Usefulness of the Addition of Beta-2-microglobulin, Cystatin C and C-reactive Protein to an Established Risk Factors Model to Improve Mortality Risk Prediction in Patients Undergoing Coronary Angiography

Overview

Journal Am J Cardiol

Specialty Cardiology & Vascular Diseases

Date 2013 Jan 8

PMID 23290308

Citations 13

Authors

Kevin T Nead

Margaret J Zhou

Roxanne Diaz Caceres

Stephen J Sharp

Mackenzie R Wehner

Jeffrey W Olin

John P Cooke

Nicholas J Leeper

Affiliations

Soon will be listed here.

Abstract

Evidence-based therapies are available to reduce the risk for death from cardiovascular disease, yet many patients go untreated. Novel methods are needed to identify those at highest risk for cardiovascular death. In this study, the biomarkers β2-microglobulin, cystatin C, and C-reactive protein were measured at baseline in a cohort of participants who underwent coronary angiography. Adjusted Cox proportional-hazards models were used to determine whether the biomarkers predicted all-cause and cardiovascular mortality. Additionally, improvements in risk reclassification and discrimination were evaluated by calculating the net reclassification improvement, C-index, and integrated discrimination improvement with the addition of the biomarkers to a baseline model of risk factors for cardiovascular disease and death. During a median follow-up period of 5.6 years, there were 78 deaths among 470 participants. All biomarkers independently predicted future all-cause and cardiovascular mortality. A significant improvement in risk reclassification was observed for all-cause (net reclassification improvement 35.8%, p = 0.004) and cardiovascular (net reclassification improvement 61.9%, p = 0.008) mortality compared to the baseline risk factors model. Additionally, there was significantly increased risk discrimination with C-indexes of 0.777 (change in C-index 0.057, 95% confidence interval 0.016 to 0.097) and 0.826 (change in C-index 0.071, 95% confidence interval 0.010 to 0.133) for all-cause and cardiovascular mortality, respectively. Improvements in risk discrimination were further supported using the integrated discrimination improvement index. In conclusion, this study provides evidence that β2-microglobulin, cystatin C, and C-reactive protein predict mortality and improve risk reclassification and discrimination for a high-risk cohort of patients who undergo coronary angiography.

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References

Harris P, Taylor R, Thielke R, Payne J, Gonzalez N, Conde J . Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2008; 42(2):377-81. PMC: 2700030. DOI: 10.1016/j.jbi.2008.08.010. View

Wilson A, Sadrzadeh-Rafie A, Myers J, Assimes T, Nead K, Higgins M . Low lifetime recreational activity is a risk factor for peripheral arterial disease. J Vasc Surg. 2011; 54(2):427-32, 432.e1-4. PMC: 3152670. DOI: 10.1016/j.jvs.2011.02.052. View

DAgostino Sr R, Vasan R, Pencina M, Wolf P, Cobain M, Massaro J . General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008; 117(6):743-53. DOI: 10.1161/CIRCULATIONAHA.107.699579. View

Pencina M, DAgostino R . Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation. Stat Med. 2004; 23(13):2109-23. DOI: 10.1002/sim.1802. View

Pencina M, DAgostino Sr R, DAgostino Jr R, Vasan R . Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2007; 27(2):157-72. DOI: 10.1002/sim.2929. View

Levey A, Bosch J, Lewis J, Greene T, Rogers N, Roth D . A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999; 130(6):461-70. DOI: 10.7326/0003-4819-130-6-199903160-00002. View

Ambrose J, Srikanth S . Vulnerable plaques and patients: improving prediction of future coronary events. Am J Med. 2010; 123(1):10-6. DOI: 10.1016/j.amjmed.2009.07.019. View

Henry R, Kostense P, Bos G, Dekker J, Nijpels G, Heine R . Mild renal insufficiency is associated with increased cardiovascular mortality: The Hoorn Study. Kidney Int. 2002; 62(4):1402-7. DOI: 10.1111/j.1523-1755.2002.kid571.x. View

Sadrzadeh Rafie A, Stefanick M, Sims S, Phan T, Higgins M, Gabriel A . Sex differences in the prevalence of peripheral artery disease in patients undergoing coronary catheterization. Vasc Med. 2010; 15(6):443-50. DOI: 10.1177/1358863X10388345. View

10.

Coll E, Botey A, Alvarez L, Poch E, Quinto L, Saurina A . Serum cystatin C as a new marker for noninvasive estimation of glomerular filtration rate and as a marker for early renal impairment. Am J Kidney Dis. 2000; 36(1):29-34. DOI: 10.1053/ajkd.2000.8237. View

11.

Kals J, Zagura M, Serg M, Kampus P, Zilmer K, Unt E . β2-microglobulin, a novel biomarker of peripheral arterial disease, independently predicts aortic stiffness in these patients. Scand J Clin Lab Invest. 2011; 71(4):257-63. DOI: 10.3109/00365513.2011.558108. View

12.

Amighi J, Hoke M, Mlekusch W, Schlager O, Exner M, Haumer M . Beta 2 microglobulin and the risk for cardiovascular events in patients with asymptomatic carotid atherosclerosis. Stroke. 2011; 42(7):1826-33. DOI: 10.1161/STROKEAHA.110.600312. View

13.

Atar D, Ramanujam P, Saunamaki K, Haunso S . Assessment of coronary artery stenosis pressure gradient by quantitative coronary arteriography in patients with coronary artery disease. Clin Physiol. 1994; 14(1):23-35. DOI: 10.1111/j.1475-097x.1994.tb00486.x. View

14.

Pencina M, DAgostino Sr R, Steyerberg E . Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med. 2011; 30(1):11-21. PMC: 3341973. DOI: 10.1002/sim.4085. View

15.

Roger V, Go A, Lloyd-Jones D, Benjamin E, Berry J, Borden W . Executive summary: heart disease and stroke statistics--2012 update: a report from the American Heart Association. Circulation. 2012; 125(1):188-97. DOI: 10.1161/CIR.0b013e3182456d46. View

16.

Kalawski R, Majewski M, Kaszkowiak E, Wysocki H, Siminiak T . Transcardiac release of soluble adhesion molecules during coronary artery bypass grafting: effects of crystalloid and blood cardioplegia. Chest. 2003; 123(5):1355-60. DOI: 10.1378/chest.123.5.1355. View

17.

Shinkai S, Chaves P, Fujiwara Y, Watanabe S, Shibata H, Yoshida H . Beta2-microglobulin for risk stratification of total mortality in the elderly population: comparison with cystatin C and C-reactive protein. Arch Intern Med. 2008; 168(2):200-6. DOI: 10.1001/archinternmed.2007.64. View

18.

Stamler J, Vaccaro O, Neaton J, Wentworth D . Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care. 1993; 16(2):434-44. DOI: 10.2337/diacare.16.2.434. View

19.

Fung E, Wilson A, Zhang F, Harris N, Edwards K, Olin J . A biomarker panel for peripheral arterial disease. Vasc Med. 2008; 13(3):217-24. PMC: 3133945. DOI: 10.1177/1358863X08089276. View

20.

Harrell Jr F, Lee K, Mark D . Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996; 15(4):361-87. DOI: 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4. View