Evaluating the Performance of Two Serologic Tests for Detection of Onchocerciasis in Two Hyperendemic Regions Open Access
Walsh, Victoria Lee (2016)
Abstract
Background: Onchocerciasis is a leading cause of blindness globally, with over 37 million individuals currently infected, and has been targeted for elimination.
Methods: A secondary analysis was performed on data from Ethiopia and Uganda to increase understanding of the diagnostic accuracy of Ov16 IgG4 enzyme-linked immunosorbent assay (ELISA) and Ov33 IgG4 multiplex bead assay (MBA) in a hyper-endemic setting. A standardized questionnaire was used to collect demographic data, a physical exam was performed to assess onchocerciasis-related eye and skin disease and other filarial infections, and skin biopsies and blood samples were collected for laboratory diagnostics. Chi-square and median tests were performed to assess for differences in covariates across country of origin. Logistic regression was performed to identify covariates significantly associated with a positive Ov16 IgG4 ELISA, controlling for country. Stepwise multivariable model selection identified covariates to include in latent class analysis (LCA). The latent class model included a priori and significant covariates, and the following diagnostic tests: skin snip microscopy, real-time polymerase chain reaction (qPCR), Ov16 IgG4 ELISA, Ov33 MBA, and Ov17 MBA to inform latent class assignment.
Results: There were 1,000 enrollees--nine were excluded for incomplete diagnostic data (N=991). The median age was 39.5 years old, and 47.3% of participants (n=469) were male. There were 774 (78.1%) Ov16 IgG4 ELISA positive individuals, 800 (80.7%) Ov16 MBA positive, 819 (82.6%) Ov33 MBA positive, and 634 (64%) Ov17 MBA positive. There were 147 (14.8%) skin snip microscopy positive individuals, 209 (21.1%) PCR positive, and 225 (22.7%) qPCR positive. Using skin snip microscopy and qPCR as the referent group, estimated sensitivities were 92.7% and 94.0%, and specificities were 26.3% and 20.9% for Ov16 IgG4 ELISA and Ov33 MBA respectively. The following covariates were included in the final model: participant's age, sex, occupation as a farmer, and presence of skin nodules. LCA estimates of specificity were 79.4% and 70.4% for Ov16 IgG4 ELISA and Ov33 MBA respectively.
Conclusions: Serologic tests are better at identifying patent infections than parasitologic methods would suggest given that estimated specificities for Ov16 IgG4 ELISA and Ov33 MBA were three-fold higher using LCA compared with skin snip results.
Table of Contents
Chapter I. Literature Review
Chapter II. Manuscript
Abstract
Background & Introduction
Methods
Data Analysis
Results
Discussion
References
Tables
Chapter III. Public Health Implications
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