Construction and assessment of a predictive framework for Enterobacterales bloodstream infection in real-world adult onco-hematology patients using Lasso-Cox regression.

Bloodstream infections (BSIs) caused by Enterobacterales, particularly Escherichia coli (EC) and Klebsiella pneumoniae (KP), are the most prevalent infectious issues in individuals with hematologic malignancies (HM). Prognostic tools integrating pathogen-specific risks are urgently needed to optimize early clinical decision-making. This retrospective cohort study analyzed 1,299 HM patients with EC- or KP-BSI (2017-2023). Patients were randomly allocated to training (n = 909) and validation (n = 390) cohorts. Prognostic variables were selected through Lasso regression, followed by Cox proportional hazards modeling to construct a 30-day mortality prediction nomogram. Model performance was rigorously validated using receiver operating characteristic curves (AUCs), calibration curves, and decision-curve analysis. The cohort comprised 653 EC-BSI and 646 KP-BSI cases, predominantly with acute myeloid leukemia (54.3%). Pulmonary/skin-soft tissue infection origins, hematopoietic stem cell transplantation, concurrent septic shock/pneumonia, hypoproteinemia, prolonged neutropenia before BSI, and carbapenem-resistant strains emerged as independent predictors of mortality. Conversely, tumor consolidation stage status and ceftazidime-avibactam-containing regimens were predictive of survival benefit. The model demonstrated high predictive accuracy (AUC 0.881), excellent calibration, and superior clinical utility. We developed a simple model using routine clinical parameters that predicts 30-day mortality in HM patients with EC- or KP-BSI, guiding therapy without complex biomarkers.