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Impact of Specific NRTI and PI Exposure on Impact of Specific NRTI and PI Exposure on the Risk of Myocardial Infarctionthe Risk of Myocardial Infarction
A Case-Control Study Nested within the A Case-Control Study Nested within the French Hospital Database on HIVFrench Hospital Database on HIV
ANRS CO4ANRS CO4
S Lang, M Mary-Krause, L Cotte, J Gilquin, M Partisani, A Simon, S Lang, M Mary-Krause, L Cotte, J Gilquin, M Partisani, A Simon, F Boccara, D CostagliolaF Boccara, D Costagliola
www.ccde.frwww.ccde.fr
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Background - I
RR (95% CI) = 1.16 (1.10 –1.23)
Mary-Krause M et al., AIDS 2003; 17: 2479 - 2486
D:A:D Study Group, Friis-Møller N et al., N Engl J Med 2007; 356:1723-1735
Cumulative exposure to protease inhibitors (Pis) has been associated with an increased risk of myocardial infarction but the role of specific protease inhibitors has not been reported
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Risk of myocardial infarction and exposure to protease inhibitors
D:A:D study group, Sabin CA, et al., Lancet 2008; 371: 1417-26
The SMART/Insight and the D:A:D study groups, Lundgren JD et al., AIDS 2008; 22: F17-F24
D:A:D Study
Patients with MIn = 517
Recent exposure to abacavir was associated witha higher risk of MI
RR (95% CI) = 1.94 (1.48 –2.55)
SMART Study
Patients with MIn = 19
Current use of abacavir wasassociated with anincreased risk of MI
HR (95% CI) = 4.3 (1.4 –13.0)
In these 2 studies, exposure to abacavir showed signals which were not completely concordant
Background - IIRisk of myocardial infarction according to exposure to abacavir
Interactions with CVD risk factors were in the opposite direction in the two studies
ObjectivesObjectives
In a nested case-control study within the French Hospital Database on HIV, to evaluate the association between the risk of myocardial infarction (MI) and
cumulative to specific NRTIs
recent (current or within last 6 months) and past exposure (>6 months ago) to specific NRTIs
cumulative exposure to specific PIs
* Luepker R et al., Circulation 2003; 108: 2543-2549
Cases
Over 115000 HIV-infected patients have been enrolled into the FHDH between 1989 and 2006
Patients with a first MI prospectively reported between January 2000 and December 2006 were included
Only definite or probable MI cases validated by a cardiologist (FB) according to the ASC/ESC criteria* were eligible
Out of the 418 cases identified, 129 were excluded 45 had incomplete medical records 36 MIs occurred before the study period 2 cases of MI were undated 4 cases of MI occurred before the diagnosis of HIV infection 6 cases had a MI before being enrolled in the cohort 36 cases did not have a confirmed MI
289 cases
Controls HIV-infected patients with no history of MI, HIV-infected patients with no history of MI, followed at the
time of MI diagnosis of the corresponding case
Matched for Age at diagnosis of MI +3 years Sex Clinical center
Matching based on these factors yields similar results in a nested case-control study to those obtained with the cohort approach used in our first study on the risk of MI *
For each validated case, up to five matched controls randomly selected with replacement from the database
Cases eligible as control up to the time of the diagnosis of MI 3 cases with 1 control, 11 with 2, 246 with 3, 24 with 4 and 5 with 5
controls
* Guiguet M et al., Pharmacoepid Drug Saf, 2008; 17: 468-474884 controls
Methods Data collected for cases and controls
Cardiovascular risk factors Smoking, family history, hypertension, hyperlipidemia,
diabetes Treatments for lipid, metabolic and hypertensive disorders BMI, current IV drug use
Validation of HIV data recorded in the database CD4 cell count, current (within 3 months of MI) and nadir CD4/CD8 ratio (within 3 months of MI) Plasma HIV-1 RNA (within 3 months of MI) ART treatment history Stage C (AIDS) before MI
Analyses - IAnalyses - I Several conditional logistic regression models were
constructed A first model including cumulative exposure to each ART A second model including cumulative exposure to each ART and
exposure to each NRTI as a three-class variable: no exposure last use > 6 months (past) ongoing exposure or interruption < 6 months (current/recent)
In these models, potential confounders which affected the association between any ART and the risk of MI by at least 10% in any of the models were included from Age, smoking, family history of CHD, BMI, hypertension,
intravenous drug use CD4 cell nadir, plasma HIV-1 RNA, CD4 cell count, CD4/CD8 cells
ratio within 3 months before MI and AIDS before MI
Analyses - IIAnalyses - II
Odds Ratios (OR) are reported only for NRTIs and PIs with at least 100 exposed patients
AZT, ddI, ddC, d4T, 3TC, ABC, TNF
SQV, IDV, NFV, LPV, APV/fAPV
although cumulative exposures to FTC, EFV, NVP, ATV and TPV were also accounted for in the analyses
CharacteristicsCharacteristicsCases (n = 289) Controls (n = 884)
Sex, male, n (% ) 257 (88.9%) 788 (89.1%)
Age, years, median (IQR ) 46.9 ± (40.7 – 54.1) 46.3 (40.2 – 53.7)
Hypertension, n (%) 59 (20.6%) 102 (11.8%)
Smoking, n (%) 210 (72.7%) 388 (43.9%)
Family history of CHD, n (%) 53 (18.5%) 58 (6.7%)
Hypercholesterolemia, n (%) 148 (51.7%) 282 (32.6%)
Intravenous drug use, n (%) 38 (13.3%) 83 (9.5%)
Number of CV risk factors :
0, n (%)
1-2 n, (%)
≥ 3 n, (%)
3 (1.0%)
172 (59.5%)
114 (39.4%)
163 (18.4%)
553 (62.6%)
168 (19.0%)
Viral load, copies/mL, median (IQR) 127 (50 - 3900) 50 (50 – 1368)
Viral load <50 copies/mL, n (%) 125 (43.3%) 457 (51.7%)
CD4 count, cells/mm3 median (IQR) 427 (256 - 638) 451 (291 – 634)
CD4/CD8 ratio 1, n (%) 19 (6.6%) 116 (13.1%)
No treatment before MI, n (%) 11 (3.8%) 55 (6.2%)
1st treatment after inclusion in FHDH, n (%) 210 (72.7%) 677 (76.6%)
Exposure to abacavir and risk of MI - I
N exposed
N exposed
casesOR [ 95% CI ] p value
Cum exposure to abacavir 410 127 0.97 0.86 - 1.10 0.651Model 1
Exposure to abacavir and risk of MI - IIN
exposed
N exposed
casesOR [ 95% CI ] p value
Cumulative exp to abacavir 410 127 0.97 0.86 - 1.10 0.651
Cumulative exp to abacavir 410 127 0.88 0.75 - 1.04 0.138
No exposure
Current/Recent exposure
Past exposure
763
290
120
162
88
39
1
1.57
1.59
-
0.91 - 2.72
0.89 - 2.83
-
0.107
0.116
Model 1
Model 2
For abacavir, there was evidence of an interaction between recent/past and cumulative exposure, while no such effect was observed for any other NRTI
A final model including exposure to abacavir as a five-class variable and cumulative exposure to all other ART was constructed
no exposureexposure <= 1 year and last use <= 6 months prior to the MI (current/recent)exposure <= 1 year and last use > 6 months prior to the MI (past)exposure > 1 year and last use <= 6 months prior to the MI (current/recent)exposure > 1 year and last use > 6 months prior to the MI (past)
Exposure to abacavir and other NRTIs and risk of MI - III
Final modelN
exposedN
exposed cases
OR [ 95% CI ] p value
No exposure
Expo < 1 year, current/recent
Expo < 1 year, past
Expo > 1 year, current/recent
Expo > 1 year, past
763
72
76
218
44
162
31
24
57
15
1
1.97
1.31
1.05
1.42
-
1.09 - 3.56
0.68 - 2.52
0.65 - 1.69
0.60 - 3.35
-
0.025
0.415
0.844
0.420
Cum exp to zidovudine 998 256 1.08 0.99 - 1.18 0.086
Cum exp to didanosine 691 186 0.91 0.82 - 1.01 0.071
Cum exp to zalcitabine 314 92 0.99 0.81 - 1.21 0.924
Cum exp to stavudine 718 199 1.09 0.98 - 1.22 0.132
Cum exp to lamivudine 1043 269 0.95 0.85 - 1.07 0.387
Cum exp to tenofovir 238 65 0.97 0.75 - 1.24 0.785
No interaction was found between exposure to abacavir and numbers of CV risk factors on the risk of MI (p = 0.384)Similar results were observed when restricting the analysis to patients with first ART after inclusion in the cohort
Cumulative exposure (per additional year)
N exposed
N exposed
casesOR [ 95% CI ] p value
Saquinavir +/-r 324 92 0.96 0.80 – 1.15 0.669
Indinavir +/-r 497 146 1.10 0.98 – 1.24 0.117
Nelfinavir 453 131 1.12 0.98 – 1.28 0.110
Lopinavir/r 290 94 1.37 1.09 – 1.72 0.006
Amprenavir/fos-amp +/-r 117 46 1.52 1.19 – 1.95 0.001
Final model
Exposure to PIs and risk of MI
Cumulative exposure
(per additional year)N
exposed
N exposed
casesOR [ 95% CI ] p value
PI +/-r 864 239 1.16 1.07 – 1.26 <0.001
Saquinavir +/-r 324 92 0.95 0.83 – 1.10 0.502
Similar results were observed when restricting the analysis to patients with first ART after inclusion in the cohort
Final modelcombining all PIs but SQV
Interpretation - IInterpretation - IExposure to abacavir and risk of MIExposure to abacavir and risk of MI
We found a signal slightly different from We found a signal slightly different from those of the D:A:D study and of the those of the D:A:D study and of the SMART StudySMART Study only only earlyearly exposure to exposure to abacavirabacavir was was
associated with an increased risk of MIassociated with an increased risk of MI no interaction between exposure to abacavir no interaction between exposure to abacavir
and CV risk factors on the risk of MIand CV risk factors on the risk of MI
Interpretation - IIInterpretation - IIExposure to other NRTIs and risk of MIExposure to other NRTIs and risk of MI
Trends towards an increased risk of MI by Trends towards an increased risk of MI by cumulative exposure to cumulative exposure to AZT and to d4T were evidenced In line with the original hypothesis in the D:A:D studyIn line with the original hypothesis in the D:A:D study These associations deserve additional evaluations in These associations deserve additional evaluations in
independent studiesindependent studies
No signal was evidenced for the other NRTIs, including ddI and TNF
Interpretation - III Exposure to PIs and risk of MIExposure to PIs and risk of MI
In our study the association between the risk of MI and In our study the association between the risk of MI and cumulative exposure to PI was in cumulative exposure to PI was in concordanceconcordance with that with that observed in the D:A:D studyobserved in the D:A:D study
Increased riskIncreased risk for all studied PIs, but saquinavirfor all studied PIs, but saquinavir Significant in specific analyses for Significant in specific analyses for lopinavir/rlopinavir/r and and
amprenavir/fos-amprenavir amprenavir/fos-amprenavir +/-r Unlikely explained by selection biases and confoundingUnlikely explained by selection biases and confounding
After 10 years of exposure, the risk would be increased After 10 years of exposure, the risk would be increased by by 4.44.4
Acknowledgments - IAcknowledgments - I We thank the study team without whom it would have We thank the study team without whom it would have
been impossible to complete the study in timebeen impossible to complete the study in time
Lydie Béniguel, Sandra Firmin, Sophie Pakianather, Serge Lydie Béniguel, Sandra Firmin, Sophie Pakianather, Serge Rodrigues, Selma Trabelsi, Sarah William-FaltaosRodrigues, Selma Trabelsi, Sarah William-Faltaos
We are grateful to the following colleagues who read and We are grateful to the following colleagues who read and provided comments on the analysis planprovided comments on the analysis plan
S Evans, M Hernán, C Sabin and I WellerS Evans, M Hernán, C Sabin and I Weller
A special thank to Rob MurphyA special thank to Rob Murphy
The study was funded by ANRSThe study was funded by ANRS
Acknowledgments - IIAcknowledgments - II Clinical Epidemiology Group of the FHDHClinical Epidemiology Group of the FHDH
Scientific committeeScientific committee S Abgrall, F Barin, M Bentata, E Billaud, F Boué, C Burty, S Abgrall, F Barin, M Bentata, E Billaud, F Boué, C Burty, A Cabié, D Costagliola, L Cotte, P De Truchis, X Duval, C Duvivier, P Enel, A Cabié, D Costagliola, L Cotte, P De Truchis, X Duval, C Duvivier, P Enel, L Fredouille-Heripret, J Gasnault, C Gaud, J Gilquin, S Grabar, C Katlama, L Fredouille-Heripret, J Gasnault, C Gaud, J Gilquin, S Grabar, C Katlama, MA Khuong, JM Lang, AS Lascaux, O Launay, A Mahamat, M Mary-Krause, MA Khuong, JM Lang, AS Lascaux, O Launay, A Mahamat, M Mary-Krause, S Matheron, JL Meynard, J Pavie, G Pialoux, F Pilorgé, I Poizot-Martin, S Matheron, JL Meynard, J Pavie, G Pialoux, F Pilorgé, I Poizot-Martin, C Pradier, J Reynes, E Rouveix, A Simon, P Tattevin, H Tissot-Dupont, JP Viard, C Pradier, J Reynes, E Rouveix, A Simon, P Tattevin, H Tissot-Dupont, JP Viard, N VigetN Viget
DMI2 coordinating centreDMI2 coordinating centre French Ministry of Health (V Salomon), Technical French Ministry of Health (V Salomon), Technical Hospitalisation Information Agency, ATIH (N Jacquemet)Hospitalisation Information Agency, ATIH (N Jacquemet)
Statistical analysis centreStatistical analysis centre U943 INSERM and UPMC (S Abgrall, D Costagliola, U943 INSERM and UPMC (S Abgrall, D Costagliola, S Grabar, M Guiguet, E Lanoy, L Lièvre, M Mary-Krause, H Selinger-Leneman), S Grabar, M Guiguet, E Lanoy, L Lièvre, M Mary-Krause, H Selinger-Leneman), INSERM-Transfert (JM Lacombe, V Potard)INSERM-Transfert (JM Lacombe, V Potard)
Clinical centresClinical centres Paris areaParis area Ambroise Paré, Antoine Béclère, Avicenne, Bichat-Claude Bernard, Cochin, Ambroise Paré, Antoine Béclère, Avicenne, Bichat-Claude Bernard, Cochin,
Henri Mondor, HEGP, Jean Verdier, Kremlin Bicêtre, Laennec, Lariboisière, Louis Henri Mondor, HEGP, Jean Verdier, Kremlin Bicêtre, Laennec, Lariboisière, Louis Mourier, Necker-adultes, Pasteur, Paul Brousse, Pitié Salpêtrière, Raymond Poincaré, Mourier, Necker-adultes, Pasteur, Paul Brousse, Pitié Salpêtrière, Raymond Poincaré, Rothschild, Saint-Antoine, Saint-Denis, Saint-Joseph, Saint-Louis, Tenon Rothschild, Saint-Antoine, Saint-Denis, Saint-Joseph, Saint-Louis, Tenon
Outside Paris areaOutside Paris area Aix en Provence, Antibes, Arles, Avignon, Belfort, Besançon, Caen, Aix en Provence, Antibes, Arles, Avignon, Belfort, Besançon, Caen, Clermont-Ferrand, Digne les Bains, Dijon, Gap, Grenoble, Lyon , Marseille, Martigues, Clermont-Ferrand, Digne les Bains, Dijon, Gap, Grenoble, Lyon , Marseille, Martigues, Montpellier, Mulhouse, Nancy, Nantes, Nice, Nîmes, Reims, Rennes, Rouen, Saint-Montpellier, Mulhouse, Nancy, Nantes, Nice, Nîmes, Reims, Rennes, Rouen, Saint-Etienne, Strasbourg, Toulon, Toulouse, Tourcoing, ToursEtienne, Strasbourg, Toulon, Toulouse, Tourcoing, Tours
OverseasOverseas Guadeloupe, Guyane, La Réunion, Martinique, Saint-Martin Guadeloupe, Guyane, La Réunion, Martinique, Saint-Martin
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