Risk Prediction and Risk Classification

Sylvia Wassertheil-Smoller and Jordan Smoller
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Sylvia Wassertheil-Smoller: Albert Einstein College of Medicine, Department of Epidemiology
Jordan Smoller: Massachusetts General Hospital, Department of Psychiatry and Center for Human Genetic Research

Chapter Chapter 9 in Biostatistics and Epidemiology, 2015, pp 205-216 from Springer

Abstract: Abstract We are interested in predicting risk of a disease for an individual because treatment decisions are often based on risk. We will use cardiovascular risk as an example in the following sections since risk prediction is most developed for this disease. Treatment guidelines for high blood pressure or high cholesterol from the American Heart Association differ for people at high risk of cardiovascular disease from those at lower risk. For example, anticoagulant drugs are recommended to people who have atrial fibrillation (a type of heart arrhythmia) if they are at high risk of stroke as determined by their age, whether they have diabetes, a history of stroke, heart failure, and hypertension. Since anticoagulants pose a risk of bleeding, they are not recommended for people who have a low risk of stroke. Prediction of risk is also very useful for public health matters. Knowing what percentage of a population is at high risk can help health planners to mount preventive measures and to plan utilization of resources.

Keywords: Risk Category; Risk Prediction; Risk Prediction Model; Stroke Case; Lower Risk Category (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-1-4939-2134-8_9

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