Addition of Biomarkers May Fine Tune Risk Stratification in Atrial Fibrillation


A novel risk score that includes several biomarkers significantly outperforms risk assessment for stroke, embolic events, and mortality when compared with traditional clinical risk stratification via the CHA2DS2-VASc score, according to the results from a new analysis of the ENGAGE-AF TIMI-48 clinical trial.

When added to the CHA2DS2-VASc score, the multimarker risk score—which included assessments of cardiac troponin I, NT-proBNP, and D-dimer levels—significantly improved prognostic accuracy, report investigators.

“Risk assessment is important, because you’re making a decision about indefinite anticoagulation,” lead investigator Christian Ruff, MD (Brigham and Women’s Hospital, Boston, MD) told TCTMD. “Obviously, patients with atrial fibrillation are at a high risk for stroke, but even with the novel oral anticoagulants, there can be a risk of serious bleeding. The CHADS2 and CHA2DS2-VASc scores are good risk scores in that they are very easy to use and they are intentionally simple. They take common clinical factors and dichotomize them—yes or no, certain age ranges—but they’re not very good at predicting specific risk.”

The new analysis was published online on October 5, 2016, in JAMA: Cardiology.

Going Up Against Traditional Risk Scores

In patients with atrial fibrillation, the most commonly used and validated risk scores are the CHADS2 and CHA2DS2-VASc scores, both of which are based on clinical variables. The scores were designed to assess the risk of thromboembolism and the corresponding need for oral anticoagulation therapy. As the researchers point out, neither risk score was designed to estimate the risk of mortality.

To TCTMD, Ruff said biomarkers are used routinely in clinical practice for risk stratification as well as for managing treatment strategies in a wide range of conditions. Various studies have suggested that markers of inflammation, coagulation activity, hemodynamic stress, myocardial injury, and renal dysfunction are associated with an increased risk of adverse events in atrial fibrillation, note the investigators.

“What we really wanted to do was, instead of just using a clinical risk score, look at how well a biomarker risk score performed,” said Ruff. “Biomarkers really capture the disease pathobiology the clinical risk scores are trying to identify. Take heart failure, for example, what exactly does a ‘history of heart failure’ mean? Is it clinical heart failure? Is it diastolic? Systolic? Is it acute heart failure? Chronic? It’s very vague, but NT-proBNP really captures the risk in that it’s a patient with varying degrees of heart failure—it’s not a yes or no answer.”

In ENGAGE-AF, 21,105 patients with documented atrial fibrillation and a CHADS2 score of 2 or higher were randomized to warfarin or edoxaban (Savaysa, Daiichi Sankyo), one of the new factor Xa inhibitors approved by the US Food and Drug Administration in 2015. Blood samples of cardiac troponin I, NT-proBNP, and D-dimer levels were collected at randomization. For the multimarker risk score, the researchers assigned a “tiered integer value” to each biomarker group, with risk scored from 0 to 11 based on these values.

The risk of stroke, systemic embolism, or death ranged from 1.2% per year among individuals with a biomarker score of 0 to 21.1% for those with a score of 10 or 11. In contrast, when using CHA2DS2-VASc, the risk of stroke, systemic embolism, or death ranged from 2.2% among patients with a CHA2DS2-VASc score of 2 to 9.9% among those with a score of 8 or 9. After adjusting for the CHA2DS2-VASc score, the biomarker risk score identified a more than 15-fold gradient of risk amongst patients in ENGAGE-AF. In addition, each individual biomarker was associated with a range of risk—from 2.8- to 4.2-fold higher—when comparing the lowest concentrations versus the highest concentrations.

The biomarker risk score also outperformed the CHA2DS2-VASc score in terms of prognostic accuracy, with a C statistic of 0.700 (95% CI 0.679-0.720) for the multimarker risk score and 0.586 (95% CI 0.565-0.607) for the CHA2DS2-VASc score. When the biomarker risk score was added to CHA2DS2-VASc, the C statistic increased to 0.708 (95% CI 0.688-0.728).  

“When you just compare the biomarker risk score to the CHA2DS2-VASc—so without any of the clinical risk factors—we found that it significantly outperforms the CHA2DS2-VASc risk score,” said Ruff. “When you add the biomarkers to the CHA2DS2-VASc score—because those scores are easy to calculate—it adds important additional information. We’re much more able to accurately predict risk by incorporating biomarkers.”

To TCTMD, Gregory Lip (University of Birmingham, England), an expert in atrial fibrillation and anticoagulation, praised the study but noted the concept is not entirely new. In fact, in 2006, Lip and others first examined the additive role of plasma von Willebrand factor levels to clinical risk factors in improving risk stratification of patients with atrial fibrillation. In that study, von Willebrand levels refined risk stratification for stroke and vascular events, with the researchers suggesting the measurement could be used to aid treatment decisions.

“As in virtually every scenario, atrial fibrillation or non-atrial fibrillation, biomarkers will always improve on clinical risk factor-based scores,” said Lip. The use of more and more biomarkers, such as a biomarker score, would only be expected to improve risk prediction further, he added.   

What Does This All Mean?

To TCTMD, Ruff cautioned the study is simply the first step, a “proof of principle” that needs to be validated in external datasets. Moreover, the biomarker risk score needs to be prospectively evaluated in A-fib patients not currently taking oral anticoagulation. As to why physicians should care about the biomarker-based risk score, Ruff said it has the potential to change patient care.  

For example, in patients at a relatively low risk for stroke, a CHA2DS2-VASc score of 2, the biomarker score is able to further stratify patients into different risk categories. Within this group of patients (CHA2DS2-VASc score of 2), individuals with a biomarker score of 8-11 have a six-fold higher risk of stroke, embolism, and death when compared with those who have a biomarker score of 0-4, he noted. This allows physicians to identify patients with a low CHA2DS2-VASc score who might actually be at higher risk than previously suspected, he said.

Conversely, “you can imagine you might also identify a patient who you think should be anticoagulated based on their CHA2DS2-VASc score, but they’re actually at much lower risk than you anticipated and might not really benefit from anticoagulation,” said Ruff. In the real world, although atrial fibrillation is common, the assessment of risk is not always obvious, he added. “You really want to be confident where the patient’s risk is high enough to warrant indefinite anticoagulation.”

To TCTMD, Lip isn’t convinced of the value. Half in jest, he said if you measured 10 or 20 different biomarkers, it might be possible to shift the C statistic—the measure of prognostic accuracy—to 0.9. He believes that measuring multiple biomarkers adds too much time and cost for busy physicians assessing the risk of thromboembolic events in patients with atrial fibrillation. Imagine, he said, you see a patient, measure multiple biomarkers, and then bring them back weeks later only to tell them they’re at high risk, with an annual risk of X per year?

“The more practical approach would be to initially identify 'low risk' quickly and simply—for a CHA2DS2-VASc score of 0 in males and 1 in females the risk would be less than 1% per year,” said Lip. “These patients do not need any antithrombotic therapy. Next step is to offer stroke prevention to atrial fibrillation patients with one or more stroke risk factors.”

 


 

 

 

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Sources
  • Ruff CT, Giugliano RP, Braunwald E, et al. Cardiovascular biomarker score and clinical outcomes in patients with atrial fibrillation. JAMA Cardiol. 2016; Epub ahead of print.

Disclosures
  • Ruff reports receiving grant support through his institution from Daiichi Sankyo and has served as a paid consultant and received honoraria from Daiichi Sankyo, Boehringer Ingelheim, Bayer, and Portola. He reports grant support through his institution outside the submitted work from AstraZeneca, Eisai, Intarcia, and GlaxoSmithKline.
  • Lip has served as a consultant for Bayer/Janssen, Astellas, Merck, Sanofi, BMS/Pfizer, Biotronik, Medtronic, Portola, Boehringer Ingelheim, Microlife and Daiichi-Sankyo; and speaker for Bayer, BMS/Pfizer, Medtronic, Boehringer Ingelheim, Microlife, Roche and Daiichi-Sankyo.

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