{"title":"Diagnostic likelihood ratio - the next-generation of diagnostic test accuracy measurement.","authors":"C G B Caraguel, A Colling","doi":"10.20506/rst.40.1.3226","DOIUrl":null,"url":null,"abstract":"<p><p>To select, interpret, and assess the fitness-for-purpose of diagnostic tests, we need to compare the likelihoods of test results being true vs. false across both infected and non-infected individuals. Diagnostic sensitivity (DSe) and specificity (DSp) report the accuracy of classification in infected and non-infected individuals separately and do not compare these likelihoods directly. Positive and negative predictive values combine these likelihoods, but they also heavily depend on the prevalence in the tested populations and, therefore, cannot be generalised. We propose the adoption of the diagnostic likelihood ratio (LR), which balances the likelihoods of true vs. false results and is population independent. As a relative measure, LR ignores the absolute accuracy of tests, and two tests with different accuracy profiles may have the same LR. This can be easily mitigated by using listed complementary measures of accuracy, including DSe and DSp, or ancillary selection criteria. Overall, LR is a more relevant and universal measure of diagnostic test accuracy, which makes it the logical next-generation measure to adopt. We illustrate the applications and benefits of LR using three assays certified by the World Organisation for Animal Health as serological tests for bovine tuberculosis.</p>","PeriodicalId":49596,"journal":{"name":"Revue Scientifique et Technique-Office International Des Epizooties","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revue Scientifique et Technique-Office International Des Epizooties","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.20506/rst.40.1.3226","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"VETERINARY SCIENCES","Score":null,"Total":0}
引用次数: 3
Abstract
To select, interpret, and assess the fitness-for-purpose of diagnostic tests, we need to compare the likelihoods of test results being true vs. false across both infected and non-infected individuals. Diagnostic sensitivity (DSe) and specificity (DSp) report the accuracy of classification in infected and non-infected individuals separately and do not compare these likelihoods directly. Positive and negative predictive values combine these likelihoods, but they also heavily depend on the prevalence in the tested populations and, therefore, cannot be generalised. We propose the adoption of the diagnostic likelihood ratio (LR), which balances the likelihoods of true vs. false results and is population independent. As a relative measure, LR ignores the absolute accuracy of tests, and two tests with different accuracy profiles may have the same LR. This can be easily mitigated by using listed complementary measures of accuracy, including DSe and DSp, or ancillary selection criteria. Overall, LR is a more relevant and universal measure of diagnostic test accuracy, which makes it the logical next-generation measure to adopt. We illustrate the applications and benefits of LR using three assays certified by the World Organisation for Animal Health as serological tests for bovine tuberculosis.
期刊介绍:
The Scientific and Technical Review is a periodical publication containing scientific information that is updated constantly. The Review plays a significant role in fulfilling some of the priority functions of the OIE. This peer-reviewed journal contains in-depth studies devoted to current scientific and technical developments in animal health and veterinary public health worldwide, food safety and animal welfare. The Review benefits from the advice of an Advisory Editorial Board and a Scientific and Technical Committee composed of top scientists from across the globe.