Establishment and validation of a nomogram to predict the in-hospital death risk of nosocomial infections in cancer patients

Attributed to the immunosuppression caused by malignancy itself and its treatments, cancer patients are vulnerable to developing nosocomial infections. This study aimed to develop a nomogram to predict the in-hospital death risk of these patients. This retrospective study was conducted at a medical center in Northwestern China. The univariate and multivariate logistic regression analyses were adopted to identify predictive factors for in-hospital mortality of nosocomial infections in cancer patients. A nomogram was developed to predict the in-hospital mortality of each patient, with receiver operating characteristic curves and calibration curves being generated to assess its predictive ability. Furthermore, decision curve analysis (DCA) was also performed to estimate the clinical utility of the nomogram. A total of 1,008 nosocomial infection episodes were recognized from 14,695 cancer patients. Extended-spectrum β-lactamase (ESBL)-producing Escherichia coli (15.5%) was the most predominant causative pathogen. Besides, multidrug-resistant strains were discovered in 25.5% of cases. The multivariate analysis indicated that Eastern Cooperative Oncology Group Performance Status 3-4, mechanical ventilation, septic shock, hypoproteinemia, and length of antimicrobial treatment