Derivation and validation of a scoring system to identify patients with bacteremia and hematological malignancies at higher risk for mortality

BACKGROUND: The aim of this study was to develop and validate a reliable clinical prediction rule that could be employed to identify patients at higher likelihood of mortality among those with hematological malignancies (HMs) and bacterial bloodstream infections (BBSIs). METHODS AND FINDINGS: We conducted a retrospective cohort study in nine Italian hematological units. The derivation cohort consisted of adult patients with BBSI and HMs admitted to the Catholic University Hospital (Rome) between January 2002 and December 2008. Survivors and nonsurvivors were compared to identify predictors of 30-day mortality. The validation cohort consisted of patients hospitalized with BBSI and HMs who were admitted in 8 other Italian hematological units between January 2009 and December 2010. The inclusion and exclusion criteria were identical for both cohorts, with type and stage of HMs used as matching criteria. In the derivation set (247 episodes), the multivariate analysis yielded the following significant mortality-related risk factors acute renal failure (Odds Ratio [OR] 6.44, Confidential Interval [CI], 2.36-17.57, P<0.001); severe neutropenia (absolute neutrophil count <100/mm(3)) (OR 4.38, CI, 2.04-9.43, P<0.001); nosocomial infection (OR, 3.73, CI, 1.36-10.22, P = 0.01); age ≥65 years (OR, 3.42, CI, 1.49-7.80, P = 0.003); and Charlson Comorbidity Index ≥4 (OR, 3.01, CI 1.36-6.65, P = 0.006). The variables unable to be evaluated at that time (for example, prolonged neutropenia) were not included in the final logistic model. The equal-weight risk score model, which assigned 1 point to each risk factor, yielded good-excellent discrimination in both cohorts, with areas under the receiver operating curve of 0.83 versus 0.93 (derivation versus validation) and good calibration (Hosmer-Lemshow P = 0.16 versus 0.75).CONCLUSIONS: The risk index accurately identifies patients with HMs and BBSIs at high risk for mortality; a better initial predictive approach may yield better therapeutic decisions for these patients, with an eventual reduction in mortality.