Auf dem Weg zur individualisierten Medizin - Grid-basierte Services für die EPA der Zukunft.

Personalized Medicine is of paramount interest for many areas in Medical Informatics. Therefore genotype data as well a phenotype data about patients have to be available. This data will be stored in Electronic Health Records or – patient controlled - in Personal Health Records. As the amount of (raw) data is rising continuously, methods for a secure data administration have to be found. Grid Services offer data storage, can support data retrieval and the presentation of the data. The basic security services could be provided by the German health professional infrastructure, but there are many security challenges to be faced

Multi-Locus Sequence Typing of Bartonella henselae Isolates from Three Continents Reveals Hypervirulent and Feline-Associated Clones

Bartonella henselae is a zoonotic pathogen and the causative agent of cat scratch disease and a variety of other disease manifestations in humans. Previous investigations have suggested that a limited subset of B. henselae isolates may be associated with human disease. In the present study, 182 human and feline B. henselae isolates from Europe, North America and Australia were analysed by multi-locus sequence typing (MLST) to detect any associations between sequence type (ST), host species and geographical distribution of the isolates. A total of 14 sequence types were detected, but over 66% (16/24) of the isolates recovered from human disease corresponded to a single genotype, ST1, and this type was detected in all three continents. In contrast, 27.2% (43/158) of the feline isolates corresponded to ST7, but this ST was not recovered from humans and was restricted to Europe. The difference in host association of STs 1 (human) and 7 (feline) was statistically significant (P≤0.001). eBURST analysis assigned the 14 STs to three clonal lineages, which contained two or more STs, and a singleton comprising ST7. These groups were broadly consistent with a neighbour-joining tree, although splits decomposition analysis was indicative of a history of recombination. These data indicate that B. henselae lineages differ in their virulence properties for humans and contribute to a better understanding of the population structure of B. henselae

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer