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An algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews
Results of medical tests are the main source to inform clinical decision making. The main information to assess the usefulness of medical tests for correct discrimination of patients are accuracy measures. For the estimation of test accuracy measures, many different study designs can be used. The st...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720081/ https://www.ncbi.nlm.nih.gov/pubmed/31481098 http://dx.doi.org/10.1186/s13643-019-1131-4 |
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author | Mathes, Tim Pieper, Dawid |
author_facet | Mathes, Tim Pieper, Dawid |
author_sort | Mathes, Tim |
collection | PubMed |
description | Results of medical tests are the main source to inform clinical decision making. The main information to assess the usefulness of medical tests for correct discrimination of patients are accuracy measures. For the estimation of test accuracy measures, many different study designs can be used. The study design is related to the clinical question to be answered (diagnosis, prognosis, prediction), determines the accuracy measures that can be calculated and it might have an influence on risk of bias. Therefore, a clear and consistent distinction of the different study designs in systematic reviews on test accuracy studies is very important. In this paper, we propose an algorithm for the classification of study designs of test accuracy, that compare the results of an index test (the test to be evaluated) with the results of a reference test (the test whose results are considered as correct/the gold standard) studies in systematic reviews. |
format | Online Article Text |
id | pubmed-6720081 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-67200812019-09-06 An algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews Mathes, Tim Pieper, Dawid Syst Rev Methodology Results of medical tests are the main source to inform clinical decision making. The main information to assess the usefulness of medical tests for correct discrimination of patients are accuracy measures. For the estimation of test accuracy measures, many different study designs can be used. The study design is related to the clinical question to be answered (diagnosis, prognosis, prediction), determines the accuracy measures that can be calculated and it might have an influence on risk of bias. Therefore, a clear and consistent distinction of the different study designs in systematic reviews on test accuracy studies is very important. In this paper, we propose an algorithm for the classification of study designs of test accuracy, that compare the results of an index test (the test to be evaluated) with the results of a reference test (the test whose results are considered as correct/the gold standard) studies in systematic reviews. BioMed Central 2019-09-03 /pmc/articles/PMC6720081/ /pubmed/31481098 http://dx.doi.org/10.1186/s13643-019-1131-4 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Mathes, Tim Pieper, Dawid An algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews |
title | An algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews |
title_full | An algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews |
title_fullStr | An algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews |
title_full_unstemmed | An algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews |
title_short | An algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews |
title_sort | algorithm for the classification of study designs to assess diagnostic, prognostic and predictive test accuracy in systematic reviews |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720081/ https://www.ncbi.nlm.nih.gov/pubmed/31481098 http://dx.doi.org/10.1186/s13643-019-1131-4 |
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