One or two serological assay testing strategy for diagnosis of HBV and HCV infection? The use of predictive modelling
| Autor: | Anita Sands, John Parry, Philippa Easterbrook |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Test strategy medicine.medical_specialty HBsAg 030106 microbiology Population Sensitivity and Specificity lcsh:Infectious and parasitic diseases Immunoenzyme Techniques 03 medical and health sciences 0302 clinical medicine Internal medicine Positive predicative value False positive paradox Medicine Humans lcsh:RC109-216 Serologic Tests 030212 general & internal medicine education education.field_of_study Hepatitis B Surface Antigens business.industry Research False Negative Reactions Bayes Theorem Hepatitis B Hepatitis C Antibodies Models Theoretical medicine.disease Hepatitis C Infectious Diseases Immunology Female Reagent Kits Diagnostic business Viral hepatitis |
| Zdroj: | BMC Infectious Diseases BMC Infectious Diseases, Vol 17, Iss S1, Pp 59-70 (2017) |
| ISSN: | 1471-2334 |
| Popis: | Background Initial serological testing for chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infection is conducted using either rapid diagnostic tests (RDT) or laboratory-based enzyme immunoassays (EIA)s for detection of hepatitis B surface antigen (HBsAg) or antibodies to HCV (anti-HCV), typically on serum or plasma specimens and, for certain RDTs, capillary whole blood. WHO recommends the use of standardized testing strategies – defined as a sequence of one or more assays to maximize testing accuracy while simplifying the testing process and ideally minimizing cost. Our objective was to examine the diagnostic outcomes of a one- versus two-assay serological testing strategy. These data were used to inform recommendations in the 2017 WHO Guidelines on hepatitis B and C testing. Methods Few published studies have compared diagnostic outcomes for one-assay versus two-assay serological testing strategies for HBsAg and anti-HCV. Therefore, the principles of Bayesian statistics were used to conduct a modelling exercise to examine the outcomes of a one-assay versus two-assay testing strategy when applied to a hypothetical population of 10,000 individuals. The resulting model examined the diagnostic outcomes (true and false positive diagnoses; true and false negative diagnoses; positive and negative predictive values as a function of prevalence; and total tests required) for both one-assay and two-assay testing strategies. The performance characteristics assumed for assays used within the testing strategies were informed by WHO prequalification assessment findings and systematic reviews for diagnostic accuracy studies. Each of the presumptive testing strategies (one-assay or two-assay) was modelled at varying prevalences of HBsAg (10%, 2% and 0.4%) and of anti-HCV (40%, 10%, 2% and 0.4%), aimed at representing the range of testing populations typically encountered in WHO Member States. When the two-assay testing strategy was considered, the model assumed the independence of the two assays. Results Modeling demonstrated that applying a single assay (HBsAg or anti-HCV), even with high specificity (99%), may result in considerable numbers of false positive diagnoses and low positive predictive values (PPV), particularly in lower prevalence settings. Even at very low prevalences shifting to a two-assay testing strategy would result in a PPV approaching 1.0. When test sensitivity is high (>99%) false negative reactions are rare at all but the highest prevalences; but a two-test strategy might yield more false negative diagnoses. The order in which the tests are used has no impact on the overall accuracy of a two-assay strategy though it may impact the total number of tests needed to complete the diagnostic strategy, incurring added cost and complexity. HBsAg assays may have a low sensitivity ( |
| Databáze: | OpenAIRE |
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