Depression and anxiety in prostate cancer: a systematic review and meta-analysis of prevalence rates

ObjectivesTo systematically review the literature pertaining to the prevalence of depression and anxiety in patients with prostate cancer as a function of treatment stage.DesignSystematic review and meta-analysis.Participants4494 patients with prostate cancer from primary research investigations.Primary outcome measureThe prevalence of clinical depression and anxiety in patients with prostate cancer as a function of treatment stage.ResultsWe identified 27 full journal articles that met the inclusion criteria for entry into the meta-analysis resulting in a pooled sample size of 4494 patients. The meta-analysis of prevalence rates identified pretreatment, on-treatment and post-treatment depression prevalences of 17.27% (95% CI 15.06% to 19.72%), 14.70% (95% CI 11.92% to 17.99%) and 18.44% (95% CI 15.18% to 22.22%), respectively. Pretreatment, on-treatment and post-treatment anxiety prevalences were 27.04% (95% CI 24.26% to 30.01%), 15.09% (95% CI 12.15% to 18.60%) and 18.49% (95% CI 13.81% to 24.31%), respectively.ConclusionsOur findings suggest that the prevalence of depression and anxiety in men with prostate cancer, across the treatment spectrum, is relatively high. In light of the growing emphasis placed on cancer survivorship, we consider that further research within this area is warranted to ensure that psychological distress in patients with prostate cancer is not underdiagnosed and undertreated

Developing digital interventions: a methodological guide.

Digital interventions are becoming an increasingly popular method of delivering healthcare as they enable and promote patient self-management. This paper provides a methodological guide to the processes involved in developing effective digital interventions, detailing how to plan and develop such interventions to avoid common pitfalls. It demonstrates the need for mixed qualitative and quantitative methods in order to develop digital interventions which are effective, feasible, and acceptable to users and stakeholders

Topological structures in the equities market network

We present a new method for articulating scale-dependent topological descriptions of the network structure inherent in many complex systems. The technique is based on "Partition Decoupled Null Models,'' a new class of null models that incorporate the interaction of clustered partitions into a random model and generalize the Gaussian ensemble. As an application we analyze a correlation matrix derived from four years of close prices of equities in the NYSE and NASDAQ. In this example we expose (1) a natural structure composed of two interacting partitions of the market that both agrees with and generalizes standard notions of scale (eg., sector and industry) and (2) structure in the first partition that is a topological manifestation of a well-known pattern of capital flow called "sector rotation.'' Our approach gives rise to a natural form of multiresolution analysis of the underlying time series that naturally decomposes the basic data in terms of the effects of the different scales at which it clusters. The equities market is a prototypical complex system and we expect that our approach will be of use in understanding a broad class of complex systems in which correlation structures are resident.Comment: 17 pages, 4 figures, 3 table

Clustering in Complex Directed Networks

Many empirical networks display an inherent tendency to cluster, i.e. to form circles of connected nodes. This feature is typically measured by the clustering coefficient (CC). The CC, originally introduced for binary, undirected graphs, has been recently generalized to weighted, undirected networks. Here we extend the CC to the case of (binary and weighted) directed networks and we compute its expected value for random graphs. We distinguish between CCs that count all directed triangles in the graph (independently of the direction of their edges) and CCs that only consider particular types of directed triangles (e.g., cycles). The main concepts are illustrated by employing empirical data on world-trade flows

A crossing probability for critical percolation in two dimensions

Langlands et al. considered two crossing probabilities, pi_h and pi_{hv}, in their extensive numerical investigations of critical percolation in two dimensions. Cardy was able to find the exact form of pi_h by treating it as a correlation function of boundary operators in the Q goes to 1 limit of the Q state Potts model. We extend his results to find an analogous formula for pi_{hv} which compares very well with the numerical results.Comment: 8 pages, Latex2e, 1 figure, uuencoded compressed tar file, (1 typo changed

Epidemics and percolation in small-world networks

We study some simple models of disease transmission on small-world networks, in which either the probability of infection by a disease or the probability of its transmission is varied, or both. The resulting models display epidemic behavior when the infection or transmission probability rises above the threshold for site or bond percolation on the network, and we give exact solutions for the position of this threshold in a variety of cases. We confirm our analytic results by numerical simulation.Comment: 6 pages, including 3 postscript figure

The orientation-preserving diffeomorphism group of S^2 deforms to SO(3) smoothly

Smale proved that the orientation-preserving diffeomorphism group of S^2 has a continuous strong deformation retraction to SO(3). In this paper, we construct such a strong deformation retraction which is diffeologically smooth.Comment: 16 page

A preliminary synthesis of major scientific results during the SALSA program

The objective of this paper is to provide an overview of the primary results of the Semi-Arid Land-Surface-Atmosphere (SALSA) Program in the context of improvements to our overall understanding of hydrologic, ecologic, and atmospheric processes and their interactions in a semi-arid basin. The major findings and future research needs associated with the different core components of the program are emphasized. First, remote-sensing investigations are discussed, especially those directed toward taking full advantage of the capabilities of the new generation of satellites (ERS2/ATSR2, VEGETATION, LANDSAT7, NASA-EOS). Second, we discuss parameterization of the water and energy fluxes in arid and semi-arid regions, with special emphasis on methods to aggregate these fluxes from patch scale to grid scale. Third, we address the issues related to grassland ecology and competition for water between native grass and invasive mesquite species. Fourth, findings related to the interactions between surface water, ground water, and vegetation in a semi-arid riparian system are discussed. Next, an assessment of land use and land cover change over the entire basin over a quarter century is reviewed. Finally, unsolved issues and the needs for further research are outlined