A multidimensional nomogram for clinical risk stratification of bloodstream infection and mortality in hematologic malignancies.

Background: Bloodstream infections (BSIs) are serious complications in patients with hematologic malignancies (HMs) and are associated with substantial morbidity and mortality. Effective risk stratification is crucial for optimizing empirical antimicrobial decisions. This study aimed to develop and internally validate nomograms for predicting BSI occurrence and post-BSI mortality among HM patients. Methods: This retrospective cohort study enrolled 3,014 HM patients, including 725 with BSI. The cohort was randomly divided into derivation and internal validation cohorts at a 6:4 ratio. The BSI occurrence model was developed using multivariable logistic regression, while the post-BSI mortality prediction model among patients with BSI was developed using Cox regression. Model performance was evaluated based on discrimination, calibration, and decision curve analysis. Results: The BSI occurrence model demonstrated acceptable discrimination, with area under the receiver operating characteristic curve (AUC) values of 0.775 in the derivation cohort and 0.761 in the internal validation cohort. The final nomogram incorporated 12 variables, among which neutrophil count ≤0.5 × 10 Conclusions: The BSI occurrence model showed acceptable discrimination in the derivation and internal validation cohorts and was preliminarily assessed in an independent cohort. The post-BSI mortality model showed moderate discrimination in the internal validation cohort and requires further evaluation in larger and more representative populations.