Prognostic factors and scoring model of hematological malignancies patients with bloodstream infections

• Published in: Infection 2018-08, Vol.46 (4), p.513-521
• Main Authors: Tang, Yishu, Cheng, Qian, Yang, Qing, Liu, Jing, Zhang, Di, Cao, Wei, Liu, Qingxia, Zhou, Tianyi, Zeng, Huiqi, Zhou, Li, Wang, QinJin, Wei, Huan, Li, Xin
• Format: Article
• Language: English
• Subjects: Antibiotics; Bacteremia; Bacteremia - etiology; Bacteremia - microbiology; Bacteremia - mortality; Bacterial infections; Blood; Cancer; China; Cohort Studies; Decision making; Derivation; Family Medicine; Female; Fungemia; General Practice; Hematologic Neoplasms - complications; Hematologic Neoplasms - microbiology; Hematologic Neoplasms - mortality; Hematology; Humans; Infectious Diseases; Internal Medicine; Male; Malignancy; Mathematical models; Medical prognosis; Medicine; Medicine & Public Health; Middle Aged; Models, Biological; Morality; Morbidity; Mortality; Mortality risk; Multivariate analysis; Neutropenia; Original Paper; Patients; Prediction models; Prognosis; Respiratory failure; Retrospective Studies; Risk analysis; Risk Assessment; Risk Factors; Risk groups; Scoring models
• ISSN: 0300-8126; 1439-0973
• DOI: 10.1007/s15010-018-1151-3

Purpose Patients with hematological malignancies (HMs) are at a higher risk for bloodstream infections (BSIs), which pose significant burden on morbidity and mortality. Better risk stratification helps in medical decision making, increasing efficiency and reducing economic burden. The aim of this study was to develop and validate a reliable prediction model which can be used to identify HM patients at higher risk for BSIs. Methods We conducted a retrospective cohort study in three university-affiliated hospitals in Hunan Province, China, from January 2010 to April 2015. A total of 521 HMs patients with BSIs were finally included in this study and were divided into the derivation set and validation set. Survivors and non-survivors were compared to identify the predictors of 30-day mortality. Results The multivariate analysis yielded the following significant mortality-related risk factors: age > 60 years (95% CI 1.047–5.474), relapsed or uncontrolled malignancy (95% CI 2.043–14.029), Pitt bacteremia score > 3 (95% CI 1.614–6.35), prolonged neutropenia (95% CI 1.181–5.824), use of vasopressors (95% CI 3.009–12.210), acute respiratory failure (95% CI 3.061–14.911), fungemia (95% CI 1.334–12.121), inadequate antibiotic treatment (95% CI 1.682–7.591), albumin  34.2 µmol/L (95% CI 1.109–5.438). In both derivation and validation sets, our model showed reliable prediction value with areas under the receiver operating curve of 0.876 and 0.873. Conclusions The risk factors in this study have the ability to identify patients with HMs and BSIs at high risk for mortality. Our model provides an excellent foundation for predicting 30-day morality in HM patients suffering from BSI and helps target high-risk patients for management decision making.