# Advancing the Identification of Risk Factors for Invasive Fungal Disease in Children with Cancer

## TL;DR

This study identifies risk factors for invasive fungal disease in children with cancer, aiming to improve early detection and treatment strategies.

## Contribution

The study proposes a novel risk factor-based model for early risk stratification of invasive fungal disease in immunocompromised children.

## Key findings

- Male sex, adolescence, elevated C-reactive protein, and critical care unit transfer are significant risk factors for IFD.
- The predictive model achieved an AUC of 0.84 with high sensitivity and specificity.
- Adolescent males with severe clinical conditions are at highest risk for IFD during high-risk febrile neutropenia.

## Abstract

Invasive fungal disease (IFD) is one of the leading causes of morbidity and mortality in immunocompromised pediatric patients. This is a multicenter prospective cohort study with a nested retrospective analysis aimed at identifying risk factors for IFD in immunocompromised children with cancer and episodes of persistent high-risk febrile neutropenia (HRFN). One hundred and seventy-four episodes of persistent HRFN were analyzed, of which 34 (19.5%) were confirmed as IFD, 52.9% were caused by filamentous fungi, and 47.1% by yeasts. Logistic regression and survival analyses identified the following significant risk factors for IFD: male sex (OR 4.04), adolescence (OR 4.65), C-reactive protein ≥ 90 mg/L at admission (OR 3.13), and transfer to a critical care unit (OR 10.73). The predictive model demonstrated strong discriminatory capacity (AUC 0.84), with 79.4% sensitivity and 82.1% specificity. These findings highlight that adolescents, particularly males with severe clinical conditions and elevated inflammatory markers, are at the highest risk for IFD during episodes of HRFN. The proposed risk factor-based model may support early risk stratification and guide targeted antifungal prophylaxis or therapy, potentially improving outcomes in this population. Validation an external cohort is required to confirm these results and optimize clinical applicability.