955 resultados para Multivariate risk model


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Diabetes has been associated to the risk of a few cancer sites, though quantification of this association in various populations remains open to discussion. We analyzed the relation between diabetes and the risk of various cancers in an integrated series of case-control studies conducted in Italy and Switzerland between 1991 and 2009. The studies included 1,468 oral and pharyngeal, 505 esophageal, 230 gastric, 2,390 colorectal, 185 liver, 326 pancreatic, 852 laryngeal, 3,034 breast, 607 endometrial, 1,031 ovarian, 1,294 prostate, and 767 renal cell cancer cases and 12,060 hospital controls. The multivariate odds ratios (OR) for subjects with diabetes as compared to those without-adjusted for major identified confounding factors for the cancers considered through logistic regression models-were significantly elevated for cancers of the oral cavity/pharynx (OR = 1.58), esophagus (OR = 2.52), colorectum (OR = 1.23), liver (OR = 3.52), pancreas (OR = 3.32), postmenopausal breast (OR = 1.76), and endometrium (OR = 1.70). For cancers of the oral cavity, esophagus, colorectum, liver, and postmenopausal breast, the excess risk persisted over 10 yr since diagnosis of diabetes. Our data confirm and further quantify the association of diabetes with colorectal, liver, pancreatic, postmenopausal breast, and endometrial cancer and suggest forthe first time that diabetes may also increase the risk of oral/pharyngeal and esophageal cancer. [Table: see text] [Table: see text].

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Standard methods for the analysis of linear latent variable models oftenrely on the assumption that the vector of observed variables is normallydistributed. This normality assumption (NA) plays a crucial role inassessingoptimality of estimates, in computing standard errors, and in designinganasymptotic chi-square goodness-of-fit test. The asymptotic validity of NAinferences when the data deviates from normality has been calledasymptoticrobustness. In the present paper we extend previous work on asymptoticrobustnessto a general context of multi-sample analysis of linear latent variablemodels,with a latent component of the model allowed to be fixed across(hypothetical)sample replications, and with the asymptotic covariance matrix of thesamplemoments not necessarily finite. We will show that, under certainconditions,the matrix $\Gamma$ of asymptotic variances of the analyzed samplemomentscan be substituted by a matrix $\Omega$ that is a function only of thecross-product moments of the observed variables. The main advantage of thisis thatinferences based on $\Omega$ are readily available in standard softwareforcovariance structure analysis, and do not require to compute samplefourth-order moments. An illustration with simulated data in the context ofregressionwith errors in variables will be presented.

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This paper presents an analysis of the credibility of the EMScurrencies that covers the period before and after the increase in thebands of fluctuation. Our credibility indicator is based on the inferredprobabilities derived from the estimation of a Markov-switching model(Hamilton (1989)) applied to the expected rate of depreciation. Theresults show that, for most of the currencies, credibility has improved,at least transitorily, after the increase in the bands. However, for allcurrencies, the credibility measured by the indicator proposed in thispaper has been eroded recently even with the widened bands.

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This paper examines the relationship between the equity premium and the risk free rate at three different maturities using post 1973 data fora panel of 7 OECD countries. We show the existence of subsample instabilities,of some cross country differences and of inconsistencies with the expectations theory of the term structure. We perform simulations using a standard consumptionbased CAPM model and demonstrate that the basic features of Mehra and Prescott's(1985) puzzle remain, regardless of the time period, the investment maturity and the country considered. Modifications of the basic setup are also considered.

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PURPOSE To develop a score predicting the risk of adverse events (AEs) in pediatric patients with cancer who experience fever and neutropenia (FN) and to evaluate its performance. PATIENTS AND METHODS Pediatric patients with cancer presenting with FN induced by nonmyeloablative chemotherapy were observed in a prospective multicenter study. A score predicting the risk of future AEs (ie, serious medical complication, microbiologically defined infection, radiologically confirmed pneumonia) was developed from a multivariate mixed logistic regression model. Its cross-validated predictive performance was compared with that of published risk prediction rules. Results An AE was reported in 122 (29%) of 423 FN episodes. In 57 episodes (13%), the first AE was known only after reassessment after 8 to 24 hours of inpatient management. Predicting AE at reassessment was better than prediction at presentation with FN. A differential leukocyte count did not increase the predictive performance. The score predicting future AE in 358 episodes without known AE at reassessment used the following four variables: preceding chemotherapy more intensive than acute lymphoblastic leukemia maintenance (weight = 4), hemoglobin > or = 90 g/L (weight = 5), leukocyte count less than 0.3 G/L (weight = 3), and platelet count less than 50 G/L (weight = 3). A score (sum of weights) > or = 9 predicted future AEs. The cross-validated performance of this score exceeded the performance of published risk prediction rules. At an overall sensitivity of 92%, 35% of the episodes were classified as low risk, with a specificity of 45% and a negative predictive value of 93%. CONCLUSION This score, based on four routinely accessible characteristics, accurately identifies pediatric patients with cancer with FN at risk for AEs after reassessment.

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We use CEX repeated cross-section data on consumption and income, to evaluate the nature of increased income inequality in the 1980s and 90s. We decompose unexpected changes in family income into transitory and permanent, and idiosyncratic and aggregate components, and estimate the contribution of each component to total inequality. The model we use is a linearized incomplete markets model, enriched to incorporate risk-sharing while maintaining tractability. Our estimates suggest that taking risk sharing into account is important for the model fit; that the increase in inequality in the 1980s was mainly permanent; and that inequality is driven almost entirely by idiosyncratic income risk. In addition we find no evidence for cyclical behavior of consumption risk, casting doubt on Constantinides and Duffie s (1995) explanation for the equity premium puzzle.

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Was the increase in income inequality in the US due to permanent shocks or merely to an increase in the variance of transitory shocks? The implications for consumption and welfare depend crucially on the answer to this question. We use CEX repeated cross-section data on consumption and income to decompose idiosyncratic changes in income into predictable life-cycle changes, transitory and permanent shocks and estimate the contribution of each to total inequality. Our model fits the joint evolution of consumption and income inequality well and delivers two main results. First, we find that permanent changes in income explain all of the increase in inequality in the 1980s and 90s. Second, we reconcile this finding with the fact that consumption inequality did not increase much over this period. Our results support the view that many permanent changes in income are predictable for consumers, even if they look unpredictable to the econometrician, consistent withmodels of heterogeneous income profiles.

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This paper combines multivariate density forecasts of output growth, inflationand interest rates from a suite of models. An out-of-sample weighting scheme based onthe predictive likelihood as proposed by Eklund and Karlsson (2005) and Andersson andKarlsson (2007) is used to combine the models. Three classes of models are considered: aBayesian vector autoregression (BVAR), a factor-augmented vector autoregression (FAVAR)and a medium-scale dynamic stochastic general equilibrium (DSGE) model. Using Australiandata, we find that, at short forecast horizons, the Bayesian VAR model is assignedthe most weight, while at intermediate and longer horizons the factor model is preferred.The DSGE model is assigned little weight at all horizons, a result that can be attributedto the DSGE model producing density forecasts that are very wide when compared withthe actual distribution of observations. While a density forecast evaluation exercise revealslittle formal evidence that the optimally combined densities are superior to those from thebest-performing individual model, or a simple equal-weighting scheme, this may be a resultof the short sample available.

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Background: Evidence for a better performance of different highly atherogenic versus traditional lipid parameters for coronary heart disease (CHD) risk prediction is conflicting. We investigated the association of the ratios of sma11 dense low density lipoprotein(LDL)/apoplipoprotein A, aolipoprotein B/apolipoprotein A-I and total cholesterol! HDL-cholesterol and CHD events in patients on combination antiretroviral therapy (cART).Methods: Case control study nested into the Swiss HIV Cohort Study: for each cART-treated patient with a first coronary event between April 1, 2000 and July 31, 2008 (case) we selected four control patients (1) that were without coronary events until the date of the event of the index case, (2) had a plasma sample within ±30 days of the sample date of the respective case, (3) received cART and (4) were then matched for age, gender and smoking status. Lipoproteins were measured by ultracentrifugation. Conditional logistic regression models were used to estimate the independent effects of different lipid ratios and the occurrence of coronary events.Results: In total, 98 cases (19 fatal myocardial infarctions [MI] and 79 non-fatal coronary events [53 definite MIs, 15 possible MIs and 11 coronary angioplasties or bypassesJ) were matched with 392 controls. Cases were more often injecting drug users, less likely to be virologically suppressed and more often on abacavir-containing regimens. In separa te multivariable models of total cholesterol, triglycerides, HDL-cholesterol, systolic blood pressure, abdominal obesity, diabetes and family history of CHD, small dense-LDL and apolipoprotein B were each statistically significantly associated with CHD events (for 1 mg/dl increase: odds ratio [OR] 1.05, 95% CI 1.00-1.11 and 1.15, 95% CI 1.01-1.31, respectively), but the ratiosof small dense-LDLlapolipoprotein A-I (OR 1.26, 95% CI 0.95-1.67), apolipoprotein B/apolipoprotein A-I (OR 1.02, 95% CI 0.97-1.07) and HDL-cholesterol! total cholesterol (OR 0.99 95% CI 0.98-1.00) were not. Following adjustment for HIV related and cART variables these associations were weakened in each model: apolipoprotein B (OR 1.27, 95% CI 1.00-1.30), sd-LDL (OR 1.04, 95% CI 0.99-1.20), small dense-LDLlapolipoprotein A-I (OR 1.17, 95% CI 0.87-1.58), apolipoprotein B/apolipoprotein A-I (OR 1.02, 95% CI 0.97-1.07) and total cholesterolJHDL- cholesterol (OR 0.99, 95% CI 0.99-1.00).Conclusions: In patients receiving cART, small dense-LDL and apolipoprotein B showed the strongest associations with CHD events in models controlling for traditional CHD risk factors including total cholesterol and triglycerides. Adding small dense LDLlapoplipoprotein A-l, apolipoprotein B/apolipoprotein A-I and total cholesterol! HDL-cholesterol ratios did not further improve models of lipid parameters and associations of increased risk for CHD events.

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BACKGROUND: New HIV infections in men who have sex with men (MSM) have increased in Switzerland since 2000 despite combination antiretroviral therapy (cART). The objectives of this mathematical modelling study were: to describe the dynamics of the HIV epidemic in MSM in Switzerland using national data; to explore the effects of hypothetical prevention scenarios; and to conduct a multivariate sensitivity analysis. METHODOLOGY/PRINCIPAL FINDINGS: The model describes HIV transmission, progression and the effects of cART using differential equations. The model was fitted to Swiss HIV and AIDS surveillance data and twelve unknown parameters were estimated. Predicted numbers of diagnosed HIV infections and AIDS cases fitted the observed data well. By the end of 2010, an estimated 13.5% (95% CI 12.5, 14.6%) of all HIV-infected MSM were undiagnosed and accounted for 81.8% (95% CI 81.1, 82.4%) of new HIV infections. The transmission rate was at its lowest from 1995-1999, with a nadir of 46 incident HIV infections in 1999, but increased from 2000. The estimated number of new infections continued to increase to more than 250 in 2010, although the reproduction number was still below the epidemic threshold. Prevention scenarios included temporary reductions in risk behaviour, annual test and treat, and reduction in risk behaviour to levels observed earlier in the epidemic. These led to predicted reductions in new infections from 2 to 26% by 2020. Parameters related to disease progression and relative infectiousness at different HIV stages had the greatest influence on estimates of the net transmission rate. CONCLUSIONS/SIGNIFICANCE: The model outputs suggest that the increase in HIV transmission amongst MSM in Switzerland is the result of continuing risky sexual behaviour, particularly by those unaware of their infection status. Long term reductions in the incidence of HIV infection in MSM in Switzerland will require increased and sustained uptake of effective interventions.

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The emphasis on integrated care implies new incentives that promote coordinationbetween levels of care. Considering a population as a whole, the resource allocation systemhas to adapt to this environment. This research is aimed to design a model that allows formorbidity related prospective and concurrent capitation payment. The model can be applied inpublicly funded health systems and managed competition settings.Methods: We analyze the application of hybrid risk adjustment versus either prospective orconcurrent risk adjustment formulae in the context of funding total health expenditures for thepopulation of an integrated healthcare delivery organization in Catalonia during years 2004 and2005.Results: The hybrid model reimburses integrated care organizations avoiding excessive risktransfer and maximizing incentives for efficiency in the provision. At the same time, it eliminatesincentives for risk selection for a specific set of high risk individuals through the use ofconcurrent reimbursement in order to assure a proper classification of patients.Conclusion: Prospective Risk Adjustment is used to transfer the financial risk to the healthprovider and therefore provide incentives for efficiency. Within the context of a National HealthSystem, such transfer of financial risk is illusory, and the government has to cover the deficits.Hybrid risk adjustment is useful to provide the right combination of incentive for efficiency andappropriate level of risk transfer for integrated care organizations.

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In this paper we address a problem arising in risk management; namely the study of price variations of different contingent claims in the Black-Scholes model due to anticipating future events. The method we propose to use is an extension of the classical Vega index, i.e. the price derivative with respect to the constant volatility, in thesense that we perturb the volatility in different directions. Thisdirectional derivative, which we denote the local Vega index, will serve as the main object in the paper and one of the purposes is to relate it to the classical Vega index. We show that for all contingent claims studied in this paper the local Vega index can be expressed as a weighted average of the perturbation in volatility. In the particular case where the interest rate and the volatility are constant and the perturbation is deterministic, the local Vega index is an average of this perturbation multiplied by the classical Vega index. We also study the well-known goal problem of maximizing the probability of a perfect hedge and show that the speed of convergence is in fact dependent of the local Vega index.

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AIMS/HYPOTHESIS: The molecular mechanisms of obesity-related insulin resistance are incompletely understood. Macrophages accumulate in adipose tissue of obese individuals. In obesity, monocyte chemoattractant protein-1 (MCP-1), a key chemokine in the process of macrophage accumulation, is overexpressed in adipose tissue. MCP-1 is an insulin-responsive gene that continues to respond to exogenous insulin in insulin-resistant adipocytes and mice. MCP-1 decreases insulin-stimulated glucose uptake into adipocytes. The A-2518G polymorphism in the distal regulatory region of MCP-1 may regulate gene expression. The aim of this study was to investigate the impact of this gene polymorphism on insulin resistance. METHODS: We genotyped the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort ( n=3307). Insulin resistance, estimated by homeostasis model assessment, and Type 2 diabetes were diagnosed in 803 and 635 patients respectively. RESULTS: Univariate analysis revealed that plasma MCP-1 levels were significantly and positively correlated with WHR ( p=0.011), insulin resistance ( p=0.0097) and diabetes ( p<0.0001). Presence of the MCP-1 G-2518 allele was associated with decreased plasma MCP-1 ( p=0.017), a decreased prevalence of insulin resistance (odds ratio [OR]=0.82, 95% CI: 0.70-0.97, p=0.021) and a decreased prevalence of diabetes (OR=0.80, 95% CI: 0.67-0.96, p=0.014). In multivariate analysis, the G allele retained statistical significance as a negative predictor of insulin resistance (OR=0.78, 95% CI: 0.65-0.93, p=0.0060) and diabetes (OR=0.80, 95% CI: 0.66-0.96, p=0.018). CONCLUSIONS/INTERPRETATION: In a large cohort of Caucasians, the MCP-1 G-2518 gene variant was significantly and negatively correlated with plasma MCP-1 levels and the prevalence of insulin resistance and Type 2 diabetes. These results add to recent evidence supporting a role for MCP-1 in pathologies associated with hyperinsulinaemia.

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We analyze risk sharing and fiscal spending in a two-region model withcomplete markets. Fiscal policy determines tax rates for each state ofnature. When fiscal policy is decentralized, it can be used to affect prices of securities. To manipulate prices to their beneffit, regionschoose pro-cyclical fiscal spending. This leads to incomplete risk sharing,despite the existence of complete markets and the absence of aggregaterisk. When a fiscal union centralizes fiscal policy, securities pricescan no longer be manipulated and complete risk sharing ensues. If regionsare homogeneous, median income residents of both regions prefer the fiscalunion. If they are heterogeneous, the median resident of the rich regionprefers the decentralized setting.

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OBJECTIVES: The purpose of this study was to evaluate the association between inflammation and heart failure (HF) risk in older adults. BACKGROUND: Inflammation is associated with HF risk factors and also directly affects myocardial function. METHODS: The association of baseline serum concentrations of interleukin (IL)-6, tumor necrosis factor-alpha, and C-reactive protein (CRP) with incident HF was assessed with Cox models among 2,610 older persons without prevalent HF enrolled in the Health ABC (Health, Aging, and Body Composition) study (age 73.6 +/- 2.9 years; 48.3% men; 59.6% white). RESULTS: During follow-up (median 9.4 years), HF developed in 311 (11.9%) participants. In models controlling for clinical characteristics, ankle-arm index, and incident coronary heart disease, doubling of IL-6, tumor necrosis factor-alpha, and CRP concentrations was associated with 29% (95% confidence interval: 13% to 47%; p < 0.001), 46% (95% confidence interval: 17% to 84%; p = 0.001), and 9% (95% confidence interval: -1% to 24%; p = 0.087) increase in HF risk, respectively. In models including all 3 markers, IL-6, and tumor necrosis factor-alpha, but not CRP, remained significant. These associations were similar across sex and race and persisted in models accounting for death as a competing event. Post-HF ejection fraction was available in 239 (76.8%) cases; inflammatory markers had stronger association with HF with preserved ejection fraction. Repeat IL-6 and CRP determinations at 1-year follow-up did not provide incremental information. Addition of IL-6 to the clinical Health ABC HF model improved model discrimination (C index from 0.717 to 0.734; p = 0.001) and fit (decreased Bayes information criterion by 17.8; p < 0.001). CONCLUSIONS: Inflammatory markers are associated with HF risk among older adults and may improve HF risk stratification.