The Risk GP Model: The standard model of prediction in medicine

Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:49-61 (2015)
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Abstract

With the ascent of modern epidemiology in the Twentieth Century came a new standard model of prediction in public health and clinical medicine. In this article, we describe the structure of the model. The standard model uses epidemiological measures-most commonly, risk measures-to predict outcomes (prognosis) and effect sizes (treatment) in a patient population that can then be transformed into probabilities for individual patients. In the first step, a risk measure in a study population is generalized or extrapolated to a target population. In the second step, the risk measure is particularized or transformed to yield probabilistic information relevant to a patient from the target population. Hence, we call the approach the Risk Generalization-Particularization (Risk GP) Model. There are serious problems at both stages, especially with the extent to which the required assumptions will hold and the extent to which we have evidence for the assumptions. Given that there are other models of prediction that use different assumptions, we should not inflexibly commit ourselves to one standard model. Instead, model pluralism should be standard in medical prediction.

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The Confounding Question of Confounding Causes in Randomized Trials.Jonathan Fuller - 2019 - British Journal for the Philosophy of Science 70 (3):901-926.
Evidence based or person centered? An ontological debate.Rani Lill Anjum - 2016 - European Journal for Person Centered Healthcare 4 (2):421-429.
Epidemiological Evidence: Use at Your ‘Own Risk’?Jonathan Fuller - 2020 - Philosophy of Science 87 (5):1119-1129.
The new medical model: a renewed challenge for biomedicine.Jonathan Fuller - 2017 - Canadian Medical Association Journal 189:E640-1.

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