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

Haeusler, GM; Thursky, KA; Mechinaud, F; Babl, FE; De Abreu Lourenco, R; Slavin, MA; Phillips, R

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

Haeusler, GM Thursky, KA Mechinaud, F Babl, FE De Abreu Lourenco, R

Slavin, MA Phillips, R

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Publication Type:: Journal Article
Citation:: British Journal of Cancer, 2017, 117 (2), pp. 171 - 178
Issue Date:: 2017-07-11

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Field	Value	Language
dc.contributor.author	Haeusler, GM	en_US
dc.contributor.author	Thursky, KA	en_US
dc.contributor.author	Mechinaud, F	en_US
dc.contributor.author	Babl, FE	en_US
dc.contributor.author	De Abreu Lourenco, R https://orcid.org/0000-0002-5978-8774	en_US
dc.contributor.author	Slavin, MA	en_US
dc.contributor.author	Phillips, R	en_US
dc.date.available	2017-05-11	en_US
dc.date.issued	2017-07-11	en_US
dc.identifier.citation	British Journal of Cancer, 2017, 117 (2), pp. 171 - 178	en_US
dc.identifier.issn	0007-0920	en_US
dc.identifier.uri	http://hdl.handle.net/10453/125747
dc.description.abstract	© 2017 Cancer Research UK. All rights reserved. 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.	en_US
dc.relation	http://purl.org/au-research/grants/nhmrc/APP 1104527
dc.relation.ispartof	British Journal of Cancer	en_US
dc.relation.isbasedon	10.1038/bjc.2017.154	en_US
dc.subject.classification	Oncology & Carcinogenesis	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Infection	en_US
dc.subject.mesh	Neoplasms	en_US
dc.subject.mesh	Neutropenia	en_US
dc.subject.mesh	Fever	en_US
dc.subject.mesh	Length of Stay	en_US
dc.subject.mesh	Risk Factors	en_US
dc.subject.mesh	Decision Support Techniques	en_US
dc.subject.mesh	Adolescent	en_US
dc.subject.mesh	Child	en_US
dc.subject.mesh	Child, Preschool	en_US
dc.subject.mesh	Australia	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Infections	en_US
dc.title	Predicting Infectious ComplicatioNs in Children with Cancer: An external validation study	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	117	en_US
utslib.for	1112 Oncology and Carcinogenesis	en_US
utslib.for	1117 Public Health and Health Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Strength - CHERE - Centre for Health Economics Research and Evaluation
utslib.copyright.status	open_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	117	en_US

Abstract:

© 2017 Cancer Research UK. All rights reserved. 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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http://hdl.handle.net/10453/125747