Usefulness of the Captia Syphilis IgG EIA test method and reverse algorithm for detection of syphilis infection in a public health setting
Doctor of Philosophy
Health Related Sciences
Teresa Nadder, PhD
William Korzun, PhD
Jenica Harrison, PhD
Diane Dodd-McCue, DBA
Syphilis, a systemic sexually transmitted disease, is on the rise in the US, with infection rates the highest recorded since 1994 according to the CDC. Useful laboratory testing is an important diagnostic tool for determining individual syphilis infection and preventing community-wide disease spread.
The purpose of this study was to determine the usefulness of a specific automated treponemal test method, the CaptiaTM Syphilis IgG EIA, and the syphilis reverse algorithm interpretation for detecting syphilis infection among patients seeking care in a public health clinic. The study employed a retrospective, nonexperimental descriptive correlational design with data collected between 2012-2013 from 4,077 public health clinic patients with 21% of the patients diagnosed with syphilis infection.
There was a statistically significant difference between the CaptiaTM Syphilis IgG and the Fujirebio Serodia TP-PA test results; between the CaptiaTM Syphilis IgG Signal to Cutoff (S/CO) and the MacroVue RPR titer continuous variables; and between the reverse and traditional syphilis interpretation algorithms. The reverse algorithm using the CaptiaTM Syphilis IgG test method provided more useful performance measures with a sensitivity of 82%; specificity of 99%; accuracy of 95%; positive likelihood ratio of 63.06 and negative likelihood of 0.18 than the traditional algorithm using the MacroVue RPR test method. Statistical comparison of the area under the curve (AUC) for the continuous variables, CaptiaTM Syphilis IgG S/CO and RPR titer, concluded that the Syphilis IgG AUC (0.9500) was higher than the RPR titer (0.8155) indicating greater accuracy for detecting syphilis infection.
This was the first study to determine that the CaptiaTM Syphilis IgG, the S/CO value, and reverse algorithm are useful diagnostic predictors of syphilis infection among public health clinic patients. The data from this study can be utilized by future researchers and scientists who are developing or improving syphilis detection methods.
© Patricia A. Armour
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