Establishment of a risk classifier to predict the in-hospital death risk of nosocomial fungal infections in cancer patients

Background Patients 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. Methods This 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. Results A 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. Conclusions Fungi-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.