Measuring Health: A Multivariate Approach

We examined the health status of 171 countries by employing factor analysis on various national health indicators for the period 2000–2005 to construct two new measures on health. The first measure is based on the health of individuals and the second on (the quality of) the health services. Our measures differ substantially from indicators used in previous studies on health and also lead to different rankings of countries. As rankings are not that informative without further information, we analyzed the distance between each country and the sample mean. Differences between countries are much more pronounced for our measure on health services than for our measure on the health of individuals. Using cluster analysis, we classified the countries in six homogenous groups

OA06.06 Impact of Systemic Anti-cancer Treatments on Outcomes of COVID-19 in Patients with Thoracic Cancers: CCC19 Registry Analysis

Introduction: Patients with thoracic cancers (TC) have one of the highest rates of mortality among patients with cancer and COVID-19. Data evaluating the impact of recent anti-cancer therapies on COVID-19 outcomes in patients with TC are confined to small heterogenous retrospective studies, with limited follow-up data. We analyzed data from the COVID-19 and Cancer Consortium (CCC19) (NCT04354701) to examine the impact of recent systemic therapies on the clinical outcomes of COVID-19 in patients with TC. Methods: The CCC19 registry was queried for adult patients with TC and lab-confirmed SARS-CoV-2 infection. Only patients with data quality scores of 0-4 were included in the analysis. The primary outcome was 30-day all-cause mortality. Secondary outcomes were need for oxygen supplementation, hospitalization, ICU admission, and mechanical ventilation. The outcomes were further stratified by demographics, smoking history, ECOG PS (0, 1, \u3e2), cancer status (remission, responding/stable, progressing) and type of systemic treatment \u3c3 months prior to COVID-19 (chemotherapy with or without immunotherapy, chemotherapy plus radiation, immunotherapy alone or targeted therapy). Results: From January 2020 to December 2021, 900 patients with thoracic cancer met the inclusion criteria. The median age was 70 years (IQR 62-77), 53% were female, 79% were former or current tobacco users, 56% of patients had ECOG PS of 0 or 1, and 34% of patients had active but stable or responding cancer. Fifty-three percent (N=477) of patients received at least one anti-cancer systemic therapy \u3c3 months prior to COVID-19 diagnosis. Chemotherapy with or without immunotherapy was the most prevalent treatment exposure (51%; N=242). After a median follow-up of 70 days (IQR 28-180), 30-day all-cause mortality was similar in patients who received any systemic cancer treatment versus no cancer treatment (23% and 22% respectively). Patients treated with immunotherapy and targeted therapy had the lowest mortality (15% and 18% respectively), the majority of whom were treated with palliative intent. Similar trends were also noted with secondary outcomes (Table 1). Conclusions: We report one of the largest studies evaluating the clinical outcomes of COVID-19 in the context of recent systemic anti-cancer treatments for TC. While continued caution is required when utilizing systemic treatments, delays in treatment may not be justified. The study provides reassuring data that patients receiving immunotherapy or targeted therapy even in the context of palliative treatment appear to have a lower risk for all-cause COVID-19 mortality. Further analysis exploring the prognostic factors associated with poor outcomes in patients with chemoradiation is planned

Resilient employees are creative employees, when the workplace forces them to be

With a basis in conservation of resources theory, this article considers the connection between employees' resilience and disruptive creative behaviour-conceptualized herein as the extent to which they generate radically new ideas for organizational improvement-as well as how this connection might be invigorated by resource-draining work conditions that stem from excessive workloads and unfavourable decision-making processes. Data collected through a survey administered to employees in an organization that operates in the distribution sector reveal that employees' resilience levels spur their disruptive creative behaviour, and this process is more prominent among employees who believe they have insufficient time to complete their work tasks (i.e., suffer from high work overload) and operate in organizational climates marked by high rigidity or dysfunctional politics. The findings accordingly inform organizational practitioners that the allocation of employees' personal resource bases to disruptive creative behaviours might be particularly useful among employees who face substantial adversity in their organizational functioning.info:eu-repo/semantics/acceptedVersio

Identifying Unique Neighborhood Characteristics to Guide Health Planning for Stroke and Heart Attack: Fuzzy Cluster and Discriminant Analyses Approaches

Socioeconomic, demographic, and geographic factors are known determinants of stroke and myocardial infarction (MI) risk. Clustering of these factors in neighborhoods needs to be taken into consideration during planning, prioritization and implementation of health programs intended to reduce disparities. Given the complex and multidimensional nature of these factors, multivariate methods are needed to identify neighborhood clusters of these determinants so as to better understand the unique neighborhood profiles. This information is critical for evidence-based health planning and service provision. Therefore, this study used a robust multivariate approach to classify neighborhoods and identify their socio-demographic characteristics so as to provide information for evidence-based neighborhood health planning for stroke and MI.The study was performed in East Tennessee Appalachia, an area with one of the highest stroke and MI risks in USA. Robust principal component analysis was performed on neighborhood (census tract) socioeconomic and demographic characteristics, obtained from the US Census, to reduce the dimensionality and influence of outliers in the data. Fuzzy cluster analysis was used to classify neighborhoods into Peer Neighborhoods (PNs) based on their socioeconomic and demographic characteristics. Nearest neighbor discriminant analysis and decision trees were used to validate PNs and determine the characteristics important for discrimination. Stroke and MI mortality risks were compared across PNs. Four distinct PNs were identified and their unique characteristics and potential health needs described. The highest risk of stroke and MI mortality tended to occur in less affluent PNs located in urban areas, while the suburban most affluent PNs had the lowest risk.Implementation of this multivariate strategy provides health planners useful information to better understand and effectively plan for the unique neighborhood health needs and is important in guiding resource allocation, service provision, and policy decisions to address neighborhood health disparities and improve population health

clusterMaker: a multi-algorithm clustering plugin for Cytoscape

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present <it>clusterMaker</it>, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. <it>clusterMaker </it>is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view), k-means, k-medoid, SCPS, AutoSOME, and native (Java) MCL.</p> <p>Results</p> <p>Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast <it>Saccharomyces cerevisiae</it>; and the cluster analysis of the vicinal oxygen chelate (VOC) enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section.</p> <p>Conclusions</p> <p>The Cytoscape plugin <it>clusterMaker </it>provides a number of clustering algorithms and visualizations that can be used independently or in combination for analysis and visualization of biological data sets, and for confirming or generating hypotheses about biological function. Several of these visualizations and algorithms are only available to Cytoscape users through the <it>clusterMaker </it>plugin. <it>clusterMaker </it>is available via the Cytoscape plugin manager.</p

Microallopatry Caused Strong Diversification in Buthus scorpions (Scorpiones: Buthidae) in the Atlas Mountains (NW Africa)

The immense biodiversity of the Atlas Mountains in North Africa might be the result of high rates of microallopatry caused by mountain barriers surpassing 4000 meters leading to patchy habitat distributions. We test the influence of geographic structures on the phylogenetic patterns among Buthus scorpions using mtDNA sequences. We sampled 91 individuals of the genus Buthus from 51 locations scattered around the Atlas Mountains (Antiatlas, High Atlas, Middle Atlas and Jebel Sahro). We sequenced 452 bp of the Cytochrome Oxidase I gene which proved to be highly variable within and among Buthus species. Our phylogenetic analysis yielded 12 distinct genetic groups one of which comprised three subgroups mostly in accordance with the orographic structure of the mountain systems. Main clades overlap with each other, while subclades are distributed parapatrically. Geographic structures likely acted as long-term barriers among populations causing restriction of gene flow and allowing for strong genetic differentiation. Thus, genetic structure and geographical distribution of genetic (sub)clusters follow the classical theory of allopatric differentiation where distinct groups evolve without range overlap until reproductive isolation and ecological differentiation has built up. Philopatry and low dispersal ability of Buthus scorpions are the likely causes for the observed strong genetic differentiation at this small geographic scale