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Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies

BACKGROUND: The diagnostic likelihood ratio (DLR) and its utility are well-known in the field of medical diagnostic testing. However, its use has been limited in the context of an outcome validation study. We considered that wider recognition of the utility of DLR would enhance the practices surroun...

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Autores principales: Ii, Yoichi, Hiro, Shintaro, Nakazuru, Yoshiomi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8783524/
https://www.ncbi.nlm.nih.gov/pubmed/35062929
http://dx.doi.org/10.1186/s12911-022-01757-1
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author Ii, Yoichi
Hiro, Shintaro
Nakazuru, Yoshiomi
author_facet Ii, Yoichi
Hiro, Shintaro
Nakazuru, Yoshiomi
author_sort Ii, Yoichi
collection PubMed
description BACKGROUND: The diagnostic likelihood ratio (DLR) and its utility are well-known in the field of medical diagnostic testing. However, its use has been limited in the context of an outcome validation study. We considered that wider recognition of the utility of DLR would enhance the practices surrounding database studies. This is particularly timely and important since the use of healthcare-related databases for pharmacoepidemiology research has greatly expanded in recent years. In this paper, we aimed to advance the use of DLR, focusing on the planning of a new database study. METHODS: Theoretical frameworks were developed for an outcome validation study and a comparative cohort database study; these two were combined to form the overall relationship. Graphical presentations based on these relationships were used to examine the implications of validation study results on the planning of a database study. Additionally, novel uses of graphical presentations were explored using some examples. RESULTS: Positive DLR was identified as a pivotal parameter that connects the expected positive-predictive value (PPV) with the disease prevalence in the planned database study, where the positive DLR is equal to sensitivity/(1-specificity). Moreover, positive DLR emerged as a pivotal parameter that links the expected risk ratio with the disease risk of the control group in the planned database study. In one example, graphical presentations based on these relationships provided a transparent and informative summary of multiple validation study results. In another example, the potential use of a graphical presentation was demonstrated in selecting a range of positive DLR values that best represented the relevant validation studies. CONCLUSIONS: Inclusion of the DLR in the results section of a validation study would benefit potential users of the study results. Furthermore, investigators planning a database study can utilize the DLR to their benefit. Wider recognition of the full utility of the DLR in the context of a validation study would contribute meaningfully to the promotion of good practice in planning, conducting, analyzing, and interpreting database studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-01757-1.
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spelling pubmed-87835242022-01-24 Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies Ii, Yoichi Hiro, Shintaro Nakazuru, Yoshiomi BMC Med Inform Decis Mak Research BACKGROUND: The diagnostic likelihood ratio (DLR) and its utility are well-known in the field of medical diagnostic testing. However, its use has been limited in the context of an outcome validation study. We considered that wider recognition of the utility of DLR would enhance the practices surrounding database studies. This is particularly timely and important since the use of healthcare-related databases for pharmacoepidemiology research has greatly expanded in recent years. In this paper, we aimed to advance the use of DLR, focusing on the planning of a new database study. METHODS: Theoretical frameworks were developed for an outcome validation study and a comparative cohort database study; these two were combined to form the overall relationship. Graphical presentations based on these relationships were used to examine the implications of validation study results on the planning of a database study. Additionally, novel uses of graphical presentations were explored using some examples. RESULTS: Positive DLR was identified as a pivotal parameter that connects the expected positive-predictive value (PPV) with the disease prevalence in the planned database study, where the positive DLR is equal to sensitivity/(1-specificity). Moreover, positive DLR emerged as a pivotal parameter that links the expected risk ratio with the disease risk of the control group in the planned database study. In one example, graphical presentations based on these relationships provided a transparent and informative summary of multiple validation study results. In another example, the potential use of a graphical presentation was demonstrated in selecting a range of positive DLR values that best represented the relevant validation studies. CONCLUSIONS: Inclusion of the DLR in the results section of a validation study would benefit potential users of the study results. Furthermore, investigators planning a database study can utilize the DLR to their benefit. Wider recognition of the full utility of the DLR in the context of a validation study would contribute meaningfully to the promotion of good practice in planning, conducting, analyzing, and interpreting database studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-01757-1. BioMed Central 2022-01-21 /pmc/articles/PMC8783524/ /pubmed/35062929 http://dx.doi.org/10.1186/s12911-022-01757-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ii, Yoichi
Hiro, Shintaro
Nakazuru, Yoshiomi
Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies
title Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies
title_full Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies
title_fullStr Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies
title_full_unstemmed Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies
title_short Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies
title_sort use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8783524/
https://www.ncbi.nlm.nih.gov/pubmed/35062929
http://dx.doi.org/10.1186/s12911-022-01757-1
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