Impact of Specific NRTI and PI Exposure on the Risk of Myocardial Infarction A Case-Control Study Nested within the French Hospital Database on HIV ANRS.

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

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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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