ArticleAntimicrobial resistance and infection control2022
Establishment and validation of a nomogram to predict the in-hospital death risk of nosocomial infections in cancer patients.
Article in Antimicrobial resistance and infection control, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 24 citations in OpenAlex.
- Prediction of pulmonary infection during chemotherapy in non-small cell lung cancer: development and internal validation of a nomogram.Frontiers in oncology · 2026Article
- Development and validation of a novel model based on hematological biomarkers for predicting risk factors and outcomes in cancer patients with carbapenem-resistant organism infection.Frontiers in public health · 2026Article
- Predictive model for meningitis after pituitary tumor resection by endoscopic nasal trans-sphenoidal sinus approach.European journal of medical research · 2025Article
- Impact of high-speed nanodroplets on various pathogenic bacterial cell walls.Journal of bacteriology · 2024Article
- Development and validation of a clinical prediction model for early ventilator weaning in post-cardiac surgery.Heliyon · 2024Article
- Development of a nomogram to predict the prognosis of patients with secondary bone tumors in the intensive care unit: a retrospective analysis based on the MIMIC IV database.Journal of cancer research and clinical oncology · 2024Article
- Article
- Application of exponential smoothing method and SARIMA model in predicting the number of admissions in a third-class hospital in Zhejiang Province.BMC public health · 2023Article
- Observational
- Establishment of a risk classifier to predict the in-hospital death risk of nosocomial fungal infections in cancer patients.BMC infectious diseases · 2023Observational
- Establishment of a risk prediction model for multidrug-resistant bacteria in deceased organ donors: a retrospective cohort study in China.Frontiers in cellular and infection microbiology · 2023Article
- A novel risk classifier to predict the in-hospital death risk of nosocomial infections in elderly cancer patients.Frontiers in cellular and infection microbiology · 2023Article
- Relation of Malnutrition and Nosocomical Infections in Cancer Patients in Hospital: An Observational Study.Journal of nutrition and metabolism · 2022Article
- Development and validation of nomograms for predicting the risk probability of carbapenem resistance and 28-day all-cause mortality in gram-negative bacteremia among patients with hematological diseases.Frontiers in cellular and infection microbiology · 2022Article
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAttributed 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.
methodsThis 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.
resultsA 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 < 7 days were correlated with higher in-hospital mortality. Patients who received curative surgery were correlated with favorable survival outcomes. Ultimately, a nomogram was constructed to predict the in-hospital mortality of nosocomial infections in cancer patients. The area under the curve values of the nomogram were 0.811 and 0.795 in the training and validation cohorts. The calibration curve showed high consistency between the actual and predicted in-hospital mortality. DCA indicated that the nomogram was of good clinical utility and more credible net clinical benefits in predicting in-hospital mortality.
conclusionsNosocomial infections stay conjoint in cancer patients, with gram-negative bacteria being the most frequent causative pathogens. We developed and verified a nomogram that could effectively predict the in-hospital death risk of nosocomial infections among these patients. Precise management of high-risk patients, early recognition of septic shock, rapid and adequate antimicrobial treatment, and dynamic monitoring of serum albumin levels may improve the prognosis of these individuals.
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