Observational studyBMC infectious diseases2023
Establishment of a risk classifier to predict the in-hospital death risk of nosocomial fungal infections in cancer patients.
Observational study in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Continuous infusion of granulocyte colony-stimulating factor is associated with an advantage in neutrophil recovery in pediatric oncologic disorders.Cancer chemotherapy and pharmacology · 2026Trial
- Clinical pathogen profiles and lung microbiome features in lung infection patients and concurrent cancer: insights from metagenomics next-generation sequencing.Open life sciences · 2026Article
- Construction of a Nomogram Prediction Model for Individualized Prediction of the Risk of Pulmonary Fungal Infection in Lung Cancer.Infection and drug resistance · 2025Article
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Authors and funding
14 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundPatients with malignancy are at a higher risk of developing nosocomial infections. However, limited studies investigated the clinical features and prognostic factors of nosocomial infections due to fungi in cancer patients. Herein, this study aims to investigate the clinical characteristics of in-hospital fungal infections and develop a nomogram to predict the risk of in-hospital death during fungal infection of hospitalized cancer patients.
methodsThis retrospective observational study enrolled cancer patients who experienced in-hospital fungal infections between September 2013 and September 2021. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of in-hospital mortality. Variables demonstrating significant statistical differences in the multivariate analysis were utilized to construct a nomogram for personalized prediction of in-hospital death risk associated with nosocomial fungal infections. The predictive performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis.
resultsA total of 216 participants were included in the study, of which 57 experienced in-hospital death. C.albicans was identified as the most prevalent fungal species (68.0%). Respiratory infection accounted for the highest proportion of fungal infections (59.0%), followed by intra-abdominal infection (8.8%). The multivariate regression analysis revealed that Eastern Cooperative Oncology Group Performance Status (ECOG-PS) 3-4 (odds ratio [OR] = 6.08, 95% confidence interval [CI]: 2.04-18.12), pulmonary metastases (OR = 2.76, 95%CI: 1.11-6.85), thrombocytopenia (OR = 2.58, 95%CI: 1.21-5.47), hypoalbuminemia (OR = 2.44, 95%CI: 1.22-4.90), and mechanical ventilation (OR = 2.64, 95%CI: 1.03-6.73) were independent risk factors of in-hospital death. A nomogram based on the identified risk factors was developed to predict the individual probability of in-hospital mortality. The nomogram demonstrated satisfactory performance in terms of classification ability (area under the curve [AUC]: 0.759), calibration ability, and net clinical benefit.
conclusionsFungi-related nosocomial infections are prevalent among cancer patients and are associated with poor prognosis. The constructed nomogram provides an invaluable tool for oncologists, enabling them to make timely and informed clinical decisions that offer substantial net clinical benefit to patients.
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