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Comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study
BACKGROUND: Nested case–control studies become increasingly popular as they can be very efficient for quantifying the diagnostic accuracy of costly or invasive tests or (bio)markers. However, they do not allow for direct estimation of the test’s predictive values or post-test probabilities, let alon...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3536560/ https://www.ncbi.nlm.nih.gov/pubmed/23114025 http://dx.doi.org/10.1186/1471-2288-12-166 |
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author | van Zaane, Bas Vergouwe, Yvonne Donders, A Rogier T Moons, Karel GM |
author_facet | van Zaane, Bas Vergouwe, Yvonne Donders, A Rogier T Moons, Karel GM |
author_sort | van Zaane, Bas |
collection | PubMed |
description | BACKGROUND: Nested case–control studies become increasingly popular as they can be very efficient for quantifying the diagnostic accuracy of costly or invasive tests or (bio)markers. However, they do not allow for direct estimation of the test’s predictive values or post-test probabilities, let alone for their confidence intervals (CIs). Correct estimates of the predictive values itself can easily be obtained using a simple correction by the (inverse) sampling fractions of the cases and controls. But using this correction to estimate the corresponding standard error (SE), falsely increases the number of patients that are actually studied, yielding too small CIs. We compared different approaches for estimating the SE and thus CI of predictive values or post-test probabilities of diagnostic test results in a nested case–control study. METHODS: We created datasets based on a large, previously published diagnostic study on 2 different tests (D-dimer test and calf difference test) with a nested case–control design. We compared six different approaches; the approaches were: 1. the standard formula for the SE of a proportion, 2. adaptation of the standard formula with the sampling fraction, 3. A bootstrap procedure, 4. A approach, which uses the sensitivity, the specificity and the prevalence, 5. Weighted logistic regression, and 6. Approach 4 on the log odds scale. The approaches were compared with respect to coverage of the CI and CI-width. RESULTS: The bootstrap procedure (approach 3) showed good coverage and relatively small CI widths. Approaches 4 and 6 showed some undercoverage, particularly for the D-dimer test with frequent positive results (positive results around 70%). Approaches 1, 2 and 5 showed clear overcoverage at low prevalences of 0.05 and 0.1 in the cohorts for all case–control ratios. CONCLUSION: The results from our study suggest that a bootstrap procedure is necessary to assess the confidence interval for the predictive values or post-test probabilities of diagnostic tests results in studies using a nested case–control design. |
format | Online Article Text |
id | pubmed-3536560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35365602013-01-08 Comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study van Zaane, Bas Vergouwe, Yvonne Donders, A Rogier T Moons, Karel GM BMC Med Res Methodol Research Article BACKGROUND: Nested case–control studies become increasingly popular as they can be very efficient for quantifying the diagnostic accuracy of costly or invasive tests or (bio)markers. However, they do not allow for direct estimation of the test’s predictive values or post-test probabilities, let alone for their confidence intervals (CIs). Correct estimates of the predictive values itself can easily be obtained using a simple correction by the (inverse) sampling fractions of the cases and controls. But using this correction to estimate the corresponding standard error (SE), falsely increases the number of patients that are actually studied, yielding too small CIs. We compared different approaches for estimating the SE and thus CI of predictive values or post-test probabilities of diagnostic test results in a nested case–control study. METHODS: We created datasets based on a large, previously published diagnostic study on 2 different tests (D-dimer test and calf difference test) with a nested case–control design. We compared six different approaches; the approaches were: 1. the standard formula for the SE of a proportion, 2. adaptation of the standard formula with the sampling fraction, 3. A bootstrap procedure, 4. A approach, which uses the sensitivity, the specificity and the prevalence, 5. Weighted logistic regression, and 6. Approach 4 on the log odds scale. The approaches were compared with respect to coverage of the CI and CI-width. RESULTS: The bootstrap procedure (approach 3) showed good coverage and relatively small CI widths. Approaches 4 and 6 showed some undercoverage, particularly for the D-dimer test with frequent positive results (positive results around 70%). Approaches 1, 2 and 5 showed clear overcoverage at low prevalences of 0.05 and 0.1 in the cohorts for all case–control ratios. CONCLUSION: The results from our study suggest that a bootstrap procedure is necessary to assess the confidence interval for the predictive values or post-test probabilities of diagnostic tests results in studies using a nested case–control design. BioMed Central 2012-10-31 /pmc/articles/PMC3536560/ /pubmed/23114025 http://dx.doi.org/10.1186/1471-2288-12-166 Text en Copyright ©2012 van Zaane et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article van Zaane, Bas Vergouwe, Yvonne Donders, A Rogier T Moons, Karel GM Comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study |
title | Comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study |
title_full | Comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study |
title_fullStr | Comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study |
title_full_unstemmed | Comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study |
title_short | Comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study |
title_sort | comparison of approaches to estimate confidence intervals of post-test probabilities of diagnostic test results in a nested case-control study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3536560/ https://www.ncbi.nlm.nih.gov/pubmed/23114025 http://dx.doi.org/10.1186/1471-2288-12-166 |
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