Generic placeholder image

Current HIV Research

Editor-in-Chief

ISSN (Print): 1570-162X
ISSN (Online): 1873-4251

Research Article

Cardiovascular Risk Prediction Equations Underestimate Risk in People Living with HIV: Comparison and Cut-point Redefinition for 19 Cardiovascular Risk Equations

Author(s): Marina Grand*, Alejandro Díaz and Daniel Bia

Volume 20, Issue 2, 2022

Published on: 14 March, 2022

Page: [137 - 151] Pages: 15

DOI: 10.2174/1570162X20666220126124149

Price: $65

Abstract

Background: Rates of cardiovascular disease are higher in people living with HIV. Early detection of high-risk subjects (applying cardiovascular risk equations) would allow preventive actions. D:A:D, ASCVD, and FRS:CVD equations are the most recommended. However, controversies surround these equations and cut-points, which have the greatest capacity to discriminate high-risk subjects.

Objectives: The study aims (i) to assess the association/agreement between cardiovascular risk levels obtained with D:A:D and fifteen other cardiovascular risk equations, (ii) to detect cardiovascular risk equation’s capability to detect high-risk subjects, and (iii) to specify the optimal cardiovascular risk equation´s cut points for the prediction of carotid plaque presence, as a surrogate of high cardiovascular risk.

Methods: 86 adults with HIV were submitted to the clinical, laboratory, and cardiovascular risk evaluation (including carotid ultrasound measurements). Cardiovascular risk was evaluated through multiple risk equations (e.g., D.A.D, ASCVD, and FRS equations). Association and agreement between equations (Correlation, Bland-Altman, Williams´test) and equation’s capacity to detect plaque presence (ROC curves, sensitivity, specificity) were evaluated.

Results: Cardiovascular risk equations showed a significant and positive correlation with plaque presence. Higher high-cardiovascular risk detection capability was obtained for ASCVD and D:A:D. Full D:A:D5y>0.88 %, ASCVD>2.80 %, and FRS:CVD>2.77 % correspond to 80 % sensitivity.

Conclusion: All cardiovascular risk equations underestimate the true risk in HIV subjects. The cut-- points for high cardiovascular risk were found to vary greatly from recommended in clinical guidelines.

Keywords: Atherosclerotic plaque, cardiovascular risk, risk equations, human immunodeficiency virus, vascular ultrasound, anti-HIV drugs.

Graphical Abstract
[1]
Patel V, Chisholm D, Dua T, et al. Global mortality and morbidity of HIV/AIDS: Mental, neurological, and substance use disorders. Disease Control Priorities, World Bank 2015; 3: 4.
[http://dx.doi.org/10.1596/978-1-4648-0426-7] [PMID: 27227246]
[2]
Shah ASV, Stelzle D, Lee KK, et al. Global burden of atherosclerotic cardiovascular disease in people living with HIV systematic review and meta-analysis. Circulation 2018; 138(11): 1100-12.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.117.033369] [PMID: 29967196]
[3]
Rosenson RS, Hubbard D, Monda KL, et al. Excess risk for atherosclerotic cardiovascular outcomes among US adults with HIV in the current era. J Am Heart Assoc 2020; 9(1): e013744.
[http://dx.doi.org/10.1161/JAHA.119.013744] [PMID: 31880980]
[4]
Graham IA. The importance of total cardiovascular risk assessment in clinical practice. Eur J Clin Practice 2009; 12(4): 148-55.
[http://dx.doi.org/10.1080/13814780600976282] [PMID: 17127600]
[5]
Grand M, Bia D, Diaz A. Cardiovascular risk assessment in people living with HIV: A systematic review and meta-analysis of real- life data. Curr HIV Res 2020; 18(1): 5-18.
[http://dx.doi.org/10.2174/1570162X17666191212091618] [PMID: 31830884]
[6]
Neuhaus J, Jacobs DR Jr, Baker JV, et al. Markers of inflammation, coagulation, and renal function are elevated in adults with HIV infection. J Infect Dis 2010; 201(12): 1788-95.
[http://dx.doi.org/10.1086/652749] [PMID: 20446848]
[7]
Islam FM, Wu J, Jansson J, Wilson DP. Relative risk of cardiovascular disease among people living with HIV: A systematic review and meta-analysis. HIV Med 2012; 13(8): 453-68.
[http://dx.doi.org/10.1111/j.1468-1293.2012.00996.x] [PMID: 22413967]
[8]
Friis-Møller N, Thiébaut R, Reiss P, et al. Predicting the risk of cardiovascular disease in HIV-infected patients: the data collection on adverse effects of anti-HIV drugs study. Eur J Cardiovasc Prev Rehabil 2010; 17(5): 491-501.
[http://dx.doi.org/10.1097/HJR.0b013e328336a150] [PMID: 20543702]
[9]
Friis-Møller N, Ryom L, Smith C, et al. An updated prediction model of the global risk of cardiovascular disease in HIV-positive persons: The data-collection on adverse effects of anti-HIV drugs (D:A:D) study. Eur J Prev Cardiol 2016; 23(2): 214-23.
[http://dx.doi.org/10.1177/2047487315579291] [PMID: 25882821]
[10]
Dhillon S, Sabin CA, Alagaratnam J, et al. Pharmacokinetic and clinical observations in people over fifty (POPPY) study. Level of agreement between frequently used cardiovascular risk calculators in people living with HIV. HIV Med 2019; 20(5): 347-52.
[http://dx.doi.org/10.1111/hiv.12731] [PMID: 30873751]
[11]
Muiru AN, Bibangambah P, Hemphill L, et al. Distribution and performance of cardiovascular risk scores in a mixed population of HIV-infected and community-based HIV-uninfected individuals in Uganda. J Acquir Immune Defic Syndr 2018; 78(4): 458-64.
[http://dx.doi.org/10.1097/QAI.0000000000001696] [PMID: 29652762]
[12]
Thompson-Paul AM, Lichtenstein KA, Armon C, et al. Cardiovascular disease risk prediction in the HIV outpatient Study. Clin Infect Dis 2016; 63(11): 1508-16.
[http://dx.doi.org/10.1093/cid/ciw615] [PMID: 27613562]
[13]
Triant VA, Perez J, Regan S, et al. Cardiovascular risk prediction functions underestimate risk in HIV infection. Circulation 2018; 137(21): 2203-14.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.117.028975] [PMID: 29444987]
[14]
Janjua SA, Staziaki PV, Szilveszter B, et al. Presence, characteristics, and prognostic associations of carotid plaque among people living with HIV. Circ Cardiovasc Imag 2017; 10(10): e005777.
[http://dx.doi.org/10.1161/CIRCIMAGING.116.005777] [PMID: 29021257]
[15]
Ryom L, Cotter A, De Miguel R, et al. 2019 update of the European AIDS clinical society guidelines for treatment of people living with HIV version 10.0. HIV Med 2020; 21(10): 617-24.
[http://dx.doi.org/10.1111/hiv.12878] [PMID: 32885559]
[16]
Feinstein MJ, Hsue PY, Benjamin LA, et al. Characteristics, prevention, and management of cardiovascular disease in People living with HIV: A scientific statement from the American heart association. Circulation 2019; 140(2): e98-e124.
[http://dx.doi.org/10.1161/CIR.0000000000000695] [PMID: 31154814]
[17]
Krikke M, Hoogeveen RC, Hoepelman AIM, Visseren FL, Arends JE. Cardiovascular risk prediction in HIV-infected patients: Comparing the Framingham, atherosclerotic cardiovascular disease risk score (ASCVD), Systematic coronary risk evaluation for the Netherlands (SCORE-NL) and data collection on adverse events of Anti-HIV drugs (D:A:D) risk prediction models. HIV Med 2016; 17(4): 289-97.
[http://dx.doi.org/10.1111/hiv.12300] [PMID: 26268806]
[18]
Silva AG, Paulo RV, Silva-Vergara ML. Subclinical carotid atherosclerosis and reduced D:A:D score for cardiovascular risk stratification in HIV-positive patients. Arq Bras Cardiol 2020; 114(1): 68-75.
[http://dx.doi.org/10.5935/abc.20190227] [PMID: 31664317]
[19]
WHO Global recommendations on physical activity for health. 2010. Available from: https://www.who.int/dietphysicalactivity/factsheet_recommendations/en/ (Accessed 1 June 20).
[20]
Mancia G, Fagard R, Narkiewicz K, et al. Task Force Members. 2013 ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens 2013; 31(7): 1281-357.
[http://dx.doi.org/10.1097/01.hjh.0000431740.32696.cc] [PMID: 23817082]
[21]
Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: A report of the American college of cardiology/American heart association task force on clinical practice guidelines. Hypertension 2018; 71(6): e13-e115.
[http://dx.doi.org/10.1161/HYP.0000000000000065] [PMID: 29133356]
[22]
Chamberlain JJ, Johnson EL, Leal S, Rhinehart AS, Shubrook JH, Peterson L. Cardiovascular disease and risk management: Review of the American diabetes association standards of medical care in diabetes 2018. Ann Intern Med 2018; 168(9): 640-50.
[http://dx.doi.org/10.7326/M18-0222] [PMID: 29610837]
[23]
Catapano AL, Graham I, De Backer G, et al. 2016 ESC/EAS guidelines for the management of dyslipidaemias: The task force for the management of dyslipidaemias of the European society of cardiology (ESC) and European atherosclerosis society (EAS) Developed with the special contribution of the European assocciation for cardiovascular prevention & rehabilitation (EACPR). Atherosclerosis 2016; 253: 281-344.
[http://dx.doi.org/10.1016/j.atherosclerosis.2016.08.018] [PMID: 27594540]
[24]
Wilson PW, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation 1998; 97(18): 1837-47.
[http://dx.doi.org/10.1161/01.CIR.97.18.1837] [PMID: 9603539]
[25]
Assmann G, Cullen P, Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Münster (PROCAM) study. Circulation 2002; 105(3): 310-5.
[http://dx.doi.org/10.1161/hc0302.102575] [PMID: 11804985]
[26]
Conroy RM, Pyörälä K, Fitzgerald AP, et al. SCORE project group. Estimation of ten-year risk of fatal cardiovascular disease in Europe: The SCORE project. Eur Heart J 2003; 24(11): 987-1003.
[http://dx.doi.org/10.1016/S0195-668X(03)00114-3] [PMID: 12788299]
[27]
JBS 2: Joint British societies’ guidelines on prevention of cardiovascular disease in clinical practice. Heart 2005; 91(Suppl. 5): v1-v52.
[http://dx.doi.org/10.1136/hrt.2005.079988] [PMID: 16365341]
[28]
Woodward M, Brindle P, Tunstall-Pedoe H. Adding social deprivation and family history to cardiovascular risk assessment: The ASSIGN score from the Scottish heart health extended cohort (SHHEC). Heart 2007; 93(2): 172-6.
[http://dx.doi.org/10.1136/hrt.2006.108167] [PMID: 17090561]
[29]
World health organization. Prevention of cardiovascular disease: guidelines for assessment and management of total cardiovascular risk. 2007. Available from: https://apps.who.int/iris/handle/10665/43685
[30]
D’Agostino RB Sr, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: The Framingham heart study. Circulation 2008; 117(6): 743-53.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.107.699579] [PMID: 18212285]
[31]
Hippisley-Cox J, Coupland C, Vinogradova Y, et al. Predicting cardiovascular risk in England and Wales: Prospective derivation and validation of QRISK2. BMJ 2008; 336(7659): 1475-82.
[http://dx.doi.org/10.1136/bmj.39609.449676.25] [PMID: 18573856]
[32]
Goff DC Jr, Lloyd-Jones DM, Bennett G, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: A report of the American college of cardiology/American heart association task force on practice guidelines. J Am Coll Cardiol 2014; 63(25 Pt B): 2935-59.
[http://dx.doi.org/10.1016/j.jacc.2013.11.005] [PMID: 24239921]
[33]
Hajifathalian K, Ueda P, Lu Y, et al. A novel risk score to predict cardiovascular disease risk in national populations (Globorisk): A pooled analysis of prospective cohorts and health examination surveys. Lancet Diabetes Endocrinol 2015; 3(5): 339-55.
[http://dx.doi.org/10.1016/S2213-8587(15)00081-9] [PMID: 25819778]
[34]
Hippisley-Cox J, Coupland C, Brindle P. Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: Prospective cohort study. BMJ 2017; 357: j2099.
[http://dx.doi.org/10.1136/bmj.j2099] [PMID: 28536104]
[35]
Touboul PJ, Hennerici MG, Meairs S, et al. Mannheim carotid intima-media thickness and plaque consensus (2004-2006-2011). An update on behalf of the advisory board of the 3rd, 4th and 5th watching the risk symposia, at the 13th, 15th and 20th European stroke conferences, Mannheim, Germany, 2004, Brussels, Belgium, 2006, and Hamburg, Germany, 2011. Cerebrovasc Dis 2012; 34(4): 290-6.
[http://dx.doi.org/10.1159/000343145] [PMID: 23128470]
[36]
Diaz A, Bia D, Zócalo Y, et al. Carotid intima media thickness reference intervals for a healthy Argentinean population aged 11-81 Years. Int J Hypertens 2018; 2018: 8086714.
[http://dx.doi.org/10.1155/2018/8086714] [PMID: 29992052]
[37]
Metz CE. Basic principles of ROC analysis. Semin Nucl Med 1978; 8(4): 283-98.
[http://dx.doi.org/10.1016/S0001-2998(78)80014-2] [PMID: 112681]
[38]
DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach. Biometrics 1988; 44(3): 837-45.
[http://dx.doi.org/10.2307/2531595] [PMID: 3203132]
[39]
Marin M, Bia D, Zócalo Y. Carotid and femoral atherosclerotic plaques in asymptomatic and non-treated subjects: Cardiovascular risk factors, 10-years risk scores, and lipid ratios´ capability to detect plaque presence, burden, fibro-lipid composition and geometry. J Cardiovasc Dev Dis 2020; 7(1): 11.
[http://dx.doi.org/10.3390/jcdd7010011]
[40]
Lumley T, Diehr P, Emerson S, Chen L. The importance of the normality assumption in large public health data sets. Annu Rev Public Health 2002; 23: 151-69.
[http://dx.doi.org/10.1146/annurev.publhealth.23.100901.140546] [PMID: 11910059]
[41]
Evans JD. Straightforward Statistics for the Behavioral Sciences. Pacific Grove, CA, USA: Brooks-Cole Publishing 1996.
[42]
Goh C, Mwandumba H, Rapala A, et al. Limited utility of cardiovascular risk scores for people living with HIV in Malawi. medRxiv 2020.
[http://dx.doi.org/10.1101/2020.08.01.20166462]
[43]
Pirš M, Jug B, Eržen B, et al. Cardiovascular risk assessment in HIV-infected male patients: A comparison of Framingham, SCORE, PROCAM and DAD risk equations. Acta Dermatovenerol Alp Panonica Adriat 2014; 23(3): 43-7.
[http://dx.doi.org/10.15570/actaapa.2014.11] [PMID: 25242159]
[44]
Policarpo S, Rodrigues T, Moreira AC, Valadas E. Cardiovascular risk in HIV-infected individuals: A comparison of three risk prediction algorithms. Rev Port Cardiol 2019; 38(7): 463-70.
[http://dx.doi.org/10.1016/j.repce.2018.10.012] [PMID: 31522936]
[45]
Pinto Neto LFDS, Dias FR, Bressan FF, Santos CRO. Comparison of the ACC/AHA and Framingham algorithms to assess cardiovascular risk in HIV-infected patients. Braz J Infect Dis 2017; 21(6): 577-80.
[http://dx.doi.org/10.1016/j.bjid.2017.06.007] [PMID: 28732190]
[46]
Monroe AK, Haberlen SA, Post WS, et al. Cardiovascular disease risk scores’ relationship to subclinical cardiovascular disease among HIV-infected and HIV-uninfected men. AIDS 2016; 30(13): 2075-84.
[http://dx.doi.org/10.1097/QAD.0000000000001163] [PMID: 27203714]
[47]
Mosepele M, Hemphill LC, Palai T, et al. Cardiovascular disease risk prediction by the American college of cardiology (ACC)/American heart association (AHA) atherosclerotic cardiovascular disease (ASCVD) risk score among HIV-infected patients in sub-Saharan Africa. PLoS One 2017; 12(2): e0172897.
[http://dx.doi.org/10.1371/journal.pone.0172897] [PMID: 28235058]
[48]
Serrano-Villar S, Estrada V, Gómez-Garre D, et al. Diagnosis of subclinical atherosclerosis in HIV-infected patients: Higher accuracy of the D:A:D risk equation over Framingham and SCORE algorithms. Eur J Prev Cardiol 2014; 21(6): 739-48.
[http://dx.doi.org/10.1177/2047487312452964] [PMID: 22718798]
[49]
Hoffmann U, Lu MT, Foldyna B, et al. Assessment of coronary artery disease with computed tomography angiography and inflammatory and immune activation biomarkers among adults with HIV eligible for primary cardiovascular prevention. JAMA Netw Open 2021; 4(6): e2114923.
[http://dx.doi.org/10.1001/jamanetworkopen.2021.14923] [PMID: 34185068]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy