Blood-based Diagnosis of Invasive Fungal Infections in Immunocompromised/Oncology Patients

Comparative accuracy of 1,3 beta-D glucan and galactomannan for diagnosis of invasive fungal infections in pediatric patients: a systematic review with meta-analysis

Invasive fungal infections (IFI) cause considerable morbidity and mortality in pediatric patients. Serum biomarkers such as 1,3-beta-D glucan (BDG) and galactomannan (GM) have been evaluated for the IFI diagnosis. However, most evidence regarding their utility is derived from studies in adult oncology patients. This systematic review aimed to compare the diagnostic accuracy of BDG and GM individually or in combination for diagnosing IFI in pediatric patients. PubMed, CINAHL, Embase, and Cochrane Library were searched until March 2019 for diagnostic studies evaluating both serum GM and BDG for diagnosing pediatric IFI. The pooled diagnostic odds ratio (DOR), specificity and sensitivity were computed. Receiver operating characteristics (ROC) curve and area under the curve (AUC) were used for summarizing overall assay performance. Six studies were included in the meta-analysis. The summary estimates of sensitivity, specificity, pooled DOR, AUC of the GM assay for proven or probable IFI were 0.74, 0.76, 13.25, and 0.845. The summary estimates of sensitivity, specificity, pooled DOR, AUC of the BDG assay were 0.70, 0.69, 4.3, and 0.722. The combined predictive ability of both tests was reported in two studies (sensitivity: 0.67, specificity: 0.877). Four studies were performed in hematology-oncology patients, while two were retrospective studies from pediatric intensive care units (ICUs). In the subgroup of hematology-oncology patients, DOR of BDG remained similar at 4.25 but increased to 40.28 for GM. We conclude that GM and BDG have a modest performance for identifying IFI in pediatric patients. GM has a better accuracy over BDG. Combining both improves the specificity at the cost of sensitivity.

Identification of Aspergillus species in human blood plasma by infrared spectroscopy and machine learning

Invasive Aspergillosis is a challenging infection that requires convenient, efficient, and cost-effective diagnostics. This study addresses the potential of infrared spectroscopy to satisfy this clinical need with the aid of machine learning. Two models, based on Partial Least Squares-Discriminant Analysis (PLS-DA), have been trained by a set of infrared spectral data of 9 Aspergillus-spiked and 7 Aspergillus-free plasma samples, and a set of 200 spectral data simulated by oversampling these 16 samples. Two further models have also been trained by the same sets but with auto-scaling performed prior to PLS-DA. These models were assessed using 45 mock samples, simulating the challenging samples of patients at risk of Invasive Aspergillosis, including the presence of drugs (9 tested) and other common pathogens (5 tested) as potential confounders. The simple model shows good prediction performance, yielding a total accuracy of 84.4%, while oversampling and autoscaling improved this accuracy to 93.3%. The results of this study have shown that infrared spectroscopy can identify Aspergillus species in blood plasma even in presence of potential confounders commonly present in blood of patients at risk of Invasive Aspergillosis.

Management of Patients With Fever and Neutropenia Through the Arc of Time: A Narrative Review

The association between fever and neutropenia and the risk for life-threatening infections in patients receiving cytotoxic chemotherapy has been known for 50 years. Indeed, infectious complications have been a leading cause of morbidity and mortality in patients with cancer. This review chronicles the progress in defining and developing approaches to the management of fever and neutropenia through observational and controlled clinical trials done by single institutions, as well as by national and international collaborative groups. The resultant data have led to recommendations and guidelines from professional societies and frame the current principles of management. Recommendations include those guiding new treatment options (from monotherapy to oral antibiotic therapy) and use of prophylactic antimicrobial regimens in high-risk patients. Of note, risk factors have changed with the advent of hematopoietic cytokines (especially granulocyte colony-stimulating factor) in shortening the duration of neutropenia, as well as with the discovery of more targeted cancer treatments that do not result in cytotoxicity, although these are still the exception. Most guiding principles that were developed decades ago-about when to begin empirical treatment after a neutropenic patient becomes febrile, whether and how to modify the initial treatment regimen (especially in patients with protracted neutropenia), and how long to continue antimicrobial therapy-are still used today. This review describes how the treatment principles related to the management of fever and neutropenia have responded to changes in the patients at risk, the microbes responsible, and the tools for their treatment, while still being sustained over the arc of time.