@article{fdi:010087738,
  title = {{A} systematic review of peptide-based serological tests for the diagnosis of leishmaniasis},
  author = {{P}agniez, {J}ulie and {P}etitdidier, {E}lodie and {P}arra-{Z}uleta, {O}. and {P}issarra, {J}. and {B}ras {G}oncalves, {R}achel},
  editor = {},
  language = {{ENG}},
  abstract = {{S}erological methods should meet the needs of leishmaniasis diagnosis due to their high sensitivity and specificity, economical and adaptable rapid diagnostic test format, and ease of use. {C}urrently, the performances of serological diagnostic tests, despite improvements with recombinant proteins, vary greatly depending on the clinical form of leishmaniasis and the endemic area. {P}eptide-based serological tests are promising as they could compensate for antigenic variability and improve performance, independently of {L}eishmania species and subspecies circulating in the endemic areas. {T}he objective of this systematic review was to inventory all studies published from 2002 to 2022 that evaluate synthetic peptides for serological diagnosis of human leishmaniases and also to highlight the performance (e.g., sensitivity and specificity) of each peptide reported in these studies. {A}ll clinical forms of leishmaniasis, visceral and tegumentary, and all {L}eishmania species responsible for these diseases were considered. {F}ollowing {PRISMA} statement recommendations, 1,405 studies were identified but only 22 articles met the selection criteria and were included in this systematic review. {T}hese original research articles described 77 different peptides, of which several have promising performance for visceral or tegumentary leishmaniasis diagnosis. {T}his review highlights the importance of and growing interest in synthetic peptides used for serological diagnosis of leishmaniases, and their performances compared to some widely used tests with recombinant proteins.},
  keywords = {},
  booktitle = {},
  journal = {{P}arasite},
  volume = {30},
  numero = {},
  pages = {10 [19 ]},
  ISSN = {1252-607{X}},
  year = {2023},
  DOI = {10.1051/parasite/2023011},
  URL = {https://www.documentation.ird.fr/hor/fdi:010087738},
}