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.

A novel risk classifier for predicting the overall survival of patients with thymic epithelial tumors based on the eighth edition of the TNM staging system: A population-based study.

Objective: Thymic epithelial tumors (TETs) are rare tumors that originated from thymic epithelial cells, with limited studies investigating their prognostic factors. This study aimed to investigate the prognostic factors of TETs and develop a new risk classifier to predict their overall survival (OS). Methods: This retrospective study consisted of 1224 TETs patients registered in the Surveillance, Epidemiology, and End Results (SEER) database, and 75 patients from the First Affiliated Hospital of Xi'an Jiaotong University. The univariate and multivariate Cox regression analyses were adopted to select the best prognostic variables. A nomogram was developed to predict the OS of these patients. The discriminative and calibrated abilities of the nomogram were assessed using the receiver operating characteristics curve (ROC) and calibration curve. Decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI) were adopted to assess its net clinical benefit and reclassification ability. Results: The multivariate analysis revealed that age, sex, histologic type, TNM staging, tumor grade, surgery, radiation, and tumor size were independent prognostic factors of TETs, and a nomogram was developed to predict the OS of these patients based on these variables. The time-dependent ROC curves displayed that the nomogram yielded excellent performance in predicting the 12-, 36- and 60-month OS of these patients. Calibration curves presented satisfying consistencies between the actual and predicted OS. DCA illustrated that the nomogram will bring significant net clinical benefits to these patients compared to the classic TNM staging system. The estimated NRI and IDI showed that the nomogram could significantly increase the predictive ability of 12-, 36- and 60-month OS compared to the classic TNM staging system. Consistent findings were discovered in the internal and external validation cohorts. Conclusion: The constructed nomogram is a reliable risk classifier to achieve personalized survival probability prediction of TETs, and could bring significant net clinical benefits to these patients.

Immune Checkpoint Inhibitor-Associated Cardiotoxicity in Solid Tumors: Real-World Incidence, Risk Factors, and Prognostic Analysis.

Background: Immune checkpoint inhibitors (ICIs) have achieved acknowledged progress in cancer therapy. However, ICI-associated cardiotoxicity as one of the most severe adverse events is potentially life-threatening, with limited real-world studies reporting its predictive factors and prognosis. This study aimed to investigate the real-world incidence, risk factors, and prognosis of ICI-related cardiotoxicity in patients with advanced solid tumors. Methods: Electronic medical records from patients with advanced solid tumors receiving ICIs in the First Affiliated Hospital of Xi'an Jiaotong University were retrospectively reviewed. All patients were divided into the cardiotoxicity group and control group, with logistic regression analysis being implemented to identify potential risk factors of ICI-related cardiotoxicity. Furthermore, survival analysis was also performed to investigate the prognosis of patients with ICI-related cardiotoxicity. Results: A total of 1,047 participants were enrolled in this retrospective study. The incidence of ICI-related cardiotoxicity in our hospital is 7.0%, while grade 3 and above cardiotoxicity was 2.4%. The logistic regression analysis revealed that diabetes mellitus [odds ratio (OR):1.96, 95% confidence Interval (CI): 1.05-3.65, p = 0.034] was an independent risk factor, whereas baseline lymphocyte/monocyte ratio (LMR) (OR: 0.59, 95% CI: 0.36-0.97, p = 0.037) was the protective factor of ICI-related cardiotoxicity. Survival analysis indicated that severe cardiotoxicity (≥grade 3) was significantly correlated with bleak overall survival (OS) than mild cardiotoxicity (≤grade 2) (8.3 months vs. not reached, p = 0.001). Patients with ICI-related overlap syndrome had poorer overall survival than patients with mere cardiotoxicity (9.4 vs. 24.7 months, p = 0.033). However, the occurrence of ICI-related cardiotoxicity was not significantly associated with the OS of overall population with solid tumors. Subgroup analysis showed that lung cancer and PD-L1 usage were significantly correlated with a higher incidence of severe cases. Conclusion: Immune checkpoint inhibitor-related cardiotoxicity is more common in the real-world setting than the previously published studies. Diabetes mellitus and baseline LMR are the potential predictive biomarkers of ICI-related cardiotoxicity. Although ICI-related cardiotoxicity is not correlated with the prognosis of these patients in our cohort, a systematic and comprehensive baseline examination and evaluation should be performed to avoid its occurrence.