2021 ESC Guidelines reduce statin eligibility in low-ASCVD-risk European countries

Statin Eligibility for Primary Prevention of Cardiovascular Disease According to 2021 European Prevention Guidelines Compared With Other International Guidelines

Literature - Mortensen MB, Tybjærg-Hansen A, Nordestgaard BG - JAMA Cardiol. 2022 Aug 1;7(8):836-843. doi: 10.1001/jamacardio.2022.1876

Introduction and methods

Background

Statin treatment is restricted to individuals who have a 10-year risk of ASCVD above certain clinical guideline–defined treatment thresholds [1]. The SCORE (Systematic Coronary Risk Evaluation) prediction model estimates the 10-year risk of fatal ASCVD events and has been used since the publication of the 2003 European Society of Cardiology (ESC) Guidelines on statin use [2]. This risk model was also used in the previous 2019 ESC/European Atherosclerosis Society (EAS) Guidelines on dyslipidemia [3].

The updated version of this risk model, the SCORE2 model, now estimates the 10-year risk of total (i.e. fatal and nonfatal) ASCVD events [4]. The SCORE2 model was incorporated in the 2021 ESC Guidelines on CVD prevention, as well as new age-specific treatment thresholds for statins [5 ]. Models assessing the 10-year risk of total ASCVD events are also recommended in the 2013 American College of Cardiology/American Heart Association (ACC/AHA) guideline on assessment of CVD risk (pooled cohort equations (PCE) model) and the (in 2016 updated) UK National Institute for Health and Care Excellence (NICE) clinical guideline on lipid modification (QRISK model) [6,7].

Aim of the study

In apparently healthy individuals, the authors compared the clinical performance of the 2021 ESC Guidelines for CVD prevention on eligibility of primary prevention with statins with that of the 2013 ACC/AHA guideline, the 2016 NICE guideline, and the 2019 ESC/EAS Guidelines.

Methods

In this population-based, contemporary cohort study, data from 66,909 White Europeans from the Copenhagen General Population Study were used who were enrolled from 2003 through 2015. As the 2021 ESC Guidelines only provide class I recommendations for statin treatment for individuals aged 40–49 years with SCORE2 risk ≥7.5% and for those aged 50–69 years with SCORE2 risk ≥10%, people in this age range were included. Exclusion criteria were preexisting ASCVD, DM, CKD, and statin use. The mean follow-up time was 9.2 years.

In this study, the low-risk version of the SCORE2 model, which is intended for most of Western Europe, the low-risk version of the SCORE1 model, and the latest version of the QRISK model, QRISK3 [8], were used.

Outcomes

Calibration of the risk models (assessed with the predicted/observed (P/O) ratio), statin eligibility of the participants, and sensitivity and specificity of the models for ASCVD events according to the different guideline criteria were assessed.

Main results

Estimated 10-year risk

  • During the follow-up, 2692 participants experienced a SCORE2 event, 2782 a PCE event, 4277 a QRISK3 event, and 180 a SCORE1 event.
  • There was a high degree of correlation between the 10-year ASCVD risks estimated by the 4 models (Spearman coefficient ranged from 0.88 to 0.99).
  • However, the mean estimated 10-year ASCVD risk was lower when the SCORE2 (4.2; 95%CI: 4.1–4.2) and SCORE1 models (2.1; 95%CI: 2.0–2.1) were used than with the PCE (6.4; 95%CI: 6.4–6.5) and QRISK3 models (7.4; 95%CI: 7.4–7.5).

Risk model calibration and discrimination

  • The overall P/O ASCVD event ratio was 0.8 for the SCORE2 model, 1.3 for both the PCE and QRISK3 models, and 5.8 for the SCORE1 model, which indicated that the SCORE2 model was slightly better calibrated than the others.
  • The discriminatory performance of the 4 models was similar, albeit significantly different: the Harrell C statistic was 0.710 for the SCORE2 model, 0.700 for the SCORE1 model (P value for difference with SCORE2<0.001), 0.712 for the PCE model (P value for difference with SCORE2=0.004), and 0.713 for the QRISK3 model (P value for difference with SCORE2=0.005).

Clinical performance of guidelines

  • According to the 2021 ESC Guidelines, a class I recommendation for statin treatment would be issued for 2862 of the 66,909 participants (4%). With the ACC/AHA guideline, 23,029 individuals (34%) would be eligible, 17,659 (26%) with the NICE guideline, and 13,496 (20%) with the ESC/EAS Guidelines.
  • The corresponding sensitivities for predicting future SCORE2–defined ASCVD events were 14% , 60%, 51%, and 36%, respectively.
  • Statin eligibility, sensitivity, and specificity varied considerably by age and gender, but the statin eligibility and sensitivity were lowest overall for the 2021 ESC Guidelines.
  • Almost none of the women and 2% of the men aged 40–49 years met the 7.5% SCORE2 risk threshold, whereas 1% of the women and 13% of the men aged 50–69 years met the 10% SCORE2 risk threshold.

Clinical performance of different SCORE2 treatment thresholds

  • By lowering the treatment thresholds in the overall population or in an age- and sex-specific manner, the sensitivity of the 2021 ESC Guidelines could be markedly increased, with small reductions in specificity.
  • To increase the clinical performance of the 2021 ESC Guidelines to a similar level as that of the other 3 guidelines, the risk threshold of the SCORE2 model should be 5% to match the ACC/AHA, 6% to match the NICE, and 7% to match the ESC/EAS Guidelines.

Conclusion

Use of the new treatment thresholds in the 2021 ESC Guidelines, which are based on the SCORE2 prediction model, reduced an individual’s eligibility for primary prevention with statins to 4% in Denmark—a low-ASCVD-risk European country—compared with 20%–34% according to the ACC/AHA, NICE, and ESC/EAS Guidelines. Lowering the treatment thresholds could improve the clinical performance of the 2021 ESC Guidelines.

The authors believe their “results are important for clinical practice and future European-ESC [G]uidelines on primary prevention with statins, as they point toward a likely unintended dramatic reduction in the potential for ASCVD prevention by implementing the 2021 European-ESC age-specific treatment criteria.”

References

1. Lloyd-Jones DM. Cardiovascular risk prediction: basic concepts, current status, and future directions. Circulation. 2010;121(15):1768-1777. doi:10.1161/circulationaha.109.849166

2. De Backer G, Ambrosioni E, Borch-Johnsen K, et al; Third Joint Task Force of European and Other Societies on Cardiovascular Disease Prevention in Clinical Practice. European guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2003;24(17):1601-1610. doi:10.1016/S0195-668X(03)00347-6

3. Mach F, Baigent C, Catapano AL, et al.; ESC Scientific Document Group. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J. 2020;41(1):111-188. doi: 10.1093/eurheartj/ehz455

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

5. Visseren FLJ, Mach F, Smulders YM, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021 Sep 7;42(34):3227-3337. doi: 10.1093/eurheartj/ehab484

6. Goff DC Jr, Lloyd-Jones DM, Bennett G, et al; American College of Cardiology/American Heart Association Task Force on Practice Guidelines. 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):2935-2959. doi:10.1016/j.jacc.2013.11.005

7. National Institute for Health and Care Excellence (NICE) National Clinical Guideline Centre. Clinical Guideline CG181: lipid modification: cardiovascular risk assessment and the modification of blood lipids for the primary and secondary prevention of cardiovascular disease. Updated November 21, 2016.

8. 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. doi:10.1136/bmj.j2099

Find this article online at JAMA Cardiol.

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