0.82 – 1.01)
Lamivudine, cumul expo
1043
269
1.06 (1.00 – 1.13)
0.96 (0.86 – 1.08)
Stavudine, cumul expo
718
199
1.09 (1.02 – 1.16)
1.11 (0.99 – 1.24)
Tenofovir, cumul expo
238
65
1.19 (0.99 – 1.44)
1.01 (0.79 – 1.30)
Zalcitabine, cumul expo
314
92
1.08 (0.94 – 1.24)
0.99 (0.82 – 1.21)
Zidovudine, cumul expo
998
256
1.03 (0.98 – 1.08)
1.09 (1.00 – 1.19)
The impact of cardiovascular risk factors on the
likelihood of receiving tenofovir and abacavir is big
Adjusted for hypertension, smoking, family history of premature CAD, use of cocaine and/or IV drug
use, plasma HIV-1 RNA level, CD4/CD8 cells ratio, exposure to emtricitabine, atazanavir, ritonavir and
tipranavir
Exposure to NNRTIs and PIs and risk of MI,
FHDH study
N
exposed
N
exposed
cases
Univariate model
Model 1: cumulative
exposure only
OR [ 95% CI ]
OR [ 95% CI ]
NNRTI
Efavirenz, cumul expo
404
109
1.00 (0.90 – 1.10)
1.01 (0.87 – 1.16)
Nevirapine, cumul expo
380
111
1.00 (0.90 – 1.10)
1.01 (0.88 – 1.15)
Ampr/fos+/-r cumul expo
117
46
1.41 (1.17 – 1.69)
1.57 (1.24– 2.00)
Indinavir+/-r, cumul expo
497
146
1.10 (1.01 – 1.19)
1.07 (0.95 – 1.21)
Lopinavir/r, cumul expo
290
94
1.35 (1.17 – 1.55)
1.37 (1.13 – 1.65)
Nelfinavir, cumul expo
453
131
1.08 (0.98 – 1.19)
1.09 (0.96 – 1.25)
Saqui+/-r, cumul expo
324
92
1.02 (0.91 – 1.13)
0.94 (0.81 – 1.09)
PI
No such impact for NNRTIs and PIs
Adjusted for hypertension, smoking, family history of premature CAD, use of cocaine and/or IV drug
use, plasma HIV-1 RNA level, CD4/CD8 cells ratio, exposure to emtricitabine, atazanavir, ritonavir and
tipranavir
Conclusion
• Can the results be extrapolated to naive patients?
• Without DAD, we would have found nothing
• In France, the confounders played a higher role on the
prescription of NRTIs, in particular tenofovir and abacavir,
than on the prescription of NNRTIs or of PIs
• If true also in other countries, the results of the different
studies will be more likely to be concordant for NNRTIs and
for PIs and discordant for NRTIs
• Results of observational studies will be more robust for
NNRTIs and PIs than for NRTIs
Chapter 2
Risks and relationship
between HIV viremia and
myocardial infarction
Rates per thousand person years
Observed and predicted rates of myocardial
infarction by duration of CART
8
7
Observed
6
rates
5
Best
estimate of
predicted
rates
4
3
2
1
0
None
< 1 year
1-2 years
2-3 years
Duration of CART
Adapted from Law et al, HIV Med 2006.
3-4 years
4+ years
HIV RNA and risk of serious non-AIDS events:
Smart CROI 2008 – A, Phillips (plenary presentation)
All serious non-AIDS
Non-AIDS malignancy
Renal
CVD
Liver
Other non-AIDS death
0,2
0,5
Adjusted hazard ratio
1,0
1,5
< 400 vs, > 400 copies/mL
Adjusted for age, gender, prior AIDS, hep B/C, smoking, latest CD4 count
SMART, unpublished
Non-AIDS-defining deaths and immunodeficiency in
the era of combination antiretroviral therapy
HIV RNA level and risk of death from cardiovascular disease (n=36)
Variables
Adj* Hazards Ratio
95% CI
p-value
Latest CD4 cell count (/µl)
0.14
349-200 vs. ≥350
1.15
(0.51-2.63)
199-50 vs. ≥350
0.89
(0.28-2.82)
<50 vs. ≥350
4.15
(1.14-15.17)
3.86
(1.57-9.51)
Latest HIV RNA (log10/ml)
≥5 vs. <5
0.003
*Adjusted for age, sex, exposure category, Hepatitis C serostatus, first line cART
The risk of death from a cardiovascular cause was associated with HIV RNA level
Adapted from Marin et al. AIDS (in press)
Risk factors of MI in HIV infected
patients apart from treatment
FHDH ANRS CO4
N
exposed
1151
N exposed
cases
278
OR [95% CI ]
0
173
5
1
1 or 2
710
166
16.8 (5.9 – 48.4)
3 or more
268
107
49.4 (16.4 – 149,0)
<= 50 copies/ml
573
121
1
> 50 copies/ml
578
157
1.6 (1,1 – 2,1)
>= 1
135
19
1
<1
1016
259
1,8 (1,0 – 3,0)
Cardiovascular risk
factors*
Plasma HIV-1 RNA
CD4 / CD8 ratio
*man more than 50 years or woman more than 60 years, current smoker or smoking cessation <
3years, family history of premature coronary arterial disease, hypertension, hypercholesterolemia,
diabetes and cocaine and/or intravenous drug use
Conclusion
• The traditional cardiovascular risk factors, including cocaine
and IV drug use, are very strong risk factors of MI in HIV-1
infected patients
• The role of HIV parameters must also be accounted for
– Plasma HIV-1 RNA (positive impact of cART)
– CD4/CD8 ratio
• Activation?
• Inflammation?
– No role of CD4 cell count?