Area under the curve-derived measures characterizing longitudinal patient responses for given thresholds
Background: Calculation of the area under the curve (AUC) is a widely used practice in longitudinal study settings. The AUC values should reflect study participants’ particular trajectories by means of a continuous measure which can be further analysed with ordinary statistical methods. However, its...
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| Format: | Article |
| Language: | English |
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Milano University Press
2018-12-01
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| Series: | Epidemiology, Biostatistics and Public Health |
| Online Access: | https://ebph.it/article/view/12948 |
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| _version_ | 1849704590979629056 |
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| author | Andreas Allgoewer Manuel Schmid Peter Radermacher Pierre Asfar Benjamin Mayer |
| author_facet | Andreas Allgoewer Manuel Schmid Peter Radermacher Pierre Asfar Benjamin Mayer |
| author_sort | Andreas Allgoewer |
| collection | DOAJ |
| description | Background: Calculation of the area under the curve (AUC) is a widely used practice in longitudinal study settings. The AUC values should reflect study participants’ particular trajectories by means of a continuous measure which can be further analysed with ordinary statistical methods. However, its sheer calculation does not necessarily mirror exactly the piece of information one is seeking for.
Methods: Available formulas for the calculation of the AUC as well as their specific advantages and limitations are presented. Furthermore, some approaches are discussed to develop AUC-derived measures for the application in particular analysis situations, especially capturing the extent of undercutting or exceeding a given threshold.
Results: The presented formulas provide an extension of the well-established AUC formulas for respective situations where threshold-dependent subareas of the entire AUC are of interest. To our knowledge, the proposed formulas have been introduced for the first time. Their application to real-world data sets demonstrated the ability to flexibly calculate AUCs of specific interest.
Conclusions: The extended AUC formulas presented in this paper may help to answer research questions more properly in situations where particular thresholds have to be considered in the course of the analysis. Future developments may address the problem of missing values as well as the current limitation of a fixed threshold. |
| format | Article |
| id | doaj-art-e3169f8d6beb4cf0a935c46ee2762b8e |
| institution | DOAJ |
| issn | 2282-0930 |
| language | English |
| publishDate | 2018-12-01 |
| publisher | Milano University Press |
| record_format | Article |
| series | Epidemiology, Biostatistics and Public Health |
| spelling | doaj-art-e3169f8d6beb4cf0a935c46ee2762b8e2025-08-20T03:16:42ZengMilano University PressEpidemiology, Biostatistics and Public Health2282-09302018-12-0115410.2427/1294811181Area under the curve-derived measures characterizing longitudinal patient responses for given thresholdsAndreas Allgoewer0Manuel Schmid1Peter Radermacher2Pierre Asfar3Benjamin Mayer4Institute of Epidemiology and Medical Biometry, Ulm University, GermanyDepartment for Neonatology, University Hospital Zurich, SwitzerlandInstitute for Anaesthesiological Pathophysiology and Process Development, University Hospital Ulm, GermanyDepartment of Medical Intensive Care, University Hospital of Angers, FranceInstitute of Epidemiology and Medical Biometry, Ulm University, GermanyBackground: Calculation of the area under the curve (AUC) is a widely used practice in longitudinal study settings. The AUC values should reflect study participants’ particular trajectories by means of a continuous measure which can be further analysed with ordinary statistical methods. However, its sheer calculation does not necessarily mirror exactly the piece of information one is seeking for. Methods: Available formulas for the calculation of the AUC as well as their specific advantages and limitations are presented. Furthermore, some approaches are discussed to develop AUC-derived measures for the application in particular analysis situations, especially capturing the extent of undercutting or exceeding a given threshold. Results: The presented formulas provide an extension of the well-established AUC formulas for respective situations where threshold-dependent subareas of the entire AUC are of interest. To our knowledge, the proposed formulas have been introduced for the first time. Their application to real-world data sets demonstrated the ability to flexibly calculate AUCs of specific interest. Conclusions: The extended AUC formulas presented in this paper may help to answer research questions more properly in situations where particular thresholds have to be considered in the course of the analysis. Future developments may address the problem of missing values as well as the current limitation of a fixed threshold.https://ebph.it/article/view/12948 |
| spellingShingle | Andreas Allgoewer Manuel Schmid Peter Radermacher Pierre Asfar Benjamin Mayer Area under the curve-derived measures characterizing longitudinal patient responses for given thresholds Epidemiology, Biostatistics and Public Health |
| title | Area under the curve-derived measures characterizing longitudinal patient responses for given thresholds |
| title_full | Area under the curve-derived measures characterizing longitudinal patient responses for given thresholds |
| title_fullStr | Area under the curve-derived measures characterizing longitudinal patient responses for given thresholds |
| title_full_unstemmed | Area under the curve-derived measures characterizing longitudinal patient responses for given thresholds |
| title_short | Area under the curve-derived measures characterizing longitudinal patient responses for given thresholds |
| title_sort | area under the curve derived measures characterizing longitudinal patient responses for given thresholds |
| url | https://ebph.it/article/view/12948 |
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