Exploring conceptual preprocessing for developing prognostic models: a case study in low back pain patients

Nielsen, Anne Molgaard and Binding, Adrian and Ahlbrandt-Rains, Casey and Boeker, Martin and Feuerriegel, Stefan and Vach, Werner. (2020) Exploring conceptual preprocessing for developing prognostic models: a case study in low back pain patients. JOURNAL OF CLINICAL EPIDEMIOLOGY, 122. pp. 27-34.

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Official URL: https://edoc.unibas.ch/84139/

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Objectives: A conceptually oriented preprocessing of a large number of potential prognostic factors may improve the development of a prognostic model. This study investigated whether various forms of conceptually oriented preprocessing or the preselection of established factors was superior to using all factors as input.Study Design and Setting: We made use of an existing project that developed two conceptually oriented subgroupings of low back pain patients. Based on the prediction of six outcome variables by seven statistical methods, this type of preprocessing was compared with medical experts' preselection of established factors, as well as using all 112 available baseline factors.Results: Subgrouping of patients was associated with low prognostic capacity. Applying a Lasso-based variable selection to all factors or to domain-specific principal component scores performed best. The preselection of established factors showed a good compromise between model complexity and prognostic capacity.Conclusion: The prognostic capacity is hard to improve by means of a conceptually oriented preprocessing when compared to purely statistical approaches. However, a careful selection of already established factors combined in a simple linear model should be considered as an option when constructing a new prognostic rule based on a large number of potential prognostic factors. (C) 2020 The Authors. Published by Elsevier Inc.
Faculties and Departments:05 Faculty of Science > Departement Umweltwissenschaften > Integrative Biologie > Integrative Prähistorische und Naturwissenschaftliche Archäologie (IPNA Schünemann)
UniBasel Contributors:Vach, Werner
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:03 Feb 2022 07:00
Deposited On:03 Feb 2022 07:00

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