Restraing Regulatory Capture? Anglo America, Crisis Politics and Trajectories of Change in Global Financial Governance

A growing number of respected commentators now argue that regulatory capture of public agencies and public policy by leading banks was one of the main causal factors behind the financial crisis of 2007–2009, resulting in a permissive regulatory environment. This regulatory environment placed a faith in banks own internal risk models, contributed to pro-cyclical behaviour and turned a blind eye to excessive risk taking. The article argues that a form of ‘multi-level regulatory capture’ characterized the global financial architecture prior to the crisis. Simultaneously, regulatory capture fed off, but also nourished the financial boom, in a fashion that mirrored the life cycle of the boom itself. Minimizing future financial booms and crises will require continuous, conscious and explicit efforts to restrain financial regulatory capture now and into the future. The article assesses the extent to which this has been achieved in current global financial governance reform efforts and highlights some of the persistent difficulties that will continue to hamper efforts to restrain regulatory capture. The evidence concerning the extent to which regulatory capture is being effectively restrained is somewhat mixed, and where it is happening it is largely unintentional and accidental. Recent reforms have overlooked the political causes of the crisis and have failed to focus explicitly or systematically on regulatory capture.

Surveillance for ocular hypertension: An evidence synthesis and economic evaluation

OBJECTIVES: To determine effective and efficient monitoring criteria for ocular hypertension [raised intraocular pressure (IOP)] through (i) identification and validation of glaucoma risk prediction models; and (ii) development of models to determine optimal surveillance pathways.

DESIGN: A discrete event simulation economic modelling evaluation. Data from systematic reviews of risk prediction models and agreement between tonometers, secondary analyses of existing datasets (to validate identified risk models and determine optimal monitoring criteria) and public preferences were used to structure and populate the economic model.

SETTING: Primary and secondary care.

PARTICIPANTS: Adults with ocular hypertension (IOP > 21 mmHg) and the public (surveillance preferences).

INTERVENTIONS: We compared five pathways: two based on National Institute for Health and Clinical Excellence (NICE) guidelines with monitoring interval and treatment depending on initial risk stratification, 'NICE intensive' (4-monthly to annual monitoring) and 'NICE conservative' (6-monthly to biennial monitoring); two pathways, differing in location (hospital and community), with monitoring biennially and treatment initiated for a ≥ 6% 5-year glaucoma risk; and a 'treat all' pathway involving treatment with a prostaglandin analogue if IOP > 21 mmHg and IOP measured annually in the community.

MAIN OUTCOME MEASURES: Glaucoma cases detected; tonometer agreement; public preferences; costs; willingness to pay and quality-adjusted life-years (QALYs).

RESULTS: The best available glaucoma risk prediction model estimated the 5-year risk based on age and ocular predictors (IOP, central corneal thickness, optic nerve damage and index of visual field status). Taking the average of two IOP readings, by tonometry, true change was detected at two years. Sizeable measurement variability was noted between tonometers. There was a general public preference for monitoring; good communication and understanding of the process predicted service value. 'Treat all' was the least costly and 'NICE intensive' the most costly pathway. Biennial monitoring reduced the number of cases of glaucoma conversion compared with a 'treat all' pathway and provided more QALYs, but the incremental cost-effectiveness ratio (ICER) was considerably more than £30,000. The 'NICE intensive' pathway also avoided glaucoma conversion, but NICE-based pathways were either dominated (more costly and less effective) by biennial hospital monitoring or had a ICERs > £30,000. Results were not sensitive to the risk threshold for initiating surveillance but were sensitive to the risk threshold for initiating treatment, NHS costs and treatment adherence.

LIMITATIONS: Optimal monitoring intervals were based on IOP data. There were insufficient data to determine the optimal frequency of measurement of the visual field or optic nerve head for identification of glaucoma. The economic modelling took a 20-year time horizon which may be insufficient to capture long-term benefits. Sensitivity analyses may not fully capture the uncertainty surrounding parameter estimates.

CONCLUSIONS: For confirmed ocular hypertension, findings suggest that there is no clear benefit from intensive monitoring. Consideration of the patient experience is important. A cohort study is recommended to provide data to refine the glaucoma risk prediction model, determine the optimum type and frequency of serial glaucoma tests and estimate costs and patient preferences for monitoring and treatment.

FUNDING: The National Institute for Health Research Health Technology Assessment Programme.

Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome

The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or

Refining Risk Estimates Using Models (Chapter 4)

In 2004 nineteen scientists from fourteen institutions in seven countries
collaborated in the landmark study described in chapter 2 (Thomas et al., 2004a). This chapter provides an overview of results of studies published subsequently and assesses how much, and why, new results differ from those of Thomas et al.
Some species distribution modeling (SDM) studies are directly comparable to the Thomas et al. estimates. Others using somewhat different methods nonetheless illuminate whether the original estimates were of the right order of magnitude. Climate similarity models (Williams et al., 2007; Williams and Jackson, 2007), biome, and vegetation dynamic models (Perry and Enright, 2006) have also been
applied in the context of climate change, providing interesting opportunities
for comparison and cross-validation with results from SDMs.
This chapter concludes with an assessment of whether the range of extinction risk estimates presented in 2004 can be narrowed, and whether the mean estimate should be revised upward or downward. To set the stage for these analyses, the chapter begins with brief reviews of advances in climate modeling and species modeling since 2004.

Combining global climate and regional landscape models to improve prediction of invasion risk

Aim
It is widely acknowledged that species distributions result from a variety of biotic and abiotic factors operating at different spatial scales. Here, we aimed to (1) determine the extent to which global climate niche models (CNMs) can be improved by the addition of fine-scale regional data; (2) examine climatic and environmental factors influencing the range of 15 invasive aquatic plant species; and (3) provide a case study for the use of such models in invasion management on an island.

Location
Global, with a case study of species invasions in Ireland.

Methods
Climate niche models of global extent (including climate only) and regional environmental niche models (with additional factors such as human influence, land use and soil characteristics) were generated using maxent for 15 invasive aquatic plants. The performance of these models within the invaded range of the study species in Ireland was assessed, and potential hotspots of invasion suitability were determined. Models were projected forward up to 2080 based on two climate scenarios.

Results
While climate variables are important in defining the global range of species, factors related to land use and nutrient level were of greater importance in regional projections. Global climatic models were significantly improved at the island scale by the addition of fine-scale environmental variables (area under the curve values increased by 0.18 and true skill statistic values by 0.36), and projected ranges decreased from an average of 86% to 36% of the island.

Main conclusions
Refining CNMs with regional data on land use, human influence and landscape may have a substantial impact on predictive capacity, providing greater value for prioritization of conservation management at subregional or local scales.

GEP analysis validates high risk MDS and acute myeloid leukemia post MDS mice models and highlights novel dysregulated pathways

BACKGROUND: In spite of the recent discovery of genetic mutations in most myelodysplasic (MDS) patients, the pathophysiology of these disorders still remains poorly understood, and only few in vivo models are available to help unravel the disease.

METHODS: We performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS) and acute myeloid leukemia (AML) post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters MRP8NRASD12/tethBCL-2 or MRP8[NRASD12/hBCL-2], respectively.

RESULTS: Analysis of dysregulated genes that were unique to the diseased HR-MDS and AML post MDS mice and not their founder mice pointed first to pathways that had previously been reported in MDS patients, including DNA replication/damage/repair, cell cycle, apoptosis, immune responses, and canonical Wnt pathways, further validating these models at the gene expression level. Interestingly, pathways not previously reported in MDS were discovered. These included dysregulated genes of noncanonical Wnt pathways and energy and lipid metabolisms. These dysregulated genes were not only confirmed in a different independent set of BM and spleen Sca1+ cells from the MDS mice but also in MDS CD34+ BM patient samples.

CONCLUSIONS: These two MDS models may thus provide useful preclinical models to target pathways previously identified in MDS patients and to unravel novel pathways highlighted by this study.

No association between hOGG1, XRCC1, and XPD polymorphisms and risk of reflux esophagitis, Barrett's Esophagus, or esophageal adenocarcinoma: Results from the factors influencing the Barrett's adenocarcinoma relationship case-control study

Reflux of gastric contents can lead to development of reflux esophagitis and Barrett's esophagus. Barrett's esophagus is a risk factor for esophageal adenocarcinoma. Damage to DNA may lead to carcinogenesis but is repaired through activation of pathways involving polymorphic enzymes, including human 8-oxoguanine glycosylase 1 (hOGG1), X-ray repair cross-complementing 1 (XRCC1), and xeroderma pigmentosum group D (XPD). Of the single nucleotide polymorphisms identified in these genes, hOGG1 Ser 326Cys, XRCC1 Arg 399Gln, and XPD Lys 751Gln are particularly common in Caucasians and have been associated with lower DNA repair capacity. Small studies have reported associations with XPD Lys 751Gln and esophageal adenocarcinoma. XRCC1 Arg 399Gln has been linked to Barrett's esophagus and reflux esophagitis. In a population-based case-control study, we examined associations of the hOGG1 Ser 326Cys, XRCC1 Arg 399Gln, and XPD Lys 751Gln polymorphisms with risk of esophageal adenocarcinoma, Barrett's esophagus, and reflux esophagitis. Genomic DNA was extracted from blood samples collected from cases of esophageal adenocarcinoma (n = 210), Barrett's esophagus (n = 212), reflux esophagitis (n = 230), and normal population controls frequency matched for age and sex (n = 248). Polymorphisms were genotyped using Taq-Man allelic discrimination assays. Odds ratios and 95% confidence intervals were obtained from logistic regression models adjusted for potential confounding factors. There were no statistically significant associations between these polymorphisms and risk of esophageal adenocarcinoma, Barrett's esophagus, or reflux esophagitis.

Cyclooxygenase-2 and inducible nitric oxide synthase gene polymorphisms and risk of reflux esophagitis, Barrett's Esophagus, and esophageal adenocarcinoma

The incidence of esophageal adenocarcinoma has increased in recent years, and Barrett's esophagus is a recognized risk factor. Gastroesophageal reflux of acid and/or bile is linked to these conditions and to reflux esophagitis. Inflammatory disorders can lead to carcinogenesis through activation of "prosurvival genes," including cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS). Increased expression of these enzymes has been found in esophageal adenocarcinoma, Barrett's esophagus, and reflux esophagitis. Polymorphic variants in COX-2 and iNOS genes may be modifiers of risk of these conditions. In a population-based case-control study, we examined associations of the COX-2 8473 T>C and iNOS Ser 608 Leu (C>T) polymorphisms with risk of esophageal adenocarcinoma, Barrett's esophagus, and reflux esophagitis. Genomic DNA was extracted from blood samples collected from cases of esophageal adenocarcinoma (n = 210), Barrett's esophagus (n = 212), and reflux esophagitis (n = 230) and normal population controls frequency matched for age and sex (n = 248). Polymorphisms were genotyped using TaqMan allelic discrimination assays. Odds ratios and 95% confidence intervals were obtained from logistic regression models adjusted for potential confounding factors. The presence of at least one COX-2 8473 C allele was associated with a significantly increased risk of esophageal adenocarcinoma (adjusted odds ratio, 1.58; 95% confidence interval, 1.04-2.40). There was no significant association between this polymorphism and risk of Barrett's esophagus or reflux esophagitis or between the iNOS Ser 608 Leu polymorphism and risk of these esophageal conditions. Our study suggests that the COX-2 8473 C allele is a potential genetic marker for susceptibility to esophageal adenocarcinoma.

Incorporating Higher Moments into Value at Risk Forecasting

Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the standard normal distribution with the first four moments, which are allowed to vary over time. In an extensive empirical study, we compare the GCE approach to other models of VaR forecasting and conclude that it provides accurate and robust estimates of the realized VaR. In spite of its simplicity, on our dataset GCE outperforms other estimates that are generated by both constant and time-varying higher-moments models.

Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.

Alternative Factor Models and Heritability of the Short Leyton Obsessional Inventory-Children's Version

An alternative models framework was used to test three confirmatory factor analytic models for the Short Leyton Obsessional Inventory-Children's Version (Short LOI-CV) in a general population sample of 517 young adolescent twins (11-16 years). A one-factor model as implicit in current classification systems of Obsessive-Compulsive Disorder (OCD), a two-factor obsessions and compulsions model, and a multidimensional model corresponding to the three proposed subscales of the Short LOI-CV (labelled Obsessions/Incompleteness, Numbers/Luck and Cleanliness) were considered. The three-factor model was the only model to provide an adequate explanation of the data. Twin analyses suggested significant quantitative sex differences in heritability for both the Obsessions/Incompleteness and Numbers/Luck dimensions with these being significantly heritable in males only (heritability of 60% and 65% respectively). The correlation between the additive genetic effects for these two dimensions in males was 0.95 suggesting they largely share the same genetic risk factors.