BACKGROUND: The D:A:D (Data Collection on Adverse Events of Anti-HIV Drugs) Study, a prospective observational study on a cohort of 23 468 patients with HIV infection, indicated that the incidence of myocardial infarction (MI) increased by 26% per year of exposure to combination antiretroviral treatment (CART). However, it remains unclear whether the observed increase in the rate of MI in this population can be attributed to changes in conventional cardiovascular risk factors. OBJECTIVE: To compare the number of MIs observed among participants in the D:A:D Study with the number predicted by assuming that conventional cardiovascular risk equations apply to patients with HIV infection. METHODS: The Framingham equation, a conventional cardiovascular risk algorithm, was applied to individual patient data in the D:A:D Study to predict rates of MI by duration of CART. A series of sensitivity analyses were performed to assess the effect of model and data assumptions. Predictions were extrapolated to provide 10-year risk estimates, and various scenarios were modelled to assess the expected effect of different interventions. RESULTS: In patients receiving CART, the observed numbers of MIs during D:A:D follow up were similar to or somewhat higher than predicted numbers: 9 observed vs 5.5 events predicted, 14 vs 9.8, 22 vs 14.9, 31 vs 23.2 and 47 vs 37.0 for<1 year, 1-2 years, 2-3 years, 3-4 years and >4 years CART exposure, respectively. In patients who had not received CART, the observed number of MIs was fewer than predicted (3 observed vs 7.6 predicted). Nine per cent of the study population have a predicted 10-year risk of MI above 10%, a level usually associated with initiation of intervention on risk factors. CONCLUSIONS: A consistent feature of all analyses was that observed and predicted rates of MI increased in a parallel fashion with increased CART duration, suggesting that the observed increase in risk of MI may at least in part be explained by CART-induced changes in conventional risk factors. These findings provide guidance in terms of choosing lifestyle or therapeutic interventions to decrease those risk factors in much the same way as in persons without HIV infection.
BACKGROUND: The D:A:D (Data Collection on Adverse Events of Anti-HIV Drugs) Study, a prospective observational study on a cohort of 23 468 patients with HIV infection, indicated that the incidence of myocardial infarction (MI) increased by 26% per year of exposure to combination antiretroviral treatment (CART). However, it remains unclear whether the observed increase in the rate of MI in this population can be attributed to changes in conventional cardiovascular risk factors. OBJECTIVE: To compare the number of MIs observed among participants in the D:A:D Study with the number predicted by assuming that conventional cardiovascular risk equations apply to patients with HIV infection. METHODS: The Framingham equation, a conventional cardiovascular risk algorithm, was applied to individual patient data in the D:A:D Study to predict rates of MI by duration of CART. A series of sensitivity analyses were performed to assess the effect of model and data assumptions. Predictions were extrapolated to provide 10-year risk estimates, and various scenarios were modelled to assess the expected effect of different interventions. RESULTS: In patients receiving CART, the observed numbers of MIs during D:A:D follow up were similar to or somewhat higher than predicted numbers: 9 observed vs 5.5 events predicted, 14 vs 9.8, 22 vs 14.9, 31 vs 23.2 and 47 vs 37.0 for<1 year, 1-2 years, 2-3 years, 3-4 years and >4 years CART exposure, respectively. In patients who had not received CART, the observed number of MIs was fewer than predicted (3 observed vs 7.6 predicted). Nine per cent of the study population have a predicted 10-year risk of MI above 10%, a level usually associated with initiation of intervention on risk factors. CONCLUSIONS: A consistent feature of all analyses was that observed and predicted rates of MI increased in a parallel fashion with increased CART duration, suggesting that the observed increase in risk of MI may at least in part be explained by CART-induced changes in conventional risk factors. These findings provide guidance in terms of choosing lifestyle or therapeutic interventions to decrease those risk factors in much the same way as in persons without HIV infection.
Authors: A Ross Eckard; C T Longenecker; Y Jiang; S M Debanne; D Labbato; N Storer; G A McComsey Journal: HIV Med Date: 2014-03-20 Impact factor: 3.180
Authors: Steven K Grinspoon; Carl Grunfeld; Donald P Kotler; Judith S Currier; Jens D Lundgren; Michael P Dubé; Steven E Lipshultz; Priscilla Y Hsue; Kathleen Squires; Morris Schambelan; Peter W F Wilson; Kevin E Yarasheski; Colleen M Hadigan; James H Stein; Robert H Eckel Journal: Circulation Date: 2008-06-19 Impact factor: 29.690
Authors: Judith S Currier; Jens D Lundgren; Andrew Carr; Daniel Klein; Caroline A Sabin; Paul E Sax; Jeffrey T Schouten; Marek Smieja Journal: Circulation Date: 2008-06-19 Impact factor: 29.690
Authors: C Noel Bairey Merz; Mark J Alberts; Gary J Balady; Christie M Ballantyne; Kathy Berra; Henry R Black; Roger S Blumenthal; Michael H Davidson; Sara B Fazio; Keith C Ferdinand; Lawrence J Fine; Vivian Fonseca; Barry A Franklin; Patrick E McBride; George A Mensah; Geno J Merli; Patrick T O'Gara; Paul D Thompson; James A Underberg Journal: J Am Coll Cardiol Date: 2009-09-29 Impact factor: 24.094
Authors: Matthew S Freiberg; Chung-Chou H Chang; Lewis H Kuller; Melissa Skanderson; Elliott Lowy; Kevin L Kraemer; Adeel A Butt; Matthew Bidwell Goetz; David Leaf; Kris Ann Oursler; David Rimland; Maria Rodriguez Barradas; Sheldon Brown; Cynthia Gibert; Kathy McGinnis; Kristina Crothers; Jason Sico; Heidi Crane; Alberta Warner; Stephen Gottlieb; John Gottdiener; Russell P Tracy; Matthew Budoff; Courtney Watson; Kaku A Armah; Donna Doebler; Kendall Bryant; Amy C Justice Journal: JAMA Intern Med Date: 2013-04-22 Impact factor: 21.873