Model helps docs choose between clopidogrel and prasugrel

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 - Doctors Reviewing Data

Researchers have designed a tool to help physicians identify acute coronary syndrome (ACS) patients undergoing PCI who are likely to benefit from prasugrel therapy. They found that the benefits and risks of antiplatelet therapy can vary greatly, depending on individual patient characteristics.

The results were published online Dec. 4 in Circulation: Cardiovascular Quality and Outcomes.

TRITON-TIMI 38 (Trial to Assess Improvement in Therapeutic Outcomes by Optimizing Platelet Inhibition With Prasugrel–Thrombolysis in MI 38) demonstrated that prasugrel (Effient, Eli Lilly/Daiichi Sankyo) compared with clopidogrel (Plavix, Bristol Myers Squibb/Sanofi Aventis) reduced ischemic events in ACS patients undergoing PCI, but it also increased serious bleeding. Although clopidogrel is less potent than prasugrel, it also is less expensive after the FDA approved generic versions of drug in May.

Using data from TRITON-TIMI 38, Adam C. Salisbury, MD, MSc, of Saint Luke’s Mid America Heart Institute in Kansas City, Mo., and colleagues designed models to predict on an individual patient level the benefits and risks of ischemic events and serious bleeding with clopidogrel or prasugrel. The goal was to develop a tool that physicians could use to provide personalized care to ACS patients undergoing PCI.

For their analysis, they identified 12,579 patients in TRITON-TIMI 38 who met the risk model’s inclusion criteria for a 14.8-month follow-up. They defined major ischemia as the composite of cardiovascular death, spontaneous acute MI and stroke. Bleeding was defined as major and minor TIMI bleeding. They calculated each individual patient’s predicted risk for major ischemia and bleeding with both clopidogrel and prasugrel.

Salisbury and colleagues discovered that there was a great deal of variability in predicted risks. The risk of major ischemia across the population ranged from 1.2 to 78.3 percent with clopidogrel treatment and from 0.5 to 61 percent with prasugrel treatment. The predicted risk of bleeding ranged from 0.3 to 28.5 percent with clopidogrel and 0.4 to 26.4 percent with prasugrel.

The mean absolute reduction in the ischemia risk with prasugrel ranged from an 8.4 percent increase in risk to a 31.2 percent reduction in risk compared with clopidogrel, while the mean absolute increase in the bleeding risk with prasugrel ranged from a 7.9 percent lower risk to an 11.2 percent higher risk compared with clopidogrel.  

They calculated that based on model predictions, 42 percent of the TRITON-TIMI 38 population would benefit from prasugrel treatment if ischemia and bleeding prevention were favored equally.

“Meeting the goals of safer, more evidence-based, patient-centered healthcare, as advocated by the Institute of Medicine, requires that accurate estimations of patients’ potential outcomes, as a function of their individual risk profiles, be understood at the time of medical decision mak­ing,” they wrote. Their predic­tion models could be used at the time of PCI to estimate an individual patient’s risk with either prasugrel or clopido­grel. “Because web-based solutions can now be leveraged to deploy prediction models at the point of care, it is pos­sible to explicitly estimate the tradeoff between benefit and risk with competing treatments for any individual at the time of clinical decision making to personalize care, to optimize outcomes and to lower costs.”

The variability based on individual patient characteristics highlighted the need for a personalized approach, they added, and the models could be adjusted to account for personal preference. This might foster more dialog about benefits and risks between a physician and his or her patient, they suggested. The models also might be adapted to other scenarios where physicians must weigh alternative therapies.

They noted that their findings have not been validated in an independent sample, and the results applied only to patients similar to those enrolled in TRITON-TIMI 38. They recommended that individualized risk prediction be further studied to evaluate its impact on clinical decision making and outcomes.