“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.” Esbenshade et al (2014).
Esbenshade, A.J., Di Pentima, M.C., Zhao, Z., Shintani, A., Esbenshade, J.C., Simpson, M.E., Montgomery, K.C., Lindell, R.B., Lee, H., Wallace, A., Garcia, K.L., Moons, K.G.M. and Friedman, D.L. (2014) Development and validation of a prediction model for diagnosing blood stream infections in febrile, non-neutropenic children with cancer. Pediatric Blood & Cancer. October 18th. .
Prediction model for diagnosing blood stream infections in children with cancer http://ctt.ec/bz2tO+ @ivteam #ivteam
Background: Pediatric oncology patients are at increased risk for blood stream infections (BSI). Risk in the absence of severe neutropenia (absolute neutrophil count ≥500/µl) is not well defined.
Procedure: In a retrospective cohort of febrile (temperature ≥38.0° for >1 hr 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 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.
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