Rethinking childhood ependymoma: a retrospective, multi-center analysis reveals poor long-term overall survival

Ependymoma is the third most common brain tumor in children, but there is a paucity of large studies with more than 10 years of follow-up examining the long-term survival and recurrence patterns of this disease. We conducted a retrospective chart review of 103 pediatric patients with WHO Grades II/III intracranial ependymoma, who were treated at Dana-Farber/Boston Children’s Cancer and Blood Disorders Center and Chicago’s Ann & Robert H. Lurie Children’s Hospital between 1985 and 2008, and an additional 360 ependymoma patients identified from the Surveillance Epidemiology and End Results (SEER) database. For the institutional cohort, we evaluated clinical and histopathological prognostic factors of overall survival (OS) and progression-free survival (PFS) using the log-rank test, and univariate and multivariate Cox proportional-hazards models. Overall survival rates were compared to those of the SEER cohort. Median follow-up time was 11 years. Ten-year OS and PFS were 50 ± 5% and 29 ± 5%, respectively. Findings were validated in the independent SEER cohort, with 10-year OS rates of 52 ± 3%. GTR and grade II pathology were associated with significantly improved OS. However, GTR was not curative for all children. Ten-year OS for patients treated with a GTR was 61 ± 7% and PFS was 36 ± 6%. Pathological examination confirmed most recurrent tumors to be ependymoma, and 74% occurred at the primary tumor site. Current treatment paradigms are not sufficient to provide long-term cure for children with ependymoma. Our findings highlight the urgent need to develop novel treatment approaches for this devastating disease. Electronic supplementary material The online version of this article (doi:10.1007/s11060-017-2568-8) contains supplementary material, which is available to authorized users

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Large-scale sequencing identifies multiple genes and rare variants associated with Crohn’s disease susceptibility

peer reviewe

Table of Contents

1. Trafficking of hematopoietic stem cells during embryogenesis and fetal development.................2 1.1. HSC migration during the embryonic period.............................................2 1. From the extraembryonic mesoderm to the embryo proper...............................

Predictors of Age of Diagnosis and Survival of Alzheimer’s Disease in Down Syndrome

BACKGROUND: People with Down syndrome (DS) are an ultra-high risk population for Alzheimer's disease (AD). Understanding the factors associated with age of onset and survival in this population could highlight factors associated with modulation of the amyloid cascade. OBJECTIVE: This study aimed to establish the typical age at diagnosis and survival associated with AD in DS and the risk factors associated with these. METHODS: Data was obtained from the Aging with Down Syndrome and Intellectual Disabilities (ADSID) research database, consisting of data extracted from clinical records of patients seen by Community Intellectual Disability Services (CIDS) in England. Survival times when considering different risk factors were calculated. RESULTS: The mean age of diagnosis was 55.80 years, SD 6.29. Median survival time after diagnosis was 3.78 years, and median age at death was approximately 60 years. Survival time was associated with age of diagnosis, severity of intellectual disability, living status, anti-dementia medication status, and history of epilepsy. Age at diagnosis and treatment status remained predictive of survival time following adjustment. CONCLUSION: This study provides the best estimate of survival in dementia within the DS population to date, and is in keeping with previous estimates from smaller studies in the DS population. This study provides important estimates and insights into possible predictors of survival and age of diagnosis of AD in adults with DS, which will inform selection of participants for treatment trials in the future

Eléments de réflexion sur l’introduction d’un module P dans le modèle STICS

National audienc

High-resolution population estimation using household survey data and building footprints.

The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with an R2 value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses

High-resolution population estimation using household survey data and building footprints

The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with an R2 value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses.</p