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External Validation of a Multivariable Diagnostic Prediction Model for Acute Invasive Fungal Rhinosinusitis in

Aviv Spillinger1, Johanna Ellefson1, Qiuyu Yang2

  • 1Department of Otolaryngology-Head & Neck Surgery, University of Wisconsin School of Medicine & Public Health, Madison, Wisconsin, USA.

International Forum of Allergy & Rhinology
|August 23, 2025
PubMed
Abstract

Insights

This study validates a diagnostic model for acute invasive fungal rhinosinusitis (AIFS), showing it performs well in identifying patients with different risk factors. The model is generalizable and aids in timely AIFS detection.

Area of Science:

  • Otolaryngology
  • Infectious Diseases
  • Medical Diagnostics

Background:

  • Prompt detection and intervention are critical for improving outcomes in acute invasive fungal rhinosinusitis (AIFS).
  • Diagnostic prediction models aid in risk-stratification but require external validation to confirm accuracy.
  • This study validates a previously developed AIFS diagnostic model in an independent patient cohort.

Purpose of the Study:

  • To externally validate a published diagnostic prediction model for acute invasive fungal rhinosinusitis (AIFS).
  • To assess the model's performance in an independent cohort with potentially different comorbidities.

Main Methods:

  • A retrospective chart review identified patients with suspected AIFS from 2008-2023.
  • The Yin et al. predictive model was applied to calculate risk in 65 patients (11 diagnosed with AIFS).
  • Model performance was evaluated using calibration and discrimination metrics.

Main Results:

  • The validation cohort had higher rates of diabetes, steroid use, and organ transplantation, but lower rates of hematologic malignancy and neutropenia compared to the development cohort.
  • Both three-variable (C-index: 0.844) and four-variable (C-index: 0.963) models demonstrated adequate discrimination.
  • Models showed slight overprediction, with calibration-in-the-large risks of 24.1% and 24.2% respectively.

Conclusions:

  • The AIFS diagnostic model shows acceptable discrimination and calibration upon external validation.
  • The model is generalizable to patients with varying comorbidities.
  • Larger studies are recommended to further confirm predictive performance and clinical utility.
Keywords:
clinical decision rulesinvasive fungal infectionssinusitisvalidation study

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