Cost-effectiveness analysis in R using a multi-state modelling survival analysis framework: a tutorial

This tutorial provides a step-by-step guide to performing cost-effectiveness analysis using a multi-state modelling approach. Alongside the tutorial we provide easy-to-use functions in the statistics package R. We argue this multi-state modelling approach using a package such as R has advantages over approaches where models are built in a spreadsheet package. In particular, using a syntax-based approach means there is a written record of what was done and the calculations are transparent. Reproducing the analysis is straightforward as the syntax just needs to be run again. The approach can be thought of as an alternative way to build a Markov decision analytic model, which also has the option to use a state-arrival extended approach if the Markov property does not hold. In the state-arrival extended multi-state model a covariate that represents patients’ history is included allowing the Markov property to be tested. We illustrate the building of multi-state survival models, making predictions from the models and assessing fits. We then proceed to perform a cost-effectiveness analysis including deterministic and probabilistic sensitivity analyses. Finally, we show how to create two common methods of visualising the results, namely cost-effectiveness planes and cost-effectiveness acceptability curves. The analysis is implemented entirely within R. It is based on adaptions to functions in the existing R package mstate, to accommodate parametric multi-state modelling which facilitates extrapolation of survival curves

Evaluating aryl esters as bench-stable C(1)-ammonium enolate precursors in catalytic, enantioselective Michael addition-lactonisations

We thank the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) ERC Grant Agreement no. 279850 (CMY, JET). ADS thanks the Royal Society for a Wolfson Merit Award. We also thank the EPSRC UK National Mass Spectrometry Facility at Swansea University. The data underpinning this research can be found at DOI: https://doi.org/10.17630/cb133261-b58e-4d72-b380-c877c993dc5dAn evaluation of a range of aryl, alkyl and vinyl esters as prospective C(1)-ammonium enolate precursors in enantioselective Michael addition-lactonisation processes with (E)-trifluoromethylenones using isothiourea catalysis is reported. Electron deficient aryl esters are required for reactivity, with 2,4,6-trichlorophenyl esters providing optimal product yields. Catalyst screening showed that tetramisole was the most effective isothiourea catalyst, giving the desired dihydropyranone product in excellent yield and stereoselectivity (up to 90:10 dr and 98:2 er). The scope and limitations of this process have been evaluated, with a range of diester products being generated after ring-opening with MeOH to give stereodefined dihydropyranones with excellent stereocontrol (10 examples, typically ~90:10 dr and >95:5 er).PostprintPeer reviewe

Models of endometriosis and their utility in studying progression to ovarian clear cell carcinoma.

Endometriosis is a common benign gynaecological condition affecting at least 10% of women of childbearing age and is characterized by pain--frequently debilitating. Although the exact prevalence is unknown, the economic burden is substantial (∼$50 billion a year in the USA alone) and it is associated with considerable morbidity. The development of endometriosis is inextricably linked to the process of menstruation and thus the models that best recapitulate the human disease are in menstruating non-human primates. However, the use of these animals is ethically challenging and very expensive. A variety of models in laboratory animals have been developed and the most recent are based on generating menstrual-like endometrial tissue that can be transferred to a recipient animal. These models are genetically manipulable and facilitate precise mechanistic studies. In addition, these models can be used to study malignant transformation in epithelial ovarian carcinoma. Epidemiological and molecular evidence indicates that endometriosis is the most plausible precursor of both clear cell and endometrioid ovarian cancer (OCCA and OEA, respectively). While this progression is rare, understanding the underlying mechanisms of transformation may offer new strategies for prevention and therapy. Our ability to pursue this is highly dependent on improved animal models but the current transgenic models, which genetically modify the ovarian surface epithelium and oviduct, are poor models of ectopic endometrial tissue. In this review we describe the various models of endometriosis and discuss how they may be applicable to developing our mechanistic understanding of OCCA and OEA.CMK was funded by a grant from CRUK (A13095). Part of the research work disclosed in this publication is funded by the Strategic Educational Pathways Scholarship (Malta) to CB. The scholarship is part-financed by the European Union-European Social Fund (ESF) under Operational Programme II-Cohesion Policy 2007-2013, "Empowering People for More Jobs and a Better Quality of Life”. JDB is supported by CRUK (A15601).This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/path.465

The Link Between Health Insurance Coverage and Citizenship Among Immigrants: Bayesian Unit-Level Regression Modeling of Categorical Survey Data Observed with Measurement Error

Social scientists are interested in studying the impact that citizenship status has on health insurance coverage among immigrants in the United States. This can be done using data from the Survey of Income and Program Participation (SIPP); however, two primary challenges emerge. First, statistical models must account for the survey design in some fashion to reduce the risk of bias due to informative sampling. Second, it has been observed that survey respondents misreport citizenship status at nontrivial rates. This too can induce bias within a statistical model. Thus, we propose the use of a weighted pseudo-likelihood mixture of categorical distributions, where the mixture component is determined by the latent true response variable, in order to model the misreported data. We illustrate through an empirical simulation study that this approach can mitigate the two sources of bias attributable to the sample design and misreporting. Importantly, our misreporting model can be further used as a component in a deeper hierarchical model. With this in mind, we conduct an analysis of the relationship between health insurance coverage and citizenship status using data from the SIPP

Genetic diversity among five T4-like bacteriophages

BACKGROUND: Bacteriophages are an important repository of genetic diversity. As one of the major constituents of terrestrial biomass, they exert profound effects on the earth's ecology and microbial evolution by mediating horizontal gene transfer between bacteria and controlling their growth. Only limited genomic sequence data are currently available for phages but even this reveals an overwhelming diversity in their gene sequences and genomes. The contribution of the T4-like phages to this overall phage diversity is difficult to assess, since only a few examples of complete genome sequence exist for these phages. Our analysis of five T4-like genomes represents half of the known T4-like genomes in GenBank. RESULTS: Here, we have examined in detail the genetic diversity of the genomes of five relatives of bacteriophage T4: the Escherichia coli phages RB43, RB49 and RB69, the Aeromonas salmonicida phage 44RR2.8t (or 44RR) and the Aeromonas hydrophila phage Aeh1. Our data define a core set of conserved genes common to these genomes as well as hundreds of additional open reading frames (ORFs) that are nonconserved. Although some of these ORFs resemble known genes from bacterial hosts or other phages, most show no significant similarity to any known sequence in the databases. The five genomes analyzed here all have similarities in gene regulation to T4. Sequence motifs resembling T4 early and late consensus promoters were observed in all five genomes. In contrast, only two of these genomes, RB69 and 44RR, showed similarities to T4 middle-mode promoter sequences and to the T4 motA gene product required for their recognition. In addition, we observed that each phage differed in the number and assortment of putative genes encoding host-like metabolic enzymes, tRNA species, and homing endonucleases. CONCLUSION: Our observations suggest that evolution of the T4-like phages has drawn on a highly diverged pool of genes in the microbial world. The T4-like phages harbour a wealth of genetic material that has not been identified previously. The mechanisms by which these genes may have arisen may differ from those previously proposed for the evolution of other bacteriophage genomes

A Socio-Spatial Approach to Enable Inclusive Well-Being in Cities: A Case Study of Birmingham, UK

This article examines density and deprivation, the two important parameters that define health and well-being in cities. Discussions are drawn from a case study conducted in Birmingham in four neighborhoods characterized by their different population density and deprivation levels. Data were collected through questionnaires developed from a set of subjective well-being measures and built environment audits, based on the Irvine Minnesota Inventory that evaluates the quality of streets and walkability in neighborhoods. The inferences from the study support the need for linking health, planning, policy and design research and decision-making to the socio-spatial practices of people, impacting well-being at the everyday level. The findings provide a holistic approach health and well-being research and suggests a conceptual framework for inclusive well-being in cities, which signifies the role of social and spatial parameters in determining peoples’ health and well-being. The study also highlights the lack of interdisciplinary research in understanding the association between well-being and social and behavioral practices in diverse communities