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The comparison of cardiovascular disease risk prediction scores and evaluation of subclinical atherosclerosis in rheumatoid arthritis: a cross-sectional study

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Abstract

Objectives

Primary objectives estimated prevalence of traditional cardiovascular disease (CVD) risk factors and compared different CVD risk prediction algorithms in an Indian rheumatoid arthritis (RA) population. Secondary objectives evaluated associations between carotid intima-media thickness (CIMT) and subclinical atherosclerosis (SCA) with CVD risk factors and CVD risk scores.

Methods

The presence of CVD risk factors were recorded, and 10-year CVD risk was predicted using Framingham risk scoring (FRS) using lipids (FRS-Lipids), FRS using body mass index (FRS-BMI), QRISK-2, SCORE, and the algorithm recommended by ACC/AHA (ASCVD). CIMT was measured on the far-wall of the common carotid artery. Subclinical atherosclerosis was defined as CIMT > 0.9 mm or the presence of carotid plaque.

Results

A total of 332 patents were enrolled, 12% had diabetes mellitus, 21.4% hypertension, and 6.9% were current/past smokers. Proportions of RA with predicted 10-year CVD risk > 10% varied from 16.2 to 41.9% between scores. Highest magnitude of risk was predicted by FRS-BMI. Agreement between scores in predicting risk was moderate in general. Mean CIMT was 0.70 ± 0.15 mm. Age, male sex, and extra-articular manifestations associated with greater CIMT. All risk scores except SCORE moderately correlated with CIMT. About one-seventh had SCA defined as CIMT > 0.9 mm or the presence of carotid plaques, associated with increasing age, male gender, or higher ratio of total cholesterol to high-density lipoprotein cholesterol. ASCVD and QRISK-2 scores had maximum area under curve for distinguishing SCA.

Conclusion

Individual CVD risk scores predict 10-year CVD risk differently in Indian patients with RA, and require validation for predicting hard end points (CVD events, mortality).

Key Points

• Diabetes mellitus and hypertension are the most prevalent cardiovascular disease risk factors in Indian patients with RA.

• Individual cardiovascular risk prediction scores predict risk differently in Indian patients with RA, highest risk being predicted by the FRS-BMI.

• Carotid intima-media thickness in RA associated with increasing age, male sex and extra-articular manifestations.

• 14% RA had subclinical atherosclerosis, associated with increasing age, male sex, and higher total cholesterol to HDL-C ratio, best distinguished by ASCVD and QRISK-2 scores.

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Data availability

Data pertaining to this article shall be shared on reasonable request to the corresponding author (Durga Prasanna Misra, durgapmisra@gmail.com).

References

  1. Sokka T, Abelson B, Pincus T (2008) Mortality in rheumatoid arthritis: 2008 update. Clin Exp Rheumatol 26:S35-61

    CAS  PubMed  Google Scholar 

  2. Aviña-Zubieta JA, Choi HK, Sadatsafavi M, Etminan M, Esdaile JM, Lacaille D (2008) Risk of cardiovascular mortality in patients with rheumatoid arthritis: a meta-analysis of observational studies. Arthritis Rheum 59:1690–1697. https://doi.org/10.1002/art.24092

    Article  PubMed  Google Scholar 

  3. Ferguson LD, Siebert S, McInnes IB, Sattar N (2019) Cardiometabolic comorbidities in RA and PsA: lessons learned and future directions. Nat Rev Rheumatol 15:461–474. https://doi.org/10.1038/s41584-019-0256-0

    Article  PubMed  Google Scholar 

  4. D’Agostino RB Sr, Vasan RS, Pencina MJ et al (2008) General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 117:743–753. https://doi.org/10.1161/circulationaha.107.699579

    Article  PubMed  Google Scholar 

  5. Conroy RM, Pyörälä K, Fitzgerald AP et al (2003) Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 24:987–1003. https://doi.org/10.1016/s0195-668x(03)00114-3

    Article  CAS  PubMed  Google Scholar 

  6. Hippisley-Cox J, Coupland C, Vinogradova Y et al (2008) Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. BMJ 336:1475–1482. https://doi.org/10.1136/bmj.39609.449676.25

    Article  PubMed  PubMed Central  Google Scholar 

  7. Goff DC Jr, Lloyd-Jones DM, Bennett G et al (2014) 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. Circulation 129:S49-73. https://doi.org/10.1161/01.cir.0000437741.48606.98

    Article  PubMed  Google Scholar 

  8. Garg N, Muduli SK, Kapoor A et al (2017) Comparison of different cardiovascular risk score calculators for cardiovascular risk prediction and guideline recommended statin uses. Indian Heart J 69:458–463. https://doi.org/10.1016/j.ihj.2017.01.015

    Article  PubMed  PubMed Central  Google Scholar 

  9. Agca R, Heslinga SC, Rollefstad S et al (2017) EULAR recommendations for cardiovascular disease risk management in patients with rheumatoid arthritis and other forms of inflammatory joint disorders: 2015/2016 update. Ann Rheum Dis 76:17–28. https://doi.org/10.1136/annrheumdis-2016-209775

    Article  CAS  PubMed  Google Scholar 

  10. Naqvi TZ, Lee MS (2014) Carotid intima-media thickness and plaque in cardiovascular risk assessment. JACC Cardiovasc Imaging 7:1025–1038. https://doi.org/10.1016/j.jcmg.2013.11.014

    Article  PubMed  Google Scholar 

  11. Holland Z, Ntyintyane L, Gill G, Raal F (2009) Carotid intima-media thickness is a predictor of coronary artery disease in South African black patients. Cardiovasc J Afr 20:237–239

    PubMed  PubMed Central  Google Scholar 

  12. Baldassarre D, Hamsten A, Veglia F et al (2012) Measurements of carotid intima-media thickness and of interadventitia common carotid diameter improve prediction of cardiovascular events: results of the IMPROVE (Carotid Intima Media Thickness [IMT] and IMT-Progression as predictors of vascular events in a high risk European population) study. J Am Coll Cardiol 60:1489–1499. https://doi.org/10.1016/j.jacc.2012.06.034

    Article  PubMed  Google Scholar 

  13. Galarza-Delgado DA, Azpiri-Lopez JR, Colunga-Pedraza IJ et al (2017) Assessment of six cardiovascular risk calculators in Mexican mestizo patients with rheumatoid arthritis according to the EULAR 2015/2016 recommendations for cardiovascular risk management. Clin Rheumatol 36:1387–1393. https://doi.org/10.1007/s10067-017-3551-7

    Article  PubMed  Google Scholar 

  14. Crowson CS, Gabriel SE, Semb AG et al (2017) Rheumatoid arthritis-specific cardiovascular risk scores are not superior to general risk scores: a validation analysis of patients from seven countries. Rheumatology (Oxford) 56:1102–1110. https://doi.org/10.1093/rheumatology/kex038

    Article  CAS  Google Scholar 

  15. Aletaha D, Neogi T, Silman AJ et al (2010) 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum 62:2569–2581. https://doi.org/10.1002/art.27584

    Article  PubMed  Google Scholar 

  16. Sohn C, Kim J, Bae W (2012) The framingham risk score, diet, and inflammatory markers in Korean men with metabolic syndrome. Nutr Res Pract 6:246–253. https://doi.org/10.4162/nrp.2012.6.3.246

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Wang TJ, Nam BH, D’Agostino RB et al (2003) Carotid intima-media thickness is associated with premature parental coronary heart disease: the Framingham Heart Study. Circulation 108:572–576. https://doi.org/10.1161/01.Cir.0000081764.35431.De

    Article  PubMed  Google Scholar 

  18. Casadei A, Floreani M, Catalini R, Serra C, Assanti AP, Conci P (2012) Sonographic characteristics of carotid artery plaques: implications for follow-up planning? J Ultrasound 15:151–157. https://doi.org/10.1016/j.jus.2012.06.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Mancia G, De Backer G, Dominiczak A et al (2007) 2007 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). Eur Heart J 28:1462–1536. https://doi.org/10.1093/eurheartj/ehm236

    Article  PubMed  Google Scholar 

  20. Kasliwal RR, Bansal M, Desai N et al (2016) A Study to derive distribution of carotid intima media thickness and to determine its correlation with cardiovascular Risk factors in asymptomatic nationwidE Indian population (SCORE-India). Indian Heart J 68:821–827. https://doi.org/10.1016/j.ihj.2016.04.009

    Article  PubMed  PubMed Central  Google Scholar 

  21. Nambi V, Chambless L, Folsom AR et al (2010) Carotid intima-media thickness and presence or absence of plaque improves prediction of coronary heart disease risk: the ARIC (Atherosclerosis Risk In Communities) study. J Am Coll Cardiol 55:1600–1607. https://doi.org/10.1016/j.jacc.2009.11.075

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Pourhoseingholi MA, Vahedi M, Rahimzadeh M (2013) Sample size calculation in medical studies. Gastroenterol Hepatol Bed Bench 6:14–17

    PubMed  PubMed Central  Google Scholar 

  23. Jenkins DG, Quintana-Ascencio PF (2020) A solution to minimum sample size for regressions. PLoS ONE 15:e0229345. https://doi.org/10.1371/journal.pone.0229345

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Drosos GC, Vedder D, Houben E et al (2022) EULAR recommendations for cardiovascular risk management in rheumatic and musculoskeletal diseases, including systemic lupus erythematosus and antiphospholipid syndrome. Ann Rheum Dis 81:768–779. https://doi.org/10.1136/annrheumdis-2021-221733

    Article  CAS  PubMed  Google Scholar 

  25. Boyer JF, Gourraud PA, Cantagrel A, Davignon JL, Constantin A (2011) Traditional cardiovascular risk factors in rheumatoid arthritis: a meta-analysis. Joint Bone Spine 78:179–183. https://doi.org/10.1016/j.jbspin.2010.07.016

    Article  PubMed  Google Scholar 

  26. Roman MJ, Moeller E, Davis A et al (2006) Preclinical carotid atherosclerosis in patients with rheumatoid arthritis. Ann Intern Med 144:249–256. https://doi.org/10.7326/0003-4819-144-4-200602210-00006

    Article  PubMed  Google Scholar 

  27. McEntegart A, Capell HA, Creran D, Rumley A, Woodward M, Lowe GD (2001) Cardiovascular risk factors, including thrombotic variables, in a population with rheumatoid arthritis. Rheumatology (Oxford) 40:640–644. https://doi.org/10.1093/rheumatology/40.6.640

    Article  CAS  Google Scholar 

  28. Dessein PH, Stanwix AE, Joffe BI (2002) Cardiovascular risk in rheumatoid arthritis versus osteoarthritis: acute phase response related decreased insulin sensitivity and high-density lipoprotein cholesterol as well as clustering of metabolic syndrome features in rheumatoid arthritis. Arthritis Res 4:R5. https://doi.org/10.1186/ar428

    Article  PubMed  PubMed Central  Google Scholar 

  29. Gerli R, Sherer Y, Vaudo G et al (2005) Early atherosclerosis in rheumatoid arthritis: effects of smoking on thickness of the carotid artery intima media. Ann N Y Acad Sci 1051:281–290. https://doi.org/10.1196/annals.1361.069

    Article  PubMed  Google Scholar 

  30. Jonsson SW, Backman C, Johnson O et al (2001) Increased prevalence of atherosclerosis in patients with medium term rheumatoid arthritis. J Rheumatol 28:2597–2602

    CAS  PubMed  Google Scholar 

  31. Desai SS, Myles JD, Kaplan MJ (2012) Suboptimal cardiovascular risk factor identification and management in patients with rheumatoid arthritis: a cohort analysis. Arthritis Res Ther 14:R270. https://doi.org/10.1186/ar4118

    Article  PubMed  PubMed Central  Google Scholar 

  32. Semb AG, Rollefstad S, Ikdahl E et al (2021) Diabetes mellitus and cardiovascular risk management in patients with rheumatoid arthritis: an international audit. RMD Open 7:e001724. https://doi.org/10.1136/rmdopen-2021-001724

    Article  PubMed  PubMed Central  Google Scholar 

  33. Chandrashekara S, Shobha V, Dharmanand BG et al (2017) Comorbidities and related factors in rheumatoid arthritis patients of south India- Karnataka Rheumatoid Arthritis Comorbidity (KRAC) study. Reumatismo 69:47–58. https://doi.org/10.4081/reumatismo.2017.898

    Article  CAS  PubMed  Google Scholar 

  34. Little M, Humphries S, Patel K, Dewey C (2017) Decoding the type 2 diabetes epidemic in rural India. Med Anthropol 36:96–110. https://doi.org/10.1080/01459740.2016.1231676

    Article  PubMed  Google Scholar 

  35. Anchala R, Kannuri NK, Pant H et al (2014) Hypertension in India: a systematic review and meta-analysis of prevalence, awareness, and control of hypertension. J Hypertens 32:1170–1177. https://doi.org/10.1097/hjh.0000000000000146

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Rollefstad S, Ikdahl E, Wibetoe G et al (2021) An international audit of the management of dyslipidaemia and hypertension in patients with rheumatoid arthritis-results from 19 countries. Eur Heart J Cardiovasc Pharmacother. https://doi.org/10.1093/ehjcvp/pvab052

    Article  Google Scholar 

  37. Arnett DK, Blumenthal RS, Albert MA et al (2019) 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 140:e596–e646. https://doi.org/10.1161/cir.0000000000000678

    Article  PubMed  PubMed Central  Google Scholar 

  38. Solomon DH, Greenberg J, Curtis JR et al (2015) Derivation and internal validation of an expanded cardiovascular risk prediction score for rheumatoid arthritis: a Consortium of Rheumatology Researchers of North America Registry Study. Arthritis Rheumatol 67:1995–2003. https://doi.org/10.1002/art.39195

    Article  CAS  PubMed  Google Scholar 

  39. SCORE2 working group and ESC Cardiovascular risk collaboration (2021) SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J 42:2439–2454. https://doi.org/10.1093/eurheartj/ehab309

    Article  CAS  Google Scholar 

  40. Chopra A, Raghunath D, Singh A, Subramanian AR (1988) The pattern of rheumatoid arthritis in the Indian population: a prospective study. Br J Rheumatol 27:454–456. https://doi.org/10.1093/rheumatology/27.6.454

    Article  CAS  PubMed  Google Scholar 

  41. Malaviya AN, Kapoor SK, Singh RR, Kumar A, Pande I (1993) Prevalence of rheumatoid arthritis in the adult Indian population. Rheumatol Int 13:131–134. https://doi.org/10.1007/bf00301258

    Article  CAS  PubMed  Google Scholar 

  42. Bedi GS, Gupta N, Handa R, Pal H, Pandey RM (2005) Quality of life in Indian patients with rheumatoid arthritis. Qual Life Res 14:1953–1958. https://doi.org/10.1007/s11136-005-4540-x

    Article  PubMed  Google Scholar 

  43. Nag T, Ghosh A (2013) Cardiovascular disease risk factors in Asian Indian population: a systematic review. J Cardiovasc Dis Res 4:222–228. https://doi.org/10.1016/j.jcdr.2014.01.004

    Article  PubMed  Google Scholar 

  44. Prabhakaran D, Jeemon P, Roy A (2016) Cardiovascular diseases in India: Current epidemiology and future directions. Circulation 133:1605–1620. https://doi.org/10.1161/circulationaha.114.008729

    Article  PubMed  Google Scholar 

  45. Wah-Suarez MI, Galarza-Delgado DA, Azpiri-Lopez JR et al (2018) The best cardiovascular risk calculator to predict carotid plaques in rheumatoid arthritis patients. Clin Rheumatol 37:2373–2380. https://doi.org/10.1007/s10067-018-4181-4

    Article  PubMed  Google Scholar 

  46. Jafri K, Ogdie A, Qasim A et al (2018) Discordance of the Framingham cardiovascular risk score and the 2013 American College of Cardiology/American Heart Association risk score in systemic lupus erythematosus and rheumatoid arthritis. Clin Rheumatol 37:467–474. https://doi.org/10.1007/s10067-017-3860-x

    Article  PubMed  Google Scholar 

  47. Sivakumaran J, Harvey P, Omar A et al (2021) Assessment of cardiovascular risk tools as predictors of cardiovascular disease events in systemic lupus erythematosus. Lupus Sci Med 8.https://doi.org/10.1136/lupus-2020-000448

  48. Galarza-Delgado DA, Azpiri-Lopez JR, Colunga-Pedraza IJ et al (2022) Cardiovascular risk reclassification according to six cardiovascular risk algorithms and carotid ultrasound in psoriatic arthritis patients. Clin Rheumatol 41:1413–1420. https://doi.org/10.1007/s10067-021-06002-0

    Article  PubMed  Google Scholar 

  49. Liew JW, Reveille JD, Castillo M et al (2021) Cardiovascular risk scores in axial spondyloarthritis versus the general population: a cross-sectional study. J Rheumatol 48:361–366. https://doi.org/10.3899/jrheum.200188

    Article  PubMed  Google Scholar 

  50. Navarini L, Caso F, Costa L et al (2020) Cardiovascular risk prediction in ankylosing spondylitis: from traditional scores to machine learning assessment. Rheumatol Ther 7:867–882. https://doi.org/10.1007/s40744-020-00233-4

    Article  PubMed  PubMed Central  Google Scholar 

  51. Shakeri A, Bazzaz MB, Khabbazi A, Fouladi RF (2011) Common carotid intima-media thickness in patients with late rheumatoid arthritis; what is the role of gender? Pak J Biol Sci 14:812–816. https://doi.org/10.3923/pjbs.2011.812.816

    Article  CAS  PubMed  Google Scholar 

  52. Semb AG, Ikdahl E, Wibetoe G, Crowson C, Rollefstad S (2020) Atherosclerotic cardiovascular disease prevention in rheumatoid arthritis. Nat Rev Rheumatol 16:361–379. https://doi.org/10.1038/s41584-020-0428-y

    Article  PubMed  Google Scholar 

  53. Turesson C, McClelland RL, Christianson TJ, Matteson EL (2007) Severe extra-articular disease manifestations are associated with an increased risk of first ever cardiovascular events in patients with rheumatoid arthritis. Ann Rheum Dis 66:70–75. https://doi.org/10.1136/ard.2006.052506

    Article  CAS  PubMed  Google Scholar 

  54. Figus FA, Piga M, Azzolin I, McConnell R, Iagnocco A (2021) Rheumatoid arthritis: extra-articular manifestations and comorbidities. Autoimmun Rev 20:102776. https://doi.org/10.1016/j.autrev.2021.102776

    Article  CAS  PubMed  Google Scholar 

  55. Ozen G, Sunbul M, Atagunduz P, Direskeneli H, Tigen K, Inanc N (2016) The 2013 ACC/AHA 10-year atherosclerotic cardiovascular disease risk index is better than SCORE and QRisk II in rheumatoid arthritis: is it enough? Rheumatology (Oxford) 55:513–522. https://doi.org/10.1093/rheumatology/kev363

    Article  Google Scholar 

  56. Ridker PM, Everett BM, Thuren T et al (2017) Antiinflammatory Therapy with canakinumab for atherosclerotic disease. N Engl J Med 377:1119–1131. https://doi.org/10.1056/NEJMoa1707914

    Article  CAS  PubMed  Google Scholar 

  57. Karpouzas GA, Ormseth SR, Hernandez E, Budoff MJ (2020) Biologics may prevent cardiovascular events in rheumatoid arthritis by inhibiting coronary plaque formation and stabilizing high-risk lesions. Arthritis Rheumatol 72:1467–1475. https://doi.org/10.1002/art.41293

    Article  CAS  PubMed  Google Scholar 

  58. Salaffi F, Carotti M, Di Carlo M et al (2018) The Expanded Risk Score in Rheumatoid Arthritis (ERS-RA): performance of a disease-specific calculator in comparison with the traditional prediction scores in the assessment of the 10-year risk of cardiovascular disease in patients with rheumatoid arthrit. Swiss Med Wkly 148:w14656. https://doi.org/10.4414/smw.2018.14656

    Article  CAS  PubMed  Google Scholar 

  59. Curtis JR, Singh JA (2011) Use of biologics in rheumatoid arthritis: current and emerging paradigms of care. Clin Ther 33:679–707. https://doi.org/10.1016/j.clinthera.2011.05.044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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The conception and design of the study – DPM, VA, SK; acquisition of data, analysis and interpretation of data – HM, DPM, NJ, SG, SSP, MKR, AKA, NM. Drafting the article – HM, DPM, NJ; revising it critically for important intellectual content – SG, SSP, MKR, AKA, NM, SK, VA. Final approval of the version to be submitted – DPM, HM, NJ, SG, SSP, MKR, AKA, NM, SK, VA. Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved – DPM, HM, NJ, SG, SSP, MKR, AKA, NM, SK, VA.

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Correspondence to Durga Prasanna Misra.

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The study was approved by the Institute Ethics Committee, SGPGIMS, Lucknow [ethics submission number 2018–5-DM-EXP, letter number PGI/BE/52/2018, date of approval 19 February 2018]. All participants were recruited into the study after obtaining written informed consent for participation.

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Muhammed, H., Misra, D.P., Jain, N. et al. The comparison of cardiovascular disease risk prediction scores and evaluation of subclinical atherosclerosis in rheumatoid arthritis: a cross-sectional study. Clin Rheumatol 41, 3675–3686 (2022). https://doi.org/10.1007/s10067-022-06349-y

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