ArticleFrontiers in cellular and infection microbiology2025
A serum galactomannan and neutrophil-to-lymphocyte ratio-based nomogram for predicting in-hospital mortality in non-neutropenic invasive pulmonary aspergillosis.
Article in Frontiers in cellular and infection microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Evaluation of the Prognostic Value of PCR Cycle Threshold and Mortality in Pulmonary Aspergillosis: A Retrospective Cohort Study.Infection and drug resistance · 2026Article
- Epidemiology, Risk Factors, and Routine Blood Biomarkers of Aspergillosis in Cancer Patients in Jiangxi, China.Infection and drug resistance · 2026Article
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10 authors.
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Abstract
Background: We developed a novel prognostic model combining serum galactomannan (GM) and neutrophil-to-lymphocyte ratio (NLR) for predicting in-hospital mortality in non-neutropenic invasive pulmonary aspergillosis (IPA). Methods: We retrospectively identified 278 eligible IPA patients using the automated natural language processing system. Patients were divided into survival (n=199) and non-survival (n=79) groups. A multivariate logistic regression was developed to predict in-hospital mortality based on age, critical condition, serum GM and NLR. Internal validation was performed using bootstrap resampling methods. Subsequently, a clinical nomogram was constructed to support clinical decision-making. Results: Serum GM exhibited a higher specificity of 78.9% (95% CI: 72.6-84.3%), whereas NLR demonstrated relatively greater sensitivity at 70.9% (95% CI: 59.6-80.6%) for mortality prediction. The combination of either positive exhibited a sensitivity of 81.0%, while the dual-positive criterion achieved a specificity of 90.5%. A comprehensive model integrating age, critical condition, serum GM, and NLR demonstrated robust discrimination, with a mean AUC of 0.815 (SD = 0.005) after bootstrap resampling with 1000 iterations. This result was consistent with the original model AUC of 0.818 (95% CI: 0.767-0.870). Decision curve analysis further confirmed that the comprehensive model provided a greater net benefit compared to the simple model based solely on age and critical condition, highlighting the clinical utility of including serum GM and NLR as biomarkers in decision-making processes. Conclusion: Our study provided novel evidence that the synergistic integration of mycological (serum GM) and inflammatory biomarkers (NLR) significantly improves prognostic accuracy in non-neutropenic IPA. The developed clinical nomogram offers a practical tool to support clinical decision-making.
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