A semiparametric approach for meta‐analysis of diagnostic accuracy studies with multiple cut‐offs
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Le résumé fourni par la source
The accuracy of a diagnostic test is often expressed using a pair of measures: sensitivity (proportion of test positives among all individuals with target condition) and specificity (proportion of test negatives among all individuals without target condition). If the outcome of a diagnostic test is binary, results from different studies can easily be summarized in a meta-analysis. However, if the diagnostic test is based on a discrete or continuous measure (e.g., a biomarker), several cut-offs within one study as well as among different studies are published. Instead of taking all information of the cut-offs into account in the meta-analysis, a single cut-off per study is often selected arbitrarily for the analysis, even though there are statistical methods for the incorporation of several cut-offs. For these methods, distributional assumptions have to be met and/or the models may not converge when specific data structures occur. We propose a semiparametric approach to overcome both problems. Our simulation study shows that the diagnostic accuracy is under-estimated, although this underestimation in sensitivity and specificity is relatively small. The comparative approach of Steinhauser et al. is better in terms of coverage probability, but may lead to convergence problems. In addition to the simulation results, we illustrate the application of the semiparametric approach using a published meta-analysis for a diagnostic test differentiating between bacterial and viral meningitis in children.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- A semiparametric approach for meta‐analysis of diagnostic accuracy studies with multiple cut‐offs
- Date Crossref
- 24/06/2022
- Éditeur
- Wiley
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Research Institute for Philosophy Hannover pays non établi dans la noticeStructure de recherche
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Hannover Re (Germany) pays non établi dans la noticeEntreprise
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Universität Hamburg pays non établi dans la noticeUniversité ou école supérieure
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University Medical Center Hamburg-Eppendorf Department of Medical Biometry and Epidemiology pays non établi dans la noticeÉtablissement de santé
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Faculty for Media Department of Information and Communication pays non établi dans la noticeUniversité ou école supérieure
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Department of Medical Biometry and Epidemiology University Medical Center Hamburg‐Eppendorf Hamburg Germany pays non établi dans la noticeUniversité ou école supérieure
Research Institute for Philosophy Hannover, Hannover Re (Germany) et Universität Hamburg, avec 3 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.