Prospective cohort study of the predictive value of inflammatory biomarkers over clinical variables in children and young people with cancer presenting with fever and neutropenia.
Robert S PhillipsPublished in: F1000Research (2021)
Introduction Fever during chemotherapy induced neutropenia is a common and potentially life-threatening complication of the treatment of childhood cancer. Predictions of poor outcome could be enhanced by incorporating serum biomarkers of inflammation at presentation and reassessment. Methods A prospective cohort study was conducted of children under 18 years old, being treated for cancer or a cancer-like condition, who presented with fever (≥ 38.0°C) and neutropenia (neutrophil count < 0.5*10 9 /L). Clinical features were recorded, along with three experimental inflammatory biomarkers: procalcitonin (PCT), interleukin-6 (IL-6) and interleukin-8 (IL-8). Outcomes included serious medical complications (SMC): any infection related mortality, critical care and organ support, severe sepsis, septic shock, significant microbiologically defined infection, or radiologically confirmed pneumonia. Results Biomarker assessments were undertaken in 43 episodes of fever and neutropenia, from 31 patients aged between four months and 17 years old (median six years): 20 were female and 22 had acute leukaemia. Five episodes of SMC were noted. PCT, IL-6 and IL-8 had poor individual discriminatory ability (C-statistic 0.48 to 0.60) and did not add to the value of clinical risk stratification tools. Insufficient data were collected to formally assess the value of repeated assessments. Conclusions Incorporating serum biomarkers of inflammation at presentation of episodes of fever with neutropenia in childhood does not clearly improve risk stratification. The value of serial assessments requires further investigation.
Keyphrases
- chemotherapy induced
- childhood cancer
- young adults
- papillary thyroid
- septic shock
- oxidative stress
- squamous cell
- end stage renal disease
- newly diagnosed
- intensive care unit
- risk factors
- case report
- healthcare
- chronic kidney disease
- lymph node metastasis
- squamous cell carcinoma
- ejection fraction
- machine learning
- electronic health record
- type diabetes
- liver failure
- coronary artery disease
- metabolic syndrome
- artificial intelligence
- peritoneal dialysis
- mechanical ventilation
- adipose tissue
- combination therapy
- deep learning