Abstract
Chronic diseases are now the major cause of ill health in both developed and developing countries. Chronic diseases evolve, over decades, from an early reversible phase, to a late stage of irreversible organ damage. Importantly, the trajectory of individual patients with a chronic disease is highly variable. This uncertainty causes substantial stress and difficulty for patients, care providers and health systems. Clinical risk prediction models address this uncertainty by incorporating multiple variables to more precisely estimate the risk of adverse events for an individual patient. In the current chapter, we describe the general approach to developing a risk prediction model. We then illustrate how these methods were applied in the development and validation of the Kidney Failure Risk Equation (KFRE), which accurately predicts the risk of kidney failure in patients with Chronic Kidney Disease Stages 3–5.
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Tangri, N., Rigatto, C. (2015). Longitudinal Studies 5: Development of Risk Prediction Models for Patients with Chronic Disease. In: Parfrey, P., Barrett, B. (eds) Clinical Epidemiology. Methods in Molecular Biology, vol 1281. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2428-8_8
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DOI: https://doi.org/10.1007/978-1-4939-2428-8_8
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