Rates of inclusion of teenagers and young adults in England into National Cancer Research Network clinical trials: Report from the National Cancer Research Institute (NCRI) Teenage and Young Adult Clinical Studies Development Group

Poor inclusion rates into clinical trials for teenagers and young adults (TYA; aged 13–24 years) have been assumed but not systematically investigated in England. We analysed accrual rates (AR) from 1 April 2005 up to 31 March 2007 to National Cancer Research Network (NCRN) Phase III trials for the commonest tumour types occurring in TYA and children: leukaemia, lymphoma, brain and central nervous system, bone sarcomas and male germ cell tumours. AR for 2005–2007 were 43.2% for patients aged 10–14 years, 25.2% for patients aged 15–19 years, and 13.1% for patients aged 20–24 years in the tumour types analysed. Compared with accrual from 1 April 2005 to 31 March 2006, AR between 1 April 2006 and 31 March 2007 increased for those aged 10–14 and 15–19 years, but fell for those aged 20–24 years. AR varied considerably among cancer types. Despite four trials being available, patients over 16 years with central nervous system tumours were not recruited. Rates of participation in clinical trials in England from 2005 to 2007 were much lower for TYA older than 15 years compared with children and younger teenagers. The variations in open trials, trial age eligibility criteria and extent of trial activation in treatment centres in part explain this observation. Other possible influences, such as difficulties associated with the consent of TYA require further evaluation. Closer dialogue between those involved in planning and running trials for children and for adults is necessary to improve trial availability and recruitment. Further research is required to identify trends in trial availability and accrual for those tumours constituting the remaining 26% of TYA cancers

Single-cell immune profiling reveals markers of emergency myelopoiesis that distinguish severe from mild respiratory syncytial virus disease in infants

Whereas most infants infected with respiratory syncytial virus (RSV) show no or only mild symptoms, an estimated 3 million children under five are hospitalized annually due to RSV disease. This study aimed to investigate biological mechanisms and associated biomarkers underlying RSV disease heterogeneity in young infants, enabling the potential to objectively categorize RSV-infected infants according to their medical needs. Immunophenotypic and functional profiling demonstrated the emergence of immature and progenitor-like neutrophils, proliferative monocytes (HLA-DRLow, Ki67+), impaired antigen-presenting function, downregulation of T cell response and low abundance of HLA-DRLow B cells in severe RSV disease. HLA-DRLow monocytes were found as a hallmark of RSV-infected infants requiring hospitalization. Complementary transcriptomics identified genes associated with disease severity and pointed to the emergency myelopoiesis response. These results shed new light on mechanisms underlying the pathogenesis and development of severe RSV disease and identified potential new candidate biomarkers for patient stratification

T cells, more than antibodies, may prevent symptoms developing from respiratory syncytial virus infections in older adults

Introduction: The immune mechanisms supporting partial protection from reinfection and disease by the respiratory syncytial virus (RSV) have not been fully characterized. In older adults, symptoms are typically mild but can be serious in patients with comorbidities when the infection extends to the lower respiratory tract. Methods: This study formed part of the RESCEU older-adults prospective-cohort study in Northern Europe (2017–2019; NCT03621930) in which a thousand participants were followed over an RSV season. Peripheral-blood samples (taken pre-season, post-season, during illness and convalescence) were analyzed from participants who (i) had a symptomatic acute respiratory tract infection by RSV (RSV-ARTI; N=35) or (ii) asymptomatic RSV infection (RSV-Asymptomatic; N=16). These analyses included evaluations of antibody (Fc-mediated–) functional features and cell-mediated immunity, in which univariate and machine-learning (ML) models were used to explore differences between groups. Results: Pre–RSV-season peripheral-blood biomarkers were predictive of symptomatic RSV infection. T-cell data were more predictive than functional antibody data (area under receiver operating characteristic curve [AUROC] for the models were 99% and 76%, respectively). The pre-RSV season T-cell phenotypes which were selected by the ML modelling and which were more frequent in RSV-Asymptomatic group than in the RSV-ARTI group, coincided with prominent phenotypes identified during convalescence from RSV-ARTI (e.g., IFN-γ+, TNF-α+ and CD40L+ for CD4+, and IFN-γ+ and 4-1BB+ for CD8+). Conclusion: The evaluation and statistical modelling of numerous immunological parameters over the RSV season suggests a primary role of cellular immunity in preventing symptomatic RSV infections in older adults

Targeted metagenomics reveals association between severity and pathogen co-detection in infants with respiratory syncytial virus

Respiratory syncytial virus (RSV) is the leading cause of hospitalisation for respiratory infection in young children. RSV disease severity is known to be age-dependent and highest in young infants, but other correlates of severity, particularly the presence of additional respiratory pathogens, are less well understood. In this study, nasopharyngeal swabs were collected from two cohorts of RSV-positive infants 100 pathogens, including all common respiratory viruses and bacteria, from samples collected from 433 infants, that burden of additional viruses is common (111/433, 26%) but only modestly correlates with RSV disease severity. In contrast, there is strong evidence in both cohorts and across age groups that presence of Haemophilus bacteria (194/433, 45%) is associated with higher severity, including much higher rates of hospitalisation (odds ratio 4.25, 95% CI 2.03–9.31). There is no evidence for association between higher severity and other detected bacteria, and no difference in severity between RSV genotypes. Our findings reveal the genomic diversity of additional pathogens during RSV infection in infants, and provide an evidence base for future causal investigations of the impact of co-infection on RSV disease severity

Protein kinase A regulatory subunit distribution in medulloblastoma

<p>Abstract</p> <p>Background</p> <p>Previous studies showed a differential distribution of the four regulatory subunits of cAMP-dependent protein kinases inside the brain, that changed in rodent gliomas: therefore, the distribution of these proteins inside the brain can give information on the functional state of the cells. Our goal was to examine human brain tumors to provide evidence for a differential distribution of protein kinase A in different tumors.</p> <p>Methods</p> <p>The distribution of detergent insoluble regulatory (R1 and R2) and catalytic subunits of cAMP dependent kinases was examined in pediatric brain tumors by immunohistochemistry and fluorescent cAMP analogues binding.</p> <p>Results</p> <p>R2 is organized in large single dots in medulloblastomas, while it has a different appearance in other tumors. Fluorescent cAMP labelling was observed only in medulloblastoma.</p> <p>Conclusions</p> <p>A different distribution of cAMP dependent protein kinases has been observed in medulloblastoma.</p

Results of NOPHO ALL2008 treatment for patients aged 1-45 years with acute lymphoblastic leukemia

Adults with acute lymphoblastic leukemia (ALL) do worse than children. From 7/2008 to 12/2014, Nordic and Baltic centers treated 1509 consecutive patients aged 1-45 years with Philadelphia chromosome-negative ALL according to the NOPHO ALL2008 without cranial irradiation. Overall, 1022 patients were of age 1-9 years (A), 266 were 10-17 years (B) and 221 were 18-45 years (C). Sixteen patients (three adults) died during induction. All others achieved remission after induction or 1-3 intensive blocks. Subsequently, 45 patients (12 adults) died, 122 patients relapsed (32 adults) with a median time to relapse of 1.6 years and 13 (no adult) developed a second malignancy. Median follow-up time was 4.6 years. Among the three age groups, older patients more often had higher risk ALL due to T-ALL (32%/25%/9%, PPeer reviewe

Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care

BACKGROUND: There is a paucity of prognostic models for COVID-19 that are usable for in-office patient assessment in general practice (GP). OBJECTIVES: To develop and validate a risk prediction model for hospital admission with readily available predictors. METHODS: A retrospective cohort study linking GP records from 8 COVID-19 centres and 55 general practices in the Netherlands to hospital admission records. The development cohort spanned March to June 2020, the validation cohort March to June 2021. The primary outcome was hospital admission within 14 days. We used geographic leave-region-out cross-validation in the development cohort and temporal validation in the validation cohort. RESULTS: In the development cohort, 4,806 adult patients with COVID-19 consulted their GP (median age 56, 56% female); in the validation cohort 830 patients did (median age 56, 52% female). In the development and validation cohort respectively, 292 (6.1%) and 126 (15.2%) were admitted to the hospital within 14 days, respectively. A logistic regression model based on sex, smoking, symptoms, vital signs and comorbidities predicted hospital admission with a c-index of 0.84 (95% CI 0.83 to 0.86) at geographic cross-validation and 0.79 (95% CI 0.74 to 0.83) at temporal validation, and was reasonably well calibrated (intercept -0.08, 95% CI -0.98 to 0.52, slope 0.89, 95% CI 0.71 to 1.07 at geographic cross-validation and intercept 0.02, 95% CI -0.21 to 0.24, slope 0.82, 95% CI 0.64 to 1.00 at temporal validation). CONCLUSION: We derived a risk model using readily available variables at GP assessment to predict hospital admission for COVID-19. It performed accurately across regions and waves. Further validation on cohorts with acquired immunity and newer SARS-CoV-2 variants is recommended