Recognition of Diagnostic Gaps for Laboratory Diagnosis of Fungal Diseases: Expert Opinion from the Fungal Diagnostics Laboratories Consortium (FDLC)

Academic Article


  • Fungal infections are a rising threat to our immunocompromised patient population, as well as other nonimmunocompromised patients with various medical conditions. However, little progress has been made in the past decade to improve fungal diagnostics. To jointly address this diagnostic challenge, the Fungal Diagnostics Laboratory Consortium (FDLC) was recently created. The FDLC consists of 26 laboratories from the United States and Canada that routinely provide fungal diagnostic services for patient care. A survey of fungal diagnostic capacity among the 26 members of the FDLC was recently completed, identifying the following diagnostic gaps: lack of molecular detection of mucormycosis; lack of an optimal diagnostic algorithm incorporating fungal biomarkers and molecular tools for early and accurate diagnosis of Pneumocystis pneumonia, aspergillosis, candidemia, and endemic mycoses; lack of a standardized molecular approach to identify fungal pathogens directly in formalin-fixed paraffin-embedded tissues; lack of robust databases to enhance mold identification with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry; suboptimal diagnostic approaches for mold blood cultures, tissue culture processing for Mucorales, and fungal respiratory cultures for cystic fibrosis patients; inadequate capacity for fungal point-of-care testing to detect and identify new, emerging or underrecognized, rare, or uncommon fungal pathogens; and performance of antifungal susceptibility testing. In this commentary, the FDLC delineates the most pressing unmet diagnostic needs and provides expert opinion on how to fulfill them. Most importantly, the FDLC provides a robust laboratory network to tackle these diagnostic gaps and ultimately to improve and enhance the clinical laboratory's capability to rapidly and accurately diagnose fungal infections.
  • Authors

    Published In

    Digital Object Identifier (doi)

    Author List

  • Zhang SX; Babady NE; Hanson KE; Harrington AT; Larkin PMK; Leal SM; Luethy PM; Martin IW; Pancholi P; Procop GW
  • Start Page

  • e0178420
  • Volume

  • 59
  • Issue

  • 7