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Identification and validation of diagnostic cutoffs of the ELISpot assay for the diagnosis of invasive aspergillosis in high-risk patients

  • F. Bettelli
  • , D. Vallerini
  • , I. Lagreca
  • , P. Barozzi
  • , G. Riva
  • , V. Nasillo
  • , A. Paolini
  • , R. D'Amico
  • , F. Forghieri
  • , M. Morselli
  • , V. Pioli
  • , A. Gilioli
  • , D. Giusti
  • , A. Messerotti
  • , P. Bresciani
  • , A. Cuoghi
  • , E. Colaci
  • , R. Marasca
  • , Livio Pagano
  • , A. Candoni
  • J. Maertens, P. Viale, C. Mussini, R. Manfredini, E. Tagliafico, M. Sarti, T. Trenti, R. Lewis, P. Comoli, A. Eccher, M. Luppi, L. Potenza*
*Corresponding author
  • University of Modena and Reggio Emilia
  • Azienda USL di Modena
  • KU Leuven
  • University of Bologna
  • University of Padua
  • IRCCS Fondazione Policlinico San Matteo - Pavia

Research output: Contribution to journalArticle

Abstract

Objective We investigated the performance of enzyme linked immunospot (ELISpot) assay for the diagnosis of invasive aspergillosis (IA) in high-risk patients with hematologic malignancies. Methods We prospectively enrolled two cohorts of patients undergoing intensive myelosuppressive or immunosuppressive treatments at high risk for IA. ELISpot was performed to detect Aspergillus-specific T cells producing Interleukin-10. Results In the discovery cohort, a derived cut-off of 40 spot forming cells (SFCs)/106 PBMCs has shown to correctly classify IA cases with a sensitivity and specificity of 89.5% and 88.6%, respectively. This cut-off is lowered to 25 SFC when considering the subset of possible IA patients, with sensitivity and specificity of 76% and 93%, respectively. The application of the 40 SFCs cut-off to the validation cohort resulted in a positivity rate of 83.3% in proven/probable cases and a negativity rate of 92.5% in possible/non-IA cases. Adopting the 25 SCFs cut-off, the assay resulted positive in 83.3% of proven/probable cases while it resulted negative in 66.7% of possible/non-IA cases. Conclusions ELISpot shows promises in the diagnosis of IA and the possibility to use two distinct cut-offs with similar diagnostic performances according to patients’ different pre-test probability of infection can widen its use in patients at risk.
Original languageEnglish
Pages (from-to)728-736
Number of pages9
JournalPLoS One
Volume19
Issue number7
DOIs
Publication statusPublished - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • General

Keywords

  • Infection

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