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. 2015 Feb;62(2):262-268.
doi: 10.1002/pbc.25275. Epub 2014 Oct 18.

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

Adam J Esbenshade  1   2 , M Cecilia Di Pentima  1 , Zhiguo Zhao  2   3 , Ayumi Shintani  2   3 , Jennifer C Esbenshade  1 , Monique E Simpson  4 , Kathleen C Montgomery  4 , Robert B Lindell  4 , Haerin Lee  4 , Ato Wallace  4 , Kelly L Garcia  4 , Karel G M Moons  3   5 , Debra L Friedman  1   2
Affiliations

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

Adam J Esbenshade et al. Pediatr Blood Cancer. 2015 Feb.

Abstract

Background: 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 >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 [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. Pediatr Blood Cancer 2015;62:262-268. © 2014 Wiley Periodicals, Inc.

Keywords: febrile neutropenia; infections in immunocompromised hosts; pediatric hematology/oncology; prediction modeling in cancer; support care.

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Conflict of interest statement

Statement All authors have no conflicts of interest to disclose.

Figures

Figure 1
Figure 1
Receiver operating curve (ROC) for the Primary Diagnostic Model to estimate the probability of having a blood stream infection in 932 episodes of fever without severe neutropenia.
Figure 2
Figure 2
Nomogram for the Primary Diagnostic Model to estimate the probability of having blood stream infection from available data. Points for each variable are added together and the estimated probability of a blood stream infection is given at the bottom of the nomogram.
Figure 3
Figure 3
Distribution of predicted risk from the Primary Diagnostic Model assigned to each case of non-high-risk blood stream infection and high-risk bacteremia.
See this image and copyright information in PMC

References

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