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    Predicting Infectious ComplicatioNs in Children with Cancer: an external validation study

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    Author
    Haeusler, GM; Thursky, KA; Mechinaud, F; Babl, FE; Lourenco, RDA; Slavin, MA; Phillips, R
    Date
    2017-07-11
    Source Title
    British Journal of Cancer
    Publisher
    NATURE PUBLISHING GROUP
    University of Melbourne Author/s
    Slavin, Monica; Thursky, Karin; Babl, Franz; Haeusler, Gabrielle
    Affiliation
    Infectious Diseases
    Medicine and Radiology
    Paediatrics (RCH)
    Metadata
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    Document Type
    Journal Article
    Citations
    Haeusler, G. M., Thursky, K. A., Mechinaud, F., Babl, F. E., Lourenco, R. D. A., Slavin, M. A. & Phillips, R. (2017). Predicting Infectious ComplicatioNs in Children with Cancer: an external validation study. BRITISH JOURNAL OF CANCER, 117 (2), pp.171-178. https://doi.org/10.1038/bjc.2017.154.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/259522
    DOI
    10.1038/bjc.2017.154
    NHMRC Grant code
    NHMRC/1056158
    Abstract
    BACKGROUND: The aim of this study was to validate the 'Predicting Infectious ComplicatioNs in Children with Cancer' (PICNICC) clinical decision rule (CDR) that predicts microbiologically documented infection (MDI) in children with cancer and fever and neutropenia (FN). We also investigated costs associated with current FN management strategies in Australia. METHODS: Demographic, episode, outcome and cost data were retrospectively collected on 650 episodes of FN. We assessed the discrimination, calibration, sensitivity and specificity of the PICNICC CDR in our cohort compared with the derivation data set. RESULTS: Using the original variable coefficients, the CDR performed poorly. After recalibration the PICNICC CDR had an area under the receiver operating characteristic (AUC-ROC) curve of 0.638 (95% CI 0.590-0.685) and calibration slope of 0.24. The sensitivity, specificity, positive predictive value and negative predictive value of the PICNICC CDR at presentation was 78.4%, 39.8%, 28.6% and 85.7%, respectively. For bacteraemia, the sensitivity improved to 85.2% and AUC-ROC to 0.71. Application at day 2, taking into consideration the proportion of MDI known (43%), further improved the sensitivity to 87.7%. Length of stay is the main contributor to cost of FN treatment, with an average cost per day of AUD 2183 in the low-risk group. CONCLUSIONS: For prediction of any MDI, the PICNICC rule did not perform as well at presentation in our cohort as compared with the derivation study. However, for bacteraemia, the predictive ability was similar to that of the derivation study, highlighting the importance of recalibration using local data. Performance also improved after an overnight period of observation. Implementation of a low-risk pathway, using the PICNICC CDR after a short period of inpatient observation, is likely to be safe and has the potential to reduce health-care expenditure.

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