Development and validation of a prediction model for diagnosing blood stream infections in febrile, non-neutropenic children with cancer

Pediatric oncology patients are at increased risk for blood stream infections (BSI). Risk in the absence of severe neutropenia (absolute neutrophil count [ANC] ≥500/μl) is not well defined. Procedure: In a retrospective cohort of febrile (temperature ≥38.0° for >1hr or ≥38.3°) pediatric oncology patients with ANC ≥500/μl, a diagnostic prediction model for BSI was constructed using logistic regression modeling and the following candidate predictors: age, ANC, absolute monocyte count, body temperature, inpatient/outpatient presentation, sex, central venous catheter type, hypotension, chills, cancer diagnosis, stem cell transplant, upper respiratory symptoms, and exposure to cytarabine, anti-thymocyte globulin, or anti-GD2 antibody. The model was internally validated with bootstrapping methods. Results: Among 932 febrile episodes in 463 patients, we identified 91 cases of BSI. Independently significant predictors for BSI were higher body temperature (Odds ratio [OR] 2.36 P<0.001), tunneled external catheter (OR 13.79 P<0.001), peripherally inserted central catheter (OR 3.95 P=0.005), elevated ANC (OR 1.19 P=0.024), chills (OR 2.09 P=0.031), and hypotension (OR 3.08 P=0.004). Acute lymphoblastic leukemia diagnosis (OR 0.34 P=0.026), increased age (OR 0.70 P=0.049), and drug exposure (OR 0.08 P<0.001) were associated with decreased risk for BSI. The risk prediction model had a C-index of 0.898; after bootstrapping adjustment for optimism, corrected C-index 0.885. Conclusions: We developed a diagnostic prediction model for BSI in febrile pediatric oncology patients without severe neutropenia. External validation is warranted before use in clinical practice.