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Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV

View Article: PubMed Central - PubMed

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.

No MeSH data available.


Flow diagram of logical AND two-tier test methodology for Lyme disease.Abbreviation: ELISA, enzyme-linked immunosorbent assay.
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f1-ijgm-10-113: Flow diagram of logical AND two-tier test methodology for Lyme disease.Abbreviation: ELISA, enzyme-linked immunosorbent assay.

Mentions: A number of tests can be used to detect LD, the most common being the enzyme-linked immunosorbent assay (ELISA) and the electrophoresis-based Western blot (WB) (also known as an immunoblot). Both depend on technologies that detect antibodies generated as a response to infection. Each can be, and is frequently, used independent of the other. However, a methodology using both tests was discussed at the Second National Conference on Serologic Diagnosis of Lyme Disease in 1994 and associated workshops and recommended for disease surveillance by the US Centers for Disease Control and Prevention (CDC), and for clinical diagnosis by a review panel at that time.1 The procedure uses the two tests in a sequential fashion with the ELISA test being the first step (or, less commonly, an immunofluorescence assay). Positive or equivocal samples are then subjected to a confirmatory WB test (Figure 1); this can be carried out on the same sample as used for the first step. If the first step is negative, the second step is not carried out. Furthermore, the CDC recommends that one should not jump straight to the second step without carrying out the first step.


Application of Bayesian decision-making to laboratory testing for Lyme disease and comparison with testing for HIV
Flow diagram of logical AND two-tier test methodology for Lyme disease.Abbreviation: ELISA, enzyme-linked immunosorbent assay.
© Copyright Policy
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5391870&req=5

f1-ijgm-10-113: Flow diagram of logical AND two-tier test methodology for Lyme disease.Abbreviation: ELISA, enzyme-linked immunosorbent assay.
Mentions: A number of tests can be used to detect LD, the most common being the enzyme-linked immunosorbent assay (ELISA) and the electrophoresis-based Western blot (WB) (also known as an immunoblot). Both depend on technologies that detect antibodies generated as a response to infection. Each can be, and is frequently, used independent of the other. However, a methodology using both tests was discussed at the Second National Conference on Serologic Diagnosis of Lyme Disease in 1994 and associated workshops and recommended for disease surveillance by the US Centers for Disease Control and Prevention (CDC), and for clinical diagnosis by a review panel at that time.1 The procedure uses the two tests in a sequential fashion with the ELISA test being the first step (or, less commonly, an immunofluorescence assay). Positive or equivocal samples are then subjected to a confirmatory WB test (Figure 1); this can be carried out on the same sample as used for the first step. If the first step is negative, the second step is not carried out. Furthermore, the CDC recommends that one should not jump straight to the second step without carrying out the first step.

View Article: PubMed Central - PubMed

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.

No MeSH data available.