Development and validation of a nomogram for predicting progression from multidrug-resistant bacterial colonization to infection in lymphoma patients

To investigate the risk factors for progression from multidrug-resistant (MDR) bacterial colonization to infection in hospitalized lymphoma patients and to develop a Nomogram predictive model. A retrospective analysis was conducted on clinical data from 70 MDR-positive lymphoma patients admitted to a tertiary hospital between March 2017 and March 2025. Patients were divided into MDR infection and MDR colonization groups based on the occurrence of MDR infection. Demographic characteristics, lymphoma subtypes, lesion sites, laboratory parameters, and treatment-related factors were collected. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors, and a Nomogram predictive model was constructed. Among 70 MDR-positive patients, 48 (68.6%) developed MDR infection and 22 (31.4%) remained as colonization. Multivariate analysis revealed that T/NK-cell lymphoma (OR = 3.82, 95% CI 1.46–9.98, P = 0.006), nasopharyngeal/nasal cavity involvement (OR = 2.94, 95% CI 1.23–7.04, P = 0.015), recent antibiotic use (OR = 2.67, 95% CI 1.15–6.21, P = 0.022), and albumin < 35 g/L (OR = 2.31, 95% CI 1.08–4.93, P = 0.031) were independent risk factors. The Nomogram model based on these factors demonstrated good discrimination (C-index = 0.812) and calibration. T/NK-cell origin, nasopharyngeal involvement, recent antibiotic exposure, and hypoalbuminemia are independent risk factors for progression from MDR colonization to infection in lymphoma patients. The Nomogram model can effectively identify high-risk patients and provide evidence for clinical prevention and control strategies.

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Publication Details

Journal
Discover Oncology
Published
2026-03-07
DOI
https://doi.org/10.1007/s12672-026-04749-z
Primary Topic
Neutropenia and Cancer Infections
Type
article
Field-Weighted Citation Impact
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article

Development and validation of a nomogram for predicting progression from multidrug-resistant bacterial colonization to infection in lymphoma patients

Yuhong Deng, Huijun Duan, Yuan Zhang, Jing Li et al.
Discover Oncology
Neutropenia and Cancer Infections
article

Development and validation of a nomogram for predicting progression from multidrug-resistant bacterial colonization to infection in lymphoma patients

Yuhong Deng, Huijun Duan, Yuan Zhang, Jing Li, Han Yan, Jing Lv, Tingting Liu, Xia Wang, Xin Ran, Xingsu Jing, Wenling Xiong
article en

Abstract

To investigate the risk factors for progression from multidrug-resistant (MDR) bacterial colonization to infection in hospitalized lymphoma patients and to develop a Nomogram predictive model. A retrospective analysis was conducted on clinical data from 70 MDR-positive lymphoma patients admitted to a tertiary hospital between March 2017 and March 2025. Patients were divided into MDR infection and MDR colonization groups based on the occurrence of MDR infection. Demographic characteristics, lymphoma subtypes, lesion sites, laboratory parameters, and treatment-related factors were collected. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors, and a Nomogram predictive model was constructed. Among 70 MDR-positive patients, 48 (68.6%) developed MDR infection and 22 (31.4%) remained as colonization. Multivariate analysis revealed that T/NK-cell lymphoma (OR = 3.82, 95% CI 1.46–9.98, P = 0.006), nasopharyngeal/nasal cavity involvement (OR = 2.94, 95% CI 1.23–7.04, P = 0.015), recent antibiotic use (OR = 2.67, 95% CI 1.15–6.21, P = 0.022), and albumin < 35 g/L (OR = 2.31, 95% CI 1.08–4.93, P = 0.031) were independent risk factors. The Nomogram model based on these factors demonstrated good discrimination (C-index = 0.812) and calibration. T/NK-cell origin, nasopharyngeal involvement, recent antibiotic exposure, and hypoalbuminemia are independent risk factors for progression from MDR colonization to infection in lymphoma patients. The Nomogram model can effectively identify high-risk patients and provide evidence for clinical prevention and control strategies.

Discover Oncology
Chongqing Cancer Hospital (CN)
Zero hunger
Openalex Percentile: Top 29%
Neutropenia and Cancer Infections
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