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Risk Prediction Using Individualized Risk Factors
Study Questions:
What is the accuracy of the LIFE-CVD (LIFEtime-perspective CardioVascular Disease) model for the estimation of individual-level 10 years and lifetime treatment-effects of cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people?
Methods:
Data from the the MESA (Multi-Ethnic Study of Atherosclerosis) study with 6,715 particiants were used for model development. Predictions for hard cardiovascular disease (CVD) events and for non-CVD mortality were included in model development. Therapy effects were estimated by combining the functions with hazard ratios from preventive therapy trials. The LIFE-CVD model was then validated in several large prospective studies including ARIC (Atherosclerosis Risk in Communities) (n = 9,250), Heinz Nixdorf Recall (n = 4,177), EPIC-NN (European Prospective Investigation into Cancer and Nutrition-Netherlands) (n = 25,833), and EPIC-Norfolk (n = 23,548). Individualized effects of cholesterol lowering, blood pressure lowering, aspirin-equivalent antithrombotic therapy, and smoking cessation can be estimated in terms of 10-year absolute risk reduction (ARR), lifetime ARR, and gain in CVD-free life-years using the LIFE-CVD model.
Results:
Studies, which included a total of 69,523 individuals, were used to develop and validate the LIFE-CVD model for apparently healthy people without CVD between 45 and 80 years of age. Calibration of the LIFE-CVD model was good and c-statistics were 0.67–0.76. The output enables the comparison of short- versus long-term therapy-benefit. In two people aged 45 and 70 years with otherwise identical risk factors, the older patient has a greater 10-year ARR (11.3% vs. 1.0%), but a smaller gain in life-years free of CVD (3.4 vs. 4.5 years) from the same therapy. The model was developed into an interactive online calculator available via www.U-Prevent.com.
Conclusions:
The investigators concluded that the model can accurately estimate individual-level prognosis and treatment effects in terms of improved 10-year risk, lifetime risk, and life-expectancy free of CVD. The model is easily accessible and can be used to facilitate personalized medicine and doctor–patient communication.
Perspective:
Using several large cohorts, the authors developed a model that allows clinicians to discuss the impact of risk factor modification for various risk factors for individual patients. The impact on changes in behaviors and/or pharmacologic management of risk factors when this tool is used in the outpatient setting will be important to assess.
Clinical Topics: Cardiovascular Care Team, Dyslipidemia, Prevention, Lipid Metabolism, Nonstatins
Keywords: Aspirin, Atherosclerosis, Blood Pressure, Calibration, Cholesterol, Fibrinolytic Agents, Life Expectancy, Neoplasms, Physician-Patient Relations, Primary Prevention, Risk Factors, Smoking Cessation
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