A TTP-incorporated scoring model for predicting mortality of solid tumor patients with bloodstream infection caused by Escherichia coli.

Background: Few mortality-scoring models are available for solid tumor patients who are predisposed to develop Escherichia coli–caused bloodstream infection (ECBSI). We aimed to develop a mortality-scoring model by using information from blood culture time to positivity (TTP) and other clinical variables. Methods: A cohort of solid tumor patients who were admitted to hospital with ECBSI and received empirical antimicrobial therapy was enrolled. Survivors and non-survivors were compared to identify the risk factors of in-hospital mortality. Univariable and multivariable regression analyses were adopted to identify the mortality-associated predictors. Risk scores were assigned by weighting the regression coefficients with corresponding natural logarithm of the odds ratio for each predictor. Results: Solid tumor patients with ECBSI were distributed in the development and validation groups, respectively. Six mortality-associated predictors were identified and included in the scoring model: acute respiratory distress (ARDS), TTP ≤ 8 h, inappropriate antibiotic therapy, blood transfusion, fever ≥ 39 °C, and metastasis. Prognostic scores were categorized into three groups that predicted mortality: low risk (< 10% mortality, 0–1 points), medium risk (10–20% mortality, 2 points), and high risk (> 20% mortality, ≥ 3 points). The TTP-incorporated scoring model showed excellent discrimination and calibration for both groups, with AUC being 0.833 vs 0.844, respectively, and no significant difference in the Hosmer–Lemeshow test (6.709, P = 0.48) and the chi-square test (6.993, P = 0.46). Youden index showed the best cutoff value of ≥ 3 with 76.11% sensitivity and 79.29% specificity. TTP-incorporated scoring model had higher AUC than no TTP-incorporated model (0.837 vs 0.817, P < 0.01). Conclusions: Our TTP-incorporated scoring model was associated with improving capability in predicting ECBSI-related mortality. It can be a practical tool for clinicians to identify and manage bacteremic solid tumor patients with high risk of mortality. [ABSTRACT FROM AUTHOR]