Risk prediction of fever in neutropenia in children with cancer: a step towards individually tailored supportive therapy?

BACKGROUND: Fever in severe chemotherapy-induced neutropenia (FN) is the most frequent manifestation of a potentially lethal complication of current intensive chemotherapy regimens. This study aimed at establishing models predicting the risk of FN, and of FN with bacteremia, in pediatric cancer patients. METHODS: In a single-centre cohort study, characteristics potentially associated with FN and episodes of FN were retrospectively extracted from charts. Poisson regression accounting for chemotherapy exposure time was used for analysis. Prediction models were constructed based on a derivation set of two thirds of observations, and validated based on the remaining third of observations. RESULTS: In 360 pediatric cancer patients diagnosed and treated for a cumulative chemotherapy exposure time of 424 years, 629 FN were recorded (1.48 FN per patient per year, 95% confidence interval (CI), 1.37-1.61), 145 of them with bacteremia (23% of FN; 0.34; 0.29-0.40). More intensive chemotherapy, shorter time since diagnosis, bone marrow involvement, central venous access device (CVAD), and prior FN were significantly and independently associated with a higher risk to develop both FN and FN with bacteremia. The prediction models explained more than 30% of the respective risks. CONCLUSIONS: The two models predicting FN and FN with bacteremia were based on five easily accessible clinical variables. Before clinical application, they need to be validated by prospective studies.

Volcanic forcing for climate modeling: a new microphysics-based data set covering years 1600–present

As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now linked not only to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for general circulation model (GCM) and chemistry–climate model (CCM) simulations. This new volcanic forcing, covering the 1600–present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions show reasonable agreement with observations. By providing these new estimates of spatial distributions of shortwave and long-wave radiative perturbations, this volcanic forcing may help to better constrain the climate model responses to volcanic eruptions in the 1600–present period. The final data set consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.