info:eu-repo/semantics/article
Diagnostic Accuracy of Five Serologic Tests for Strongyloides stercoralis Infection
Fecha
2014-01Registro en:
Bisoffi, Zeno; Buonfrate, Dora; Sequi, Marco; Mejia, Rojelio; Cimino, Rubén Oscar; et al.; Diagnostic Accuracy of Five Serologic Tests for Strongyloides stercoralis Infection; Public Library of Science; Neglected Tropical Diseases; 8; 1; 1-2014; 1-8; e2640
1935-2735
CONICET Digital
CONICET
Autor
Bisoffi, Zeno
Buonfrate, Dora
Sequi, Marco
Mejia, Rojelio
Cimino, Rubén Oscar
Krolewiecki, Alejandro Javier
Albonico, Marco
Gobbo, Maria
Bonafini, Stefania
Angheben, Andrea
Requena-Mendez, Ana
Muñoz, José
Nutman, Thomas B.
Resumen
Background:The diagnosis of Strongyloides stercoralis (S. stercoralis) infection is hampered by the suboptimal sensitivity of fecal-based tests. Serological methods are believed to be more sensitive, although assessing their accuracy is difficult because of the lack of sensitivity of a fecal-based reference ("gold") standard.Methods:The sensitivity and specificity of 5 serologic tests for S. stercoralis (in-house IFAT, NIE-ELISA and NIE-LIPS and the commercially available Bordier-ELISA and IVD-ELISA) were assessed on 399 cryopreserved serum samples. Accuracy was measured using fecal results as the primary reference standard, but also using a composite reference standard (based on a combination of tests).Results:According to the latter standard, the most sensitive test was IFAT, with 94.6% sensitivity (91.2-96.9), followed by IVD-ELISA (92.3%, 87.7-96.9). The most specific test was NIE-LIPS, with specificity 99.6% (98.9-100), followed by IVD-ELISA (97.4%, 95.5-99.3). NIE-LIPS did not cross-react with any of the specimens from subjects with other parasitic infections. NIE-LIPS and the two commercial ELISAs approach 100% specificity at a cut off level that maintains ≥70% sensitivity.Conclusions:NIE-LIPS is the most accurate serologic test for the diagnosis of S. stercoralis infection. IFAT and each of the ELISA tests are sufficiently accurate, above a given cut off, for diagnosis, prevalence studies and inclusion in clinical trials.