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Abstract

Aims

The aim of this study was to evaluate the performance of the US Preventive Services Task Force (USPSTF) cholesterol recommendations in a contemporary non-US cohort.

Methods and results

This is a historical cohort analysis of electronic records from Israel's largest health provider. All patients in the Tel Aviv district eligible for primary cardiovascular prevention were followed between January 2005 and December 2015. Risk was estimated by the pooled cohort equations. Statin eligibility was determined by USPSTF and American College of Cardiology and American Heart Association (ACC/AHA) recommendations. Atherosclerotic cardiovascular disease events were retrieved from electronic registration. The mean ± standard deviation age of the 10,889 (98,258 person-years) participants was 60.3 ± 9.4 years, and 69.1% were women. Outcome events were recorded for 1351 patients (12.4%). Treatment recommendations were discordant in 901 patients (8.3%) whose treatment was indicated only by the ACC/AHA guidelines, implying a 26% reduction in newly eligible patients for statin treatment had the USPSTF recommendations been implemented. Among the statin-naive patients, the pooled cohort equations underestimated the risk, with a predicted-to-observed event ratio of 0.88. The recommended treatment thresholds provided excellent calibration, with ratios of 1.0 for USPSTF and 0.98 for ACC/AHA-eligible patients. Both models showed similar discrimination (Harrel's C = 0.63 (0.62–0.65) for USPSTF vs. 0.64 (0.63–0.66) for ACC/AHA, P = 0.26). The USPSTF recommendations were less sensitive and more specific for the detection of outcome events than the ACC/AHA recommendations (61% vs. 75% and 68% vs. 55%, respectively). The net reclassification index was −0.01.

Conclusions

Calibration, discrimination and net reclassifications were very similar for USPSTF and ACC/AHA recommendations. Applying the USPSTF recommendations could reduce over-treatment.

Keywords

Cardiovascular risk prediction pooled cohort equations primary prevention over-treatment

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References

Collins

Reith

Emberson

et al.

Interpretation of the evidence for the efficacy and safety of statin therapy. Lancet 2016; 388: 2532–2561.

Piepoli

Hoes

Agewall

et al.

European Guidelines on cardiovascular disease prevention in clinical practice. Eur J Prev Cardiol 2016; 23: NP1–NP96.

Damen

JAAG

Hooft

Schuit

et al.

Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ 2016, pp. i2416.

Goff

Lloyd-Jones

Bennett

et al.

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 2014; 129: S49–S73.

Stone

Robinson

Lichtenstein

et al.

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. Circulation 2014; 63: 2889–2934.

Cook

Ridker

. Calibration of the pooled cohort equations for atherosclerotic cardiovascular disease. Ann Intern Med 2016; 165: 786–794.

Ray

Kastelein

JJP

Matthijs Boekholdt

et al.

The ACC/AHA 2013 Guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular disease risk in adults: the good the bad and the uncertain: a comparison with ESC/EAS guidelines for the management of dyslipidaemias 2011. Eur Heart J 2014; 35: 960–968.

Mortensen

Nordestgaard

Afzal

et al.

ACC/AHA Guidelines superior to ESC/EAS guidelines for primary prevention with statins in non-diabetic Europeans: the Copenhagen General Population Study. Eur Heart J 2016; 38: ehw426.

Muntner

Colantonio

Cushman

et al.

Validation of the atherosclerotic cardiovascular disease pooled cohort risk equations. JAMA 2014; 311: 1406.

10.

Wolfson

Vock

Bandyopadhyay

et al.

Use and customization of risk scores for predicting cardiovascular events using electronic health record data. J Am Heart Assoc 2017; 6: e003670.

11.

Colantonio

Richman

Carson

et al.

Performance of the atherosclerotic cardiovascular disease pooled cohort risk equations by social deprivation status. J Am Heart Assoc 2017; 6: e005676.

12.

US Preventive Services Task Force. Statin use for the primary prevention of cardiovascular disease in adults. JAMA 2016; 316: 1997–2007.

13.

Pagidipati

Navar

Mulder

et al.

Comparison of recommended eligibility for primary prevention statin therapy based on the US Preventive Services Task Force recommendations vs. the ACC/AHA guidelines. JAMA 2017; 317: 1563.

14.

Goldstein

Navar

Pencina

. Risk prediction with electronic health records: the importance of model validation and clinical context. JAMA Cardiol 2016; 1: 976–977.

15.

Rana

Tabada

Solomon

et al.

Accuracy of the atherosclerotic cardiovascular risk equation in a large contemporary, multiethnic population. J Am Coll Cardiol 2016; 67: 2118–2130.

16.

Bitzur

Rozenman

Vinker

et al.

[Israeli guidelines for the treatment of hyperlipidemia – 2014 update]. Harefuah 2015; 154: 330–333. 337–338.

17.

Cohen R and Rabin H.; National Insurance Institute Research and Planning Administration. Membership in Sick Funds, 2015. Jerusalem: National Insurance Institute Research and Planning Administration, 2016.

18.

Rennert

Peterburg

. Prevalence of selected chronic diseases in Israel. Isr Med Assoc J 2001; 3: 404–408.

19.

Dicker

Feldman

Leventer-Roberts

et al.

Obesity or smoking: which factor contributes more to the incidence of myocardial infarction?. Eur J Intern Med 2016; 32: 43–46.

20.

Tabenkin H (ed.). Clinical guidelines. Israeli Task Force for Health Promotion and Disease Prevention. Israel: Israeli Medical Association, Ramat Gan, 2008 [Hebrew].

21.

Rosen

Nakar

Cohen

et al.

Low rate of non-attenders to primary care providers in Israel – a retrospective longitudinal study. Isr J Health Policy Res 2014; 3: 15.

22.

Cohen

Dreiher

Regev-Rosenberg

et al.

[The quality indigators program in Clalit Health Services: the first decade]. Harefuah 2010; 149: 204–299. 265.

23.

Porath A, Rabinowitz G and Raskin Segal A. Quality Indicators for Community Health Care in Israel–Public Report 2005–2007. Israel: Ben Gurion University of the Negev, Be'er Sheva, 2008. http://healthindicators.org.il/wp-content/uploads/2014/08/Israel-quality-indicators-2005-2007-English.pdf.

24.

Ministry of Health Israel. The Israel Drug Registry. http://www.old.health.gov.il/units/pharmacy/trufot/index.asp?safa=e (accessed 13 April 2016).

25.

WHO Collaborating Centre for Drug Statistics Methodology. Guidelines for ATC classification and DDD assignment 2016, Oslo: WHO, 2016.

26.

Viallon

Ragusa

Clavel-Chapelon

et al.

How to evaluate the calibration of a disease risk prediction tool. Stat Med 2009; 28: 901–916.

27.

Pencina

D'Agostino

Steyerberg

. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011; 30: 11–21.

28.

Newson

. Comparing the predictive power of survival models using Harrell's c or Somers' D. Stata J 2010; 10: 1–19.

29.

Shah

Spahillari

Mwasongwe

et al.

Subclinical atherosclerosis, statin eligibility, and outcomes in African American individuals. JAMA Cardiol 2017; 2: 644.

30.

Mortensen

Afzal

Nordestgaard

et al.

Primary prevention with statins: ACC/AHA risk-based approach versus trial-based approaches to guide statin therapy. J Am Coll Cardiol 2015; 66: 2699–2709.

31.

DeFilippis

Young

Carrubba

et al.

An analysis of calibration and discrimination among multiple cardiovascular risk scores in a modern multiethnic cohort. Ann Intern Med 2015; 162: 266–275.

32.

Balicer

Afek

. Digital health nation: Israel's global big data innovation hub. Lancet 2017; 6736: 8–10.

33.

George

Rapsomaniki

Pujades-Rodriguez

et al.

How does cardiovascular disease first present in women and men? Incidence of 12 cardiovascular diseases in a contemporary cohort of 1,937,360 people. Circulation 2015; 132: 1320–1328.

34.

Kark

Goldberger

Fink

et al.

Myocardial infarction occurrence in Jerusalem: a Mediterranean anomaly. Atherosclerosis 2005; 178: 129–138.

35.

Hayashi

Shimizu

Albert

. The spectrum of epidemiology underlying sudden cardiac death. Circ Res 2015; 116: 1887–1906.

36.

Cook

Ridker

. Further insight into the cardiovascular risk calculator: the roles of statins, revascularizations, and underascertainment in the Women's Health Study. JAMA Intern Med 2014; 1204: 1964–1971.

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Validation of the 2016 USPSTF recommendations for primary cardiovascular prevention in a large contemporary cohort

Abstract

Aims

Methods and results

Conclusions

Keywords

Get full access to this article

References

Supplementary Material