Prognostic Integrated Image-Based Immune and Molecular Profiling in Early-Stage Endometrial Cancer

Optimum risk stratification in early-stage endometrial cancer (EC) combines clinicopathological factors and the molecular EC classification defined by The Cancer Genome Atlas (TCGA). It is unclear whether analysis of intratumoral immune infiltrate improves this. We developed a machine-learning image-based algorithm to quantify density of CD8+ and CD103+ immune cells in tumor epithelium and stroma in 695 stage I endometrioid ECs from the PORTEC-1&-2 trials. The relationship between immune cell density and clinicopathological/molecular factors was analyzed by hierarchical clustering and multiple regression. The prognostic value of immune infiltrate by cell type and location was analyzed by univariable and multivariable Cox regression, incorporating the molecular EC classification. Tumor-infiltrating immune cell density varied substantially between cases, and more modestly by immune cell type and location. Clustering revealed three groups with high, intermediate and low densities, with highly significant variation in the proportion of molecular EC subgroups between them. Univariable analysis revealed intraepithelial CD8+ cell density as the strongest predictor of EC recurrence; multivariable analysis confirmed this was independent of pathological factors and molecular subgroup. Exploratory analysis suggested this association was not uniform across molecular subgroups, but greatest in tumors with mutant p53 and absent in DNA mismatch repair deficient cancers. Thus, this work identified that quantification of intraepithelial CD8+ cells improved upon the prognostic utility of the molecular EC classification in early-stage EC

The Mental Vitality @ Work study: design of a randomized controlled trial on the effect of a workers' health surveillance mental module for nurses and allied health professionals

Employees in health care service are at high risk for developing mental health complaints. The effects of mental health complaints on work can have serious consequences for the quality of care provided by these workers. To help health service workers remain healthy and productive, preventive actions are necessary. A Workers' Health Surveillance (WHS) mental module may be an effective strategy to monitor and promote good (mental) health and work performance. The objective of this paper is to describe the design of a three arm cluster randomized controlled trial on the effectiveness of a WHS mental module for nurses and allied health professionals. Two strategies for this WHS mental module will be compared along with data from a control group. Additionally, the cost effectiveness of the approaches will be evaluated from a societal perspective. The study is designed as a cluster randomized controlled trial consisting of three arms (two intervention groups, 1 control group) with randomization at ward level. The study population consists of 86 departments in one Dutch academic medical center with a total of 1731 nurses and allied health professionals. At baseline, after three months and after six months of follow-up, outcomes will be assessed by online questionnaires. In both intervention arms, participants will complete a screening to detect problems in mental health and work functioning and receive feedback on their screening results. In cases of impairments in mental health or work functioning in the first intervention arm, a consultation with an occupational physician will be offered. The second intervention arm offers a choice of self-help e-mental health interventions, which will be tailored based on each individual's mental health state and work functioning. The primary outcomes will be help-seeking behavior and work functioning. Secondary outcomes will be mental health and wellbeing. Furthermore, cost-effectiveness in both intervention arms will be assessed, and a process evaluation will be performed. When it is proven effective compared to a control group, a WHS mental module for nurses and allied health professionals could be implemented and used on a regular basis by occupational health services in hospitals to improve employees' mental health and work functioning. NTR278

Self-rated coping styles and registered sickness absence among nurses working in hospital care:A prospective 1-year cohort study

Background: Sickness absence is an important problem in healthcare that affects the quality of care. Sickness absence has been related to coping strategies. Problem-focused coping was shown to be associated with low sickness absence and emotion-focused coping with high sickness absence among postal workers. Objectives: This study investigated the relationship between coping styles and sickness absence in healthcare. Design: Prospective study linking self-rated coping styles at baseline with the number of episodes of sickness absence during one year of follow-up. Setting: Somatic hospital employing 1153 persons. Participants: Convenience sample of 566 female nurses working in the hospital's clinical wards and outpatient clinic. Of these, 386 (68%) nurses had complete data for analysis. Methods: The nurses completed a questionnaire at baseline with items on health, work, and coping styles. Three styles of coping were defined: problem-solving coping (i.e., looking for opportunities to solve a problem), social coping (i.e., seeking social support in solving a problem), and palliative avoidant coping (i.e., seeking distraction and avoiding problems). Sickness absence data were retrieved from the hospital's register in the following year. The association between the coping styles and the number of both short (1-7 days) and long (>7 days) episodes of sickness absence was assessed by Poisson regression analyses with age, work hours per week, general health, mental health, and effort-reward [ER] ratio as covariates. Results: Problem-solving coping was negatively associated with the number of long episodes of sickness absence (rate ratio [RR] = 0.78, 95% confidence interval [CI] = 0.64-0.95). Social coping was negatively associated with the number of both short episodes (RR = 0.88,95% Cl = 0.79-0.97) and long episodes (RR = 0.79,95% Cl = 0.64-0.97) of sickness absence. After adjustment for the ER-ratio, the associations of coping with short episodes of sickness absence strengthened and associations with long episodes weakened, however, significance was lost for both types of sickness absence. Palliative avoidant coping was not associated with sickness absence among female hospital nurses. Conclusion: Problem-solving coping and social coping styles were associated with less sickness absence among female nurses working in hospital care. Nurse managers may use this knowledge and reduce sickness absence and understaffing by stimulating problem-solving strategies and social support within nursing teams. (C) 2011 Elsevier Ltd. All rights reserved

Consumer Mobility and the Communication of Difference: Reflecting on Cross-Border Shopping Practices and Experiences in the Dutch-German Borderland

Contains fulltext : 87070.pdf (publisher's version ) (Closed access) Contains fulltext : 87070_1.pdf (author's version ) (Open Access)16 p

Prognosetafel AG2016

De levensverwachting in Nederland is de laatste 50 jaar gestaag toegenomen. Deze tendens heeft grote impact op de samenleving. Voor pensioenfondsen en levensverzekeraars is het van belang continu inzicht te hebben in deze ontwikkeling om gedane beloften na te kunnen komen. Het Koninklijk Actuarieel Genootschap (AG) ziet het als haar rol de financiële sector inzicht te verschaffen in deze ontwikkelingen met behulp van prognosetafels. De nieuwe Prognosetafel AG2016 is gebaseerd op hetzelfde model dat de basis vormde voor de Prognosetafel AG2014. Het is een volledig transparant model met een beperkt aantal parameters zodat het goed uitlegbaar en exact na te bouwen is. Dit sluit aan bij de doelstelling van het AG om kennis beschikbaar én toepasbaar te maken voor de financiële sector. De belangrijkste kenmerken van de AG2016 prognose staan hieronder vermeld: •De Prognosetafel AG2016 is gebaseerd op een stochastisch model, waardoor het voor pensioenfondsen en levensverzekeraars mogelijk is ook de onzekerheid van de prognose in te schatten. Dit is belangrijk bij de prijsstelling van financiële derivaten en de bepaling van aan te houden buffers in relatie tot sterfteonzekerheid. •De Prognosetafel AG2016 is, naast op de historische sterfte in Nederland, ook gebaseerd op de sterfte in een aantal Europese landen met een vergelijkbare welvaart. Deze combinatie van data zorgt voor een stabiel model dat minder gevoelig is voor incidentele Nederlandse afwijkingen in een bepaald jaar. •Met de Prognosetafel AG2016 kan een inschatting van de sterfte worden gegeven die ver in de toekomst ligt. Het is mogelijk iemand die in 2016 wordt geboren zijn hele leven te volgen, omdat voor elke toekomstige leeftijd de overlevingskans kan worden ingeschat. De Prognosetafel AG2014 werd voor mannen en vrouwen apart bepaald. Bij de prognosetafel van 2016 wordt gebruik gemaakt van correlatie tussen de sterfteontwikkeling van mannen en vrouwen. In deze publicatie gaat de AG-Commissie Sterfte Onderzoek (CSO) nader in op de totstandkoming en uitkomsten van de Prognosetafel AG2016