EBioMedicine (Dec 2022)

Trypanosome spliced leader RNA for diagnosis of acoziborole treatment outcome in gambiense human African trypanosomiasis: A longitudinal follow-up studyResearch in context

  • Ipos Ngay Lukusa,
  • Nick Van Reet,
  • Dieudonné Mumba Ngoyi,
  • Erick Mwamba Miaka,
  • Justin Masumu,
  • Pati Patient Pyana,
  • Wilfried Mutombo,
  • Digas Ngolo,
  • Vincent Kobo,
  • Felix Akwaso,
  • Médard Ilunga,
  • Lewis Kaninda,
  • Sylvain Mutanda,
  • Dieudonné Mpoyi Muamba,
  • Olaf Valverde Mordt,
  • Antoine Tarral,
  • Sandra Rembry,
  • Philippe Büscher,
  • Veerle Lejon

Journal volume & issue
Vol. 86
p. 104376

Abstract

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Summary: Background: Detection of spliced leader (SL)-RNA allows sensitive diagnosis of gambiense human African trypanosomiasis (HAT). We investigated its diagnostic performance for treatment outcome assessment. Methods: Blood and cerebrospinal fluid (CSF) from a consecutive series of 97 HAT patients, originating from the Democratic Republic of the Congo, were prospectively collected before treatment with acoziborole, and during 18 months of longitudinal follow-up after treatment. For treatment outcome assessment, SL-RNA detection was compared with microscopic trypanosome detection and CSF white blood cell count. The trial was registered under NCT03112655 in clinicaltrials.gov. Findings: Before treatment, respectively 94.9% (92/97; CI 88.5–97.8%) and 67.7% (65/96; CI 57.8–76.2%) HAT patients were SL-RNA positive in blood or CSF. During follow-up, one patient relapsed with trypanosomes observed at 18 months, and was SL-RNA positive in blood and CSF at 12 months, and CSF positive at 18 months. Among cured patients, one individual tested SL-RNA positive in blood at month 12 (Specificity 98.9%; 90/91; CI 94.0–99.8%) and 18 (Specificity 98.9%; 88/89; CI 93.9–99.8%). Interpretation: SL-RNA detection for HAT treatment outcome assessment shows ≥98.9% specificity in blood and 100% in CSF, and may detect relapses without lumbar puncture. Funding: The DiTECT-HAT project is part of the EDCTP2 programme, supported by Horizon 2020, the European Union Funding for Research and Innovation (grant number DRIA-2014-306-DiTECT-HAT).

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