The Risk GP Model: The standard model of prediction in medicine
| Autor: | Jonathan Fuller, Luis J. Flores |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Risk
History medicine.medical_specialty 030503 health policy & services Risk measure Probabilistic logic General Medicine Commit Target population Evidence-based medicine Models Theoretical 3. Good health 03 medical and health sciences 0302 clinical medicine History and Philosophy of Science Philosophy of medicine Epidemiology Econometrics medicine Humans Population study Public Health 030212 general & internal medicine Epidemiologic Methods 0305 other medical science |
| Zdroj: | Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 54:49-61 |
| ISSN: | 1369-8486 |
| DOI: | 10.1016/j.shpsc.2015.06.006 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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