Clinical Performance of the BioPlex 2200 Syphilis Total & RPR Assay at a Tertiary Medical Center with a High Rate of Syphilis

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Abstract

Manual treponemal and nontreponemal serologic testing has historically been used for the diagnosis of syphilis. This approach is simple and reproducible but labor intensive. Recently, the FDA cleared the fully automated BioPlex 2200 Syphilis Total & RPR assay for the detection of treponemal and nontreponemal antibodies. We evaluated the clinical performance of this assay at a tertiary medical center with a high syphilis prevalence. Prospective consecutively collected (n = 400) and known RPR-positive (n = 100) specimens were compared using predicate manual rapid plasma reagin (RPR) and fluorescent treponemal antibody absorption (FTA) methods and the BioPlex 2200 Syphilis Total & RPR assay. Positive and negative percent agreements (PPA and NPA, respectively) between the assays were calculated. The PPA and NPA between the manual and BioPlex 2200 RPR results for the prospective population were 85% (17/20; 95% confidence interval [CI], 69% to 100%) and 98% (373/380; 95% CI, 97% to 99%), respectively. The PPA for the manual RPRpositive population was 88% (88/100; 95% CI, 82% to 94%). Overall, the manual and BioPlex 2200 RPR titers demonstrated 78% (99/127) concordance within ±1 dilution and 94% (120/127) within ±2 dilutions. An interpretation of the syphilis serologic profile using the traditional algorithm showed a concordance of 99.5% in the prospective population and 85% in the manual RPR-positive cohort. The performance of the BioPlex 2200 Syphilis Total & RPR assay is comparable to those of manual methods. The high NPA of this assay combined with the ability to automate a historically labor-intensive assay is an appealing attribute for syphilis screening in a high-volume laboratory.

Original languageEnglish
Article numbere01487
JournalJournal of clinical microbiology
Volume57
Issue number1
DOIs
StatePublished - Jan 2019

Keywords

  • BioPlex
  • FTA
  • RPR
  • Syphilis
  • Traditional algorithm

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