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Original article

Vol. 149 No. 2930 (2019)

Advanced carotid atherosclerosis in middle-aged subjects: comparison with PROCAM and SCORE risk categories, the potential for reclassification and cost-efficiency of carotid ultrasound in the setting of primary care

  • Michel Romanens
  • Isabella Sudano
  • Ansgar Adams
  • Walter Warmuth
DOI
https://doi.org/10.4414/smw.2019.20006
Cite this as:
Swiss Med Wkly. 2019;149:w20006
Published
24.07.2019

Summary

OBJECTIVE

About 50% of acute coronary syndromes occur in patients classified as being at low coronary risk. We aimed to assess the potential preventive benefit of carotid plaque imaging with ultrasound.

METHODS

We assessed the prevalence of “old” arteries (vascular age ≥70 years; VA70) in 3248 healthy subjects aged 40–65 years from the Swiss region of Olten and the German region of Koblenz. We compared sensitivity, specificity and discriminatory performance of SCORE, PROCAM and AGLA coronary risk calculators to detect VA70 for various decision thresholds and performed reclassification and cost-efficiency analysis.

RESULTS

VA70 was found in one out of eight subjects. Sensitivity for VA70 was 6% at the 10% AGLA threshold in women and 30% in men in the Olten area, which was confirmed for the Koblenz area with PROCAM (sensitivity 8% in women, 56% in men). Results were similar for SCORE. The discriminatory performance ranged between 0.69 and 0.82. Reclassification from low risk to a higher risk category occurred in 17–35% of patients. Analysis showed that carotid imaging for CHF 100 per person was highly cost efficient.

CONCLUSIONS

In subjects aged 40–65 years, the prevalence of old arteries is one out of eight and the detection rate of AGLA and SCORE is lower in women (6% for PROCAM) than for men (30%) at the 10% threshold. Carotid imaging may be used to reclassify subjects from low to intermediate or high cardiovascular risk. Our method is highly cost efficient at a price of CHF 100 per examination.

References

  1. Selby K, Nanchen D, Auer R, Gencer B, Räber L, Klingenberg R, et al. Low statin use in adults hospitalized with acute coronary syndrome. Prev Med. 2015;77:131–6. doi:.https://doi.org/10.1016/j.ypmed.2015.05.012
  2. Mortensen MB, Afzal S, Nordestgaard BG, Falk E. The high-density lipoprotein-adjusted SCORE model worsens SCORE-based risk classification in a contemporary population of 30,824 Europeans: the Copenhagen General Population Study. Eur Heart J. 2015;36(36):2446–53. doi:.https://doi.org/10.1093/eurheartj/ehv251
  3. Mortensen MB, Falk E. Real-life evaluation of European and American high-risk strategies for primary prevention of cardiovascular disease in patients with first myocardial infarction. BMJ Open. 2014;4(10):e005991. doi:.https://doi.org/10.1136/bmjopen-2014-005991
  4. Riesen WF, Darioli R, Noseda G, Bertel O, Buser P. Empfehlungen zur Prävention der Atherosklerose. Schweiz Arzteztg. 2005;86(22):1355–61. doi:.https://doi.org/10.4414/saez.2005.11250
  5. Johnsen SH, Mathiesen EB, Joakimsen O, Stensland E, Wilsgaard T, Løchen M-LL, et al. Carotid atherosclerosis is a stronger predictor of myocardial infarction in women than in men: a 6-year follow-up study of 6226 persons: the Tromsø Study. Stroke. 2007;38(11):2873–80. doi:.https://doi.org/10.1161/STROKEAHA.107.487264
  6. Navar-Boggan AM, Peterson ED, D’Agostino RB, Sr, Pencina MJ, Sniderman AD. Using age- and sex-specific risk thresholds to guide statin therapy: one size may not fit all. J Am Coll Cardiol. 2015;65(16):1633–9. doi:.https://doi.org/10.1016/j.jacc.2015.02.025
  7. Romanens M, Ackermann F, Sudano I, Szucs T, Spence JDD. Arterial age as a substitute for chronological age in the AGLA risk function could improve coronary risk prediction. Swiss Med Wkly. 2014;144:w13967. doi:.https://doi.org/10.4414/smw.2014.13967
  8. Romanens M. Vascular risk foundation (Varifo) [Internet]. Available from: www.varifo.ch
  9. Adams A, Bojara W. Vorhersage einer stenosierenden KHK durch Bestimmung von Plaque-Fläche und -Dicke vs. IMT an der A. carotis [Prediction of coronary artery stenosis by measurement of total plaque area and thickness versus intima media thickness of the carotid artery]. Herz. 2015;40(5):817–22. Article in German. doi:.https://doi.org/10.1007/s00059-015-4312-5
  10. Descamps OS, Cooney MT, De Backer G, Graham I. A simple multiplier to calculate the impact of HDL cholesterol on cardiovascular risk estimation using SCORE. Atherosclerosis. 2012;222(2):564–6. doi:.https://doi.org/10.1016/j.atherosclerosis.2012.03.035
  11. Perk J, De Backer G, Gohlke H, Graham I, Reiner Z, Verschuren M, et al.; European Association for Cardiovascular Prevention & Rehabilitation (EACPR); ESC Committee for Practice Guidelines (CPG). European Guidelines on cardiovascular disease prevention in clinical practice (version 2012). The Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts). Eur Heart J. 2012;33(13):1635–701. doi:.https://doi.org/10.1093/eurheartj/ehs092
  12. Assmann G, Schulte H, Cullen P, Seedorf U. Assessing risk of myocardial infarction and stroke: new data from the Prospective Cardiovascular Münster (PROCAM) study. Eur J Clin Invest. 2007;37(12):925–32. doi:.https://doi.org/10.1111/j.1365-2362.2007.01888.x
  13. Eckardstein A. AGLA Guidelines [Internet]. 2014 [cited 2016 Aug 1]. Available from: www.agla.ch
  14. Romanens M, Ackermann F, Sudano I, Szucs T, Riesen WF, Darioli R, et al. LDL-cholesterol and the potential for coronary risk improvement: evidence from a practice based carotid Imaging study. Cardiovasc Med. 2011;14(12):345–50. doi:.https://doi.org/10.4414/cvm.2011.01628
  15. Felder S, Jüni P, Meier CA, et al. SMB Statin Recommendation [Internet]. 2014. Available from: http://www.medical-board.ch/fileadmin/docs/public/mb/fachberichte/2014-07-21_bericht_statine_final_anpassung.pdf
  16. Romanens M, Sudano I, Szucs T, Adams A. Medical costs per QALY of statins based on Swiss Medical Board assumptions. Cardiovasc Med. 2017;17:96–100. doi:
  17. Mihaylova B, Emberson J, Blackwell L, Keech A, Simes J, Barnes EH, et al., Cholesterol Treatment Trialists’ (CTT) Collaborators. The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: meta-analysis of individual data from 27 randomised trials. Lancet. 2012;380(9841):581–90. doi:.https://doi.org/10.1016/S0140-6736(12)60367-5
  18. Cholesterol Treatment Trialists’ Ctt Collaborators. CTT Appendix Online 2012. Append online [Internet]. Available from: https://researchonline.lshtm.ac.uk/1649027/1/mmc1.pdf.
  19. Romanens M. VARIFO Cost Model for direct and indirect costs of cardiovascular events in Switzerland [Internet]. 2018. Available from: www.docfind.ch/CVDCosts2011.xlsx
  20. Wieser S, Tomonaga Y, Riguzzi M, Fischer B, Telser H, Pletscher M, et al. Die Kosten der nicht übertragbaren Krankheiten in der Schweiz. 2014;195. Available from: http://www.bag.admin.ch/themen/medizin/00683
  21. Philipp Lyrer. Epidemiologie des Hirnschlages. Schweizerische Aerztezeitung [Internet]. 2000 [cited 2018 Mar 30];81:835–8. Available from: https://saez.ch/de/resource/jf/journal/file/view/article/saez/de/saez.2000.07245/2000-16-224.pdf/
  22. Yeo KK, Zheng H, Chow KY, Ahmad A, Chan BPL, Chang HM, et al. Comparative analysis of recurrent events after presentation with an index myocardial infarction or ischaemic stroke. Eur Heart J Qual Care Clin Outcomes. 2017;3(3):234–42.
  23. Romanens M, Ackermann F, Spence JD, Darioli R, Rodondi N, Corti R, et al. Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics. Eur J Cardiovasc Prev Rehabil. 2010;17(1):18–23. doi:.https://doi.org/10.1097/HJR.0b013e3283347059
  24. MedCalc Software bvba, Ostend B. MedCalc Statistical Software version 17.8.1 [Internet]. 2017. Available from: http://www.medcalc.org
  25. Mortensen MB, Falk E. Limitations of the SCORE-guided European guidelines on cardiovascular disease prevention. Eur Heart J. 2017;38(29):2259–63.
  26. Baber U, Mehran R, Sartori S, Schoos M, Falk E, Sillesen H, et al. Detection and Impact of Subclinical Coronary and Carotid Atherosclerosis on Cardiovascular Risk Prediction and Reclassification in Asymptomatic Us Adults: Insights From the High Risk Plaque Bioimage Study. J Am Coll Cardiol. 2014;63(12):A998. doi:.https://doi.org/10.1016/S0735-1097(14)60998-0
  27. Spence JD, Eliasziw M, DiCicco M, Hackam DG, Galil R, Lohmann T. Carotid plaque area: a tool for targeting and evaluating vascular preventive therapy. Stroke. 2002;33(12):2916–22. doi:.https://doi.org/10.1161/01.STR.0000042207.16156.B9
  28. López-Melgar B, Fernández-Friera L, Oliva B, García-Ruiz JM, Peñalvo JL, Gómez-Talavera S, et al. Subclinical Atherosclerosis Burden by 3D Ultrasound in Mid-Life: The PESA Study. J Am Coll Cardiol. 2017;70(3):301–13. doi:.https://doi.org/10.1016/j.jacc.2017.05.033
  29. Fernández-Friera L, Peñalvo JL, Fernández-Ortiz A, Ibañez B, López-Melgar B, Laclaustra M, et al. Prevalence, Vascular Distribution, and Multiterritorial Extent of Subclinical Atherosclerosis in a Middle-Aged Cohort: The PESA (Progression of Early Subclinical Atherosclerosis) Study. Circulation. 2015;131(24):2104–13. doi:.https://doi.org/10.1161/CIRCULATIONAHA.114.014310
  30. Lindenmaier TJ, Buchanan DN, Pike D, Hartley T, Reid RD, Spence JD, et al. One, two and three-dimensional ultrasound measurements of carotid atherosclerosis before and after cardiac rehabilitation: preliminary results of a randomized controlled trial. Cardiovasc Ultrasound. 2013;11(1):39. doi:.https://doi.org/10.1186/1476-7120-11-39
  31. Groenewegen KA, den Ruijter HM, Pasterkamp G, Polak JF, Bots ML, Peters SA. Vascular age to determine cardiovascular disease risk: A systematic review of its concepts, definitions, and clinical applications. Eur J Prev Cardiol. 2016;23(3):264–74. doi:.https://doi.org/10.1177/2047487314566999
  32. Robinson JG, Stone NJ. The 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular disease risk: a new paradigm supported by more evidence. Eur Heart J. 2015;36(31):2110–8. doi:.https://doi.org/10.1093/eurheartj/ehv182
  33. Piepoli M, Hoes A, Agewall S, Albus C, Brotons C, Catapano A, et al. 2016 European guidelines on cardiovascular disease prevention in clinical practice, update 2016. Eur Heart J. 2016;37(29):2315–81. doi:.https://doi.org/10.1093/eurheartj/ehw106
  34. Sehestedt T, Jeppesen J, Hansen TW, Wachtell K, Ibsen H, Torp-Pedersen C, et al. Risk prediction is improved by adding markers of subclinical organ damage to SCORE. Eur Heart J. 2010;31(7):883–91. doi:.https://doi.org/10.1093/eurheartj/ehp546
  35. Mansia G, De Backer G, Dominiczak A, Cifkova R, Fagard R, Germano G, et al., European Society of Cardiology. 2007 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). Blood Press. 2007;16(3):135–232. doi:.https://doi.org/10.1080/08037050701461084
  36. De Backer G, Ambrosioni E, Borch-Johnsen K, Brotons C, Cifkova R, Dallongeville J, et al., European Society of Cardiology Committee for Practice Guidelines. European guidelines on cardiovascular disease prevention in clinical practice: third joint task force of European and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of eight societies and by invited experts). Eur J Cardiovasc Prev Rehabil. 2003;10(4):S1–10. doi:.https://doi.org/10.1097/00149831-200308000-00004
  37. Stone NJ, Robinson JG, Lichtenstein AH, Bairey Merz CN, Blum CB, Eckel RH, et al.; American College of Cardiology/American Heart Association Task Force on Practice Guidelines. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: 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):2889–934. doi:.https://doi.org/10.1016/j.jacc.2013.11.002
  38. Damen JAAG, Hooft L, Schuit E, Debray TPA, Collins GS, Tzoulaki I, et al. Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ. 2016;353:i2416. doi:.https://doi.org/10.1136/bmj.i2416
  39. Spitalnic S. Test Properties 2: Likelihood Ratios, Bayes’ Formula, and Receiver Operating Characteristic Curves. Hosp Physician. 2004;(October):53–8.
  40. Bayes T, Price M. An essay towards solving a problem in the doctrine of chances. Philos Trans. 1763;53(0):370–418. doi:.https://doi.org/10.1098/rstl.1763.0053