AN INTEGRATIVE BOIMARKER: OPPORTUNITIES FOR NON-INVASIVE DIAGNOSTICS OF CORONARY ATHEROSCLEROSIS
https://doi.org/10.15829/1560-4071-2017-6-132-138
Abstract
Aim. With the multimarker approach, to investigate and implement an integrative biomarker for non-invasive risk assessment of the presence and severity of coronary atherosclerosis.
Material and methods. Totally, 205 consecutive patients included, age 18 and older, mean age 62,8±9,0 y., admitted and investigated in-patient at National Research Center for Preventive Medicine of the Ministry of Health in 2011-2013, underwent diagnostic coronary arteriography (CG) and duplex carotid scanning. Localization and grade of coronary atherosclerosis were assessed with the score Gensini (GS).
Results. The analysis was done in 3 groups: no coronary atherosclerosis (GS =0), with coronary atherosclerosis of any grade (GS >0), and severe (GS ≥35). Based in the preliminary analysis of mathemathical models that included visual and biochemical markers, the most siginificant were selected that have been included into the integrated biomarker. Value of i-BIO >4 points with sensitivity 87,9% makes it to reveal coronary atherosclerosis patients, when i-BIO >9, with specificity 79,8%, makes it to rule out the persons with no coronary atherosclerosis.
Conclusion. The invented complex parameter i-BIO might be regarded as a novel integrative biomarker of coronary atherosclerosis and its severity grade.
About the Authors
V. A. Metelskaya
National Research Center for Preventive Medicine of the Ministry of Health
Russian Federation
Russian Federation
N. E. Gavrilova
National Research Center for Preventive Medicine of the Ministry of Health
Russian Federation
Russian Federation
E. A. Yarovaya
National Research Center for Preventive Medicine of the Ministry of Health
Russian Federation
Russian Federation
S. A. Boytsov
Russian Cardiological Research-and-Production Complex of the Ministry of Health
Russian Federation
Russian Federation
References
1. Roth GA, Johnson C, Abajobir A, et al. Global, Regional, and National Burden of Cardiovascular Diseases for 10 Causes, 1990 to 2015. JACC July 2017; 1 (70) DOI: 10.1016/j.jacc.2017.04.052.
2. Oganov RG, Maslennikova GYa. Demographic trends in the Russian Federation: the impact of cardiovascular disease. Cardiovascular Therapy and Prevention 2012; 1 (11): 5-10. Russian (Оганов Р. Г ., Масленникова Г . Я. Демографические тенденции в Российской Федерации: вклад болезней системы кровообращения. Кардиоваск терапия и профилакт 2012; 1 (11): 5-10).
3. Fruchart J-C, Davignon J, Hermans MP, et al. Residual macrovascular risk in 2013: what have we learned? Cardiovascular Diabetol 2014; 13: 26-43.
4. Wong ND, Chuang K, Wong K, et al. Residual dyslipidemia among United States adults treated with lipid modifying therapy (data from National Health and Nutrition Examination Survey 2009-2010). Am J Cardiol 2013; 3 (112): 373-9.
5. Lloyd-Jones DM, Leip E, Larson MG, et al. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age. Circulation 2006; 113: 791-8.
6. Brown TM, Bittner V. Biomarkers of atherosclerosis: clinical applications. Curr Cardiol Rep 2008; 10 (6): 497-504.
7. Khot UN, Khot MB, Bajzer CT, et al. Prevalence of conventional risk factors in patients with coronary heart disease. JAMA 2003; 290: 898-904.
8. Vasan RS. Biomarkers of cardiovascular disease: molecular basis and practical considerations. Circulation 2006; 113: 2335-62.
9. Schiendorf KH, Nasir K, Blumenthal RS. Limitations of the Framingham risk score are now much clearer. Prev Med 2009; 48: 115-6.
10. Steyerberg EW, Vickers AJ, Cook NR, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology 2010; 21: 128-38.
11. Langlois MR Laboratory approaches for predicting and managing the risk of cardiovascular disease: postanalytical opportunities of lipid and lipoprotein testing. Clin Chem Lab Med 2012; 7 (50): 1169-81.
12. Helfand M, Buckley DI, Freeman M, et al. Emerging risk factors for coronary heart disease: a summary of systematic reviews conducted for the U. S. Preventive Services Task Force. Ann Intern Med 2009; 151: 496-507.
13. Wang TJ, Gona P, Larson MG, et al. Multiple biomarkers for the prediction of first major cardiovascular events and death. N Engl J Med 2006; 355: 2631-9.
14. Melander O, Newton-Cheh C, Almgren P, et al. Novel and conventional biomarkers for prediction of incident cardiovascular events in the community. JAMA 2009; 302: 49-57.
15. Blankenberg S, Zeller T, Saarela O, et al. Contribution of 30 biomarkers to 10-year cardiovascular risk estimation in 2 population cohorts: the MONICA, risk, genetics, archiving, and monograph (MORGAM) biomarker project. Circulation 2010; 121: 2388-97.
16. Wang TJ. Assessing the Role of Circulating, Genetic, and Imaging Biomarkers in Cardiovascular Risk Prediction. Circulation 2011; 123: 551-65.
17. Merculov EV, Mironov VM, Samko AN. Coronary angiography, ventriculography, bypass angiography in graphics and diagrams. M.: Media Medika 2011; 100p. Russian (Меркулов Е. В., Миронов В. М., Самко А . Н. Коронароангиография, вентрикулография, шунтография в иллюстрациях и схемах. М.: Медиа Медика, 2011; 100 с).
18. Gensini G. A more meaningful scoring system for determining the severity of coronary artery disease. Am J Cardiol 1983; 51: 606.
19. Gavrilova NE, Metelskaya VA, Perova NV, et al. The choice of method of quantitative evaluation of coronary artery disease based on comparative analysis of angiographic scales. Russ J Cardiol 2014; 6 (110): 24-9. Russian (Гаврилова Н. Е., Метельская В. А ., Перова Н. В. и др. Выбор метода количественной оценки поражения коронарных артерий на основе сравнительного анализа ангиографических шкал. Российский кардиологический журнал 2014; 6 (110): 24-9).
20. Gavrilova NE, Metelskaya VA, Yarovaya EB, Boytsov SA. Carotid artery duplex scan in diagnosing coronary atherosclerosis and assessing its severity. Russ J Cardiol 2014; 4 (108): 108-12. Russian (Гаврилова Н. Е., Метельская В. А ., Яровая Е. Б., Бойцов С . А . Роль дуплексного сканирования сонных артерий в выявлении коронарного атеросклероза и определении степени его выраженности. Российский кардиологический журнал 2014; 4 (108): 108-12).
21. Gavrilova N, Metelskaya V, Yarovaya E, Boytsov S. Intima-media thickness and the degree of coronary atherosclerosis. Vrach 2014; 10: 56-9 Russian (Гаврилова Н. Е., Метельская В. А ., Яровая Е. Б., Бойцов С . А . Толщина комплекса интима-медиа и выраженность коронарного атеросклероза. Врач 2014; 10: 56-9).
22. Metelskaya VA, Gavrilova NE, Gumanova NG, et al. Combination of visual and metabolic markers in assessment of probability of presence and severity of atherosclerosis of coronary Arteries. Kardiologiia 2016; 7 (56): 47-53. Russian (Метельская В. А ., Гаврилова Н. Е., Гуманова Н. Г . и др. Комбинация визуальных и метаболических маркеров в оценке вероятности наличия и выраженности атеросклероза коронарных артерий. Кардиология 2016; 7 (56): 47-53).
23. Greenland P, Knoll MD, Stamler J, et al. Major risk factors as antecedents of fatal and nonfatal coronary heart disease events. JAMA 2003; 290: 891-7.
24. Cui J. O verview of risk prediction models in cardiovascular disease research. Ann Epidemiol 2009; 19 (10): 711-7.
25. Cao JJ, Arnold AM, Manolio TA, et al. Association of carotid artery intima-media thickness, plaques, and C-reactive protein with future cardiovascular disease and all-cause mortality: the Cardiovascular Health Study. Circulation 2007; 116 (1): 32-8.
26. Marcovina SM, Crea F, Davignon J, et al. Biochemical and bioimaging markers for risk assessment and diagnosis in major cardiovascular diseases: a road to integration of complementary diagnostic tools. J Intern Med 2007; 261: 214-34.
27. Pencina MJ, D’Agostino RB, Sr D’Agostino RB, Jr, et al. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008; 27: 157-72.
28. Koenig W. Integrating biomarkers: the new frontier? Scand J Clin Lab Invest Suppl 2010; 242: 117-23.
29. Hoefer IE, Steffens S, Ala-Korpela M, et al. Novel methodologies for biomarker discovery in atherosclerosis. Eur Heart J 2015; 36 (39): 2635-42.
30. Kathiresan S, Melander O, Anevski D, et al. Polymorphisms associated with cholesterol and risk of cardiovascular events. N Engl J Med 2008; 358: 1240-49.
31. Stakhanova EA, Shevchenko AO. Multimarker analysis in heart transplant recipients and patients with acute coronary syndrome. Russian Journal of Transplantology and Artificial Organs 2014; 16: 197-8. Russian (Стаханова Е. А ., Шевченко А . О. Мультимаркерный анализ у реципиентов сердца и больных острым коронарным синдромом. Вестник трансплантологии и искусственных органов 2014: 16: 197-8).
Review
For citations:
Metelskaya V.A., Gavrilova N.E., Yarovaya E.A., Boytsov S.A. AN INTEGRATIVE BOIMARKER: OPPORTUNITIES FOR NON-INVASIVE DIAGNOSTICS OF CORONARY ATHEROSCLEROSIS. Russian Journal of Cardiology. 2017;(6):132-138. (In Russ.) https://doi.org/10.15829/1560-4071-2017-6-132-138
Views:
1163
Email this article 