TY - JOUR
T1 - Predicting microbiologically defined infection in febrile neutropenic episodes in children
T2 - Global individual participant data multivariable meta-analysis
AU - S Phillips, Robert
AU - Sung, Lillian
AU - Amman, Roland A.
AU - Riley, Richard D.
AU - Castagnola, Elio
AU - Haeusler, Gabrielle M.
AU - Klaassen, Robert
AU - Tissing, Wim J.E.
AU - Lehrnbecher, Thomas
AU - Chisholm, Julia
AU - Hakim, Hana
AU - Ranasinghe, Neil
AU - Paesmans, Marianne
AU - Hann, Ian M.
AU - Stewart, Lesley A.
N1 - Publisher Copyright:
© 2016 Cancer Research UK.
PY - 2016/3/15
Y1 - 2016/3/15
N2 - Background:Risk-stratified management of fever with neutropenia (FN), allows intensive management of high-risk cases and early discharge of low-risk cases. No single, internationally validated, prediction model of the risk of adverse outcomes exists for children and young people. An individual patient data (IPD) meta-analysis was undertaken to devise one.Methods:The 'Predicting Infectious Complications in Children with Cancer' (PICNICC) collaboration was formed by parent representatives, international clinical and methodological experts. Univariable and multivariable analyses, using random effects logistic regression, were undertaken to derive and internally validate a risk-prediction model for outcomes of episodes of FN based on clinical and laboratory data at presentation.Results:Data came from 22 different study groups from 15 countries, of 5127 episodes of FN in 3504 patients. There were 1070 episodes in 616 patients from seven studies available for multivariable analysis. Univariable analyses showed associations with microbiologically defined infection (MDI) in many items, including higher temperature, lower white cell counts and acute myeloid leukaemia, but not age. Patients with osteosarcoma/Ewings sarcoma and those with more severe mucositis were associated with a decreased risk of MDI. The predictive model included: malignancy type, temperature, clinically 'severely unwell', haemoglobin, white cell count and absolute monocyte count. It showed moderate discrimination (AUROC 0.723, 95% confidence interval 0.711-0.759) and good calibration (calibration slope 0.95). The model was robust to bootstrap and cross-validation sensitivity analyses.Conclusions:This new prediction model for risk of MDI appears accurate. It requires prospective studies assessing implementation to assist clinicians and parents/patients in individualised decision making.
AB - Background:Risk-stratified management of fever with neutropenia (FN), allows intensive management of high-risk cases and early discharge of low-risk cases. No single, internationally validated, prediction model of the risk of adverse outcomes exists for children and young people. An individual patient data (IPD) meta-analysis was undertaken to devise one.Methods:The 'Predicting Infectious Complications in Children with Cancer' (PICNICC) collaboration was formed by parent representatives, international clinical and methodological experts. Univariable and multivariable analyses, using random effects logistic regression, were undertaken to derive and internally validate a risk-prediction model for outcomes of episodes of FN based on clinical and laboratory data at presentation.Results:Data came from 22 different study groups from 15 countries, of 5127 episodes of FN in 3504 patients. There were 1070 episodes in 616 patients from seven studies available for multivariable analysis. Univariable analyses showed associations with microbiologically defined infection (MDI) in many items, including higher temperature, lower white cell counts and acute myeloid leukaemia, but not age. Patients with osteosarcoma/Ewings sarcoma and those with more severe mucositis were associated with a decreased risk of MDI. The predictive model included: malignancy type, temperature, clinically 'severely unwell', haemoglobin, white cell count and absolute monocyte count. It showed moderate discrimination (AUROC 0.723, 95% confidence interval 0.711-0.759) and good calibration (calibration slope 0.95). The model was robust to bootstrap and cross-validation sensitivity analyses.Conclusions:This new prediction model for risk of MDI appears accurate. It requires prospective studies assessing implementation to assist clinicians and parents/patients in individualised decision making.
KW - infectious complications
KW - meta-analysis
KW - neutropenic sepsis
KW - paediatric oncology
KW - supportive care
UR - http://www.scopus.com/inward/record.url?scp=84960157266&partnerID=8YFLogxK
U2 - 10.1038/bjc.2016.28
DO - 10.1038/bjc.2016.28
M3 - Article
C2 - 27228292
VL - 114
SP - 623
EP - 630
JO - British Journal of Cancer
JF - British Journal of Cancer
SN - 0007-0920
IS - 6
ER -