Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV
Michael J Cook,1 Basant K Puri2 1Independent Researcher, Highcliffe, 2Department of Medicine, Hammersmith Hospital, Imperial College London, London, UK Abstract: In this study, Bayes’ theorem was used to determine the probability of a patient having Lyme disease (LD), given a positive tes...
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doaj-a44a216956634c939cb56239af7abced2020-11-24T22:34:21ZengDove Medical PressInternational Journal of General Medicine1178-70742017-04-01Volume 1011312332303Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIVCook MJPuri BKMichael J Cook,1 Basant K Puri2 1Independent Researcher, Highcliffe, 2Department of Medicine, Hammersmith Hospital, Imperial College London, London, UK Abstract: In this study, Bayes’ theorem was used to determine the probability of a patient having Lyme disease (LD), given a positive test result obtained using commercial test kits in clinically diagnosed patients. In addition, an algorithm was developed to extend the theorem to the two-tier test methodology. Using a disease prevalence of 5%–75% in samples sent for testing by clinicians, evaluated with a C6 peptide enzyme-linked immunosorbent assay (ELISA), the probability of infection given a positive test ranged from 26.4% when the disease was present in 5% of referrals to 95.3% when disease was present in 75%. When applied in the case of a C6 ELISA followed by a Western blot, the algorithm developed for the two-tier test demonstrated an improvement with the probability of disease given a positive test ranging between 67.2% and 96.6%. Using an algorithm to determine false-positive results, the C6 ELISA generated 73.6% false positives with 5% prevalence and 4.7% false positives with 75% prevalence. Corresponding data for a group of test kits used to diagnose HIV generated false-positive rates from 5.4% down to 0.1% indicating that the LD tests produce up to 46 times more false positives. False-negative test results can also influence patient treatment and outcomes. The probability of a false-negative test for LD with a single test for early-stage disease was high at 66.8%, increasing to 74.9% for two-tier testing. With the least sensitive HIV test used in the two-stage test, the false-negative rate was 1.3%, indicating that the LD test generates ~60 times as many false-negative results. For late-stage LD, the two-tier test generated 16.7% false negatives compared with 0.095% false negatives generated by a two-step HIV test, which is over a 170-fold difference. Using clinically representative LD test sensitivities, the two-tier test generated over 500 times more false-negative results than two-stage HIV testing. Keywords: false-positive test, false-negative tests, probability of disease, serology testing methodology, Lyme borreliosis, Bayes’ theorem, two-tier test, test sensitivity, ELISA test, Western blot test, HIV testinghttps://www.dovepress.com/application-of-bayesian-decision-making-to-laboratory-testing-for-lyme-peer-reviewed-article-IJGMLyme diseaseLyme borreliosisBayes Theoremtwo-tier testtwo tier testtest sensitivityELISA testHIV testing |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Cook MJ Puri BK |
spellingShingle |
Cook MJ Puri BK Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV International Journal of General Medicine Lyme disease Lyme borreliosis Bayes Theorem two-tier test two tier test test sensitivity ELISA test HIV testing |
author_facet |
Cook MJ Puri BK |
author_sort |
Cook MJ |
title |
Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV |
title_short |
Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV |
title_full |
Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV |
title_fullStr |
Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV |
title_full_unstemmed |
Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV |
title_sort |
application of bayesian decision-making to laboratory testing for lyme disease and comparison with testing for hiv |
publisher |
Dove Medical Press |
series |
International Journal of General Medicine |
issn |
1178-7074 |
publishDate |
2017-04-01 |
description |
Michael J Cook,1 Basant K Puri2 1Independent Researcher, Highcliffe, 2Department of Medicine, Hammersmith Hospital, Imperial College London, London, UK Abstract: In this study, Bayes’ theorem was used to determine the probability of a patient having Lyme disease (LD), given a positive test result obtained using commercial test kits in clinically diagnosed patients. In addition, an algorithm was developed to extend the theorem to the two-tier test methodology. Using a disease prevalence of 5%–75% in samples sent for testing by clinicians, evaluated with a C6 peptide enzyme-linked immunosorbent assay (ELISA), the probability of infection given a positive test ranged from 26.4% when the disease was present in 5% of referrals to 95.3% when disease was present in 75%. When applied in the case of a C6 ELISA followed by a Western blot, the algorithm developed for the two-tier test demonstrated an improvement with the probability of disease given a positive test ranging between 67.2% and 96.6%. Using an algorithm to determine false-positive results, the C6 ELISA generated 73.6% false positives with 5% prevalence and 4.7% false positives with 75% prevalence. Corresponding data for a group of test kits used to diagnose HIV generated false-positive rates from 5.4% down to 0.1% indicating that the LD tests produce up to 46 times more false positives. False-negative test results can also influence patient treatment and outcomes. The probability of a false-negative test for LD with a single test for early-stage disease was high at 66.8%, increasing to 74.9% for two-tier testing. With the least sensitive HIV test used in the two-stage test, the false-negative rate was 1.3%, indicating that the LD test generates ~60 times as many false-negative results. For late-stage LD, the two-tier test generated 16.7% false negatives compared with 0.095% false negatives generated by a two-step HIV test, which is over a 170-fold difference. Using clinically representative LD test sensitivities, the two-tier test generated over 500 times more false-negative results than two-stage HIV testing. Keywords: false-positive test, false-negative tests, probability of disease, serology testing methodology, Lyme borreliosis, Bayes’ theorem, two-tier test, test sensitivity, ELISA test, Western blot test, HIV testing |
topic |
Lyme disease Lyme borreliosis Bayes Theorem two-tier test two tier test test sensitivity ELISA test HIV testing |
url |
https://www.dovepress.com/application-of-bayesian-decision-making-to-laboratory-testing-for-lyme-peer-reviewed-article-IJGM |
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