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Updated: Jun 14, 2025

Histological Quantification to Determine Lung Fungal Burden in Experimental Aspergillosis
Published on: March 9, 2018
Pulmonary Aspergillosis: Epidemiology and unresolved diagnostic challenges - insights from a two-year retrospective
Thi Quynh Pham1, Léa Delorme2, Sébastien Cortaredona3
1Aix Marseille Univ, SSA, RITMES, Marseille, France; IHU-Méditerranée Infection, Marseille, France.
Objective:
Aspergillus spp. are ubiquitous fungi that cause invasive pulmonary aspergillosis (IPA), chronic pulmonary aspergillosis (CPA), allergic bronchopulmonary aspergillosis (ABPA), and some other less common forms depending on the immune status of the host. This study aimed to evaluate the epidemiology and clinical diagnosis of Aspergillus-related diseases at the University Hospital of Marseille (AP-HM).
Methods:
We performed a retrospective cohort study of patients treated at the AP-HM between January 2022 and December 2023. Aspergillus-specific serologic tests (IgG, IgE) and galactomannan antigen (GM) tests were integrated with clinical, imaging data from patients' medical records. Diagnostic frameworks were established based on the standard diagnostic criteria to identify IPA, CPA, and ABPA.
Results:
Of 2412 patients with GM testing, 46 (1.9 %) had IPA. Of 2889 patients with Aspergillus-specific IgG testing, 16 (0.6 %) were diagnosed with CPA. Of 1779 patients with Aspergillus-specific IgE testing, 46 (2.6 %) were diagnosed with ABPA. We noted biotherapy (tocilizumab and oblinutuzumab) as potential emerging risk factors for IPA. Strikingly, only 10 of 46 patients with ABPA were treated by physicians, highlighting potential gaps in clinical practice and current diagnostic guidelines. The 3-month case fatality rate was 46.7 % for IPA, 13.3 % for CPA and 0 for APBA. Despite treatment, 13 % of patients with ABPA experienced an exacerbation.
Conclusions:
This study highlights the prevalence of Aspergillus-related lung disease and the high 3-month mortality rate in IPA and CPA in AP-HM. Discrepancies in ABPA diagnosis highlight the need for improved diagnostic algorithms that better reflect real-world clinical practice and address these challenges.
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