BACKGROUND: Algorithms for the diagnosis of syphilis continue to be a source of great controversy, and numerous test interpretations have perplexed many clinicians. METHODS: We conducted a cross-sectional study of 24 124 subjects to analyze 3 syphilis testing algorithms: traditional algorithm, reverse algorithm, and the European Centre for Disease Prevention and Control (ECDC) algorithm. Every serum sample was simultaneously evaluated using the rapid plasma reagin, Treponema pallidum particle agglutination, and chemiluminescence immunoassay tests. With the results of clinical diagnoses of syphilis as a gold standard, we evaluated the diagnostic accuracy of the 3 syphilis testing algorithms. The κ coefficient was used to compare the concordance between the reverse algorithm and the ECDC algorithm. RESULTS: Overall, 2749 patients in our cohort were diagnosed with syphilis. The traditional algorithm had the highest negative likelihood ratio (0.24), a missed diagnosis rate of 24.2%, and only 75.81% sensitivity. However, both the reverse and ECDC algorithms had higher diagnostic efficacy than the traditional algorithm. Their sensitivity, specificity, and accuracy were 99.38%-99.85%, 99.98%-100.00%, and 99.93%-99.96%, respectively. Moreover, the overall percentage of agreement and κ value between the reverse and the ECDC algorithms were 99.9% and 0.996, respectively. CONCLUSIONS: Our research supported use of the ECDC algorithm, in which syphilis screening begins with a treponemal immunoassay that is followed by a second, different treponemal assay as a confirmatory test in high-prevalence populations. In addition, our results indicated that nontreponemal assay is unnecessary for syphilis diagnosis but can be recommended for determining serological activity and the effect of syphilis treatment.
BACKGROUND: Algorithms for the diagnosis of syphilis continue to be a source of great controversy, and numerous test interpretations have perplexed many clinicians. METHODS: We conducted a cross-sectional study of 24 124 subjects to analyze 3 syphilis testing algorithms: traditional algorithm, reverse algorithm, and the European Centre for Disease Prevention and Control (ECDC) algorithm. Every serum sample was simultaneously evaluated using the rapid plasma reagin, Treponema pallidum particle agglutination, and chemiluminescence immunoassay tests. With the results of clinical diagnoses of syphilis as a gold standard, we evaluated the diagnostic accuracy of the 3 syphilis testing algorithms. The κ coefficient was used to compare the concordance between the reverse algorithm and the ECDC algorithm. RESULTS: Overall, 2749 patients in our cohort were diagnosed with syphilis. The traditional algorithm had the highest negative likelihood ratio (0.24), a missed diagnosis rate of 24.2%, and only 75.81% sensitivity. However, both the reverse and ECDC algorithms had higher diagnostic efficacy than the traditional algorithm. Their sensitivity, specificity, and accuracy were 99.38%-99.85%, 99.98%-100.00%, and 99.93%-99.96%, respectively. Moreover, the overall percentage of agreement and κ value between the reverse and the ECDC algorithms were 99.9% and 0.996, respectively. CONCLUSIONS: Our research supported use of the ECDC algorithm, in which syphilis screening begins with a treponemal immunoassay that is followed by a second, different treponemal assay as a confirmatory test in high-prevalence populations. In addition, our results indicated that nontreponemal assay is unnecessary for syphilis diagnosis but can be recommended for determining serological activity and the effect of syphilis treatment.
Entities:
Keywords:
nontreponemal antibody test; serodiagnosis; syphilis; treponemal antibody test
Authors: Rosanna W Peeling; David Mabey; Mary L Kamb; Xiang-Sheng Chen; Justin D Radolf; Adele S Benzaken Journal: Nat Rev Dis Primers Date: 2017-10-12 Impact factor: 52.329
Authors: Paul N Levett; Kevin Fonseca; Raymond Sw Tsang; Kamran Kadkhoda; Bouchra Serhir; Sandra M Radons; Muhammad Morshed Journal: Can J Infect Dis Med Microbiol Date: 2015 Jan-Feb Impact factor: 2.471