Predicting Risk for Percutaneous Coronary Intervention
Cluster of Biomarkers Identifies High-Risk Subgroup
By Bill Malone
Although morbidity and mortality in patients undergoing percutaneous coronary intervention (PCI) for ST-segment elevation myocardial infarction have improved, clinicians have been determined to reduce risk even further for this common procedure. Now, for the first time, a study reported success using a multimarker approach for predicting death in patients undergoing PCI. This issue of Strategies explores its findings.
Early primary percutaneous coronary intervention (PCI), which encompasses balloon angioplasty, stent placement, and other procedures that treat narrowed coronary arteries, is the standard treatment for ST-segment elevated myocardial infarction (STEMI). STEMI indicates that the blood supply to a significant area of the heart has been obstructed for a prolonged period, causing changes in an electrocardiogram, as well as blood levels of cardiac biomarkers. Over time, technical advances have reduced serious complications during PCI. However, several factors can increase a patient’s risk, including but not limited to older age, kidney disease, and diabetes. Some patients also experience an allergic reaction to the dye given during angiography.
Seeking to improve upon the individual predictive value of discrete biomarkers, researchers from the Academic Medical Center University of Amsterdam in the Netherlands investigated whether combined biomarkers could add prognostic value for STEMI patients undergoing PCI (J Am Coll Cardiol 2011; 57: 29-36). The biomarkers included N-terminal pro-brain natriuretic peptide (NT-proBNP), glucose, C-reactive protein (CRP), estimated glomerular filtration rate (eGFR), and cardiac troponin T (cTnT). These markers relate to left ventricular dysfunction, glucose metabolism, inflammation, renal function, and myocardial cell damage, respectively.
The retrospective, single-center study included 1,034 STEMI patients undergoing primary PCI between January 2005 and January 2007. Most of the patients (73%) were male. Patients had blood drawn routinely before primary PCI. The researchers looked at whether combining NT-proBNP, CRP, glucose, cTnT, and eGFR improved mortality prediction. During a mean follow-up of 2 ½ years, 120 patients died. In a multivariate analysis, three of the markers proved to be statistically significant in predicting mortality: NT-proBNP (≥150 ng/L), glucose (≥8 mmol/L), and eGFR (<90 mL/min.). After adjustment for conventional risk factors, including body mass index, age, history of diabetes or hypertension, blood pressure, heart rate, location of the MI, and time to treatment, these three biomarkers retained their predictive power.
The researchers also created a risk score incorporating NT-proBNP, glucose, and eGFR that identified a high-risk STEMI subgroup with a higher mortality compared to an intermediate- and low-risk subgroup. The mortality rates in the high-, intermediate- and low-risk groups were 42%, 17.4% and 5.8%, respectively.
“We performed this study because a lot of research has focused on combining biomarkers for prognostication in patients presenting with non-ST-elevation acute coronary syndromes, but data has been lacking in patients presenting with STEMI,” said Peter Damman, MD of the department of cardiology at the University of Amsterdam and an author of the study. “We think that this is partly based on the perception that mortality and morbidity is decreasing in these patients. However, as shown by others, high-risk subgroups for mortality remain. Therefore, we focused on the additional prognostic value of combined biomarkers to established risk factors in STEMI.”
Exploring the use of such multimarker risk scores is important because they will likely be a critical tool in the future of medicine, commented Alan Wu, PhD, who co-authored the 2007 National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines on Biomarkers of Acute Coronary Syndrome and Heart Failure. “The authors’ finding that biomarkers predict mortality in STEMI patients is not a new concept. We’ve known that for a long time,” he said. “However, their use of a multivariate analysis is an advancement of the field. I think we’ll be seeing much more of these multimarker risk scores because we may be close to the point where we will not be discovering many more individual markers for cardiac disease, so we’re going to need to combine them somehow.” Wu is chief of clinical chemistry and toxicology at San Francisco General Hospital and professor of laboratory medicine at the University of California, San Francisco.
This risk score could be helpful in determining what kind of before and after care PCI patients receive, the authors noted. “When confirmed by other independent cohorts, our multimarker score may be useful in identifying patients eligible for adjuvant therapies during or after primary PCI,” Damman and his colleagues wrote. “This is particularly important in view of the number of new treatments investigated in STEMI patients, such as ticagrelor and delta-protein kinase C inhibitors, potentially leading to resource-limited treatment options.”
In an accompanying editorial, Luigi Biasucci, MD, and Roberta Della Bona, MD, of Catholic University of the Sacred Heart, in Rome, warned about rushing to conclusions based on the paper’s findings. “The authors’ hypothesis that use of a biomarker score may help to address the best therapies may seem consequential,” they wrote. “However, this may represent a dangerous oversimplification: the step from higher nonspecific risk to more aggressive specific therapy is long and should not be considered until definitive data are provided.”
Damman emphasized that more work remains to be done in order to refine the multimarker risk score, including validation in a separate patient cohort and further research focusing on clinical implications in the intermediate- and high-risk subgroups. “This is the most important step—the risk score only has clinical utility once therapeutic consequences can be coupled to it,” he said. “We also hope that this score can assist in identifying high-risk patients for clinical trials in order to design moderately sized trials while being adequately powered.”
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