High body mass index and pre-existing autoimmune disease are associated with an increased risk of immune-related adverse events in cancer patients treated with PD-(L)1 inhibitors across different solid tumors

BACKGROUND\nPATIENTS AND METHODS\nRESULTS\nCONCLUSION\nTreatment with anti-PD-(L)1 antibodies, approved for several oncology indications, can lead to immune-related adverse events (irAEs). We aimed to investigate risk factors associated with an increased reporting of irAEs in patients treated with PD-(L)1 inhibitors approved for solid tumor indications.\nA retrospective review was performed of individual data from patients in phase II/III registrational studies for PD-(L)1 inhibitors in solid tumors. Data on baseline characteristics and adverse events were extracted. Univariate and multivariable logistic regression models were used to identify risk factors.\nIn total, 5123 patients were included from 15 studies reporting on the use of four PD-(L)1 inhibitors for five solid tumor indications. Univariate analysis suggested that type of study drug (P 2 [odds ratio (OR) 1.5, 95% confidence interval (CI) 1.2-1.8] in comparison to normal BMI, having an autoimmune disease at baseline (OR 1.8, 95% CI 1.1-2.7), and use of a PD-L1 inhibitor (OR 1.6, 95% CI 1.2-2.0). The latter finding is probably biased due to the selection of the studies in the dataset with complete information on baseline characteristics.\nThis study was conducted using a large dataset of individual patient data from clinical trials comprising multiple solid tumor indications. We demonstrated that patients with obesity and concurrent autoimmune disease were at increased risk of developing irAEs.FWN – Publicaties zonder aanstelling Universiteit Leide

Seashore disturbance and management of the clonal Arctophila fulva : Modelling patch dynamics

Question: What is the population viability of a critically endangered seashore grass, Arctophila fulva var. pendulina. Location: Liminka Bay, W Finland, 25°21'70 N, 64°51'90 E. Methods: We constructed a matrix population model based on colonization and disappearance events and patch size changes of A. fulva. Patches were divided into hydric and nonhydric zones according to proximity to the seashore and intensity of disturbance. Perturbation analyses were carried out in order to identify transitions critical for population growth. Seed bank and seed germination studies provided background information for the model design. Results: A. fulva patches observed in the more disturbed hydric zone (closest to the sea) increased in number, as did the total number of patches. However, the number of patches in the less disturbed non-hydric zone decreased. Conclusions: Short-term dynamics of the A. fulva population at Liminka Bay seem to be determined by environmental fluctuations, which cause annual variation in transition rates between patch size classes. The long-term dynamics are probably governed by initiation of primary succession by isostatic land uplift. Increased disturbance at the water’s edge may promote persistence of A. fulva through reduced interspecific competition. Our results suggest that shoreline disturbance of the hydric zone is sufficient for maintaining a viable population. Competitive exclusion of A. fulva in the non-hydric zone may be delayed by management practices, such as mowing

Using job strain and organizational justice models to predict multiple forms of employee performance behaviours among Australian policing personnel

The overall purpose of this investigation was to examine the relationship between stress-related working conditions and three forms of employee performance behaviours: in-role behaviours, citizenship behaviours directed at other individuals and citizenship behaviours directed at the organization. The potentially stressful working conditions were based on the job strain model (incorporating job demands, job control and social support) as well as organizational justice theory. A sample of Australian-based police officers (n = 640) took part in this study and the data were collected via a mail-out survey. Multiple regression analyses were undertaken to assess both the strength and the nature of the relationships between the working conditions and employee performance and these analyses included tests for additive, interactional and curvilinear effects. The overall results indicated that a significant proportion of the explained variance in all three outcome measures was attributed to the additive effects of demand, control and support. The level of variance associated with the organizational justice dimensions was relatively small, although there were signs that specific dimensions of justice may provide unique insights into the relationship between job stressors and employee performance. The implications of these and other notable findings are discussed.<br /

Inter-observer variation in habitat survey data: investigating the consequences for professional practice

Knowledge of the extent and distribution of vegetation types is essential to underpin conservation assessments, land-use planning and management of wildlife populations (Hill et al. 2005; IEEM 2006; Morris and Thrivel 2009). Despite improvements in remote sensing of land cover, field survey remains an essential method for collection of data on the distribution of habitats and their floristic composition (IEEM 2006). Surveying of vegetation is recognised as a key skill required by ecologists and environmental managers (IEEM 2007, 2011), but studies of variability between surveyors have often revealed significant levels of disagreement in terms of the plant species and habitats recorded (e.g. Scott and Hallam 2002; Milberg et al. 2008; Stevens et al. 2004; Hearn et al. 2011). For example, a study using the National Vegetation Classification (NVC) in the UK found that pairwise spatial agreement between seven surveyors mapping vegetation at the same site averaged only 34% at the community level (Hearn et al. 2011). Comparisons between plant species lists drawn up by different surveyors working in the same plots typically show agreement in the range of 50%–70% for a variety of habitats (Scott and Hallam 2002). Professionals working in the environmental and conservation sectors are therefore aware of the potential for inter-observer variation and its impact on data quality, but there is a dearth of information on the extent to which it is perceived to be an impediment to good decision-making in practice (Cherrill 2013a). If inter-observer variation causes few problems, then the issue may be largely irrelevant in day-to-day practice. However, if inter-observer variation in interpretation of habitat types is a cause of disagreement and poor decision-making there may be a mandate to change training and/or survey methods.\ud The focus of the present study is inter-observer variation in habitat mapping using two of the standard classifications in the United Kingdom, namely the Phase 1 habitat classification (JNCC 1993) and the NVC (Rodwell 2006). Studies focussing on these methods have revealed spatial agreement between surveyors using the same method at the same site in the range of 25%–70% (Cherrill 2013a). These studies, however, were conducted either as bespoke academic research projects designed to directly assess observer variation (Cherrill and McClean 1995, 1999a, 1999b, 2000, 2001; Hearn et al. 2011) or as part of Quality Assurance procedures within a large-scale national monitoring programme designed to detect landscape change (Stevens et al. 2004). The extent to which these results are representative of inter-observer variation in professional practice involving environmental assessment and site management planning is therefore unknown (Cherrill 2013a). None the less, it can be hypothesised that errors made in identifying vegetation types in these spheres of activity may be frequent and that there may be consequences for conservation assessments, site management and planning decisions.\ud The present paper uses a questionnaire survey of members of the Chartered Institute of Ecology and Environmental Management (CIEEM) in the United Kingdom to address two main questions. First, how frequently are errors in data detected in reports describing the results of vegetation surveys? Second, what are the practical consequences of these errors? CIEEM has approximately five thousand members in the UK. They are ideally placed to respond to these questions being employed primarily in environmental consultancy, planning authorities, governmental environmental agencies, and non-governmental conservation organisations. The Phase 1 and NVC survey methods are used only in the UK, but similar approaches are used elsewhere (Alexander and Millington 2000). The wider applicability of the study is, therefore, to illustrate the need to extend academic studies of inter-observer variation to investigate their relevance to the day-to-day experiences of environmental professionals. The implications for further research and development of professional practice are discussed

Simulation of the hydrological impacts of climate change on a restored floodplain

Thirty UK Climate Projections 2009 (UKCP09) scenarios are simulated using a MIKE SHE/MIKE 11 model of a restored floodplain in eastern England. Annual precipitation exhibits uncertainty in direction of change. Extreme changes (10 and 90% probability) range between −27 and +30%. The central probability projects small declines ( < −4%). Wetter winters and drier summers predominate. Potential evapotranspiration increases for most scenarios (annual range of change: −41 to +2%). Declines in mean discharge predominate (range: −41 to +25%). Reductions of 11–17% are projected for the central probability. High and low flows, and the frequency of bankfull discharge exceedence reduce in most cases. Duration of winter high floodplain water tables declines. Summer water tables are on average at least 0.11 and 0.18 m lower for the 2050s and 2080s, respectively. Flood extent declines in most scenarios. Drier conditions will likely induce ecological responses including impacts on floodplain vegetation

Distribution maps of vegetation alliances in Europe

Aim The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

Vegetation-plot data and databases in Europe: an overview

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