The Russian prognostic scale "PHOENIX" — a novel domestic tool for cardiovascular risk assessment

3Pavlov Ryazan State Medical University. Ryazan, Russia

Aim. To develop a national cardiovascular risk prediction score based on the prevalence of risk factors (RFs), their contribution to survival, and the occurrence of a composite endpoint.

Material and methods. The prevalence of risk factors was studied in the cross-sectional studies ESSE-RF and ESSE-RF2. The prognostic value of risk factors was assessed during subsequent prospective follow-up. The algorithm was developed using a sample without prior myocardial infarction, stroke, or diabetes at baseline. Validation was performed using the MERIDIAN-RO study. Statistical analysis was performed in R (version 4.2). Kaplan-Meier curves and Cox models were used. Sex and region were included in the stratified model, while the remaining covariates were included in the regression equation. Multicollinearity was assessed using a variance inflation factor. The resulting relative risk scores were converted to an absolute 10-year probability of the composite endpoint using the Fine-Gray model. Validation was performed using the Cox model and C-indexes. Differences were considered significant at p<0,05.

Results. We excluded factors that were not modifiable by prevention and treatment, factors requiring special training for collection, biomarkers, and RFs without a significant association with the endpoint. The risk score for men included smoking, high blood pressure, tachycardia, hyperglycemia, poor self-rated health, adding extra salt to food, and a visual analog scale score <70. For women, we additionally excluded hyperuricemia, obesity, and high stress levels. The beta coefficients of the multivariate model were transformed into integers (0100). The 10-year probability of cardiovascular events was calculated in the following risk categories: "low", "moderate", "high", "very high", and "extremely high". External validation confirmed the scale prognostic significance (C-index 0,65).

Conclusion. Russian 10-year cardiovascular risk prognostic scale PHOENIX was developed as a tool for cardiovascular risk stratification in primary prevention.

1. Kobiakova OS, Deev IA, Kulikov ES, et al. Chronic noncommunicable diseases: combined effects of risk factors. Russian Journal of Preventive Medicine. 2019;22(2):45­50. (In Russ.) doi:10.17116/profmed20192202145.

2. Graham IM, Di Angelantonio E, Visseren FLJ, et al. Systematic Coronary Risk Evaluation (SCORE): JACC Focus Seminar 4/8. J Am Coll Cardiol. 2021;77(24):3046­57. doi:10.1016/j.jacc.2021. 04.052.

3. Damen JA, Pajouheshnia R, Heus P, et al. Performance of the Framingham risk models and pooled cohort equations for predicting 10­year risk of cardiovascular disease: a systematic review and meta­analysis. BMC Med. 2019;17(1):109. doi:10.1186/s12916­019­1340­7.

4. Milne RJ, Gamble G, Whitlock G, et al. Framingham heart study risk equation predicts first cardiovascular event rates in New Zealanders at the population level. N Z Med J. 2003; 116(1185):U662.

5. SCORE2 working group and ESC Cardiovascular risk collaboration. SCORE2 risk prediction algorithms: new models to estimate 10­year risk of cardiovascular disease in Europe. Eur Heart J. 2021;42(25):2439­54. doi:10.1093/eurheartj/ehab309.

6. Shalnova SA. Comments on the section "Cardiovascular risk estimation" in the 2021 European Society of Cardiology guidelines on cardiovascular disease prevention in clinical practice. Cardiovascular Therapy and Prevention. 2022;21(1):3171. (In Russ.) doi:10.15829/1728­8800­2022­3171.

7. Chipayo­Gonzales D, Ramakrishna H, Nuñez­Gil IJ. Score2: A New Updated Algorithm to Predict Cardiovascular Disease Risk in Europe. J Cardiothorac Vasc Anesth. 2022;36(1):18­21. doi:10.1053/j.jvca.2021.09.033.

8. Zairova AR, Rogoza AN, Oshchepkova EV, et al. SCORE2 cardiovascular risk stratification of an urban adult population sample and evaluation of its effectiveness based on 5­year follow­up. Cardiovascular Therapy and Prevention. 2025;24(1):4184. (In Russ.) doi:10.15829/1728­8800­2025­4184.

9. Tregubov AV, Tregubova AA, Alekseeva IV, et al. Comparison of the results of cardiovascular risk assessment using the SCORE and SCORE2 scales. The Journal of Atherosclerosis and Dyslipidemias. 2022;3(48):41­7. (In Russ.) doi:10.34687/2219­8202. JAD.2022.03.0005.

10. Svinin GE, Kutsenko VA, Shalnova SA, et al. Validation of SCORE2 on a sample from the Russian population and adaptation for the very high cardiovascular disease risk region. PLoS One. 2024;19(4):e0300974. doi:10.1371/journal.pone.0300974.

11. Beswick A, Brindle P, Fahey T, Ebrahim SA. A Systematic Review of Risk Scoring Methods and Clinical Decision Aids Used in the Primary Prevention of Coronary Heart Disease. (Supplement) [Internet]. London: Royal College of General Practitioners (UK); 2008 May.

12. Sofogianni A, Stalikas N, Antza C, et al. Cardiovascular Risk Prediction Models and Scores in the Era of Personalized Medicine. J Pers Med. 2022;12(7):1180. doi:10.3390/jpm12071180.

13. Shalnova SA, Kalinina AM, Deev AD, et al. Russian expert system ORISKON — assessment of the major non­communicable disease risk. Cardiovascular Therapy and Prevention. 2013;12(4): 51­5. (In Russ.) doi:10.15829/1728­8800­2013­4­51­55.

14. Rymar OD, Shcherbakova LV, Mustafina SV, et al. 10­year risk scale of cardiovascular events for middle­aged and elderly people with type 2 diabetes mellitus. Ateroscleroz. 2024;20(3):319­25. (In Russ.) doi:10.52727/2078­256Х­2024­20­3­319­325.

15. Mishkin IA, Kontsevaya AV, Gusev AV, et al. Development and testing of new methodical approaches for predicting cardiovascular events in healthy people using machine learning technology based on the "INTEREPID" international research. Russian Journal of Preventive Medicine. 2024;27(3):72­9. (In Russ.) doi:10.17116/profmed20242703172.

16. Research organizing committee of the ESSE­RF project. Epidemiology of cardiovascular diseases in different regions of Russia (ESSE­RF). The rationale for and design of the study. Russian Journal of Preventive Medicine. 2013;16(6):25­34. (In Russ.)

17. Balanova YuA, Imaeva AE, Kontseva AV, et al. Epidemiological monitoring of risk factors for chronic noncommunicable diseases in practical healthcare. Methodological recommendations. Edited by professor S. A. Boytsov 2016, 111p. (In Russ.) doi:10.17116/profmed2016metod01.

18. Imaeva AE, Balanova YuA, Gomanova LI, et al. Prognostic value of socioeconomic parameters among the Russian population aged 25­64: results of a population­based study. Cardiovascular Therapy and Prevention. 2024;23(12):4226. (In Russ.) doi:10.15829/17288800­2024­4226.

19. Balanova IuA, Shalnova SA, Deev AD, et al. Smoking prevalence In Russia. What has changed over 20 years? Russian Journal of Preventive Medicine. 2015;18(6):47­52. (In Russ.) doi:10.17116/profmed201518647­52.

20. Balanova IuA, Kontsevaia AV, Shalnova SA, et al. Prevalence of behavioral risk factors for cardiovascular disease in the Russian population: Results of the ESSE­RF epidemiological study. Russian Journal of Preventive Medicine. 2014;17(5):42­52. (In Russ.)

21. Maksimov SA, Shalnova SA, Volkov VV, et al. Physical activity of the Russian population depending on regional housing conditions. (ESSE­RF study). Russian Journal of Preventive Medicine. 2023;26(5):31­40. (In Russ.) doi:10.17116/profmed20232605131.

22. Karamnova NS, Maksimov SA, Kapustina AV, et al. High salt intake in the Russian population: prevalence, regional aspects, associations with socio­demographic characteristics, risk factors and diseases. Results of epidemiological studies ESSERF and EGIDA­Moscow. Cardiovascular Therapy and Prevention. 2023;22(12):3827. (In Russ.) doi:10.15829/1728­8800­2023­3827.

23. Muromtseva GA, Kontsevaya AV, Konstantinov VV, et al. The prevalence of non­infectious diseases risk factors In Russian population in 2012­2013 years. The results of ESSE­RF. Cardiovascular Therapy and Prevention. 2014;13(6):4­11. (In Russ.) doi:10.15829/1728­8800­2014­6­4­11.

24. Balanova YuA, Shalnova SA, Imaeva AE, et al. Prediabetes: prevalence, associations with cardiovascular risk factors and contribution to survival in the Russian population. Cardiovascular Therapy and Prevention. 2024;23(5):4022. (In Russ.) doi:10.15829/1728­8800­2024­4022.

25. Balanova YuA, Shalnova SA, Deev AD, et al. Obesity In Russian population — prevalence and association with the non­communicable diseases risk factors. Russian Journal of Cardiology. 2018;(6):123­30. (In Russ.) doi:10.15829/1560­4071­2018­6­123­130.

26. Balanova YuA, Shalnova SA, Imaeva AE, et al. Prevalence, Awareness, Treatment and Control of Hypertension In Russian Federation (Data of Observational ESSERF­2 Study). Rational Pharmacotherapy in Cardiology. 2019;15(4):450­66. (In Russ.) doi:10.20996/1819­6446­2019­15­4­450­466.

27. Balanova YuA, Shalnova SA, Kutsenko VA, et al. Contribution of hypertension and other risk factors to survival and mortality in the Russian population. Cardiovascular Therapy and Prevention. 2021;20(5):3003. (In Russ.) doi:10.15829/1728­8800­2021­3003.

28. Shalnova SА, Deev AD, Belova OA, et al. Heart rate and its association with the main risk factors in the population of men and women of working age. Rational Pharmacotherapy in Cardiology. 2017;13(6):819­26. (In Russ.) doi:10.20996/1819­6446­2017­13­6­819­826.

29. Gomanova LI, Balanova YuA, Shalnova SA, et al. Does the level of psychological stress affect the death risk in the Russian population. Results of ESSE­RF and ESSE­RF2. Cardiovascular Therapy and Prevention. 2024;23(12):4150. (In Russ.) doi:10.15829/1728­8800­2024­4150.

30. Gomanova LI, Balanova YuA, Shalnova SA, et al. Medical and social portrait of a person with a high level of psycho­emotional stress — justification for the prevention of chronic noncommunicable diseases. Data from ESSE­RF and ESSE­RF2. Complex Issues of Cardiovascular Diseases. 2025;14(1):37­50. (In Russ.) doi:10.17802/2306­1278­2025­14­1­37­50.

31. Shalnova SA, Evstifeeva SE, Deev AD, et al. The prevalence of anxiety and depression in different regions of the Russian Federation and its association with sociodemographic factors (according to the data of the ESSE­RF study). Therapeutic Archive. 2014;86(12):53­60. (In Russ.) doi:10.17116/terarkh2014861253­60.

32. Evstifeeva SE, Shalnova SA, Makarova YuK, et al. Is the population level of anxiety and depression associated with mortality? Data from the ESSE­RF study. Cardiovascular Therapy and Prevention. 2021;20(5):3009. (In Russ.) doi:10.15829/17288800­2021­3009.

33. Kontsevaya AV, Shalnova SA, Balanova YuA, et al. Life quality of the Russian population by the data from ESSE­RF study. Cardiovascular Therapy and Prevention. 2016;15(5):84­90. (In Russ.) doi:10.15829/1728­8800­2016­5­84­90.

34. Metelskaya VA, Shalnova SA, Deev AD, et al. Analysis of atherogenic dyslipidemias prevalence among population of Russian Federation (results of the ESSE­RF Study). Russian Journal of Preventive Medicine. 2016;19(1):15­23. (In Russ.) doi:10.17116/profmed201619115­23.

35. Shalnova SA, Metelskaya VA, Kutsenko VA, et al. Non­High Density Lipoprotein Cholesterol: A Modern Benchmark for Assessing Lipid Metabolism Disorders. Rational Pharmacotherapy in Cardiology. 2022;18(4):366­75. (In Russ.) doi:10.20996/1819­6446­2022­07­01.

36. Shalnova SA, Deev AD, Artamonova GV, et al. Hyperuricemia and its correlates in the russian population (results of ESSE­RF epidemiological study). Rational Pharmacotherapy in Cardiology. 2014;10(2):153­9. (In Russ.) doi:10.20996/1819­64462014­10­2­153­159.

37. Shalnova SA, Imaeva AE, Kutsenko VA, et al. Hyperuricemia and hypertension in working­age people: results of a population study. Cardiovascular Therapy and Prevention. 2023; 22(9S):3783. (In Russ.) doi:10.15829/1728­8800­2023­3783.

38. Drapkina OM, Shalnova SA, Kontsevaya AV, et al. Prognostic significance of troponin I in assessing cardiovascular risk in the Russian population. Data from ESSE­RF1 and ESSE­RF2 multicenter studies. Cardiovascular Therapy and Prevention. 2023;22(5):3548. (In Russ.) doi:10.15829/1728­8800­2023­3548.

39. Evstifeeva SE, Shalnova SA, Deev AD, et al. The prevalence of elevated levels of С­reactive protein and its association with traditional risk factors and morbidity among residents of the Russian Federation (according to the ESSE­RF study). Rational Pharmacotherapy in Cardiology. 2014;10(6):597­605. (In Russ.)

40. Shalnova SA, Kutsenko VA, Yakushin SS, et al. Associations of elevated levels of brain natriuretic peptide and heart failure and their contribution to survival in the Russian middle­aged population: data from the ESSE­RF study. Cardiovascular Therapy and Prevention. 2023;22(6):3553. (In Russ.) doi:10.15829/1728­8800­2023­3553.

41. Shalnova SA, Ezhov MV, Metelskaya VA, et al. Association Between Lipoprotein(a) and Risk Factors of Atherosclerosis In Russian Population (Data of Observational ESSE­RF study). Rational Pharmacotherapy in Cardiology. 2019;15(5):612­21. (In Russ.) doi:10.20996/1819­6446­2019­15­5­612­621.

42. Shalnova SA, Maksimov SA, Balanova YuA, et al. Glomerular Filtration Rate, its Association with Risk Factors and Cardiovascular Diseases. The Results of the ESSE­RF­2 Study. Rational Pharmacotherapy in Cardiology. 2020;16(2):240­9. (In Russ.)doi:10.20996/1819­64462020­04­09.

43. Muromtseva GA, Vilkov VG, Konstantinov VV, et al. The prevalence of electrocardiographic abnormalities in the Russian population in the early 21st century (the ESSE­RF study). Russian Journal of Cardiology. 2018;(12):7­17. (In Russ.) doi:10.15829/1560­4071­2018­12­7­17.

44. Muromtseva GA, Deev AD, Konstantinov VV, et al. The Prevalence of Electrocardiographic Indicators among Men and Women of Older Ages in the Russian Federation. Rational Pharmacotherapy in Cardiology. 2016;12(6):711­7. (In Russ.) doi:10.20996/1819­6446­2016­12­6­711­717.

45. Drapkina OM, Evstifeeva SE, Shalnova SA, et al. Prevalence of non­alcoholic fatty liver disease and its association with cardiovascular risk factors (data from Russian epidemiological studies). Cardiovascular Therapy and Prevention. 2025;24(2):4316. (In Russ.) doi:10.15829/1728­8800­2025­4316. EDN: CVQNXA.

46. Shalnova SA, Drapkina OM, Kutsenko VA, et al. Myocardial infarction in the population of some Russian regions and its prognostic value. Russian Journal of Cardiology. 2022;27(6):4952. (In Russ.) doi:10.15829/1560­4071­2022­4952.

47. Shalnova SA, Yarovaya EB, Filichkina EM, et al. Reclassification of ischemic heart disease epidemiological criteria. Russian Journal of Preventive Medicine. 2024;27(12):61­8. (In Russ.) Шdoi:10.17116/profmed20242712161.

48. Boytsov SA, Filippov EV, Shalnova SA, et al. Risk factors for noncommunicable diseases in the Ryazan Region (according to the data of the MERIDIAN­RO trial as the ESSE­RF pilot project). Russian Journal of Preventive Medicine. 2013;16(6):48­54. (In Russ.)

49. Filippov EV, Vorobyev AN, Dobrynina NV, et al. Adverse cardiovascular outcomes and their relationship with risk factors according to the prospective study MERIDIAN­RO. Russian Journal of Cardiology. 2019;(6):42­8. (In Russ.) doi:10.15829/1560­4071­2019­6­42­48.

50. Filippov EV, Petrov VS, Okorokov VG. IHD, Myocardial Infarction, and Stroke. Prevalence, Associations, and Impact on Outcomes (Based on the MERIDIAN­RO Study). Medical Council. 2015;(8):14­21. (In Russ.) doi:10.21518/2079­701X­2015­8­14­21.

51. Konstantinov VV, Deev AD, Balanova IuA, et al. The cardiovascular risk profile and its contribution to survival in Moscow men and women aged 35­64 years. Russian Journal of Preventive Medicine. 2013;16(1):3­7. (In Russ.)

52. Gusev AV, Gavrilov DV, Novitsky RE, et al. Improvement of cardiovascular risk assessment using machine learning methods. Russian Journal of Cardiology. 2021;26(12):4618. (In Russ.) doi:10.15829/1560­4071­2021­4618.

53. Maksimov SA, Shalnova SA, Kutsenko VA, et al. Effect of regional living conditions on middle­term cardiovascular outcomes: data from prospective stage of the ESSE­RF study. Cardiovascular Therapy and Prevention. 2021;20(5):2965. (In Russ.) doi:10.15829/1728­8800­2021­2965.