42 CFR 81.12 - Procedure to update NIOSH-IREP.

Code of Federal Regulations, 2012 CFR

2012-10-01

... HEALTH RESEARCH AND RELATED ACTIVITIES GUIDELINES FOR DETERMINING PROBABILITY OF CAUSATION UNDER THE... periodically revise NIOSH-IREP to add, modify, or replace cancer risk models, improve the modeling of... using NIOSH-IREP, including the addition of new cancer risk models) to the Advisory Board on Radiation...

42 CFR 81.12 - Procedure to update NIOSH-IREP.

Code of Federal Regulations, 2013 CFR

2013-10-01

... HEALTH RESEARCH AND RELATED ACTIVITIES GUIDELINES FOR DETERMINING PROBABILITY OF CAUSATION UNDER THE... periodically revise NIOSH-IREP to add, modify, or replace cancer risk models, improve the modeling of... using NIOSH-IREP, including the addition of new cancer risk models) to the Advisory Board on Radiation...

42 CFR 81.12 - Procedure to update NIOSH-IREP.

Code of Federal Regulations, 2011 CFR

2011-10-01

... HEALTH RESEARCH AND RELATED ACTIVITIES GUIDELINES FOR DETERMINING PROBABILITY OF CAUSATION UNDER THE... periodically revise NIOSH-IREP to add, modify, or replace cancer risk models, improve the modeling of... using NIOSH-IREP, including the addition of new cancer risk models) to the Advisory Board on Radiation...

42 CFR 81.12 - Procedure to update NIOSH-IREP.

Code of Federal Regulations, 2014 CFR

2014-10-01

... HEALTH RESEARCH AND RELATED ACTIVITIES GUIDELINES FOR DETERMINING PROBABILITY OF CAUSATION UNDER THE... periodically revise NIOSH-IREP to add, modify, or replace cancer risk models, improve the modeling of... using NIOSH-IREP, including the addition of new cancer risk models) to the Advisory Board on Radiation...

Risk selection into consumer-directed health plans: an analysis of family choices within large employers.

PubMed

McDevitt, Roland D; Haviland, Amelia M; Lore, Ryan; Laudenberger, Laura; Eisenberg, Matthew; Sood, Neeraj

2014-04-01

To identify the degree of selection into consumer-directed health plans (CDHPs) versus traditional plans over time, and factors that influence choice and temper risk selection. Sixteen large employers offering both CDHP and traditional plans during the 2004–2007 period, more than 200,000 families. We model CDHP choice with logistic regression; predictors include risk scores, in addition to family, choice setting, and plan characteristics. Additional models stratify by account type or single enrollee versus family. Risk scores, family characteristics, and enrollment decisions are derived from medical claims and enrollment files. Interviews with human resources executives provide additional data. CDHP risk scores were 74 percent of traditional plan scores in the first year, and this difference declined over time. Employer contributions to accounts and employee premium savings fostered CDHP enrollment and reduced risk selection. Having to make an active choice of plan increased CDHP enrollment but also increased risk selection. Risk selection was greater for singles than families and did not differ between HRA and HSA-based CDHPs. Risk selection was not severe and it was well managed. Employers have effective methods to encourage CDHP enrollment and temper selection against traditional plans.

Assessing the Risk of Crew Injury Due to Dynamic Loads During Spaceflight

NASA Technical Reports Server (NTRS)

Somers, J. T.; Gernhardt, M.; Newby, N.

2014-01-01

Spaceflight requires tremendous amounts of energy to achieve Earth orbit and to attain escape velocity for interplanetary missions. Although the majority of the energy is managed in such a way as to limit the accelerations on the crew, several mission phases may result in crew exposure to dynamic loads. In the automotive industry, risk of serious injury can be tolerated because the probability of a crash is remote each time a person enters a vehicle, resulting in a low total risk of injury. For spaceflight, the level of acceptable injury risk must be lower to achieve a low total risk of injury because the dynamic loads are expected on each flight. To mitigate the risk of injury due to dynamic loads, the NASA Human Research Program has developed a research plan to inform the knowledge gaps and develop relevant tools for assessing injury risk. The risk of injury due to dynamic loads can be further subdivided into extrinsic and intrinsic risk factors. Extrinsic risk factors include the vehicle dynamic profile, seat and restraint design, and spacesuit design. Human tolerance to loads varies considerably depending on the direction, amplitude, and rise-time of acceleration therefore the orientation of the body to the dynamic vector is critical to determining crew risk of injury. Although a particular vehicle dynamic profile may be safe for a particular design, the seat, restraint, and suit designs can affect the risk of injury due to localized effects. In addition, characteristics intrinsic to the crewmember may also contribute to the risk of injury, such as crewmember sex, age, anthropometry, and deconditioning due to spaceflight, and each astronaut may have a different risk profile because of these factors. The purpose of the research plan is to address any knowledge gaps in the risk factors to mitigate injury risk. Methods for assessing injury risk have been well documented in other analogous industries and include human volunteer testing, human exposure to dynamic environments, post-mortem human subject (PMHS) testing, animal testing, anthropomorphic test devices (ATD), dynamic models of the human, numerical models of ATDs, and numerical models of the human. Each has inherent strengths and limitations. For example, human volunteer testing is advantageous because a population can be selected that is similar to the astronaut corps; however, because of the inherent ethical limitations, only sub-injurious conditions can be tested. PMHSs can be tested in a variety of conditions including injurious levels, but the responses are not completely analogous to living human subjects. In addition, it is exceedingly difficult to select a PMHS population that is similar to the astronaut corps. ATDs are currently widely used in the automotive industry and military because they are highly repeatable and durable. Unfortunately, because they are mechanical models of the human body, the biofidelity of the responses are limited to dynamic conditions used to validate the ATD. Numerical models of the ATD, in addition to the strengths and limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional uncertainty. Dynamic models are simple and easy to use, but do not account for localized effects of the seat and suit. Finally, numerical models of the human have the potential to have the most advantages; however, the current models are not validated for the conditions expected during spaceflight. To properly assess spaceflight conditions with numerical human models, human data would be needed to optimize the model responses for those conditions. Using the appropriate assessment method with the knowledge gained for each risk factor, an appropriate approach for mitigating the risk of injury due to dynamic loads can be developed ensuring crew safety in future NASA vehicles.

Risk stratification following acute myocardial infarction.

PubMed

Singh, Mandeep

2007-07-01

This article reviews the current risk assessment models available for patients presenting with myocardial infarction (MI). These practical tools enhance the health care provider's ability to rapidly and accurately assess patient risk from the event or revascularization therapy, and are of paramount importance in managing patients presenting with MI. This article highlights the models used for ST-elevation MI (STEMI) and non-ST elevation MI (NSTEMI) and provides an additional description of models used to assess risks after primary angioplasty (ie, angioplasty performed for STEMI).

Integration of second cancer risk calculations in a radiotherapy treatment planning system

NASA Astrophysics Data System (ADS)

Hartmann, M.; Schneider, U.

2014-03-01

Second cancer risk in patients, in particular in children, who were treated with radiotherapy is an important side effect. It should be minimized by selecting an appropriate treatment plan for the patient. The objectives of this study were to integrate a risk model for radiation induced cancer into a treatment planning system which allows to judge different treatment plans with regard to second cancer induction and to quantify the potential reduction in predicted risk. A model for radiation induced cancer including fractionation effects which is valid for doses in the radiotherapy range was integrated into a treatment planning system. From the three-dimensional (3D) dose distribution the 3D-risk equivalent dose (RED) was calculated on an organ specific basis. In addition to RED further risk coefficients like OED (organ equivalent dose), EAR (excess absolute risk) and LAR (lifetime attributable risk) are computed. A risk model for radiation induced cancer was successfully integrated in a treatment planning system. Several risk coefficients can be viewed and used to obtain critical situations were a plan can be optimised. Risk-volume-histograms and organ specific risks were calculated for different treatment plans and were used in combination with NTCP estimates for plan evaluation. It is concluded that the integration of second cancer risk estimates in a commercial treatment planning system is feasible. It can be used in addition to NTCP modelling for optimising treatment plans which result in the lowest possible second cancer risk for a patient.

Bayesian structured additive regression modeling of epidemic data: application to cholera

PubMed Central

2012-01-01

Background A significant interest in spatial epidemiology lies in identifying associated risk factors which enhances the risk of infection. Most studies, however, make no, or limited use of the spatial structure of the data, as well as possible nonlinear effects of the risk factors. Methods We develop a Bayesian Structured Additive Regression model for cholera epidemic data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (MCMC) simulations. The model is applied to cholera epidemic data in the Kumasi Metropolis, Ghana. Proximity to refuse dumps, density of refuse dumps, and proximity to potential cholera reservoirs were modeled as continuous functions; presence of slum settlers and population density were modeled as fixed effects, whereas spatial references to the communities were modeled as structured and unstructured spatial effects. Results We observe that the risk of cholera is associated with slum settlements and high population density. The risk of cholera is equal and lower for communities with fewer refuse dumps, but variable and higher for communities with more refuse dumps. The risk is also lower for communities distant from refuse dumps and potential cholera reservoirs. The results also indicate distinct spatial variation in the risk of cholera infection. Conclusion The study highlights the usefulness of Bayesian semi-parametric regression model analyzing public health data. These findings could serve as novel information to help health planners and policy makers in making effective decisions to control or prevent cholera epidemics. PMID:22866662

Lung Cancer Risk from Occupational and Environmental Radon and Role of Smoking in Two Czech Nested Case-Control Studies

PubMed Central

Tomasek, Ladislav

2013-01-01

The aim of the present study was to evaluate the risk of lung cancer from combined exposure to radon and smoking. Methodologically, it is based on case-control studies nested within two Czech cohort studies of nearly 11,000 miners followed-up for mortality in 1952–2010 and nearly 12,000 inhabitants exposed to high levels of radon in homes, with mortality follow-up in 1960–2010. In addition to recorded radon exposure, these studies use information on smoking collected from the subjects or their relatives. A total of 1,029 and 370 cases with smoking information have been observed in the occupational and environmental (residential) studies, respectively. Three or four control subjects have been individually matched to cases according to sex, year of birth, and age. The combined effect from radon and smoking is analyzed in terms of geometric mixture models of which the additive and multiplicative models are special cases. The resulting models are relatively close to the additive interaction (mixing parameter 0.2 and 0.3 in the occupational and residential studies, respectively). The impact of the resulting model in the residential radon study is illustrated by estimates of lifetime risk in hypothetical populations of smokers and non-smokers. In comparison to the multiplicative risk model, the lifetime risk from the best geometric mixture model is considerably higher, particularly in the non-smoking population. PMID:23470882

Initial Risk Analysis and Decision Making Framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engel, David W.

2012-02-01

Commercialization of new carbon capture simulation initiative (CCSI) technology will include two key elements of risk management, namely, technical risk (will process and plant performance be effective, safe, and reliable) and enterprise risk (can project losses and costs be controlled within the constraints of market demand to maintain profitability and investor confidence). Both of these elements of risk are incorporated into the risk analysis subtask of Task 7. Thus far, this subtask has developed a prototype demonstration tool that quantifies risk based on the expected profitability of expenditures when retrofitting carbon capture technology on a stylized 650 MW pulverized coalmore » electric power generator. The prototype is based on the selection of specific technical and financial factors believed to be important determinants of the expected profitability of carbon capture, subject to uncertainty. The uncertainty surrounding the technical performance and financial variables selected thus far is propagated in a model that calculates the expected profitability of investments in carbon capture and measures risk in terms of variability in expected net returns from these investments. Given the preliminary nature of the results of this prototype, additional work is required to expand the scope of the model to include additional risk factors, additional information on extant and proposed risk factors, the results of a qualitative risk factor elicitation process, and feedback from utilities and other interested parties involved in the carbon capture project. Additional information on proposed distributions of these risk factors will be integrated into a commercial implementation framework for the purpose of a comparative technology investment analysis.« less

Associations of TF Gene Polymorphisms with the Risk of Ischemic Stroke.

PubMed

Cai, Yi; Wu, Shaofang; Zeng, Chaosheng; Su, Qingjie; Zhou, Jingxia; Li, Pengxiang; Dai, Mingming; Wang, Desheng; Long, Faqing

2018-06-23

Ischemic stroke (IS) is the main cause of mortality and disability in China; thus, this study aimed to examine the association between six variants and their haplotypes within the transferrin (TF) gene and the risk of IS in the Southern Chinese Han population. Genotyping was performed using the Sequenom MassARRAY platform for 249 IS patients and 249 age- and sex-matched controls. The association between polymorphisms and IS risk was tested by Chi squared test and haplotype and stratification analysis. Odds ratios (ORs) and confidence intervals (CIs) were estimated by unconditional logistic regression analysis. The results of genetic model analyses indicated that the two SNPs (rs1880669 and rs2692695) were associated with decreased IS risk under the co-dominant, dominant, and additive models. Additionally, rs4525863 was also associated with decreased IS risk both under the dominant and additive models in males. Moreover, the CG haplotype of TF (rs1880669 and rs2692695) was significantly associated with a decreased risk of IS in the total population and males. Our findings suggested that polymorphisms (rs4525863, rs1880669, and rs2692695) of the TF gene might be a protective factor for IS in Southern Chinese Han population. Further large prospective studies are required to confirm these findings.

Early Life Stress and Sleep Restriction as Risk Factors in PTSD: An Integrative Pre-Clinical Approach

DTIC Science & Technology

2014-04-01

potential risk factors, with high relevance to soldiers. The primary aims of the project are thus. 1) To establish an effective animal model of PTSD that...develop the model as a platform for pharmacological testing of novel targets for drug development 5) As an additional aim – once an effective animal model...thus: 1) To establish an effective animal model of PTSD that would take into consideration the contribution of risk factors to the induction of the

Risk Selection into Consumer-Directed Health Plans: An Analysis of Family Choices within Large Employers

PubMed Central

McDevitt, Roland D; Haviland, Amelia M; Lore, Ryan; Laudenberger, Laura; Eisenberg, Matthew; Sood, Neeraj

2014-01-01

Objective To identify the degree of selection into consumer-directed health plans (CDHPs) versus traditional plans over time, and factors that influence choice and temper risk selection. Data Sources/Study Setting Sixteen large employers offering both CDHP and traditional plans during the 2004–2007 period, more than 200,000 families. Study Design We model CDHP choice with logistic regression; predictors include risk scores, in addition to family, choice setting, and plan characteristics. Additional models stratify by account type or single enrollee versus family. Data Collection/Extraction Methods Risk scores, family characteristics, and enrollment decisions are derived from medical claims and enrollment files. Interviews with human resources executives provide additional data. Principal Findings CDHP risk scores were 74 percent of traditional plan scores in the first year, and this difference declined over time. Employer contributions to accounts and employee premium savings fostered CDHP enrollment and reduced risk selection. Having to make an active choice of plan increased CDHP enrollment but also increased risk selection. Risk selection was greater for singles than families and did not differ between HRA and HSA-based CDHPs. Conclusions Risk selection was not severe and it was well managed. Employers have effective methods to encourage CDHP enrollment and temper selection against traditional plans. PMID:24800305

RTEL1 and TERT polymorphisms are associated with astrocytoma risk in the Chinese Han population.

PubMed

Jin, Tian-Bo; Zhang, Jia-Yi; Li, Gang; Du, Shu-Li; Geng, Ting-Ting; Gao, Jing; Liu, Qian-Ping; Gao, Guo-Dong; Kang, Long-Li; Chen, Chao; Li, Shan-Qu

2013-12-01

Common variants of multiple genes play a role in glioma onset. However, research related to astrocytoma, the most common primary brain neoplasm, is rare. In this study, we chose 21 tagging SNPs (tSNPs), previously reported to be associated with glioma risk in a Chinese case-control study from Xi'an, China, and identified their contributions to astrocytoma susceptibility. We found an association with astrocytoma susceptibility for two tSNPs (rs6010620 and rs2853676) in two different genes: regulator of telomere elongation helicase 1 (RTEL1) and telomerase reverse transcriptase (TERT), respectively. We confirmed our results using recessive, dominant, and additive models. In the recessive model, we found two tSNPs (rs2297440 and rs6010620) associated with increased astrocytoma risk. In the dominant model, we found that rs2853676 was associated with increased astrocytoma risk. In the additive model, all three tSNPs (rs2297440, rs2853676, and rs6010620) were associated with increased astrocytoma risk. Our results demonstrate, for the first time, the potential roles of RTEL1 and TERT in astrocytoma development.

SEMIPARAMETRIC ADDITIVE RISKS REGRESSION FOR TWO-STAGE DESIGN SURVIVAL STUDIES

PubMed Central

Li, Gang; Wu, Tong Tong

2011-01-01

In this article we study a semiparametric additive risks model (McKeague and Sasieni (1994)) for two-stage design survival data where accurate information is available only on second stage subjects, a subset of the first stage study. We derive two-stage estimators by combining data from both stages. Large sample inferences are developed. As a by-product, we also obtain asymptotic properties of the single stage estimators of McKeague and Sasieni (1994) when the semiparametric additive risks model is misspecified. The proposed two-stage estimators are shown to be asymptotically more efficient than the second stage estimators. They also demonstrate smaller bias and variance for finite samples. The developed methods are illustrated using small intestine cancer data from the SEER (Surveillance, Epidemiology, and End Results) Program. PMID:21931467

Innovative Models of Dental Care Delivery and Coverage: Patient-Centric Dental Benefits Based on Digital Oral Health Risk Assessment.

PubMed

Martin, John; Mills, Shannon; Foley, Mary E

2018-04-01

Innovative models of dental care delivery and coverage are emerging across oral health care systems causing changes to treatment and benefit plans. A novel addition to these models is digital risk assessment, which offers a promising new approach that incorporates the use of a cloud-based technology platform to assess an individual patient's risk for oral disease. Risk assessment changes treatment by including risk as a modifier of treatment and as a determinant of preventive services. Benefit plans are being developed to use risk assessment to predetermine preventive benefits for patients identified at elevated risk for oral disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Application of the two-stage clonal expansion model in characterizing the joint effect of exposure to two carcinogens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zielinski, J.M.; Krewski, D.

1992-12-31

In this paper, we describe application of the two-stage clonal expansion model to characterize the joint effect of exposure to two carcinogens. This biologically based model of carcinogenesis provides a useful framework for the quantitative description of carcinogenic risks and for defining agents that act as initiators, promoters, and completers. Depending on the mechanism of action, the agent-specific relative risk following exposure to two carcinogens can be additive, multiplicative, or supramultiplicative, with supra-additive relative risk indicating a synergistic effect between the two agents. Maximum-likelihood methods for fitting the two-stage clonal expansion model with intermittent exposure to two carcinogens are describedmore » and illustrated, using data on lung-cancer mortality among Colorado uranium miners exposed to both radon and tobacco smoke.« less

Improving measurement of injection drug risk behavior using item response theory.

PubMed

Janulis, Patrick

2014-03-01

Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored. To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning. Data is used from three studies in the National Institute on Drug Abuse's Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning. Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data. Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.

Additivity and Interactions in Ecotoxicity of Pollutant Mixtures: Some Patterns, Conclusions, and Open Questions

PubMed Central

Rodea-Palomares, Ismael; González-Pleiter, Miguel; Martín-Betancor, Keila; Rosal, Roberto; Fernández-Piñas, Francisca

2015-01-01

Understanding the effects of exposure to chemical mixtures is a common goal of pharmacology and ecotoxicology. In risk assessment-oriented ecotoxicology, defining the scope of application of additivity models has received utmost attention in the last 20 years, since they potentially allow one to predict the effect of any chemical mixture relying on individual chemical information only. The gold standard for additivity in ecotoxicology has demonstrated to be Loewe additivity which originated the so-called Concentration Addition (CA) additivity model. In pharmacology, the search for interactions or deviations from additivity (synergism and antagonism) has similarly captured the attention of researchers over the last 20 years and has resulted in the definition and application of the Combination Index (CI) Theorem. CI is based on Loewe additivity, but focused on the identification and quantification of synergism and antagonism. Despite additive models demonstrating a surprisingly good predictive power in chemical mixture risk assessment, concerns still exist due to the occurrence of unpredictable synergism or antagonism in certain experimental situations. In the present work, we summarize the parallel history of development of CA, IA, and CI models. We also summarize the applicability of these concepts in ecotoxicology and how their information may be integrated, as well as the possibility of prediction of synergism. Inside the box, the main question remaining is whether it is worthy to consider departures from additivity in mixture risk assessment and how to predict interactions among certain mixture components. Outside the box, the main question is whether the results observed under the experimental constraints imposed by fractional approaches are a de fide reflection of what it would be expected from chemical mixtures in real world circumstances. PMID:29051468

Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population

PubMed Central

Yamakado, Minoru; Nagao, Kenji; Imaizumi, Akira; Tani, Mizuki; Toda, Akiko; Tanaka, Takayuki; Jinzu, Hiroko; Miyano, Hiroshi; Yamamoto, Hiroshi; Daimon, Takashi; Horimoto, Katsuhisa; Ishizaka, Yuko

2015-01-01

Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals’ future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. PMID:26156880

A Dual-Process Approach to Health Risk Decision Making: The Prototype Willingness Model

ERIC Educational Resources Information Center

Gerrard, Meg; Gibbons, Frederick X.; Houlihan, Amy E.; Stock, Michelle L.; Pomery, Elizabeth A.

2008-01-01

Although dual-process models in cognitive, personality, and social psychology have stimulated a large body of research about analytic and heuristic modes of decision making, these models have seldom been applied to the study of adolescent risk behaviors. In addition, the developmental course of these two kinds of information processing, and their…

Quantile uncertainty and value-at-risk model risk.

PubMed

Alexander, Carol; Sarabia, José María

2012-08-01

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value-at-Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of "model risk" in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value-at-Risk model risk and compute the required regulatory capital add-on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value-at-Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks. © 2012 Society for Risk Analysis.

Evaluating cardiovascular mortality in type 2 diabetes patients: an analysis based on competing risks Markov chains and additive regression models.

PubMed

Rosato, Rosalba; Ciccone, G; Bo, S; Pagano, G F; Merletti, F; Gregori, D

2007-06-01

Type 2 diabetes represents a condition significantly associated with increased cardiovascular mortality. The aims of the study are: (i) to estimate the cumulative incidence function for cause-specific mortality using Cox and Aalen model; (ii) to describe how the prediction of cardiovascular or other causes mortality changes for patients with different pattern of covariates; (iii) to show if different statistical methods may give different results. Cox and Aalen additive regression model through the Markov chain approach, are used to estimate the cause-specific hazard for cardiovascular or other causes mortality in a cohort of 2865 type 2 diabetic patients without insulin treatment. The models are compared in the estimation of the risk of death for patients of different severity. For younger patients with a better covariates profile, the Cumulative Incidence Function estimated by Cox and Aalen model was almost the same; for patients with the worst covariates profile, models gave different results: at the end of follow-up cardiovascular mortality rate estimated by Cox and Aalen model was 0.26 [95% confidence interval (CI) = 0.21-0.31] and 0.14 (95% CI = 0.09-0.18). Standard Cox and Aalen model capture the risk process for patients equally well with average profiles of co-morbidities. The Aalen model, in addition, is shown to be better at identifying cause-specific risk of death for patients with more severe clinical profiles. This result is relevant in the development of analytic tools for research and resource management within diabetes care.

A post-crisis assessment of retirement income adequacy for Baby Boomers and Gen Xers.

PubMed

VanDerhei, Jack

2011-02-01

DETERMINING THOSE "AT RISK" OF INSUFFICIENT RETIREMENT INCOME: The analysis in this paper was designed to answer two questions: 1) What percentage of U.S. households became "at risk" of insufficient retirement income as a result of the financial market and real estate crisis in 2008 and 2009? 2) Of those who are at risk, what additional savings do they need to make each year until retirement age to make up for their losses from the crisis? The results are from the 2010 EBRI Retirement Security Projection Model by the Employee Benefit Research Institute. Range at risk: The percentage of households that would not have been "at risk" without the 2008-2009 crisis but that ended up "at risk" varies from a low of 3.8 percent to a high of 14.3 percent. 50-50 chance of adequacy: Looking at all Early Boomer households that would need to save an additional amount (over and above the savings already factored into the baseline model), the median percentage of additional compensation for these households desiring a 50 percent probability of retirement income adequacy would be 3.0 percent of compensation each year until retirement age to account for the financial and housing market crisis in 2008 and 2009. 90 percent chance of adequacy: Looking at all Early Boomer households that would need to save an additional amount (over and above the savings already factored into the baseline model), the median percentage of additional compensation for these households desiring a 90 percent probability of retirement income adequacy would be 4.3 percent of compensation. Range of adequacy: Looking only at Early Boomer households that would need to save an additional amount (over and above the savings already factored into the baseline model), that had account balances in defined contribution plans and IRAs as well as exposure to the real estate crisis in 2008 and 2009 shows a median percentage for of 5.6 percent for a 50 percent probability and 6.7 percent for a 90 percent probability of retirement income adequacy.

Cardiovascular Risk Reduction in Children.

ERIC Educational Resources Information Center

Murray, David M.; And Others

1987-01-01

The paper presents a community model for reducing the risk of coronary heart disease in children and youth. The model addresses the individual, the family, social groups, and the larger social and physical environments. Exemplary programs are described and recommendations are made for additional research and program development. (Author/DB)

Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study

PubMed Central

ten Haaf, Kevin; Tammemägi, Martin C.; Han, Summer S.; Kong, Chung Yin; Plevritis, Sylvia K.; de Koning, Harry J.; Steyerberg, Ewout W.

2017-01-01

Background Selection of candidates for lung cancer screening based on individual risk has been proposed as an alternative to criteria based on age and cumulative smoking exposure (pack-years). Nine previously established risk models were assessed for their ability to identify those most likely to develop or die from lung cancer. All models considered age and various aspects of smoking exposure (smoking status, smoking duration, cigarettes per day, pack-years smoked, time since smoking cessation) as risk predictors. In addition, some models considered factors such as gender, race, ethnicity, education, body mass index, chronic obstructive pulmonary disease, emphysema, personal history of cancer, personal history of pneumonia, and family history of lung cancer. Methods and findings Retrospective analyses were performed on 53,452 National Lung Screening Trial (NLST) participants (1,925 lung cancer cases and 884 lung cancer deaths) and 80,672 Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) ever-smoking participants (1,463 lung cancer cases and 915 lung cancer deaths). Six-year lung cancer incidence and mortality risk predictions were assessed for (1) calibration (graphically) by comparing the agreement between the predicted and the observed risks, (2) discrimination (area under the receiver operating characteristic curve [AUC]) between individuals with and without lung cancer (death), and (3) clinical usefulness (net benefit in decision curve analysis) by identifying risk thresholds at which applying risk-based eligibility would improve lung cancer screening efficacy. To further assess performance, risk model sensitivities and specificities in the PLCO were compared to those based on the NLST eligibility criteria. Calibration was satisfactory, but discrimination ranged widely (AUCs from 0.61 to 0.81). The models outperformed the NLST eligibility criteria over a substantial range of risk thresholds in decision curve analysis, with a higher sensitivity for all models and a slightly higher specificity for some models. The PLCOm2012, Bach, and Two-Stage Clonal Expansion incidence models had the best overall performance, with AUCs >0.68 in the NLST and >0.77 in the PLCO. These three models had the highest sensitivity and specificity for predicting 6-y lung cancer incidence in the PLCO chest radiography arm, with sensitivities >79.8% and specificities >62.3%. In contrast, the NLST eligibility criteria yielded a sensitivity of 71.4% and a specificity of 62.2%. Limitations of this study include the lack of identification of optimal risk thresholds, as this requires additional information on the long-term benefits (e.g., life-years gained and mortality reduction) and harms (e.g., overdiagnosis) of risk-based screening strategies using these models. In addition, information on some predictor variables included in the risk prediction models was not available. Conclusions Selection of individuals for lung cancer screening using individual risk is superior to selection criteria based on age and pack-years alone. The benefits, harms, and feasibility of implementing lung cancer screening policies based on risk prediction models should be assessed and compared with those of current recommendations. PMID:28376113

Detection of the toughest: Pedestrian injury risk as a smooth function of age.

PubMed

Niebuhr, Tobias; Junge, Mirko

2017-07-04

Though it is common to refer to age-specific groups (e.g., children, adults, elderly), smooth trends conditional on age are mainly ignored in the literature. The present study examines the pedestrian injury risk in full-frontal pedestrian-to-passenger car accidents and incorporates age-in addition to collision speed and injury severity-as a plug-in parameter. Recent work introduced a model for pedestrian injury risk functions using explicit formulae with easily interpretable model parameters. This model is expanded by pedestrian age as another model parameter. Using the German In-Depth Accident Study (GIDAS) to obtain age-specific risk proportions, the model parameters are fitted to the raw data and then smoothed by broken-line regression. The approach supplies explicit probabilities for pedestrian injury risk conditional on pedestrian age, collision speed, and injury severity under investigation. All results yield consistency to each other in the sense that risks for more severe injuries are less probable than those for less severe injuries. As a side product, the approach indicates specific ages at which the risk behavior fundamentally changes. These threshold values can be interpreted as the most robust ages for pedestrians. The obtained age-wise risk functions can be aggregated and adapted to any population. The presented approach is formulated in such general terms that in can be directly used for other data sets or additional parameters; for example, the pedestrian's sex. Thus far, no other study using age as a plug-in parameter can be found.

C-reactive protein, fibrinogen, and cardiovascular disease prediction.

PubMed

Kaptoge, Stephen; Di Angelantonio, Emanuele; Pennells, Lisa; Wood, Angela M; White, Ian R; Gao, Pei; Walker, Matthew; Thompson, Alexander; Sarwar, Nadeem; Caslake, Muriel; Butterworth, Adam S; Amouyel, Philippe; Assmann, Gerd; Bakker, Stephan J L; Barr, Elizabeth L M; Barrett-Connor, Elizabeth; Benjamin, Emelia J; Björkelund, Cecilia; Brenner, Hermann; Brunner, Eric; Clarke, Robert; Cooper, Jackie A; Cremer, Peter; Cushman, Mary; Dagenais, Gilles R; D'Agostino, Ralph B; Dankner, Rachel; Davey-Smith, George; Deeg, Dorly; Dekker, Jacqueline M; Engström, Gunnar; Folsom, Aaron R; Fowkes, F Gerry R; Gallacher, John; Gaziano, J Michael; Giampaoli, Simona; Gillum, Richard F; Hofman, Albert; Howard, Barbara V; Ingelsson, Erik; Iso, Hiroyasu; Jørgensen, Torben; Kiechl, Stefan; Kitamura, Akihiko; Kiyohara, Yutaka; Koenig, Wolfgang; Kromhout, Daan; Kuller, Lewis H; Lawlor, Debbie A; Meade, Tom W; Nissinen, Aulikki; Nordestgaard, Børge G; Onat, Altan; Panagiotakos, Demosthenes B; Psaty, Bruce M; Rodriguez, Beatriz; Rosengren, Annika; Salomaa, Veikko; Kauhanen, Jussi; Salonen, Jukka T; Shaffer, Jonathan A; Shea, Steven; Ford, Ian; Stehouwer, Coen D A; Strandberg, Timo E; Tipping, Robert W; Tosetto, Alberto; Wassertheil-Smoller, Sylvia; Wennberg, Patrik; Westendorp, Rudi G; Whincup, Peter H; Wilhelmsen, Lars; Woodward, Mark; Lowe, Gordon D O; Wareham, Nicholas J; Khaw, Kay-Tee; Sattar, Naveed; Packard, Chris J; Gudnason, Vilmundur; Ridker, Paul M; Pepys, Mark B; Thompson, Simon G; Danesh, John

2012-10-04

There is debate about the value of assessing levels of C-reactive protein (CRP) and other biomarkers of inflammation for the prediction of first cardiovascular events. We analyzed data from 52 prospective studies that included 246,669 participants without a history of cardiovascular disease to investigate the value of adding CRP or fibrinogen levels to conventional risk factors for the prediction of cardiovascular risk. We calculated measures of discrimination and reclassification during follow-up and modeled the clinical implications of initiation of statin therapy after the assessment of CRP or fibrinogen. The addition of information on high-density lipoprotein cholesterol to a prognostic model for cardiovascular disease that included age, sex, smoking status, blood pressure, history of diabetes, and total cholesterol level increased the C-index, a measure of risk discrimination, by 0.0050. The further addition to this model of information on CRP or fibrinogen increased the C-index by 0.0039 and 0.0027, respectively (P<0.001), and yielded a net reclassification improvement of 1.52% and 0.83%, respectively, for the predicted 10-year risk categories of "low" (<10%), "intermediate" (10% to <20%), and "high" (≥20%) (P<0.02 for both comparisons). We estimated that among 100,000 adults 40 years of age or older, 15,025 persons would initially be classified as being at intermediate risk for a cardiovascular event if conventional risk factors alone were used to calculate risk. Assuming that statin therapy would be initiated in accordance with Adult Treatment Panel III guidelines (i.e., for persons with a predicted risk of ≥20% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), additional targeted assessment of CRP or fibrinogen levels in the 13,199 remaining participants at intermediate risk could help prevent approximately 30 additional cardiovascular events over the course of 10 years. In a study of people without known cardiovascular disease, we estimated that under current treatment guidelines, assessment of the CRP or fibrinogen level in people at intermediate risk for a cardiovascular event could help prevent one additional event over a period of 10 years for every 400 to 500 people screened. (Funded by the British Heart Foundation and others.).

Chemotherapy effectiveness and mortality prediction in surgically treated osteosarcoma dogs: A validation study.

PubMed

Schmidt, A F; Nielen, M; Withrow, S J; Selmic, L E; Burton, J H; Klungel, O H; Groenwold, R H H; Kirpensteijn, J

2016-03-01

Canine osteosarcoma is the most common bone cancer, and an important cause of mortality and morbidity, in large purebred dogs. Previously we constructed two multivariable models to predict a dog's 5-month or 1-year mortality risk after surgical treatment for osteosarcoma. According to the 5-month model, dogs with a relatively low risk of 5-month mortality benefited most from additional chemotherapy treatment. In the present study, we externally validated these results using an independent cohort study of 794 dogs. External performance of our prediction models showed some disagreement between observed and predicted risk, mean difference: -0.11 (95% confidence interval [95% CI]-0.29; 0.08) for 5-month risk and 0.25 (95%CI 0.10; 0.40) for 1-year mortality risk. After updating the intercept, agreement improved: -0.0004 (95%CI-0.16; 0.16) and -0.002 (95%CI-0.15; 0.15). The chemotherapy by predicted mortality risk interaction (P-value=0.01) showed that the chemotherapy compared to no chemotherapy effectiveness was modified by 5-month mortality risk: dogs with a relatively lower risk of mortality benefited most from additional chemotherapy. Chemotherapy effectiveness on 1-year mortality was not significantly modified by predicted risk (P-value=0.28). In conclusion, this external validation study confirmed that our multivariable risk prediction models can predict a patient's mortality risk and that dogs with a relatively lower risk of 5-month mortality seem to benefit most from chemotherapy. Copyright © 2016 Elsevier B.V. All rights reserved.

How to interpret a small increase in AUC with an additional risk prediction marker: decision analysis comes through.

PubMed

Baker, Stuart G; Schuit, Ewoud; Steyerberg, Ewout W; Pencina, Michael J; Vickers, Andrew; Vickers, Andew; Moons, Karel G M; Mol, Ben W J; Lindeman, Karen S

2014-09-28

An important question in the evaluation of an additional risk prediction marker is how to interpret a small increase in the area under the receiver operating characteristic curve (AUC). Many researchers believe that a change in AUC is a poor metric because it increases only slightly with the addition of a marker with a large odds ratio. Because it is not possible on purely statistical grounds to choose between the odds ratio and AUC, we invoke decision analysis, which incorporates costs and benefits. For example, a timely estimate of the risk of later non-elective operative delivery can help a woman in labor decide if she wants an early elective cesarean section to avoid greater complications from possible later non-elective operative delivery. A basic risk prediction model for later non-elective operative delivery involves only antepartum markers. Because adding intrapartum markers to this risk prediction model increases AUC by 0.02, we questioned whether this small improvement is worthwhile. A key decision-analytic quantity is the risk threshold, here the risk of later non-elective operative delivery at which a patient would be indifferent between an early elective cesarean section and usual care. For a range of risk thresholds, we found that an increase in the net benefit of risk prediction requires collecting intrapartum marker data on 68 to 124 women for every correct prediction of later non-elective operative delivery. Because data collection is non-invasive, this test tradeoff of 68 to 124 is clinically acceptable, indicating the value of adding intrapartum markers to the risk prediction model. Copyright © 2014 John Wiley & Sons, Ltd.

Empirically Based Composite Fracture Prediction Model From the Global Longitudinal Study of Osteoporosis in Postmenopausal Women (GLOW)

PubMed Central

Compston, Juliet E.; Chapurlat, Roland D.; Pfeilschifter, Johannes; Cooper, Cyrus; Hosmer, David W.; Adachi, Jonathan D.; Anderson, Frederick A.; Díez-Pérez, Adolfo; Greenspan, Susan L.; Netelenbos, J. Coen; Nieves, Jeri W.; Rossini, Maurizio; Watts, Nelson B.; Hooven, Frederick H.; LaCroix, Andrea Z.; March, Lyn; Roux, Christian; Saag, Kenneth G.; Siris, Ethel S.; Silverman, Stuart; Gehlbach, Stephen H.

2014-01-01

Context: Several fracture prediction models that combine fractures at different sites into a composite outcome are in current use. However, to the extent individual fracture sites have differing risk factor profiles, model discrimination is impaired. Objective: The objective of the study was to improve model discrimination by developing a 5-year composite fracture prediction model for fracture sites that display similar risk profiles. Design: This was a prospective, observational cohort study. Setting: The study was conducted at primary care practices in 10 countries. Patients: Women aged 55 years or older participated in the study. Intervention: Self-administered questionnaires collected data on patient characteristics, fracture risk factors, and previous fractures. Main Outcome Measure: The main outcome is time to first clinical fracture of hip, pelvis, upper leg, clavicle, or spine, each of which exhibits a strong association with advanced age. Results: Of four composite fracture models considered, model discrimination (c index) is highest for an age-related fracture model (c index of 0.75, 47 066 women), and lowest for Fracture Risk Assessment Tool (FRAX) major fracture and a 10-site model (c indices of 0.67 and 0.65). The unadjusted increase in fracture risk for an additional 10 years of age ranges from 80% to 180% for the individual bones in the age-associated model. Five other fracture sites not considered for the age-associated model (upper arm/shoulder, rib, wrist, lower leg, and ankle) have age associations for an additional 10 years of age from a 10% decrease to a 60% increase. Conclusions: After examining results for 10 different bone fracture sites, advanced age appeared the single best possibility for uniting several different sites, resulting in an empirically based composite fracture risk model. PMID:24423345

Genetic polymorphisms in ALDH2 are associated with drug addiction in a Chinese Han population

PubMed Central

Zhang, Chan; Ding, Heng; Cheng, Yujing; Chen, Wanlu; Li, Qi; Li, Qing; Dai, Run; Luo, Manlin

2017-01-01

We investigated the association between single nucleotide polymorphisms (SNPs) in ALDH2, which has been associated with alcohol dependence and several types of diseases, and the risk of drug addiction in a Chinese Han population. In a case-control study that included 692 cases and 700 healthy controls, eight SNPs in ALDH2 were selected and genotyped using the Sequenom MassARRAY platform. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression after adjusting for age and gender. We determined that rs671 is significantly associated with a 1.551-fold increased drug addiction risk (95% CI = 1.263-1.903; p < 0.001). In the genetic model analysis, we found that rs671 is associated with an increased risk of drug addiction under additive, dominant and recessive models (p < 0.001), while rs886205, rs441 and rs4646778 displayed a decreased drug addiction risk under additive and recessive model, respectively (p < 0.05). SNP rs671 remained significant after Bonferroni correction (p<0.00125). Additionally, we observed that haplotype “GTCAC” was associated with increased drug addiction risk (OR = 1.668; 95% CI, 1.328–2.094, p < 0.001); in contrast, “ATCGC” was a protective haplotype for drug addiction risk (OR = 0.444; 95% CI, 0.281–0.704, p < 0.001). Our findings showed that ALDH2 polymorphisms are significantly associated with the risk of drug addiction in the Chinese Han population. PMID:28052001

Genetic polymorphisms in ALDH2 are associated with drug addiction in a Chinese Han population.

PubMed

Zhang, Chan; Ding, Heng; Cheng, Yujing; Chen, Wanlu; Li, Qi; Li, Qing; Dai, Run; Luo, Manlin

2017-01-31

We investigated the association between single nucleotide polymorphisms (SNPs) in ALDH2, which has been associated with alcohol dependence and several types of diseases, and the risk of drug addiction in a Chinese Han population. In a case-control study that included 692 cases and 700 healthy controls, eight SNPs in ALDH2 were selected and genotyped using the Sequenom MassARRAY platform. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression after adjusting for age and gender. We determined that rs671 is significantly associated with a 1.551-fold increased drug addiction risk (95% CI = 1.263-1.903; p < 0.001). In the genetic model analysis, we found that rs671 is associated with an increased risk of drug addiction under additive, dominant and recessive models (p < 0.001), while rs886205, rs441 and rs4646778 displayed a decreased drug addiction risk under additive and recessive model, respectively (p < 0.05). SNP rs671 remained significant after Bonferroni correction (p<0.00125). Additionally, we observed that haplotype "GTCAC" was associated with increased drug addiction risk (OR = 1.668; 95% CI, 1.328-2.094, p < 0.001); in contrast, "ATCGC" was a protective haplotype for drug addiction risk (OR = 0.444; 95% CI, 0.281-0.704, p < 0.001). Our findings showed that ALDH2 polymorphisms are significantly associated with the risk of drug addiction in the Chinese Han population.

Prediction of HIV Sexual Risk Behaviors among Disadvantaged African American Adults using a Syndemic Conceptual Framework

PubMed Central

Nehl, Eric J.; Klein, Hugh; Sterk, Claire E.; Elifson, Kirk W.

2015-01-01

The focus of this paper is on HIV sexual risk taking among a community-based sample of disadvantaged African American adults. The objective is to examine multiple factors associated with sexual HIV risk behaviors within a syndemic conceptual framework. Face-to-face, computer-assisted, structured interviews were conducted with 1,535 individuals in Atlanta, Georgia. Bivariate analyses indicated a high level of relationships among the HIV sexual risks and other factors. Results from multivariate models indicated that gender, sexual orientation, relationship status, self-esteem, condom use self-efficacy, sex while the respondent was high, and sex while the partner was high were significant predictors of condomless sex. Additionally, a multivariate additive model of risk behaviors indicated that the number of health risks significantly increased the risk of condomless sex. This intersection of HIV sexual risk behaviors and their associations with various other behavioral, socio-demographics, and psychological functioning factors helps explain HIV risk-taking among this sample of African American adults and highlights the need for research and practice that accounts for multiple health behaviors and problems. PMID:26188618

DEVELOPMENT AND REVIEW OF MONITORING METHODS AND RISK ASSESSMENT MODELS USED TO DETERMINE THE EFFECTS OF BIOSOLIDS LAND APPLICATION ON HUMAN HEALTH AND THE ENVIRONMENT

EPA Science Inventory

Development and Review of monitoring methods and risk assessment models for biosolids land application impacts on air and land

Ronald F Herrmann (NRMRL), Mike Broder (NCEA), and Mike Ware (NERL)

Science Questions .

MYP Science Question: What additional model...

Spatial model for risk prediction and sub-national prioritization to aid poliovirus eradication in Pakistan.

PubMed

Mercer, Laina D; Safdar, Rana M; Ahmed, Jamal; Mahamud, Abdirahman; Khan, M Muzaffar; Gerber, Sue; O'Leary, Aiden; Ryan, Mike; Salet, Frank; Kroiss, Steve J; Lyons, Hil; Upfill-Brown, Alexander; Chabot-Couture, Guillaume

2017-10-11

Pakistan is one of only three countries where poliovirus circulation remains endemic. For the Pakistan Polio Eradication Program, identifying high risk districts is essential to target interventions and allocate limited resources. Using a hierarchical Bayesian framework we developed a spatial Poisson hurdle model to jointly model the probability of one or more paralytic polio cases, and the number of cases that would be detected in the event of an outbreak. Rates of underimmunization, routine immunization, and population immunity, as well as seasonality and a history of cases were used to project future risk of cases. The expected number of cases in each district in a 6-month period was predicted using indicators from the previous 6-months and the estimated coefficients from the model. The model achieves an average of 90% predictive accuracy as measured by area under the receiver operating characteristic (ROC) curve, for the past 3 years of cases. The risk of poliovirus has decreased dramatically in many of the key reservoir areas in Pakistan. The results of this model have been used to prioritize sub-national areas in Pakistan to receive additional immunization activities, additional monitoring, or other special interventions.

Drivers and hotspots of extinction risk in marine mammals.

PubMed

Davidson, Ana D; Boyer, Alison G; Kim, Hwahwan; Pompa-Mansilla, Sandra; Hamilton, Marcus J; Costa, Daniel P; Ceballos, Gerardo; Brown, James H

2012-02-28

The world's oceans are undergoing profound changes as a result of human activities. However, the consequences of escalating human impacts on marine mammal biodiversity remain poorly understood. The International Union for the Conservation of Nature (IUCN) identifies 25% of marine mammals as at risk of extinction, but the conservation status of nearly 40% of marine mammals remains unknown due to insufficient data. Predictive models of extinction risk are crucial to informing present and future conservation needs, yet such models have not been developed for marine mammals. In this paper, we: (i) used powerful machine-learning and spatial-modeling approaches to understand the intrinsic and extrinsic drivers of marine mammal extinction risk; (ii) used this information to predict risk across all marine mammals, including IUCN "Data Deficient" species; and (iii) conducted a spatially explicit assessment of these results to understand how risk is distributed across the world's oceans. Rate of offspring production was the most important predictor of risk. Additional predictors included taxonomic group, small geographic range area, and small social group size. Although the interaction of both intrinsic and extrinsic variables was important in predicting risk, overall, intrinsic traits were more important than extrinsic variables. In addition to the 32 species already on the IUCN Red List, our model identified 15 more species, suggesting that 37% of all marine mammals are at risk of extinction. Most at-risk species occur in coastal areas and in productive regions of the high seas. We identify 13 global hotspots of risk and show how they overlap with human impacts and Marine Protected Areas.

A model-based analysis of decision making under risk in obsessive-compulsive and hoarding disorders.

PubMed

Aranovich, Gabriel J; Cavagnaro, Daniel R; Pitt, Mark A; Myung, Jay I; Mathews, Carol A

2017-07-01

Attitudes towards risk are highly consequential in clinical disorders thought to be prone to "risky behavior", such as substance dependence, as well as those commonly associated with excessive risk aversion, such as obsessive-compulsive disorder (OCD) and hoarding disorder (HD). Moreover, it has recently been suggested that attitudes towards risk may serve as a behavioral biomarker for OCD. We investigated the risk preferences of participants with OCD and HD using a novel adaptive task and a quantitative model from behavioral economics that decomposes risk preferences into outcome sensitivity and probability sensitivity. Contrary to expectation, compared to healthy controls, participants with OCD and HD exhibited less outcome sensitivity, implying less risk aversion in the standard economic framework. In addition, risk attitudes were strongly correlated with depression, hoarding, and compulsion scores, while compulsion (hoarding) scores were associated with more (less) "rational" risk preferences. These results demonstrate how fundamental attitudes towards risk relate to specific psychopathology and thereby contribute to our understanding of the cognitive manifestations of mental disorders. In addition, our findings indicate that the conclusion made in recent work that decision making under risk is unaltered in OCD is premature. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improving risk assessment of color additives in medical device polymers.

PubMed

Chandrasekar, Vaishnavi; Janes, Dustin W; Forrey, Christopher; Saylor, David M; Bajaj, Akhil; Duncan, Timothy V; Zheng, Jiwen; Riaz Ahmed, Kausar B; Casey, Brendan J

2018-01-01

Many polymeric medical device materials contain color additives which could lead to adverse health effects. The potential health risk of color additives may be assessed by comparing the amount of color additive released over time to levels deemed to be safe based on available toxicity data. We propose a conservative model for exposure that requires only the diffusion coefficient of the additive in the polymer matrix, D, to be specified. The model is applied here using a model polymer (poly(ether-block-amide), PEBAX 2533) and color additive (quinizarin blue) system. Sorption experiments performed in an aqueous dispersion of quinizarin blue (QB) into neat PEBAX yielded a diffusivity D = 4.8 × 10 -10 cm 2  s -1 , and solubility S = 0.32 wt %. On the basis of these measurements, we validated the model by comparing predictions to the leaching profile of QB from a PEBAX matrix into physiologically representative media. Toxicity data are not available to estimate a safe level of exposure to QB, as a result, we used a Threshold of Toxicological Concern (TTC) value for QB of 90 µg/adult/day. Because only 30% of the QB is released in the first day of leaching for our film thickness and calculated D, we demonstrate that a device may contain significantly more color additive than the TTC value without giving rise to a toxicological concern. The findings suggest that an initial screening-level risk assessment of color additives and other potentially toxic compounds found in device polymers can be improved. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 310-319, 2018. © 2017 Wiley Periodicals, Inc.

A probabilistic topic model for clinical risk stratification from electronic health records.

PubMed

Huang, Zhengxing; Dong, Wei; Duan, Huilong

2015-12-01

Risk stratification aims to provide physicians with the accurate assessment of a patient's clinical risk such that an individualized prevention or management strategy can be developed and delivered. Existing risk stratification techniques mainly focus on predicting the overall risk of an individual patient in a supervised manner, and, at the cohort level, often offer little insight beyond a flat score-based segmentation from the labeled clinical dataset. To this end, in this paper, we propose a new approach for risk stratification by exploring a large volume of electronic health records (EHRs) in an unsupervised fashion. Along this line, this paper proposes a novel probabilistic topic modeling framework called probabilistic risk stratification model (PRSM) based on Latent Dirichlet Allocation (LDA). The proposed PRSM recognizes a patient clinical state as a probabilistic combination of latent sub-profiles, and generates sub-profile-specific risk tiers of patients from their EHRs in a fully unsupervised fashion. The achieved stratification results can be easily recognized as high-, medium- and low-risk, respectively. In addition, we present an extension of PRSM, called weakly supervised PRSM (WS-PRSM) by incorporating minimum prior information into the model, in order to improve the risk stratification accuracy, and to make our models highly portable to risk stratification tasks of various diseases. We verify the effectiveness of the proposed approach on a clinical dataset containing 3463 coronary heart disease (CHD) patient instances. Both PRSM and WS-PRSM were compared with two established supervised risk stratification algorithms, i.e., logistic regression and support vector machine, and showed the effectiveness of our models in risk stratification of CHD in terms of the Area Under the receiver operating characteristic Curve (AUC) analysis. As well, in comparison with PRSM, WS-PRSM has over 2% performance gain, on the experimental dataset, demonstrating that incorporating risk scoring knowledge as prior information can improve the performance in risk stratification. Experimental results reveal that our models achieve competitive performance in risk stratification in comparison with existing supervised approaches. In addition, the unsupervised nature of our models makes them highly portable to the risk stratification tasks of various diseases. Moreover, patient sub-profiles and sub-profile-specific risk tiers generated by our models are coherent and informative, and provide significant potential to be explored for the further tasks, such as patient cohort analysis. We hypothesize that the proposed framework can readily meet the demand for risk stratification from a large volume of EHRs in an open-ended fashion. Copyright © 2015 Elsevier Inc. All rights reserved.

Adolescent mental health and academic functioning: empirical support for contrasting models of risk and vulnerability.

PubMed

Lucier-Greer, Mallory; O'Neal, Catherine W; Arnold, A Laura; Mancini, Jay A; Wickrama, Kandauda K A S

2014-11-01

Adolescents in military families contend with normative stressors that are universal and exist across social contexts (minority status, family disruptions, and social isolation) as well as stressors reflective of their military life context (e.g., parental deployment, school transitions, and living outside the United States). This study utilizes a social ecological perspective and a stress process lens to examine the relationship between multiple risk factors and relevant indicators of youth well-being, namely depressive symptoms and academic performance, as well as the mediating role of self-efficacy (N = 1,036). Three risk models were tested: an additive effects model (each risk factor uniquely influences outcomes), a full cumulative effects model (the collection of risk factors influences outcomes), a comparative model (a cumulative effects model exploring the differential effects of normative and military-related risks). This design allowed for the simultaneous examination of multiple risk factors and a comparison of alternative perspectives on measuring risk. Each model was predictive of depressive symptoms and academic performance through persistence; however, each model provides unique findings about the relationship between risk factors and youth outcomes. Discussion is provided pertinent to service providers and researchers on how risk is conceptualized and suggestions for identifying at-risk youth. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.

MeProRisk - a Joint Venture for Minimizing Risk in Geothermal Reservoir Development

NASA Astrophysics Data System (ADS)

Clauser, C.; Marquart, G.

2009-12-01

Exploration and development of geothermal reservoirs for the generation of electric energy involves high engineering and economic risks due to the need for 3-D geophysical surface surveys and deep boreholes. The MeProRisk project provides a strategy guideline for reducing these risks by combining cross-disciplinary information from different specialists: Scientists from three German universities and two private companies contribute with new methods in seismic modeling and interpretation, numerical reservoir simulation, estimation of petrophysical parameters, and 3-D visualization. The approach chosen in MeProRisk consists in considering prospecting and developing of geothermal reservoirs as an iterative process. A first conceptual model for fluid flow and heat transport simulation can be developed based on limited available initial information on geology and rock properties. In the next step, additional data is incorporated which is based on (a) new seismic interpretation methods designed for delineating fracture systems, (b) statistical studies on large numbers of rock samples for estimating reliable rock parameters, (c) in situ estimates of the hydraulic conductivity tensor. This results in a continuous refinement of the reservoir model where inverse modelling of fluid flow and heat transport allows infering the uncertainty and resolution of the model at each iteration step. This finally yields a calibrated reservoir model which may be used to direct further exploration by optimizing additional borehole locations, estimate the uncertainty of key operational and economic parameters, and optimize the long-term operation of a geothermal resrvoir.

A Team Mental Model Perspective of Pre-Quantitative Risk

NASA Technical Reports Server (NTRS)

Cooper, Lynne P.

2011-01-01

This study was conducted to better understand how teams conceptualize risk before it can be quantified, and the processes by which a team forms a shared mental model of this pre-quantitative risk. Using an extreme case, this study analyzes seven months of team meeting transcripts, covering the entire lifetime of the team. Through an analysis of team discussions, a rich and varied structural model of risk emerges that goes significantly beyond classical representations of risk as the product of a negative consequence and a probability. In addition to those two fundamental components, the team conceptualization includes the ability to influence outcomes and probabilities, networks of goals, interaction effects, and qualitative judgments about the acceptability of risk, all affected by associated uncertainties. In moving from individual to team mental models, team members employ a number of strategies to gain group recognition of risks and to resolve or accept differences.

Persistent hemifacial spasm after microvascular decompression: a risk assessment model.

PubMed

Shah, Aalap; Horowitz, Michael

2017-06-01

Microvascular decompression (MVD) for hemifacial spasm (HFS) provides resolution of disabling symptoms such as eyelid twitching and muscle contractions of the entire hemiface. The primary aim of this study was to evaluate the predictive value of patient demographics and spasm characteristics on long-term outcomes, with or without intraoperative lateral spread response (LSR) as an additional variable in a risk assessment model. A retrospective study was undertaken to evaluate the associations of pre-operative patient characteristics, as well as intraoperative LSR and need for a staged procedure on the presence of persistent or recurrent HFS at the time of hospital discharge and at follow-up. A risk assessment model was constructed with the inclusion of six clinically or statistically significant variables from the univariate analyses. A receiving operator characteristic curve was generated, and area under the curve was calculated to determine the strength of the predictive model. A risk assessment model was first created consisting of significant pre-operative variables (Model 1) (age >50, female gender, history of botulinum toxin use, platysma muscle involvement). This model demonstrated borderline predictive value for persistent spasm at discharge (AUC .60; p=.045) and fair predictive value at follow-up (AUC .75; p=.001). Intraoperative variables (e.g. LSR persistence) demonstrated little additive value (Model 2) (AUC .67). Patients with a higher risk score (three or greater) demonstrated greater odds of persistent HFS at the time of discharge (OR 1.5 [95%CI 1.16-1.97]; p=.035), as well as greater odds of persistent or recurrent spasm at the time of follow-up (OR 3.0 [95%CI 1.52-5.95]; p=.002) Conclusions: A risk assessment model consisting of pre-operative clinical characteristics is useful in prognosticating HFS persistence at follow-up.

Impact of climate change on global malaria distribution.

PubMed

Caminade, Cyril; Kovats, Sari; Rocklov, Joacim; Tompkins, Adrian M; Morse, Andrew P; Colón-González, Felipe J; Stenlund, Hans; Martens, Pim; Lloyd, Simon J

2014-03-04

Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution.

Impact of climate change on global malaria distribution

PubMed Central

Caminade, Cyril; Kovats, Sari; Rocklov, Joacim; Tompkins, Adrian M.; Morse, Andrew P.; Colón-González, Felipe J.; Stenlund, Hans; Martens, Pim; Lloyd, Simon J.

2014-01-01

Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution. PMID:24596427

Interaction of Reward Seeking and Self-Regulation in the Prediction of Risk Taking: A Cross-National Test of the Dual Systems Model

ERIC Educational Resources Information Center

Duell, Natasha; Steinberg, Laurence; Chein, Jason; Al-Hassan, Suha M.; Bacchini, Dario; Lei, Chang; Chaudhary, Nandita; Di Giunta, Laura; Dodge, Kenneth A.; Fanti, Kostas A.; Lansford, Jennifer E.; Malone, Patrick S.; Oburu, Paul; Pastorelli, Concetta; Skinner, Ann T.; Sorbring, Emma; Tapanya, Sombat; Uribe Tirado, Liliana Maria; Alampay, Liane Peña

2016-01-01

In the present analysis, we test the dual systems model of adolescent risk taking in a cross-national sample of over 5,200 individuals aged 10 through 30 (M = 17.05 years, SD = 5.91) from 11 countries. We examine whether reward seeking and self-regulation make independent, additive, or interactive contributions to risk taking, and ask whether…

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.

2011-01-01

With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455

Improving risk prediction accuracy for new soldiers in the U.S. Army by adding self-report survey data to administrative data.

PubMed

Bernecker, Samantha L; Rosellini, Anthony J; Nock, Matthew K; Chiu, Wai Tat; Gutierrez, Peter M; Hwang, Irving; Joiner, Thomas E; Naifeh, James A; Sampson, Nancy A; Zaslavsky, Alan M; Stein, Murray B; Ursano, Robert J; Kessler, Ronald C

2018-04-03

High rates of mental disorders, suicidality, and interpersonal violence early in the military career have raised interest in implementing preventive interventions with high-risk new enlistees. The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) developed risk-targeting systems for these outcomes based on machine learning methods using administrative data predictors. However, administrative data omit many risk factors, raising the question whether risk targeting could be improved by adding self-report survey data to prediction models. If so, the Army may gain from routinely administering surveys that assess additional risk factors. The STARRS New Soldier Survey was administered to 21,790 Regular Army soldiers who agreed to have survey data linked to administrative records. As reported previously, machine learning models using administrative data as predictors found that small proportions of high-risk soldiers accounted for high proportions of negative outcomes. Other machine learning models using self-report survey data as predictors were developed previously for three of these outcomes: major physical violence and sexual violence perpetration among men and sexual violence victimization among women. Here we examined the extent to which this survey information increases prediction accuracy, over models based solely on administrative data, for those three outcomes. We used discrete-time survival analysis to estimate a series of models predicting first occurrence, assessing how model fit improved and concentration of risk increased when adding the predicted risk score based on survey data to the predicted risk score based on administrative data. The addition of survey data improved prediction significantly for all outcomes. In the most extreme case, the percentage of reported sexual violence victimization among the 5% of female soldiers with highest predicted risk increased from 17.5% using only administrative predictors to 29.4% adding survey predictors, a 67.9% proportional increase in prediction accuracy. Other proportional increases in concentration of risk ranged from 4.8% to 49.5% (median = 26.0%). Data from an ongoing New Soldier Survey could substantially improve accuracy of risk models compared to models based exclusively on administrative predictors. Depending upon the characteristics of interventions used, the increase in targeting accuracy from survey data might offset survey administration costs.

Insecure attachment style as a vulnerability factor for depression: recent findings in a community-based study of Malay single and married mothers.

PubMed

Abdul Kadir, Nor Ba'yah; Bifulco, Antonia

2013-12-30

The role of marital breakdown in women's mental health is of key concern in Malaysia and internationally. A cross-sectional questionnaire study of married and separated/divorced and widowed women examined insecure attachment style as an associated risk factor for depression among 1002 mothers in an urban community in Malaysia. A previous report replicated a UK-based vulnerability-provoking agent model of depression involving negative evaluation of self (NES) and negative elements in close relationships (NECRs) interacting with severe life events to model depression. This article reports on the additional contribution of insecure attachment style to the model using the Vulnerable Attachment Style Questionnaire (VASQ). The results showed that VASQ scores were highly correlated with NES, NECR and depression. A multiple regression analysis of depression with backward elimination found that VASQ scores had a significant additional effect. Group comparisons showed different risk patterns for single and married mothers. NES was the strongest risk factor for both groups, with the 'anxious style' subset of the VASQ being the best additional predictor for married mothers and the total VASQ score (general attachment insecurity) for single mothers. The findings indicate that attachment insecurity adds to a psychosocial vulnerability model of depression among mothers cross-culturally and is important in understanding and identifying risk. © 2013 Elsevier Ireland Ltd. All rights reserved.

Clinical Predictive Models for Chemotherapy-Induced Febrile Neutropenia in Breast Cancer Patients: A Validation Study

PubMed Central

Zhu, Liling; Su, Fengxi; Jia, Weijuan; Deng, Xiaogeng

2014-01-01

Background Predictive models for febrile neutropenia (FN) would be informative for physicians in clinical decision making. This study aims to validate a predictive model (Jenkin’s model) that comprises pretreatment hematological parameters in early-stage breast cancer patients. Patients and Methods A total of 428 breast cancer patients who received neoadjuvant/adjuvant chemotherapy without any prophylactic use of colony-stimulating factor were included. Pretreatment absolute neutrophil counts (ANC) and absolute lymphocyte counts (ALC) were used by the Jenkin’s model to assess the risk of FN. In addition, we modified the threshold of Jenkin’s model and generated Model-A and B. We also developed Model-C by incorporating the absolute monocyte count (AMC) as a predictor into Model-A. The rates of FN in the 1st chemotherapy cycle were calculated. A valid model should be able to significantly identify high-risk subgroup of patients with FN rate >20%. Results Jenkin’s model (Predicted as high-risk when ANC≦3.1*10∧9/L;ALC≦1.5*10∧9/L) did not identify any subgroups with significantly high risk (>20%) of FN in our population, even if we used different thresholds in Model-A(ANC≦4.4*10∧9/L;ALC≦2.1*10∧9/L) or B(ANC≦3.8*10∧9/L;ALC≦1.8*10∧9/L). However, with AMC added as an additional predictor, Model-C(ANC≦4.4*10∧9/L;ALC≦2.1*10∧9/L; AMC≦0.28*10∧9/L) identified a subgroup of patients with a significantly high risk of FN (23.1%). Conclusions In our population, Jenkin’s model, cannot accurately identify patients with a significant risk of FN. The threshold should be changed and the AMC should be incorporated as a predictor, to have excellent predictive ability. PMID:24945817

Changes in diet, cardiovascular risk factors and modelled cardiovascular risk following diagnosis of diabetes: 1-year results from the ADDITION-Cambridge trial cohort.

PubMed

Savory, L A; Griffin, S J; Williams, K M; Prevost, A T; Kinmonth, A-L; Wareham, N J; Simmons, R K

2014-02-01

To describe change in self-reported diet and plasma vitamin C, and to examine associations between change in diet and cardiovascular disease risk factors and modelled 10-year cardiovascular disease risk in the year following diagnosis of Type 2 diabetes. Eight hundred and sixty-seven individuals with screen-detected diabetes underwent assessment of self-reported diet, plasma vitamin C, cardiovascular disease risk factors and modelled cardiovascular disease risk at baseline and 1 year (n = 736) in the ADDITION-Cambridge trial. Multivariable linear regression was used to quantify the association between change in diet and cardiovascular disease risk at 1 year, adjusting for change in physical activity and cardio-protective medication. Participants reported significant reductions in energy, fat and sodium intake, and increases in fruit, vegetable and fibre intake over 1 year. The reduction in energy was equivalent to an average-sized chocolate bar; the increase in fruit was equal to one plum per day. There was a small increase in plasma vitamin C levels. Increases in fruit intake and plasma vitamin C were associated with small reductions in anthropometric and metabolic risk factors. Increased vegetable intake was associated with an increase in BMI and waist circumference. Reductions in fat, energy and sodium intake were associated with reduction in HbA1c , waist circumference and total cholesterol/modelled cardiovascular disease risk, respectively. Improvements in dietary behaviour in this screen-detected population were associated with small reductions in cardiovascular disease risk, independently of change in cardio-protective medication and physical activity. Dietary change may have a role to play in the reduction of cardiovascular disease risk following diagnosis of diabetes. © 2013 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.

Prognostic value, clinical effectiveness and cost-effectiveness of high sensitivity C-reactive protein as a marker in primary prevention of major cardiac events.

PubMed

Schnell-Inderst, Petra; Schwarzer, Ruth; Göhler, Alexander; Grandi, Norma; Grabein, Kristin; Stollenwerk, Björn; Klauß, Volker; Wasem, Jürgen; Siebert, Uwe

2009-05-12

In a substantial portion of patients (= 25%) with coronary heart disease (CHD), a myocardial infarction or sudden cardiac death without prior symptoms is the first manifestation of disease. The use of new risk predictors for CHD such as the high-sensitivity C-reactive Protein (hs-CRP) in addition to established risk factors could improve prediction of CHD. As a consequence of the altered risk assessment, modified preventive actions could reduce the number of cardiac death and non-fatal myocardial infarction. Does the additional information gained through the measurement of hs-CRP in asymptomatic patients lead to a clinically relevant improvement in risk prediction as compared to risk prediction based on traditional risk factors and is this cost-effective? A literature search of the electronic databases of the German Institute of Medical Documentation and Information (DIMDI) was conducted. Selection, data extraction, assessment of the study-quality and synthesis of information was conducted according to the methods of evidence-based medicine. Eight publications about predictive value, one publication on the clinical efficacy and three health-economic evaluations were included. In the seven study populations of the prediction studies, elevated CRP-levels were almost always associated with a higher risk of cardiovascular events and non-fatal myocardial infarctions or cardiac death and severe cardiovascular events. The effect estimates (odds ratio (OR), relative risk (RR), hazard ratio (HR)), once adjusted for traditional risk factors, demonstrated a moderate, independent association between hs-CRP and cardiac and cardiovascular events that fell in the range of 0.7 to 2.47. In six of the seven studies, a moderate increase in the area under the curve (AUC) could be detected by adding hs-CRP as a predictor to regression models in addition to established risk factors though in three cases this was not statistically significant. The difference [in the AUC] between the models with and without hs-CRP fell between 0.00 and 0.023 with a median of 0.003. A decision-analytic modeling study reported a gain in life-expectancy for those using statin therapy for populations with elevated hs-CRP levels and normal lipid levels as compared to statin therapy for those with elevated lipid levels (approximately 6.6 months gain in life-expectancy for 58 year olds). Two decision-analytic models (three publications) on cost-effectiveness reported incremental cost-effectiveness ratios between Euro 8,700 and 50,000 per life year gained for the German context and between 52,000 and 708,000 for the US context. The empirical input data for the model is highly uncertain. No sufficient evidence is available to support the notion that hs-CRP-values should be measured during the global risk assessment for CAD or cardiovascular disease in addition to the traditional risk factors. The additional measurement of the hs-CRP-level increases the incremental predictive value of the risk prediction. It has not yet been clarified whether this increase is clinically relevant resulting in reduction of cardiovascular morbidity and mortality. For people with medium cardiovascular risk (5 to 20% in ten years) additional measurement of hs-CRP seems most likely to be clinical relevant to support the decision as to whether or not additional statin therapy should be initiated for primary prevention. Statin therapy can reduce the occurrence of cardiovascular events for asymptomatic individuals with normal lipid and elevated hs-CRP levels. However, this is not enough to provide evidence for a clinical benefit of hs-CRP-screening. The cost-effectiveness of general hs-CRP-screening as well as screening among only those with normal lipid levels remains unknown at present.

Temporal and geographical external validation study and extension of the Mayo Clinic prediction model to predict eGFR in the younger population of Swiss ADPKD patients.

PubMed

Girardat-Rotar, Laura; Braun, Julia; Puhan, Milo A; Abraham, Alison G; Serra, Andreas L

2017-07-17

Prediction models in autosomal dominant polycystic kidney disease (ADPKD) are useful in clinical settings to identify patients with greater risk of a rapid disease progression in whom a treatment may have more benefits than harms. Mayo Clinic investigators developed a risk prediction tool for ADPKD patients using a single kidney value. Our aim was to perform an independent geographical and temporal external validation as well as evaluate the potential for improving the predictive performance by including additional information on total kidney volume. We used data from the on-going Swiss ADPKD study from 2006 to 2016. The main analysis included a sample size of 214 patients with Typical ADPKD (Class 1). We evaluated the Mayo Clinic model performance calibration and discrimination in our external sample and assessed whether predictive performance could be improved through the addition of subsequent kidney volume measurements beyond the baseline assessment. The calibration of both versions of the Mayo Clinic prediction model using continuous Height adjusted total kidney volume (HtTKV) and using risk subclasses was good, with R 2 of 78% and 70%, respectively. Accuracy was also good with 91.5% and 88.7% of the predicted within 30% of the observed, respectively. Additional information regarding kidney volume did not substantially improve the model performance. The Mayo Clinic prediction models are generalizable to other clinical settings and provide an accurate tool based on available predictors to identify patients at high risk for rapid disease progression.

Integration of PKPD relationships into benefit–risk analysis

PubMed Central

Bellanti, Francesco; van Wijk, Rob C; Danhof, Meindert; Della Pasqua, Oscar

2015-01-01

Aim Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit–risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit–risk assessment. In addition, we propose the use of pharmacokinetic–pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents. Methods A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit–risk assessment and modelling and simulation were identified. In parallel, a critical review of multi-criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile. Results A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit–risk balance continue to rely on subjective expert opinion. By contrast, a model-informed approach offers the opportunity for a more comprehensive evaluation of benefit–risk balance before extensive evidence is generated in clinical practice. Conclusions Benefit–risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials. PMID:25940398

Integration of PKPD relationships into benefit-risk analysis.

PubMed

Bellanti, Francesco; van Wijk, Rob C; Danhof, Meindert; Della Pasqua, Oscar

2015-11-01

Despite the continuous endeavour to achieve high standards in medical care through effectiveness measures, a quantitative framework for the assessment of the benefit-risk balance of new medicines is lacking prior to regulatory approval. The aim of this short review is to summarise the approaches currently available for benefit-risk assessment. In addition, we propose the use of pharmacokinetic-pharmacodynamic (PKPD) modelling as the pharmacological basis for evidence synthesis and evaluation of novel therapeutic agents. A comprehensive literature search has been performed using MESH terms in PubMed, in which articles describing benefit-risk assessment and modelling and simulation were identified. In parallel, a critical review of multi-criteria decision analysis (MCDA) is presented as a tool for characterising a drug's safety and efficacy profile. A definition of benefits and risks has been proposed by the European Medicines Agency (EMA), in which qualitative and quantitative elements are included. However, in spite of the value of MCDA as a quantitative method, decisions about benefit-risk balance continue to rely on subjective expert opinion. By contrast, a model-informed approach offers the opportunity for a more comprehensive evaluation of benefit-risk balance before extensive evidence is generated in clinical practice. Benefit-risk balance should be an integral part of the risk management plan and as such considered before marketing authorisation. Modelling and simulation can be incorporated into MCDA to support the evidence synthesis as well evidence generation taking into account the underlying correlations between favourable and unfavourable effects. In addition, it represents a valuable tool for the optimization of protocol design in effectiveness trials. © 2015 The British Pharmacological Society.

Reference centiles for the middle cerebral artery and umbilical artery pulsatility index and cerebro-placental ratio from a low-risk population - a Generalised Additive Model for Location, Shape and Scale (GAMLSS) approach.

PubMed

Flatley, Christopher; Kumar, Sailesh; Greer, Ristan M

2018-02-06

The primary aim of this study was to create reference ranges for the fetal Middle Cerebral artery Pulsatility Index (MCA PI), Umbilical Artery Pulsatility Index (UA PI) and the Cerebro-Placental Ratio (CPR) in a clearly defined low-risk cohort using the Generalised Additive Model for Location, Shape and Scale (GAMLSS) method. Prospectively collected cross-sectional biometry and Doppler data from low-risk women attending the Mater Mother's Hospital, Maternal and Fetal Medicine Department in Brisbane, Australia between January 2010 and April 2017 were used to derive gestation specific centiles for the MCA PI, UA PI and CPR. All ultrasound scans were performed between 18 + 0 and 41 + 6 weeks gestation with recorded data for the MCA PI and/or UA PI. The GAMLSS method was used for the calculation of gestational age-adjusted centiles. Distributions and additive terms were assessed and the final model was chosen on the basis of the Global Deviance, Akaike information criterion (AIC) and Schwartz bayesian criterion (SBC), along with the results of the model and residual diagnostics as well as visual assessment of the centiles themselves. Over the study period 6013 women met the inclusion criteria. The MCA PI was recorded in 4473 fetuses, the UA PI in 6008 fetuses and the CPR was able to be calculated in 4464 cases. The centiles for the MCA PI used a fractional polynomial additive term and Box-Cox t (BCT) distribution. Centiles for the UA PI used a cubic spline additive term with BCT distribution and the CPR used a fractional polynomial additive term and a BCT distribution. We have created gestational centile reference ranges for the MCA PI, UA PI and CPR from a large low-risk cohort that supports their applicability and generalisability.

Maps, Models and Data from Southeastern Great Basin PFA, Phase II Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nash, Greg

This submission includes composite risk segment models in raster format for permeability, heat of the earth, and MT, as well as the final PFA model of geothermal exploration risk in Southwestern Utah, USA. Additionally, this submission has data regarding hydrothermally altered areas, and opal sinter deposits in the study area. All of this information lends to the understanding and exploration for hidden geothermal systems in the area.

Prediction model with metabolic syndrome to predict recurrent vascular events in patients with clinically manifest vascular diseases.

PubMed

Wassink, Annemarie M; van der Graaf, Yolanda; Janssen, Kristel J; Cook, Nancy R; Visseren, Frank L

2012-12-01

Although the overall average 10-year cardiovascular risk for patients with manifest atherosclerosis is considered to be more than 20%, actual risk for individual patients ranges from much lower to much higher. We investigated whether information on metabolic syndrome (MetS) or its individual components improves cardiovascular risk stratification in these patients. We conducted a prospective cohort study in 3679 patients with clinical manifest atherosclerosis from the Secondary Manifestations of ARTerial disease (SMART) study. Primary outcome was defined as any cardiovascular event (cardiovascular death, ischemic stroke or myocardial infarction). Three pre-specified prediction models were derived, all including information on established MetS components. The association between outcome and predictors was quantified using a Cox proportional hazard analysis. Model performance was assessed using global goodness-of-fit fit (χ(2)), discrimination (C-index) and ability to improve risk stratification. A total of 417 cardiovascular events occurred among 3679 patients with 15,102 person-years of follow-up (median follow-up 3.7 years, range 1.6-6.4 years). Compared to a model with age and gender only, all MetS-based models performed slightly better in terms of global model fit (χ(2)) but not C-index. The Net Reclassification Index associated with the addition of MetS (yes/no), the dichotomous MetS-components or the continuous MetS-components on top of age and gender was 2.1% (p = 0.29), 2.3% (p = 0.31) and 7.5% (p = 0.01), respectively. Prediction models incorporating age, gender and MetS can discriminate between patients with clinical manifest atherosclerosis at the highest vascular risk and those at lower risk. The addition of MetS components to a model with age and gender correctly reclassifies only a small proportion of patients into higher- and lower-risk categories. The clinical utility of a prediction model with MetS is therefore limited.

External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

PubMed

Hickey, Graeme L; Blackstone, Eugene H

2016-08-01

Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Improving coeliac disease risk prediction by testing non-HLA variants additional to HLA variants.

PubMed

Romanos, Jihane; Rosén, Anna; Kumar, Vinod; Trynka, Gosia; Franke, Lude; Szperl, Agata; Gutierrez-Achury, Javier; van Diemen, Cleo C; Kanninga, Roan; Jankipersadsing, Soesma A; Steck, Andrea; Eisenbarth, Georges; van Heel, David A; Cukrowska, Bozena; Bruno, Valentina; Mazzilli, Maria Cristina; Núñez, Concepcion; Bilbao, Jose Ramon; Mearin, M Luisa; Barisani, Donatella; Rewers, Marian; Norris, Jill M; Ivarsson, Anneli; Boezen, H Marieke; Liu, Edwin; Wijmenga, Cisca

2014-03-01

The majority of coeliac disease (CD) patients are not being properly diagnosed and therefore remain untreated, leading to a greater risk of developing CD-associated complications. The major genetic risk heterodimer, HLA-DQ2 and DQ8, is already used clinically to help exclude disease. However, approximately 40% of the population carry these alleles and the majority never develop CD. We explored whether CD risk prediction can be improved by adding non-HLA-susceptible variants to common HLA testing. We developed an average weighted genetic risk score with 10, 26 and 57 single nucleotide polymorphisms (SNP) in 2675 cases and 2815 controls and assessed the improvement in risk prediction provided by the non-HLA SNP. Moreover, we assessed the transferability of the genetic risk model with 26 non-HLA variants to a nested case-control population (n=1709) and a prospective cohort (n=1245) and then tested how well this model predicted CD outcome for 985 independent individuals. Adding 57 non-HLA variants to HLA testing showed a statistically significant improvement compared to scores from models based on HLA only, HLA plus 10 SNP and HLA plus 26 SNP. With 57 non-HLA variants, the area under the receiver operator characteristic curve reached 0.854 compared to 0.823 for HLA only, and 11.1% of individuals were reclassified to a more accurate risk group. We show that the risk model with HLA plus 26 SNP is useful in independent populations. Predicting risk with 57 additional non-HLA variants improved the identification of potential CD patients. This demonstrates a possible role for combined HLA and non-HLA genetic testing in diagnostic work for CD.

Preventive care delivered within Public Dental Service after caries risk assessment of young adults.

PubMed

Hänsel Petersson, G; Ericson, E; Twetman, S

2016-08-01

To study preventive care provided to young adults in relation to their estimated risk category over a 3-year period. The amount and type of preventive treatment during 3 years was extracted from the digital dental records of 982 patients attending eight public dental clinics. The baseline caries risk assessment was carried out by the patient's regular team in four classes according to a predetermined model, and the team was responsible for all treatment decisions. Based on the variables 'oral health information', 'additional fluoride' and 'professional tooth cleaning', a cumulative score was constructed and dichotomized to 'basic prevention' and 'additional prevention'. More additional preventive care was provided to the patients in the 'low-risk' and 'some risk' categories than to those classified as 'high' or 'very high' risk (OR = 2.0, 95% CI 1.4-3.0; P < 0.05). Professional tooth cleaning and additional fluorides were most frequently employed in the 'low-risk' and 'some risk' categories, respectively. Around 15% of the patients in the high-risk categories did not receive additional preventive measures over the 3-year period. There was an insignificant tendency that patients with additional prevention developed less caries than those that received basic prevention in all risk categories except for the 'very high-risk' group. The caries risk assessment process was not accompanied by a corresponding targeted individual preventive care in a cohort of young adults attending public dental service. Further research is needed how to reach those with the greatest need of primary and secondary prevention. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The estimation of time-varying risks in asset pricing modelling using B-Spline method

NASA Astrophysics Data System (ADS)

Nurjannah; Solimun; Rinaldo, Adji

2017-12-01

Asset pricing modelling has been extensively studied in the past few decades to explore the risk-return relationship. The asset pricing literature typically assumed a static risk-return relationship. However, several studies found few anomalies in the asset pricing modelling which captured the presence of the risk instability. The dynamic model is proposed to offer a better model. The main problem highlighted in the dynamic model literature is that the set of conditioning information is unobservable and therefore some assumptions have to be made. Hence, the estimation requires additional assumptions about the dynamics of risk. To overcome this problem, the nonparametric estimators can also be used as an alternative for estimating risk. The flexibility of the nonparametric setting avoids the problem of misspecification derived from selecting a functional form. This paper investigates the estimation of time-varying asset pricing model using B-Spline, as one of nonparametric approach. The advantages of spline method is its computational speed and simplicity, as well as the clarity of controlling curvature directly. The three popular asset pricing models will be investigated namely CAPM (Capital Asset Pricing Model), Fama-French 3-factors model and Carhart 4-factors model. The results suggest that the estimated risks are time-varying and not stable overtime which confirms the risk instability anomaly. The results is more pronounced in Carhart’s 4-factors model.

Evidence That Environmental and Familial Risks for Psychosis Additively Impact a Multidimensional Subthreshold Psychosis Syndrome.

PubMed

Pries, Lotta-Katrin; Guloksuz, Sinan; Ten Have, Margreet; de Graaf, Ron; van Dorsselaer, Saskia; Gunther, Nicole; Rauschenberg, Christian; Reininghaus, Ulrich; Radhakrishnan, Rajiv; Bak, Maarten; Rutten, Bart P F; van Os, Jim

2018-06-06

The observed link between positive psychotic experiences (PE) and psychosis spectrum disorder (PSD) may be stronger depending on concomitant presence of PE with other dimensions of psychopathology. We examined whether the effect of common risk factors for PSD on PE is additive and whether the impact of risk factors on the occurrence of PE depends on the co-occurrence of other symptom dimensions (affective dysregulation, negative symptoms, and cognitive alteration). Data from the Netherlands Mental Health Survey and Incidence Study 2 were used. Risk factors included childhood adversity, cannabis use, urbanicity, foreign born, hearing impairment, and family history of affective disorders. Logistic regression models were applied to test (1) the additive effect of risk factors (4 levels) on PE and (2) the moderating effects of symptom dimensions on the association between risk factors (present/absent) and PE, using additive interaction, expressed as the interaction contrast ratio. Risk factors were additive: the greater the number of risk factors, the greater the odds of PE. Furthermore, concomitant presence of the other symptom dimensions all increased the impact of risk factors on PE. After controlling for age, sex, and education, only affective dysregulation and negative symptoms remained significant moderators; only affective dysregulation remained a significant moderator if all dimensions were adjusted for each other. Risk factors may not be directly associated with PE but additively give rise to a multidimensional subthreshold state anticipating the multidimensional clinical syndrome. Early motivational and cognitive impairments in the context of PE may be reducible to affective dysregulation.

Delivery of primary health care to persons who are socio-economically disadvantaged: does the organizational delivery model matter?

PubMed Central

2013-01-01

Background As health systems evolve, it is essential to evaluate their impact on the delivery of health services to socially disadvantaged populations. We evaluated the delivery of primary health services for different socio-economic groups and assessed the performance of different organizational models in terms of equality of health care delivery in Ontario, Canada. Methods Cross sectional study of 5,361 patients receiving care from primary care practices using Capitation, Salaried or Fee-For-Service remuneration models. We assessed self-reported health status of patients, visit duration, number of visits per year, quality of health service delivery, and quality of health promotion. We used multi-level regressions to study service delivery across socio-economic groups and within each delivery model. Identified disparities were further analysed using a t-test to determine the impact of service delivery model on equity. Results Low income individuals were more likely to be women, unemployed, recent immigrants, and in poorer health. These individuals were overrepresented in the Salaried model, reported more visits/year across all models, and tended to report longer visits in the Salaried model. Measures of primary care services generally did not differ significantly between low and higher income/education individuals; when they did, the difference favoured better service delivery for at-risk groups. At-risk patients in the Salaried model were somewhat more likely to report health promotion activities than patients from Capitation and Fee-For-Service models. At-risk patients from Capitation models reported a smaller increase in the number of additional clinic visits/year than Fee-For-Service and Salaried models. At-risk patients reported better first contact accessibility than their non-at-risk counterparts in the Fee-For-Service model only. Conclusions Primary care service measures did not differ significantly across socio-economic status or primary care delivery models. In Ontario, capitation-based remuneration is age and sex adjusted only. Patients of low socio-economic status had fewer additional visits compared to those with high socio-economic status under the Capitation model. This raises the concern that Capitation may not support the provision of additional care for more vulnerable groups. Regions undertaking primary care model reforms need to consider the potential impact of the changes on the more vulnerable populations. PMID:24341530

Delivery of primary health care to persons who are socio-economically disadvantaged: does the organizational delivery model matter?

PubMed

Dahrouge, Simone; Hogg, William; Ward, Natalie; Tuna, Meltem; Devlin, Rose Anne; Kristjansson, Elizabeth; Tugwell, Peter; Pottie, Kevin

2013-12-17

As health systems evolve, it is essential to evaluate their impact on the delivery of health services to socially disadvantaged populations. We evaluated the delivery of primary health services for different socio-economic groups and assessed the performance of different organizational models in terms of equality of health care delivery in Ontario, Canada. Cross sectional study of 5,361 patients receiving care from primary care practices using Capitation, Salaried or Fee-For-Service remuneration models. We assessed self-reported health status of patients, visit duration, number of visits per year, quality of health service delivery, and quality of health promotion. We used multi-level regressions to study service delivery across socio-economic groups and within each delivery model. Identified disparities were further analysed using a t-test to determine the impact of service delivery model on equity. Low income individuals were more likely to be women, unemployed, recent immigrants, and in poorer health. These individuals were overrepresented in the Salaried model, reported more visits/year across all models, and tended to report longer visits in the Salaried model. Measures of primary care services generally did not differ significantly between low and higher income/education individuals; when they did, the difference favoured better service delivery for at-risk groups. At-risk patients in the Salaried model were somewhat more likely to report health promotion activities than patients from Capitation and Fee-For-Service models. At-risk patients from Capitation models reported a smaller increase in the number of additional clinic visits/year than Fee-For-Service and Salaried models. At-risk patients reported better first contact accessibility than their non-at-risk counterparts in the Fee-For-Service model only. Primary care service measures did not differ significantly across socio-economic status or primary care delivery models. In Ontario, capitation-based remuneration is age and sex adjusted only. Patients of low socio-economic status had fewer additional visits compared to those with high socio-economic status under the Capitation model. This raises the concern that Capitation may not support the provision of additional care for more vulnerable groups. Regions undertaking primary care model reforms need to consider the potential impact of the changes on the more vulnerable populations.

Review and comparison between the Wells-Riley and dose-response approaches to risk assessment of infectious respiratory diseases.

PubMed

Sze To, G N; Chao, C Y H

2010-02-01

Infection risk assessment is very useful in understanding the transmission dynamics of infectious diseases and in predicting the risk of these diseases to the public. Quantitative infection risk assessment can provide quantitative analysis of disease transmission and the effectiveness of infection control measures. The Wells-Riley model has been extensively used for quantitative infection risk assessment of respiratory infectious diseases in indoor premises. Some newer studies have also proposed the use of dose-response models for such purpose. This study reviews and compares these two approaches to infection risk assessment of respiratory infectious diseases. The Wells-Riley model allows quick assessment and does not require interspecies extrapolation of infectivity. Dose-response models can consider other disease transmission routes in addition to airborne route and can calculate the infectious source strength of an outbreak in terms of the quantity of the pathogen rather than a hypothetical unit. Spatial distribution of airborne pathogens is one of the most important factors in infection risk assessment of respiratory disease. Respiratory deposition of aerosol induces heterogeneous infectivity of intake pathogens and randomness on the intake dose, which are not being well accounted for in current risk models. Some suggestions for further development of the risk assessment models are proposed. This review article summarizes the strengths and limitations of the Wells-Riley and the dose-response models for risk assessment of respiratory diseases. Even with many efforts by various investigators to develop and modify the risk assessment models, some limitations still persist. This review serves as a reference for further development of infection risk assessment models of respiratory diseases. The Wells-Riley model and dose-response model offer specific advantages. Risk assessors can select the approach that is suitable to their particular conditions to perform risk assessment.

Using in vitro/in silico data for consumer safety assessment of feed flavoring additives--A feasibility study using piperine.

PubMed

Thiel, A; Etheve, S; Fabian, E; Leeman, W R; Plautz, J R

2015-10-01

Consumer health risk assessment for feed additives is based on the estimated human exposure to the additive that may occur in livestock edible tissues compared to its hazard. We present an approach using alternative methods for consumer health risk assessment. The aim was to use the fewest possible number of animals to estimate its hazard and human exposure without jeopardizing the safety upon use. As an example we selected the feed flavoring substance piperine and applied in silico modeling for residue estimation, results from literature surveys, and Read-Across to assess metabolism in different species. Results were compared to experimental in vitro metabolism data in rat and chicken, and to quantitative analysis of residues' levels from the in vivo situation in livestock. In silico residue modeling showed to be a worst case: the modeled residual levels were considerably higher than the measured residual levels. The in vitro evaluation of livestock versus rodent metabolism revealed no major differences in metabolism between the species. We successfully performed a consumer health risk assessment without performing additional animal experiments. As shown, the use and combination of different alternative methods supports animal welfare consideration and provides future perspective to reducing the number of animals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

KIT polymorphisms were associated with the risk for head and neck squamous carcinoma in Chinese population.

PubMed

Hang, Dong; Yuan, Hua; Liu, Li; Wang, Lihua; Miao, Limin; Zhu, Meng; Du, Jiangbo; Dai, Juncheng; Hu, Zhibin; Chen, Ning; Shen, Hongbing; Ma, Hongxia

2017-01-01

KITLG/KIT pathway plays a vital role in multiple types of human cancer including head and neck squamous cell carcinoma (HNSCC). Genetic variations in KITLG and KIT may affect the expression or function of these genes, thereby modifying cancer risk. In this study, we evaluated the association of KITLG and KIT polymorphisms with HNSCC risk among Chinese population. Twenty-two tagging SNPs in KITLG and KIT genes were genotyped in a case-control study with 576 HNSCC patients and 1552 healthy controls. Logistic regression analyses revealed that an upstream SNP rs6554198 [additive model: adjusted odds ratio (OR) = 0.85, 95% confidence interval (CI) = 0.74-0.97, P = 0.019] and two intron SNPs rs2237025 (additive model: adjusted OR = 0.82, 95%CI = 0.70-0.95, P = 0.007), and rs17084687 (additive model: adjusted OR = 0.85, 95%CI = 0.73-0.99, P = 0.042) of KIT were significantly associated with the decreased risk of HNSCC. Combined analysis of the three SNPs showed that subjects carrying the protective alleles had decreased risk of HNSCC in a dose-response manner (P trend  = 0.001). Furthermore, interaction analyses revealed a significant multiplicative interaction between rs17084687 and drinking on HNSCC risk (P = 0.012). Luciferase activity assay indicated that the allele A of potentially functional rs6554198 led to significantly lower transcription activity of KIT compared to the risk allele G. Summarily, our findings suggested that SNPs in KIT gene may play a role in genetic susceptibility to HNSCC, which may improve our understanding of the pathogenic mechanisms of this disease. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Association of colorectal cancer susceptibility variants with esophageal cancer in a Chinese population.

PubMed

Geng, Ting-Ting; Xun, Xiao-Jie; Li, Sen; Feng, Tian; Wang, Li-Ping; Jin, Tian-Bo; Hou, Peng

2015-06-14

To investigate the association between colorectal cancer (CRC) genetic susceptibility variants and esophageal cancer in a Chinese Han population. A case-control study was conducted including 360 esophageal cancer patients and 310 healthy controls. Thirty-one single-nucleotide polymorphisms (SNPs) associated with CRC risk from previous genome-wide association studies were analyzed. SNPs were genotyped using Sequenom Mass-ARRAY technology, and genotypic frequencies in controls were tested for departure from Hardy-Weinberg equilibrium using a Fisher's exact test. The allelic frequencies were compared between cases and controls using a χ(2) test. Associations between the SNPs and the risk of esophageal cancer were tested using various genetic models (codominant, dominant, recessive, overdominant, and additive). ORs and 95%CIs were calculated by unconditional logistic regression with adjustments for age and sex. The minor alleles of rs1321311 and rs4444235 were associated with a 1.53-fold (95%CI: 1.15-2.06; P = 0.004) and 1.28-fold (95%CI: 1.03-1.60; P = 0.028) increased risk of esophageal cancer in the allelic model analysis, respectively. In the genetic model analysis, the C/C genotype of rs3802842 was associated with a reduced risk of esophageal cancer in the codominant model (OR = 0.52, 95%CI: 0.31-0.88; P = 0.033) and recessive model (OR = 0.55, 95%CI: 0.34-0.87; P = 0.010). The rs4939827 C/T-T/T genotype was associated with a 0.67-fold (95%CI: 0.46-0.98; P = 0.038) decreased esophageal cancer risk under the dominant model. In addition, rs6687758, rs1321311, and rs4444235 were associated with an increased risk. In particular, the T/T genotype of rs1321311 was associated with an 8.06-fold (95%CI: 1.96-33.07; P = 0.004) increased risk in the codominant model. These results provide evidence that known genetic variants associated with CRC risk confer risk for esophageal cancer, and may bring risk for other digestive system tumors.

Low dose radiation risks for women surviving the a-bombs in Japan: generalized additive model.

PubMed

Dropkin, Greg

2016-11-24

Analyses of cancer mortality and incidence in Japanese A-bomb survivors have been used to estimate radiation risks, which are generally higher for women. Relative Risk (RR) is usually modelled as a linear function of dose. Extrapolation from data including high doses predicts small risks at low doses. Generalized Additive Models (GAMs) are flexible methods for modelling non-linear behaviour. GAMs are applied to cancer incidence in female low dose subcohorts, using anonymous public data for the 1958 - 1998 Life Span Study, to test for linearity, explore interactions, adjust for the skewed dose distribution, examine significance below 100 mGy, and estimate risks at 10 mGy. For all solid cancer incidence, RR estimated from 0 - 100 mGy and 0 - 20 mGy subcohorts is significantly raised. The response tapers above 150 mGy. At low doses, RR increases with age-at-exposure and decreases with time-since-exposure, the preferred covariate. Using the empirical cumulative distribution of dose improves model fit, and capacity to detect non-linear responses. RR is elevated over wide ranges of covariate values. Results are stable under simulation, or when removing exceptional data cells, or adjusting neutron RBE. Estimates of Excess RR at 10 mGy using the cumulative dose distribution are 10 - 45 times higher than extrapolations from a linear model fitted to the full cohort. Below 100 mGy, quasipoisson models find significant effects for all solid, squamous, uterus, corpus, and thyroid cancers, and for respiratory cancers when age-at-exposure > 35 yrs. Results for the thyroid are compatible with studies of children treated for tinea capitis, and Chernobyl survivors. Results for the uterus are compatible with studies of UK nuclear workers and the Techa River cohort. Non-linear models find large, significant cancer risks for Japanese women exposed to low dose radiation from the atomic bombings. The risks should be reflected in protection standards.

Modelling tsunami inundation for risk analysis at the Andaman Sea Coast of Thailand

NASA Astrophysics Data System (ADS)

Kaiser, G.; Kortenhaus, A.

2009-04-01

The mega-tsunami of Dec. 26, 2004 strongly impacted the Andaman Sea coast of Thailand and devastated coastal ecosystems as well as towns, settlements and tourism resorts. In addition to the tragic loss of many lives, the destruction or damage of life-supporting infrastructure, such as buildings, roads, water & power supply etc. caused high economic losses in the region. To mitigate future tsunami impacts there is a need to assess the tsunami hazard and vulnerability in flood prone areas at the Andaman Sea coast in order to determine the spatial distribution of risk and to develop risk management strategies. In the bilateral German-Thai project TRAIT research is performed on integrated risk assessment for the Provinces Phang Nga and Phuket in southern Thailand, including a hazard analysis, i.e. modelling tsunami propagation to the coast, tsunami wave breaking and inundation characteristics, as well as vulnerability analysis of the socio-economic and the ecological system in order to determine the scenario-based, specific risk for the region. In this presentation results of the hazard analysis and the inundation simulation are presented and discussed. Numerical modelling of tsunami propagation and inundation simulation is an inevitable tool for risk analysis, risk management and evacuation planning. While numerous investigations have been made to model tsunami wave generation and propagation in the Indian Ocean, there is still a lack in determining detailed inundation patterns, i.e. water depth and flow dynamics. However, for risk management and evacuation planning this knowledge is essential. As the accuracy of the inundation simulation is strongly depending on the available bathymetric and the topographic data, a multi-scale approach is chosen in this work. The ETOPO Global Relief Model as a bathymetric basis and the Shuttle Radar Topography Mission (SRTM90) have been widely applied in tsunami modelling approaches as these data are free and almost world-wide available. However, to model tsunami-induced inundation for risk analysis and management purposes the accuracy of these data is not sufficient as the processes in the near-shore zone cannot be modelled accurately enough and the spatial resolution of the topography is weak. Moreover, the SRTM data provide a digital surface model which includes vegetation and buildings in the surface description. To improve the data basis additional bathymetric data were used in the near shore zone of the Phang Nga and Phuket coastlines and various remote sensing techniques as well as additional GPS measurements were applied to derive a high resolution topography from satellite and airborne data. Land use classifications and filter methods were developed to correct the digital surface models to digital elevation models. Simulations were then performed with a non-linear shallow water model to model the 2004 Asian Tsunami and to simulate possible future ones. Results of water elevation near the coast were compared with field measurements and observations, and the influence of the resolution of the topography on inundation patterns like water depth, velocity, dispersion and duration of the flood were analysed. The inundation simulation provides detailed hazard maps and is considered a reliable basis for risk assessment and risk zone mapping. Results are regarded vital for estimation of tsunami induced damages and evacuation planning. Results of the aforementioned simulations will be discussed during the conference. Differences of the numerical results using topographic data of different scales and modified by different post processing techniques will be analysed and explained. Further use of the results with respect to tsunami risk analysis and management will also be demonstrated.

Divorce as Risky Behavior

PubMed Central

LIGHT, AUDREY; AHN, TAEHYUN

2010-01-01

Given that divorce often represents a high-stakes income gamble, we ask how individual levels of risk tolerance affect the decision to divorce. We extend the orthodox divorce model by assuming that individuals are risk averse, that marriage is risky, and that divorce is even riskier. The model predicts that conditional on the expected gains to marriage and divorce, the probability of divorce increases with relative risk tolerance because risk averse individuals require compensation for the additional risk that is inherent in divorce. To implement the model empirically, we use data for first-married women and men from the 1979 National Longitudinal Survey of Youth to estimate a probit model of divorce in which a measure of risk tolerance is among the covariates. The estimates reveal that a 1-point increase in risk tolerance raises the predicted probability of divorce by 4.3% for a representative man and by 11.4% for a representative woman. These findings are consistent with the notion that divorce entails a greater income gamble for women than for men. PMID:21308563

Divorce as risky behavior.

PubMed

Light, Audrey; Ahn, Taehyun

2010-11-01

Given that divorce often represents a high-stakes income gamble, we ask how individual levels of risk tolerance affect the decision to divorce. We extend the orthodox divorce model by assuming that individuals are risk averse, that marriage is risky, and that divorce is even riskier. The model predicts that conditional on the expected gains to marriage and divorce, the probability of divorce increases with relative risk tolerance because risk averse individuals require compensation for the additional risk that is inherent in divorce. To implement the model empirically, we use data for first-married women and men from the 1979 National Longitudinal Survey of Youth to estimate a probit model of divorce in which a measure of risk tolerance is among the covariates. The estimates reveal that a 1-point increase in risk tolerance raises the predicted probability of divorce by 4.3% for a representative man and by 11.4% for a representative woman. These findings are consistent with the notion that divorce entails a greater income gamble for women than for men.

Cumulative effects of antiandrogenic chemical mixtures and their relevance to human health risk assessment.

PubMed

Howdeshell, Kembra L; Hotchkiss, Andrew K; Gray, L Earl

2017-03-01

Toxicological studies of defined chemical mixtures assist human health risk assessment by establishing how chemicals interact with one another to induce an effect. This paper reviews how antiandrogenic chemical mixtures can alter reproductive tract development in rats with a focus on the reproductive toxicant phthalates. The reviewed studies compare observed mixture data to mathematical mixture model predictions based on dose addition or response addition to determine how the individual chemicals in a mixture interact (e.g., additive, greater, or less than additive). Phthalate mixtures were observed to act in a dose additive manner based on the relative potency of the individual phthalates to suppress fetal testosterone production. Similar dose additive effects have been reported for mixtures of phthalates with antiandrogenic pesticides of differing mechanisms of action. Overall, data from these phthalate experiments in rats can be used in conjunction with human biomonitoring data to determine individual hazard indices, and recent cumulative risk assessments in humans indicate an excess risk to antiandrogenic chemical mixtures that include phthalates only or phthalates in combination with other antiandrogenic chemicals. Published by Elsevier GmbH.

Adaptation of a Biomarker-Based Sepsis Mortality Risk Stratification Tool for Pediatric Acute Respiratory Distress Syndrome.

PubMed

Yehya, Nadir; Wong, Hector R

2018-01-01

The original Pediatric Sepsis Biomarker Risk Model and revised (Pediatric Sepsis Biomarker Risk Model-II) biomarker-based risk prediction models have demonstrated utility for estimating baseline 28-day mortality risk in pediatric sepsis. Given the paucity of prediction tools in pediatric acute respiratory distress syndrome, and given the overlapping pathophysiology between sepsis and acute respiratory distress syndrome, we tested the utility of Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II for mortality prediction in a cohort of pediatric acute respiratory distress syndrome, with an a priori plan to revise the model if these existing models performed poorly. Prospective observational cohort study. University affiliated PICU. Mechanically ventilated children with acute respiratory distress syndrome. Blood collection within 24 hours of acute respiratory distress syndrome onset and biomarker measurements. In 152 children with acute respiratory distress syndrome, Pediatric Sepsis Biomarker Risk Model performed poorly and Pediatric Sepsis Biomarker Risk Model-II performed modestly (areas under receiver operating characteristic curve of 0.61 and 0.76, respectively). Therefore, we randomly selected 80% of the cohort (n = 122) to rederive a risk prediction model for pediatric acute respiratory distress syndrome. We used classification and regression tree methodology, considering the Pediatric Sepsis Biomarker Risk Model biomarkers in addition to variables relevant to acute respiratory distress syndrome. The final model was comprised of three biomarkers and age, and more accurately estimated baseline mortality risk (area under receiver operating characteristic curve 0.85, p < 0.001 and p = 0.053 compared with Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II, respectively). The model was tested in the remaining 20% of subjects (n = 30) and demonstrated similar test characteristics. A validated, biomarker-based risk stratification tool designed for pediatric sepsis was adapted for use in pediatric acute respiratory distress syndrome. The newly derived Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model demonstrates good test characteristics internally and requires external validation in a larger cohort. Tools such as Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model have the potential to provide improved risk stratification and prognostic enrichment for future trials in pediatric acute respiratory distress syndrome.

Additive Genetic Risk from Five Serotonin System Polymorphisms Interacts with Interpersonal Stress to Predict Depression

PubMed Central

Vrshek-Schallhorn, Suzanne; Stroud, Catherine B.; Mineka, Susan; Zinbarg, Richard E.; Adam, Emma K.; Redei, Eva E.; Hammen, Constance; Craske, Michelle G.

2016-01-01

Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (GxE). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a GxE predicting depression, we created an additive multilocus profile score from five serotonin system polymorphisms (one each in the genes HTR1A, HTR2A, HTR2C, and two in TPH2). Analyses focused on two forms of interpersonal stress as environmental risk factors. Using five years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (HR = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The GxE effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the GxE effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. PMID:26595467

Attributional style as a mediator between parental abuse risk and child internalizing symptomatology.

PubMed

Rodriguez, Christina M

2006-05-01

This study examined a model wherein children's attributional style mediates the relationship between parental physical child-abuse risk and children's internalizing problems. Using structural equation modeling, three indices of abuse risk were selected (child abuse potential, physical discipline use, and dysfunctional parenting style) and two indices of children's internalizing problems (depression and anxiety). The sample included 75 parent-child dyads, in which parents reported on their abuse risk and children independently completed measures of depressive and anxious symptomatology and a measure on their attributional style. Findings supported the model that children's attributional style for positive events (but not negative events) partially mediated the relationship between abuse risk and internalizing symptoms, with significant direct and indirect effects of abuse risk on internalizing symptomatology. Future directions to continue evaluating additional mediators and other possible contextual variables are discussed.

A cooperative model for IS security risk management in distributed environment.

PubMed

Feng, Nan; Zheng, Chundong

2014-01-01

Given the increasing cooperation between organizations, the flexible exchange of security information across the allied organizations is critical to effectively manage information systems (IS) security in a distributed environment. In this paper, we develop a cooperative model for IS security risk management in a distributed environment. In the proposed model, the exchange of security information among the interconnected IS under distributed environment is supported by Bayesian networks (BNs). In addition, for an organization's IS, a BN is utilized to represent its security environment and dynamically predict its security risk level, by which the security manager can select an optimal action to safeguard the firm's information resources. The actual case studied illustrates the cooperative model presented in this paper and how it can be exploited to manage the distributed IS security risk effectively.

Variance computations for functional of absolute risk estimates.

PubMed

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

Variance computations for functional of absolute risk estimates

PubMed Central

Pfeiffer, R.M.; Petracci, E.

2011-01-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476

Quantification of key long-term risks at CO₂ sequestration sites: Latest results from US DOE's National Risk Assessment Partnership (NRAP) Project

DOE PAGES

Pawar, Rajesh; Bromhal, Grant; Carroll, Susan; ...

2014-12-31

Risk assessment for geologic CO₂ storage including quantification of risks is an area of active investigation. The National Risk Assessment Partnership (NRAP) is a US-Department of Energy (US-DOE) effort focused on developing a defensible, science-based methodology and platform for quantifying risk profiles at geologic CO₂ sequestration sites. NRAP has been developing a methodology that centers round development of an integrated assessment model (IAM) using system modeling approach to quantify risks and risk profiles. The IAM has been used to calculate risk profiles with a few key potential impacts due to potential CO₂ and brine leakage. The simulation results are alsomore » used to determine long-term storage security relationships and compare the long-term storage effectiveness to IPCC storage permanence goal. Additionally, we also demonstrate application of IAM for uncertainty quantification in order to determine parameters to which the uncertainty in model results is most sensitive.« less

Predictions of Leukemia Risks to Astronauts from Solar Particle Events

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Atwell, W.; Kim, M. Y.; George, K. A.; Ponomarev, A.; Nikjoo, H.; Wilson, J. W.

2006-01-01

Leukemias consisting of acute and chronic myeloid leukemia and acute lymphatic lymphomas represent the earliest cancers that appear after radiation exposure, have a high lethality fraction, and make up a significant fraction of the overall fatal cancer risk from radiation for adults. Several considerations impact the recommendation of a preferred model for the estimation of leukemia risks from solar particle events (SPE's): The BEIR VII report recommends several changes to the method of calculation of leukemia risk compared to the methods recommended by the NCRP Report No. 132 including the preference of a mixture model with additive and multiplicative components in BEIR VII compared to the additive transfer model recommended by NCRP Report No. 132. Proton fluences and doses vary considerably across marrow regions because of the characteristic spectra of primary solar protons making the use of an average dose suspect. Previous estimates of bone marrow doses from SPE's have used an average body-shielding distribution for marrow based on the computerized anatomical man model (CAM). We have developed an 82-point body-shielding distribution that faithfully reproduces the mean and variance of SPE doses in the active marrow regions (head and neck, chest, abdomen, pelvis and thighs) allowing for more accurate estimation of linear- and quadratic-dose components of the marrow response. SPE's have differential dose-rates and a pseudo-quadratic dose response term is possible in the peak-flux period of an event. Also, the mechanistic basis for leukemia risk continues to improve allowing for improved strategies in choosing dose-rate modulation factors and radiation quality descriptors. We make comparisons of the various choices of the components in leukemia risk estimates in formulating our preferred model. A major finding is that leukemia could be the dominant risk to astronauts for a major solar particle event.

Cardiorespiratory fitness and classification of risk of cardiovascular disease mortality.

PubMed

Gupta, Sachin; Rohatgi, Anand; Ayers, Colby R; Willis, Benjamin L; Haskell, William L; Khera, Amit; Drazner, Mark H; de Lemos, James A; Berry, Jarett D

2011-04-05

Cardiorespiratory fitness (fitness) is associated with cardiovascular disease (CVD) mortality. However, the extent to which fitness improves risk classification when added to traditional risk factors is unclear. Fitness was measured by the Balke protocol in 66 371 subjects without prior CVD enrolled in the Cooper Center Longitudinal Study between 1970 and 2006; follow-up was extended through 2006. Cox proportional hazards models were used to estimate the risk of CVD mortality with a traditional risk factor model (age, sex, systolic blood pressure, diabetes mellitus, total cholesterol, and smoking) with and without the addition of fitness. The net reclassification improvement and integrated discrimination improvement were calculated at 10 and 25 years. Ten-year risk estimates for CVD mortality were categorized as <1%, 1% to <5%, and ≥5%, and 25-year risk estimates were categorized as <8%, 8% to 30%, and ≥30%. During a median follow-up period of 16 years, there were 1621 CVD deaths. The addition of fitness to the traditional risk factor model resulted in reclassification of 10.7% of the men, with significant net reclassification improvement at both 10 years (net reclassification improvement=0.121) and 25 years (net reclassification improvement=0.041) (P<0.001 for both). The integrated discrimination improvement was 0.010 at 10 years (P<0.001), and the relative integrated discrimination improvement was 29%. Similar findings were observed for women at 25 years. A single measurement of fitness significantly improves classification of both short-term (10-year) and long-term (25-year) risk for CVD mortality when added to traditional risk factors.

Synergy and other ineffective mixture risk definitions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hertzberg, R.; MacDonell, M.; Environmental Assessment

2002-04-08

A substantial effort has been spent over the past few decades to label toxicologic interaction outcomes as synergistic, antagonistic, or additive. Although useful in influencing the emotions of the public and the press, these labels have contributed fairly little to our understanding of joint toxic action. Part of the difficulty is that their underlying toxicological concepts are only defined for two chemical mixtures, while most environmental and occupational exposures are to mixtures of many more chemicals. Furthermore, the mathematical characterizations of synergism and antagonism are inextricably linked to the prevailing definition of 'no interaction,' instead of some intrinsic toxicological property.more » For example, the US EPA has selected dose addition as the no-interaction definition for mixture risk assessment, so that synergism would represent toxic effects that exceed those predicted from dose addition. For now, labels such as synergism are useful to regulatory agencies, both for qualitative indications of public health risk as well as numerical decision tools for mixture risk characterization. Efforts to quantify interaction designations for use in risk assessment formulas, however, are highly simplified and carry large uncertainties. Several research directions, such as pharmacokinetic measurements and models, and toxicogenomics, should promote significant improvements by providing multi-component data that will allow biologically based mathematical models of joint toxicity to replace these pairwise interaction labels in mixture risk assessment procedures.« less

The 100-year flood seems to be changing. Can we really tell?

NASA Astrophysics Data System (ADS)

Ceres, R. L., Jr.; Forest, C. E.; Keller, K.

2017-12-01

Widespread flooding from Hurricane Harvey greatly exceeded the Federal Emergency Management Agency's 100-year flood levels. In the US, this flood level is often used as an important line of demarcation where areas above this level are considered safe, while areas below the line are at risk and require additional flood risk mitigation. In the wake of Harvey's damage, the US media has highlighted at least two important questions. First, has the 100-year flood level changed? Second, is the 100-year flood level a good metric for determining flood risk? To address the first question, we use an Observation System Simulation Experiment of storm surge flood levels and find that gradual changes to the 100-year storm surge level may not be reliably detected over the long lifespans expected of major flood risk mitigation strategies. Additionally, we find that common extreme value analysis models lead to biased results and additional uncertainty when incorrect assumptions are used for the underlying statistical model. These incorrect assumptions can lead to examples of negative learning. Addressing the second question, these findings further challenge the validity of using simple return levels such as the 100-year flood as a decision tool for assessing flood risk. These results indicate risk management strategies must account for such uncertainties to build resilient and robust planning tools that stakeholders desperately need.

A model for assessing the risk of human trafficking on a local level

NASA Astrophysics Data System (ADS)

Colegrove, Amanda

Human trafficking is a human rights violation that is difficult to quantify. Models for estimating the number of victims of trafficking presented by previous researchers depend on inconsistent, poor quality data. As an intermediate step to help current efforts by nonprofits to combat human trafficking, this project presents a model that is not dependent on quantitative data specific to human trafficking, but rather profiles the risk of human trafficking at the local level through causative factors. Businesses, indicated by the literature, were weighted based on the presence of characteristics that increase the likelihood of trafficking in persons. The mean risk was calculated by census tract to reveal the multiplicity of risk levels in both rural and urban settings. Results indicate that labor trafficking may be a more diffuse problem in Missouri than sex trafficking. Additionally, spatial patterns of risk remained largely the same regardless of adjustments made to the model.

Geographic exposure risk of variant Creutzfeldt-Jakob disease in US blood donors: a risk-ranking model to evaluate alternative donor-deferral policies.

PubMed

Yang, Hong; Huang, Yin; Gregori, Luisa; Asher, David M; Bui, Travis; Forshee, Richard A; Anderson, Steven A

2017-04-01

Variant Creutzfeldt-Jakob disease (vCJD) has been transmitted by blood transfusion (TTvCJD). The US Food and Drug Administration (FDA) recommends deferring blood donors who resided in or traveled to 30 European countries where they may have been exposed to bovine spongiform encephalopathy (BSE) through beef consumption. Those recommendations warrant re-evaluation, because new cases of BSE and vCJD have markedly abated. The FDA developed a risk-ranking model to calculate the geographic vCJD risk using country-specific case rates and person-years of exposure of US blood donors. We used the reported country vCJD case rates, when available, or imputed vCJD case rates from reported BSE and UK beef exports during the risk period. We estimated the risk reduction and donor loss should the deferral be restricted to a few high-risk countries. We also estimated additional risk reduction by leukocyte reduction (LR) of red blood cells (RBCs). The United Kingdom, Ireland, and France had the greatest vCJD risk, contributing approximately 95% of the total risk. The model estimated that deferring US donors who spent extended periods of time in these three countries, combined with currently voluntary LR (95% of RBC units), would reduce the vCJD risk by 89.3%, a reduction similar to that achieved under the current policy (89.8%). Limiting deferrals to exposure in these three countries would potentially allow donations from an additional 100,000 donors who are currently deferred. Our analysis suggests that a deferral option focusing on the three highest risk countries would achieve a level of blood safety similar to that achieved by the current policy. © 2016 AABB.

Improving Risk Adjustment for Mortality After Pediatric Cardiac Surgery: The UK PRAiS2 Model.

PubMed

Rogers, Libby; Brown, Katherine L; Franklin, Rodney C; Ambler, Gareth; Anderson, David; Barron, David J; Crowe, Sonya; English, Kate; Stickley, John; Tibby, Shane; Tsang, Victor; Utley, Martin; Witter, Thomas; Pagel, Christina

2017-07-01

Partial Risk Adjustment in Surgery (PRAiS), a risk model for 30-day mortality after children's heart surgery, has been used by the UK National Congenital Heart Disease Audit to report expected risk-adjusted survival since 2013. This study aimed to improve the model by incorporating additional comorbidity and diagnostic information. The model development dataset was all procedures performed between 2009 and 2014 in all UK and Ireland congenital cardiac centers. The outcome measure was death within each 30-day surgical episode. Model development followed an iterative process of clinical discussion and development and assessment of models using logistic regression under 25 × 5 cross-validation. Performance was measured using Akaike information criterion, the area under the receiver-operating characteristic curve (AUC), and calibration. The final model was assessed in an external 2014 to 2015 validation dataset. The development dataset comprised 21,838 30-day surgical episodes, with 539 deaths (mortality, 2.5%). The validation dataset comprised 4,207 episodes, with 97 deaths (mortality, 2.3%). The updated risk model included 15 procedural, 11 diagnostic, and 4 comorbidity groupings, and nonlinear functions of age and weight. Performance under cross-validation was: median AUC of 0.83 (range, 0.82 to 0.83), median calibration slope and intercept of 0.92 (range, 0.64 to 1.25) and -0.23 (range, -1.08 to 0.85) respectively. In the validation dataset, the AUC was 0.86 (95% confidence interval [CI], 0.82 to 0.89), and the calibration slope and intercept were 1.01 (95% CI, 0.83 to 1.18) and 0.11 (95% CI, -0.45 to 0.67), respectively, showing excellent performance. A more sophisticated PRAiS2 risk model for UK use was developed with additional comorbidity and diagnostic information, alongside age and weight as nonlinear variables. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Does consideration of either psychological or material disadvantage improve coronary risk prediction? Prospective observational study of Scottish men.

PubMed

Macleod, John; Metcalfe, Chris; Smith, George Davey; Hart, Carole

2007-09-01

To assess the value of psychosocial risk factors in discriminating between individuals at higher and lower risk of coronary heart disease, using risk prediction equations. Prospective observational study. Scotland. 5191 employed men aged 35 to 64 years and free of coronary heart disease at study enrollment Area under receiver operating characteristic (ROC) curves for risk prediction equations including different risk factors for coronary heart disease. During the first 10 years of follow up, 203 men died of coronary heart disease and a further 200 were admitted to hospital with this diagnosis. Area under the ROC curve for the standard Framingham coronary risk factors was 74.5%. Addition of "vital exhaustion" and psychological stress led to areas under the ROC curve of 74.5% and 74.6%, respectively. Addition of current social class and lifetime social class to the standard Framingham equation gave areas under the ROC curve of 74.6% and 74.9%, respectively. In no case was there strong evidence for improved discrimination of the model containing the novel risk factor over the standard model. Consideration of psychosocial risk factors, including those that are strong independent predictors of heart disease, does not substantially influence the ability of risk prediction tools to discriminate between individuals at higher and lower risk of coronary heart disease.

Separating spatial search and efficiency rates as components of predation risk

PubMed Central

DeCesare, Nicholas J.

2012-01-01

Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk—the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)—imposed by wolves (Canis lupus) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator–prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk. PMID:22977145

Comparison of risk estimates using life-table methods.

PubMed

Sullivan, R E; Weng, P S

1987-08-01

Risk estimates promulgated by various radiation protection authorities in recent years have become increasingly more complex. Early "integral" estimates in the form of health effects per 0.01 person-Gy (per person-rad) or per 10(4) person-Gy (per 10(6) person-rad) have tended to be replaced by "differential" estimates which are age- and sex-dependent and specify both minimum induction (latency) and duration of risk expression (plateau) periods. These latter types of risk estimate must be used in conjunction with a life table in order to reduce them to integral form. In this paper, the life table has been used to effect a comparison of the organ and tissue risk estimates derived in several recent reports. In addition, a brief review of life-table methodology is presented and some features of the models used in deriving differential coefficients are discussed. While the great number of permutations possible with dose-response models, detailed risk estimates and proposed projection models precludes any unique result, the reduced integral coefficients are required to conform to the linear, absolute-risk model recommended for use with the integral risk estimates reviewed.

Cascade reservoir flood control operation based on risk grading and warning in the Upper Yellow River

NASA Astrophysics Data System (ADS)

Xuejiao, M.; Chang, J.; Wang, Y.

2017-12-01

Flood risk reduction with non-engineering measures has become the main idea for flood management. It is more effective for flood risk management to take various non-engineering measures. In this paper, a flood control operation model for cascade reservoirs in the Upper Yellow River was proposed to lower the flood risk of the water system with multi-reservoir by combining the reservoir flood control operation (RFCO) and flood early warning together. Specifically, a discharge control chart was employed to build the joint RFCO simulation model for cascade reservoirs in the Upper Yellow River. And entropy-weighted fuzzy comprehensive evaluation method was adopted to establish a multi-factorial risk assessment model for flood warning grade. Furthermore, after determining the implementing mode of countermeasures with future inflow, an intelligent optimization algorithm was used to solve the optimization model for applicable water release scheme. In addition, another model without any countermeasure was set to be a comparative experiment. The results show that the model developed in this paper can further decrease the flood risk of water system with cascade reservoirs. It provides a new approach to flood risk management by coupling flood control operation and flood early warning of cascade reservoirs.

Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

PubMed Central

Holt, Ashley C; Salkeld, Daniel J; Fritz, Curtis L; Tucker, James R; Gong, Peng

2009-01-01

Background Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Results Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Conclusion Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly correlated with coyote samples, indicating that carnivore surveillance programs will continue to be important for tracking the response of plague to future climate conditions. PMID:19558717

Breast cancer risks and risk prediction models.

PubMed

Engel, Christoph; Fischer, Christine

2015-02-01

BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

PubMed

Clark, Renee M; Besterfield-Sacre, Mary E

2009-03-01

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

Effects of radon mitigation vs smoking cessation in reducing radon-related risk of lung cancer.

PubMed Central

Mendez, D; Warner, K E; Courant, P N

1998-01-01

OBJECTIVES: The purpose of this paper is to provide smokers with information on the relative benefits of mitigating radon and quitting smoking in reducing radon-related lung cancer risk. METHODS: The standard radon risk model, linked with models characterizing residential radon exposure and patterns of moving to new homes, was used to estimate the risk reduction produced by remediating high-radon homes, quitting smoking, or both. RESULTS: Quitting smoking reduces lung cancer risk from radon more than does reduction of radon exposure itself. CONCLUSIONS: Smokers should understand that, in addition to producing other health benefits, quitting smoking dominates strategies to deal with the problem posed by radon. PMID:9585753

Environmental Risk Profiling of the Volta Delta, Ghana

NASA Astrophysics Data System (ADS)

Nyarko, B. K.; Appeaning-Addo, K.; Amisigo, B.

2017-12-01

Volta Delta communities find it difficult to absorb or bear risk at different levels, because of the physical and economic impacts of environmental hazards. In this regards various agencies and organizations have in recent years launched initiatives to measure and identify risk areas with a set of indicators and indices. The theory underpinning this study is concepts of Modern Portfolio Theory (MPT). The Cox proportional hazards regression model will be used as the model for the risk profile. Finding the optimal level of environmental risk for activities in the Volta Delta considering the risk required, risk capacity and risk tolerance. Using data from different sources, an environmental risk profile was developed for the Volta Delta. The result indicates that risks are distributed across the Delta. However, areas that have government interventions, such as sea defense system and irrigation facilities have less threat. In addition wealthy areas do effectively reduce the threat of any form of disaster.

Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases.

PubMed

Lenz, Tobias L; Deutsch, Aaron J; Han, Buhm; Hu, Xinli; Okada, Yukinori; Eyre, Stephen; Knapp, Michael; Zhernakova, Alexandra; Huizinga, Tom W J; Abecasis, Gonçalo; Becker, Jessica; Boeckxstaens, Guy E; Chen, Wei-Min; Franke, Andre; Gladman, Dafna D; Gockel, Ines; Gutierrez-Achury, Javier; Martin, Javier; Nair, Rajan P; Nöthen, Markus M; Onengut-Gumuscu, Suna; Rahman, Proton; Rantapää-Dahlqvist, Solbritt; Stuart, Philip E; Tsoi, Lam C; van Heel, David A; Worthington, Jane; Wouters, Mira M; Klareskog, Lars; Elder, James T; Gregersen, Peter K; Schumacher, Johannes; Rich, Stephen S; Wijmenga, Cisca; Sunyaev, Shamil R; de Bakker, Paul I W; Raychaudhuri, Soumya

2015-09-01

Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a heterozygote's two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (ncases = 5,337), type 1 diabetes (T1D; ncases = 5,567), psoriasis vulgaris (ncases = 3,089), idiopathic achalasia (ncases = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 × 10(-12); T1D, P = 2.4 × 10(-10); psoriasis, P = 5.9 × 10(-6); celiac disease, P = 1.2 × 10(-87)). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 × 10(-3); T1D, P = 8.6 × 10(-27); celiac disease, P = 6.0 × 10(-100)). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4%; T1D, 4.0%; celiac disease, 4.1%) beyond a simple additive model.

Differential Gene Expression in Explanted Human Retinal Pigment Epithelial Cells 24-Hours Post-Exposure to 532 nm, 3.0 ns Pulsed Laser Light and 1064 nm, 170 ps Pulsed Laser Light 12-Hours Post-Exposure: Results Compendium

DTIC Science & Technology

2004-06-01

Additionally, we offer 3 conceptual cartoons outlining our vision for the future progres of laser bioeffects research, metabonomic risk assessment...future progress of laser bioeffects research, metabonomic risk assessment modeling and knowledge building from laser bioeffects data. BACKGROUND In the...our concepts of future laser bioeffects research directions (Figure 5), a metabonomic risk assessment model of laser tissue interaction (Figure 6

A Cooperative Model for IS Security Risk Management in Distributed Environment

PubMed Central

Zheng, Chundong

2014-01-01

Given the increasing cooperation between organizations, the flexible exchange of security information across the allied organizations is critical to effectively manage information systems (IS) security in a distributed environment. In this paper, we develop a cooperative model for IS security risk management in a distributed environment. In the proposed model, the exchange of security information among the interconnected IS under distributed environment is supported by Bayesian networks (BNs). In addition, for an organization's IS, a BN is utilized to represent its security environment and dynamically predict its security risk level, by which the security manager can select an optimal action to safeguard the firm's information resources. The actual case studied illustrates the cooperative model presented in this paper and how it can be exploited to manage the distributed IS security risk effectively. PMID:24563626

Problems With Risk Reclassification Methods for Evaluating Prediction Models

PubMed Central

Pepe, Margaret S.

2011-01-01

For comparing the performance of a baseline risk prediction model with one that includes an additional predictor, a risk reclassification analysis strategy has been proposed. The first step is to cross-classify risks calculated according to the 2 models for all study subjects. Summary measures including the percentage of reclassification and the percentage of correct reclassification are calculated, along with 2 reclassification calibration statistics. The author shows that interpretations of the proposed summary measures and P values are problematic. The author's recommendation is to display the reclassification table, because it shows interesting information, but to use alternative methods for summarizing and comparing model performance. The Net Reclassification Index has been suggested as one alternative method. The author argues for reporting components of the Net Reclassification Index because they are more clinically relevant than is the single numerical summary measure. PMID:21555714

A probabilistic assessment of health risks associated with short-term exposure to tropospheric ozone

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitfield, R.G; Biller, W.F.; Jusko, M.J.

1996-06-01

The work described in this report is part of a larger risk assessment sponsored by the U.S. Environmental Protection Agency. Earlier efforts developed exposure-response relationships for acute health effects among populations engaged in heavy exertion. Those efforts also developed a probabilistic national ambient air quality standards exposure model and a general methodology for integrating probabilistic exposure-response relation- ships and exposure estimates to calculate overall risk results. Recently published data make it possible to model additional health endpoints (for exposure at moderate exertion), including hospital admissions. New air quality and exposure estimates for alternative national ambient air quality standards for ozonemore » are combined with exposure-response models to produce the risk results for hospital admissions and acute health effects. Sample results explain the methodology and introduce risk output formats.« less

Prediction of individual genetic risk to prostate cancer using a polygenic score.

PubMed

Szulkin, Robert; Whitington, Thomas; Eklund, Martin; Aly, Markus; Eeles, Rosalind A; Easton, Douglas; Kote-Jarai, Z Sofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Southey, Melissa C; Fitzgerald, Liesel M; Henderson, Brian E; Schumacher, Fredrick; Haiman, Christopher A; Schleutker, Johanna; Wahlfors, Tiina; Tammela, Teuvo L J; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Lubiński, Jan; Kluźniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Butterbach, Katja; Stegmaier, Christa; Park, Jong Y; Sellers, Thomas; Lin, Hui-Yi; Lim, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Gronberg, Henrik; Wiklund, Fredrik

2015-09-01

Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. © 2015 Wiley Periodicals, Inc.

How pharmacokinetic modeling could improve a risk assessment for manganese

EPA Science Inventory

The neurotoxicity of manganese (Mn) is well established, yet the risk assessment of Mn is made complex by certain enigmas. These include apparently greatertoxicity via inhalation compared to oral exposure and greater toxicity in humans compared to rats. In addition, until recentl...

Method and system for dynamic probabilistic risk assessment

NASA Technical Reports Server (NTRS)

Dugan, Joanne Bechta (Inventor); Xu, Hong (Inventor)

2013-01-01

The DEFT methodology, system and computer readable medium extends the applicability of the PRA (Probabilistic Risk Assessment) methodology to computer-based systems, by allowing DFT (Dynamic Fault Tree) nodes as pivot nodes in the Event Tree (ET) model. DEFT includes a mathematical model and solution algorithm, supports all common PRA analysis functions and cutsets. Additional capabilities enabled by the DFT include modularization, phased mission analysis, sequence dependencies, and imperfect coverage.

Additive genetic risk from five serotonin system polymorphisms interacts with interpersonal stress to predict depression.

PubMed

Vrshek-Schallhorn, Suzanne; Stroud, Catherine B; Mineka, Susan; Zinbarg, Richard E; Adam, Emma K; Redei, Eva E; Hammen, Constance; Craske, Michelle G

2015-11-01

Behavioral genetic research supports polygenic models of depression in which many genetic variations each contribute a small amount of risk, and prevailing diathesis-stress models suggest gene-environment interactions (G×E). Multilocus profile scores of additive risk offer an approach that is consistent with polygenic models of depression risk. In a first demonstration of this approach in a G×E predicting depression, we created an additive multilocus profile score from 5 serotonin system polymorphisms (1 each in the genes HTR1A, HTR2A, HTR2C, and 2 in TPH2). Analyses focused on 2 forms of interpersonal stress as environmental risk factors. Using 5 years of longitudinal diagnostic and life stress interviews from 387 emerging young adults in the Youth Emotion Project, survival analyses show that this multilocus profile score interacts with major interpersonal stressful life events to predict major depressive episode onsets (hazard ratio [HR] = 1.815, p = .007). Simultaneously, there was a significant protective effect of the profile score without a recent event (HR = 0.83, p = .030). The G×E effect with interpersonal chronic stress was not significant (HR = 1.15, p = .165). Finally, effect sizes for genetic factors examined ignoring stress suggested such an approach could lead to overlooking or misinterpreting genetic effects. Both the G×E effect and the protective simple main effect were replicated in a sample of early adolescent girls (N = 105). We discuss potential benefits of the multilocus genetic profile score approach and caveats for future research. (c) 2015 APA, all rights reserved).

Development of a GCR Event-based Risk Model

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Ponomarev, Artem L.; Plante, Ianik; Carra, Claudio; Kim, Myung-Hee

2009-01-01

A goal at NASA is to develop event-based systems biology models of space radiation risks that will replace the current dose-based empirical models. Complex and varied biochemical signaling processes transmit the initial DNA and oxidative damage from space radiation into cellular and tissue responses. Mis-repaired damage or aberrant signals can lead to genomic instability, persistent oxidative stress or inflammation, which are causative of cancer and CNS risks. Protective signaling through adaptive responses or cell repopulation is also possible. We are developing a computational simulation approach to galactic cosmic ray (GCR) effects that is based on biological events rather than average quantities such as dose, fluence, or dose equivalent. The goal of the GCR Event-based Risk Model (GERMcode) is to provide a simulation tool to describe and integrate physical and biological events into stochastic models of space radiation risks. We used the quantum multiple scattering model of heavy ion fragmentation (QMSFRG) and well known energy loss processes to develop a stochastic Monte-Carlo based model of GCR transport in spacecraft shielding and tissue. We validated the accuracy of the model by comparing to physical data from the NASA Space Radiation Laboratory (NSRL). Our simulation approach allows us to time-tag each GCR proton or heavy ion interaction in tissue including correlated secondary ions often of high multiplicity. Conventional space radiation risk assessment employs average quantities, and assumes linearity and additivity of responses over the complete range of GCR charge and energies. To investigate possible deviations from these assumptions, we studied several biological response pathway models of varying induction and relaxation times including the ATM, TGF -Smad, and WNT signaling pathways. We then considered small volumes of interacting cells and the time-dependent biophysical events that the GCR would produce within these tissue volumes to estimate how GCR event rates mapped to biological signaling induction and relaxation times. We considered several hypotheses related to signaling and cancer risk, and then performed simulations for conditions where aberrant or adaptive signaling would occur on long-duration space mission. Our results do not support the conventional assumptions of dose, linearity and additivity. A discussion on how event-based systems biology models, which focus on biological signaling as the mechanism to propagate damage or adaptation, can be further developed for cancer and CNS space radiation risk projections is given.

A case-control study of rheumatoid arthritis revealed abdominal obesity and environmental risk factor interactions in northern China.

PubMed

Fu, Lingyu; Zhang, Jianming; Jin, Lei; Zhang, Yao; Cui, Saisai; Chen, Meng

2018-03-01

The aim of this study was to evaluate new and previously hypothesized environmental risk factors and their interaction with rheumatoid arthritis (RA). Four hundred patients recently diagnosed with RA and 400 controls frequency-matched by gender and birth year using Propensity Score Matching (PSM) were selected from northern China. Investigation was performed using self-reported data from interviewer-administered surveys. Associations between exposure variables and risk of RA were evaluated using multifactor non-conditional logistic regression. It showed that damp localities, draft indoor, abdominal obesity (AO), and family history of RA among first-degree relatives were independent risk factors and drinking of milk was independent protective factors for RA. Besides these risk factors, in women, infrequent delivery times, early age at menopause, and late age at menarche were also independent risk factors for RA. Both the additive model and the multiplication model suggested that there was an interaction relationship between AO and damp localities (p < .001), and only the additive model suggested that there was interaction relationship between AO and no milk drinking (p < .001) in our study population. In women, there was interaction relationship between AO and damp localities (p < .001) and between AO and age at menopause (p < .001). In northern China, damp localities, draft indoor, AO, family history of RA among first-degree relatives, and no milk drinking may be important risk factors of RA patients.

Nonelective colon cancer resections in elderly patients: results from the dutch surgical colorectal audit.

PubMed

Kolfschoten, N E; Wouters, M W J M; Gooiker, G A; Eddes, E H; Kievit, J; Tollenaar, R A E M; Marang-van de Mheen, P J

2012-01-01

The aim of the study was to assess which factors contribute to postoperative mortality, especially in elderly patients who undergo emergency colon cancer resections, using a nationwide population-based database. 6,161 patients (1,172 nonelective) who underwent a colon cancer resection in 2010 in the Netherlands were included. Risk factors for postoperative mortality were investigated using a multivariate logistic regression model for different age groups, elective and nonelective patients separately. For both elective and nonelective patients, mortality risk increased with increasing age. For nonelective elderly patients (80+ years), each additional risk factor increased the mortality risk. For a nonelective patient of 80+ years with an American Society of Anesthesiologists score of III+ and a left hemicolectomy or extended resection, postoperative mortality rate was 41% compared with 7% in patients without additional risk factors. For elderly patients with two or more additional risk factors, a nonelective resection should be considered a high-risk procedure with a mortality risk of up to 41%. The results of this study could be used to adequately inform patient and family and should have consequences for composing an operative team. Copyright © 2012 S. Karger AG, Basel.

Advantages of new cardiovascular risk-assessment strategies in high-risk patients with hypertension.

PubMed

Ruilope, Luis M; Segura, Julian

2005-10-01

Accurate assessment of cardiovascular disease (CVD) risk in patients with hypertension is important when planning appropriate treatment of modifiable risk factors. The causes of CVD are multifactorial, and hypertension seldom exists as an isolated risk factor. Classic models of risk assessment are more accurate than a simple counting of risk factors, but they are not generalizable to all populations. In addition, the risk associated with hypertension is graded, continuous, and independent of other risk factors, and this is not reflected in classic models of risk assessment. This article is intended to review both classic and newer models of CVD risk assessment. MEDLINE was searched for articles published between 1990 and 2005 that contained the terms cardiovascular disease, hypertension, or risk assessment. Articles describing major clinical trials, new data about cardiovascular risk, or global risk stratification were selected for review. Some patients at high long-term risk for CVD events (eg, patients aged <50 years with multiple risk factors) may go untreated because they do not meet the absolute risk-intervention threshold of 20% risk over 10 years with the classic model. Recognition of the limitations of classic risk-assessment models led to new guidelines, particularly those of the European Society of Hypertension-European Society of Cardiology. These guidelines view hypertension as one of many risk and disease factors that require treatment to decrease risk. These newer guidelines include a more comprehensive range of risk factors and more finely graded blood pressure ranges to stratify patients by degree of risk. Whether they accurately predict CVD risk in most populations is not known. Evidence from the Valsartan Antihypertensive Long-term Use Evaluation (VALUE) study, which stratified patients by several risk and disease factors, highlights the predictive value of some newer CVD risk assessments. Modern risk assessments, which include blood pressure along with a wide array of modifiable risk factors, may be more accurate than classic models for CVD risk prediction.

A Study of the Factors Associated with Risk for Development of Pressure Ulcers: A Longitudinal Analysis.

PubMed

Thomas, Elizebeth; Vinodkumar, Sudhaya; Mathew, Silvia; Setia, Maninder Singh

2015-01-01

Pressure ulcers (PUs) are prevalent in hospitalized patients; they may cause clinical, psychological, and economic problems in these patients. Previous studies are cross-sectional, have used pooled data, or cox-regression models to assess the risk for developing PU. However, PU risk scores change over time and models that account for time varying variables are useful for cohort analysis of data. The present longitudinal study was conducted to compare the risk of PU between surgical and nonsurgical patients, and to evaluate the factors associated with the development of these ulcers over a period of time. We evaluated 290 hospitalized patients over a 4 months period. The main outcomes for our analysis were: (1) Score on the pressure risk assessment scale; and (2) the proportion of individuals who were at severe risk for developing PUs. We used random effects models for longitudinal analysis of the data. The mean PU score was significantly higher in the nonsurgical patients compared with surgical patients at baseline (15.23 [3.86] vs. 9.33 [4.57]; P < 0.01). About 7% of the total patients had a score of >20 at baseline and were considered as being at high-risk for PU; the proportion was significantly higher among the nonsurgical patients compared with the surgical patients (14% vs. 4%, P = 0.003). In the adjusted models, there was no difference for severe risk for PU between surgical and nonsurgical patients (odds ratios [ORs]: 0.37, 95% confidence interval [CI]: 0.01-12.80). An additional day in the ward was associated with a significantly higher likelihood of being at high-risk for PU (OR: 1.47, 95% CI: 1.16-1.86). There were no significant differences between patients who were admitted for surgery compared with those who were not. An additional day in the ward, however, is important for developing a high-risk score for PU on the monitoring scale, and these patients require active interventions.

Challenges of developing a cardiovascular risk calculator for patients with rheumatoid arthritis.

PubMed

Crowson, Cynthia S; Rollefstad, Silvia; Kitas, George D; van Riel, Piet L C M; Gabriel, Sherine E; Semb, Anne Grete

2017-01-01

Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.

Risk adjustment for health care financing in chronic disease: what are we missing by failing to account for disease severity?

PubMed

Omachi, Theodore A; Gregorich, Steven E; Eisner, Mark D; Penaloza, Renee A; Tolstykh, Irina V; Yelin, Edward H; Iribarren, Carlos; Dudley, R Adams; Blanc, Paul D

2013-08-01

Adjustment for differing risks among patients is usually incorporated into newer payment approaches, and current risk models rely on age, sex, and diagnosis codes. It is unknown the extent to which controlling additionally for disease severity improves cost prediction. Failure to adjust for within-disease variation may create incentives to avoid sicker patients. We address this issue among patients with chronic obstructive pulmonary disease (COPD). Cost and clinical data were collected prospectively from 1202 COPD patients at Kaiser Permanente. Baseline analysis included age, sex, and diagnosis codes (using the Diagnostic Cost Group Relative Risk Score) in a general linear model predicting total medical costs in the following year. We determined whether adding COPD severity measures-forced expiratory volume in 1 second, 6-Minute Walk Test, dyspnea score, body mass index, and BODE Index (composite of the other 4 measures)-improved predictions. Separately, we examined household income as a cost predictor. Mean costs were $12,334/y. Controlling for Relative Risk Score, each ½ SD worsening in COPD severity factor was associated with $629 to $1135 in increased annual costs (all P<0.01). The lowest stratum of forced expiratory volume in 1 second (<30% normal) predicted $4098 (95% confidence interval, $576-$8773) additional costs. Household income predicted excess costs when added to the baseline model (P=0.038), but this became nonsignificant when also incorporating the BODE Index. Disease severity measures explain significant cost variations beyond current risk models, and adding them to such models appears important to fairly compensate organizations that accept responsibility for sicker COPD patients. Appropriately controlling for disease severity also accounts for costs otherwise associated with lower socioeconomic status.

Risk Based Reservoir Operations Using Ensemble Streamflow Predictions for Lake Mendocino in Mendocino County, California

NASA Astrophysics Data System (ADS)

Delaney, C.; Mendoza, J.; Whitin, B.; Hartman, R. K.

2017-12-01

Ensemble Forecast Operations (EFO) is a risk based approach of reservoir flood operations that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, each member of an ESP is individually modeled to forecast system conditions and calculate risk of reaching critical operational thresholds. Reservoir release decisions are computed which seek to manage forecasted risk to established risk tolerance levels. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC, which approximates flow forecasts for 61 ensemble members for a 15-day horizon. Model simulation results of the EFO alternative demonstrate a 36% increase in median end of water year (September 30) storage levels over existing operations. Additionally, model results show no increase in occurrence of flows above flood stage for points downstream of Lake Mendocino. This investigation demonstrates that the EFO alternative may be a viable approach for managing Lake Mendocino for multiple purposes (water supply, flood mitigation, ecosystems) and warrants further investigation through additional modeling and analysis.

Pretreatment Nomogram to Predict the Risk of Acute Urinary Retention After I-125 Prostate Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roeloffzen, Ellen M., E-mail: e.m.a.roeloffzen@umcutrecht.nl; Vulpen, Marco van; Battermann, Jan J.

Purpose: Acute urinary retention (AUR) after iodine-125 (I-125) prostate brachytherapy negatively influences long-term quality of life and therefore should be prevented. We aimed to develop a nomogram to preoperatively predict the risk of AUR. Methods: Using the preoperative data of 714 consecutive patients who underwent I-125 prostate brachytherapy between 2005 and 2008 at our department, we modeled the probability of AUR. Multivariate logistic regression analysis was used to assess the predictive ability of a set of pretreatment predictors and the additional value of a new risk factor (the extent of prostate protrusion into the bladder). The performance of the finalmore » model was assessed with calibration and discrimination measures. Results: Of the 714 patients, 57 patients (8.0%) developed AUR after implantation. Multivariate analysis showed that the combination of prostate volume, IPSS score, neoadjuvant hormonal treatment and the extent of prostate protrusion contribute to the prediction of AUR. The discriminative value (receiver operator characteristic area, ROC) of the basic model (including prostate volume, International Prostate Symptom Score, and neoadjuvant hormonal treatment) to predict the development of AUR was 0.70. The addition of prostate protrusion significantly increased the discriminative power of the model (ROC 0.82). Calibration of this final model was good. The nomogram showed that among patients with a low sum score (<18 points), the risk of AUR was only 0%-5%. However, in patients with a high sum score (>35 points), the risk of AUR was more than 20%. Conclusion: This nomogram is a useful tool for physicians to predict the risk of AUR after I-125 prostate brachytherapy. The nomogram can aid in individualized treatment decision-making and patient counseling.« less

Assessment of production risks for winter wheat in different German regions under climate change conditions

NASA Astrophysics Data System (ADS)

Kersebaum, K. C.; Gandorfer, M.; Wegehenkel, M.

2012-04-01

The study shows climate change impacts on wheat production in selected regions across Germany. To estimate yield and economic effects the agro-ecosystem model HERMES was used. The model performed runs using 2 different releases of the model WETTREG providing statistically downscaled climate change scenarios for the weather station network of the German Weather Service. Simulations were done using intersected GIS information on soil types and land use identifying the most relevant sites for wheat production. The production risks for wheat yields at the middle of this century were compared to a reference of the present climate. The irrigation demand was determined by the model using an automatic irrigation mode. Production risks with and without irrigation were assessed and the economic feasibility to reduce production risks by irrigation was evaluated. Costs and benefits were compared. Additionally, environmental effects, e.g. groundwater recharge and nitrogen emissions were assessed for irrigated and rain fed systems. Results show that positive and negative effects of climate change occur within most regions depending on the site conditions. Water holding capacity and groundwater distance were the most important factors which determined the vulnerability of sites. Under climate change condition in the middle of the next century we can expect especially at sites with low water holding capacity decreasing average gross margins, higher production risks and a reduced nitrogen use efficiency under rainfed conditions. Irrigation seems to be profitable and risk reducing at those sites, provided that water for irrigation is available. Additionally, the use of irrigation can also increase nitrogen use efficiency which reduced emissions by leaching. Despite the site conditions results depend strongly on the used regional climate scenario and the model approach to consider the effect of elevated CO2 in the atmosphere.

Controlling the self-organizing dynamics in a sandpile model on complex networks by failure tolerance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qi, Junjian; Pfenninger, Stefan

In this paper, we propose a strategy to control the self-organizing dynamics of the Bak-Tang-Wiesenfeld (BTW) sandpile model on complex networks by allowing some degree of failure tolerance for the nodes and introducing additional active dissipation while taking the risk of possible node damage. We show that the probability for large cascades significantly increases or decreases respectively when the risk for node damage outweighs the active dissipation and when the active dissipation outweighs the risk for node damage. By considering the potential additional risk from node damage, a non-trivial optimal active dissipation control strategy which minimizes the total cost inmore » the system can be obtained. Under some conditions the introduced control strategy can decrease the total cost in the system compared to the uncontrolled model. Moreover, when the probability of damaging a node experiencing failure tolerance is greater than the critical value, then no matter how successful the active dissipation control is, the total cost of the system will have to increase. This critical damage probability can be used as an indicator of the robustness of a network or system. Copyright (C) EPLA, 2015« less

Space Shuttle critical function audit

NASA Technical Reports Server (NTRS)

Sacks, Ivan J.; Dipol, John; Su, Paul

1990-01-01

A large fault-tolerance model of the main propulsion system of the US space shuttle has been developed. This model is being used to identify single components and pairs of components that will cause loss of shuttle critical functions. In addition, this model is the basis for risk quantification of the shuttle. The process used to develop and analyze the model is digraph matrix analysis (DMA). The DMA modeling and analysis process is accessed via a graphics-based computer user interface. This interface provides coupled display of the integrated system schematics, the digraph models, the component database, and the results of the fault tolerance and risk analyses.

Development and Example Application of a Pilot Model for the Biogeochemical Cycling of Mercury in Watersheds: SERAFM-NPS

EPA Science Inventory

Mercury is a developmental neurotoxicant, ubiquitous in the environment, existing both naturally and through anthropogenic additions, resulting in human and ecological exposure risks primarily via consumption of mercury contaminated fish tissue. To better understand the risk ass...

Use of Academic Detailing With Audit and Feedback to Improve Antipsychotic Pharmacotherapy.

PubMed

Brunette, Mary F; Cotes, Robert O; de Nesnera, Alexander; McHugo, Gregory; Dzebisashvili, Nino; Xie, Haiyi; Bartels, Stephen J

2018-06-08

Second-generation antipsychotics vary in their propensity to cause serious cardiometabolic side effects. In addition, use of two or more antipsychotics (polypharmacy) may lead to additive side effects and has not been shown to be consistently more effective than monotherapy. This study examined the use of academic detailing with audit and feedback to improve antipsychotic prescribing practices, including antipsychotic polypharmacy and utilization of medication with high or low risk of cardiometabolic side effects ("high risk" or "low risk," respectively). Four intervention sessions were provided over two years to psychiatric care providers at community mental health centers. Segmented regression within the general estimating equation model framework used Medicaid pharmacy claims to examine prescribing patterns before and after the intervention among all beneficiaries (67,721 person-months) over a five-year period. After the intervention, 10.9% of beneficiaries with antipsychotic claims were on polypharmacy, compared with 13.1% before the invention. Use of high-risk and low-risk antipsychotics did not change. The final adjusted polypharmacy model showed that antipsychotic polypharmacy decreased among young adults and adults ages 40 or older compared with beneficiaries ages 30-39 (β=-.02, p=.04, and β=-.02, p=.007, respectively). The raw proportion of beneficiaries on high- and low-risk agents did not change, although final adjusted models demonstrated changes in use of high- and low-risk agents by diagnosis and risk group. Polypharmacy decreased among young and older adults after academic detailing with audit and feedback. Although further research is needed, this low-intensity intervention may help mental health systems reduce antipsychotic polypharmacy.

Validation of a novel air toxic risk model with air monitoring.

PubMed

Pratt, Gregory C; Dymond, Mary; Ellickson, Kristie; Thé, Jesse

2012-01-01

Three modeling systems were used to estimate human health risks from air pollution: two versions of MNRiskS (for Minnesota Risk Screening), and the USEPA National Air Toxics Assessment (NATA). MNRiskS is a unique cumulative risk modeling system used to assess risks from multiple air toxics, sources, and pathways on a local to a state-wide scale. In addition, ambient outdoor air monitoring data were available for estimation of risks and comparison with the modeled estimates of air concentrations. Highest air concentrations and estimated risks were generally found in the Minneapolis-St. Paul metropolitan area and lowest risks in undeveloped rural areas. Emissions from mobile and area (nonpoint) sources created greater estimated risks than emissions from point sources. Highest cancer risks were via ingestion pathway exposures to dioxins and related compounds. Diesel particles, acrolein, and formaldehyde created the highest estimated inhalation health impacts. Model-estimated air concentrations were generally highest for NATA and lowest for the AERMOD version of MNRiskS. This validation study showed reasonable agreement between available measurements and model predictions, although results varied among pollutants, and predictions were often lower than measurements. The results increased confidence in identifying pollutants, pathways, geographic areas, sources, and receptors of potential concern, and thus provide a basis for informing pollution reduction strategies and focusing efforts on specific pollutants (diesel particles, acrolein, and formaldehyde), geographic areas (urban centers), and source categories (nonpoint sources). The results heighten concerns about risks from food chain exposures to dioxins and PAHs. Risk estimates were sensitive to variations in methodologies for treating emissions, dispersion, deposition, exposure, and toxicity. © 2011 Society for Risk Analysis.

PP087. Multicenter external validation and recalibration of a model for preconceptional prediction of recurrent early-onset preeclampsia.

PubMed

van Kuijk, Sander; Delahaije, Denise; Dirksen, Carmen; Scheepers, Hubertina C J; Spaanderman, Marc; Ganzevoort, W; Duvekot, Hans; Oudijk, M A; van Pampus, M G; Dadelszen, Peter von; Peeters, Louis L; Smiths, Luc

2013-04-01

In an earlier paper we reported on the development of a model aimed at the prediction of preeclampsia recurrence, based on variables obtained before the next pregnancy (fasting glucose, BMI, previous birth of a small-for-gestational-age infant, duration of the previous pregnancy, and the presence of hypertension). To externally validate and recalibrate the prediction model for the risk of recurrence of early-onset preeclampsia. We collected data about course and outcome of the next ongoing pregnancy in 229 women with a history of early-onset preeclampsia. Recurrence was defined as preeclampsia requiring delivery before 34 weeks. We computed risk of recurrence and assessed model performance. In addition, we constructed a table comparing sensitivity, specificity, and predictive values for different suggested risk-thresholds. Early-onset preeclampsia recurred in 6.6% of women. The model systematically underestimated recurrence risk. The model's discriminative ability was modest, the area under the receiver operating characteristic curve was 58.9% (95% CI: 45.1 - 72.7). Using relevant risk-thresholds, the model created groups that were only moderately different in terms of their average risk of recurrent preeclampsia (Table 1). Compared to an AUC of 65% in the development cohort, the discriminate ability of the model was diminished. It had inadequate performance to classify women into clinically relevant risk groups. Copyright © 2013. Published by Elsevier B.V.

Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors.

PubMed

Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin

2016-08-01

Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.

Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases

PubMed Central

Lenz, Tobias L.; Deutsch, Aaron J.; Han, Buhm; Hu, Xinli; Okada, Yukinori; Eyre, Stephen; Knapp, Michael; Zhernakova, Alexandra; Huizinga, Tom W.J.; Abecasis, Goncalo; Becker, Jessica; Boeckxstaens, Guy E.; Chen, Wei-Min; Franke, Andre; Gladman, Dafna D.; Gockel, Ines; Gutierrez-Achury, Javier; Martin, Javier; Nair, Rajan P.; Nöthen, Markus M.; Onengut-Gumuscu, Suna; Rahman, Proton; Rantapää-Dahlqvist, Solbritt; Stuart, Philip E.; Tsoi, Lam C.; Van Heel, David A.; Worthington, Jane; Wouters, Mira M.; Klareskog, Lars; Elder, James T.; Gregersen, Peter K.; Schumacher, Johannes; Rich, Stephen S.; Wijmenga, Cisca; Sunyaev, Shamil R.; de Bakker, Paul I.W.; Raychaudhuri, Soumya

2015-01-01

Human leukocyte antigen (HLA) genes confer strong risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen binding repertoires between a heterozygote’s two expressed HLA variants may result in additional non-additive risk effects. We tested non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (RA, Ncases=5,337), type 1 diabetes (T1D, Ncases=5,567), psoriasis vulgaris (Ncases=3,089), idiopathic achalasia (Ncases=727), and celiac disease (Ncases=11,115). In four out of five diseases, we observed highly significant non-additive dominance effects (RA: P=2.5×1012; T1D: P=2.4×10−10; psoriasis: P=5.9×10−6; celiac disease: P=1.2×10−87). In three of these diseases, the dominance effects were explained by interactions between specific classical HLA alleles (RA: P=1.8×10−3; T1D: P=8.6×1027; celiac disease: P=6.0×10−100). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (RA: 1.4%, T1D: 4.0%, and celiac disease: 4.1%, beyond a simple additive model). PMID:26258845

The returns and risks of investment portfolio in stock market crashes

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Long, Chao; Chen, Xiao-Dan

2015-06-01

The returns and risks of investment portfolio in stock market crashes are investigated by considering a theoretical model, based on a modified Heston model with a cubic nonlinearity, proposed by Spagnolo and Valenti. Through numerically simulating probability density function of returns and the mean escape time of the model, the results indicate that: (i) the maximum stability of returns is associated with the maximum dispersion of investment portfolio and an optimal stop-loss position; (ii) the maximum risks are related with a worst dispersion of investment portfolio and the risks of investment portfolio are enhanced by increasing stop-loss position. In addition, the good agreements between the theoretical result and real market data are found in the behaviors of the probability density function and the mean escape time.

Assessing interactions between HLA-DRB1*15 and infectious mononucleosis on the risk of multiple sclerosis.

PubMed

Disanto, Giulio; Hall, Carolina; Lucas, Robyn; Ponsonby, Anne-Louise; Berlanga-Taylor, Antonio J; Giovannoni, Gavin; Ramagopalan, Sreeram V

2013-09-01

Gene-environment interactions may shed light on the mechanisms underlying multiple sclerosis (MS). We pooled data from two case-control studies on incident demyelination and used different methods to assess interaction between HLA-DRB1*15 (DRB1-15) and history of infectious mononucleosis (IM). Individuals exposed to both factors were at substantially increased risk of disease (OR=7.32, 95% CI=4.92-10.90). In logistic regression models, DRB1-15 and IM status were independent predictors of disease while their interaction term was not (DRB1-15*IM: OR=1.35, 95% CI=0.79-2.23). However, interaction on an additive scale was evident (Synergy index=2.09, 95% CI=1.59-2.59; excess risk due to interaction=3.30, 95%CI=0.47-6.12; attributable proportion due to interaction=45%, 95% CI=22-68%). This suggests, if the additive model is appropriate, the DRB1-15 and IM may be involved in the same causal process leading to MS and highlights the benefit of reporting gene-environment interactions on both a multiplicative and additive scale.

Impact of model-based risk analysis for liver surgery planning.

PubMed

Hansen, C; Zidowitz, S; Preim, B; Stavrou, G; Oldhafer, K J; Hahn, H K

2014-05-01

A model-based risk analysis for oncologic liver surgery was described in previous work (Preim et al. in Proceedings of international symposium on computer assisted radiology and surgery (CARS), Elsevier, Amsterdam, pp. 353–358, 2002; Hansen et al. Int I Comput Assist Radiol Surg 4(5):469–474, 2009). In this paper, we present an evaluation of this method. To prove whether and how the risk analysis facilitates the process of liver surgery planning, an explorative user study with 10 liver experts was conducted. The purpose was to compare and analyze their decision-making. The results of the study show that model-based risk analysis enhances the awareness of surgical risk in the planning stage. Participants preferred smaller resection volumes and agreed more on the safety margins’ width in case the risk analysis was available. In addition, time to complete the planning task and confidence of participants were not increased when using the risk analysis. This work shows that the applied model-based risk analysis may influence important planning decisions in liver surgery. It lays a basis for further clinical evaluations and points out important fields for future research.

Risk Prediction for Epithelial Ovarian Cancer in 11 United States–Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci

PubMed Central

Clyde, Merlise A.; Palmieri Weber, Rachel; Iversen, Edwin S.; Poole, Elizabeth M.; Doherty, Jennifer A.; Goodman, Marc T.; Ness, Roberta B.; Risch, Harvey A.; Rossing, Mary Anne; Terry, Kathryn L.; Wentzensen, Nicolas; Whittemore, Alice S.; Anton-Culver, Hoda; Bandera, Elisa V.; Berchuck, Andrew; Carney, Michael E.; Cramer, Daniel W.; Cunningham, Julie M.; Cushing-Haugen, Kara L.; Edwards, Robert P.; Fridley, Brooke L.; Goode, Ellen L.; Lurie, Galina; McGuire, Valerie; Modugno, Francesmary; Moysich, Kirsten B.; Olson, Sara H.; Pearce, Celeste Leigh; Pike, Malcolm C.; Rothstein, Joseph H.; Sellers, Thomas A.; Sieh, Weiva; Stram, Daniel; Thompson, Pamela J.; Vierkant, Robert A.; Wicklund, Kristine G.; Wu, Anna H.; Ziogas, Argyrios; Tworoger, Shelley S.; Schildkraut, Joellen M.

2016-01-01

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted. PMID:27698005

The Missing Stakeholder Group: Why Patients Should be Involved in Health Economic Modelling.

PubMed

van Voorn, George A K; Vemer, Pepijn; Hamerlijnck, Dominique; Ramos, Isaac Corro; Teunissen, Geertruida J; Al, Maiwenn; Feenstra, Talitha L

2016-04-01

Evaluations of healthcare interventions, e.g. new drugs or other new treatment strategies, commonly include a cost-effectiveness analysis (CEA) that is based on the application of health economic (HE) models. As end users, patients are important stakeholders regarding the outcomes of CEAs, yet their knowledge of HE model development and application, or their involvement therein, is absent. This paper considers possible benefits and risks of patient involvement in HE model development and application for modellers and patients. An exploratory review of the literature has been performed on stakeholder-involved modelling in various disciplines. In addition, Dutch patient experts have been interviewed about their experience in, and opinion about, the application of HE models. Patients have little to no knowledge of HE models and are seldom involved in HE model development and application. Benefits of becoming involved would include a greater understanding and possible acceptance by patients of HE model application, improved model validation, and a more direct infusion of patient expertise. Risks would include patient bias and increased costs of modelling. Patient involvement in HE modelling seems to carry several benefits as well as risks. We claim that the benefits may outweigh the risks and that patients should become involved.

Development and Validation of a Practical Two-Step Prediction Model and Clinical Risk Score for Post-Thrombotic Syndrome.

PubMed

Amin, Elham E; van Kuijk, Sander M J; Joore, Manuela A; Prandoni, Paolo; Cate, Hugo Ten; Cate-Hoek, Arina J Ten

2018-06-04

 Post-thrombotic syndrome (PTS) is a common chronic consequence of deep vein thrombosis that affects the quality of life and is associated with substantial costs. In clinical practice, it is not possible to predict the individual patient risk. We develop and validate a practical two-step prediction tool for PTS in the acute and sub-acute phase of deep vein thrombosis.  Multivariable regression modelling with data from two prospective cohorts in which 479 (derivation) and 1,107 (validation) consecutive patients with objectively confirmed deep vein thrombosis of the leg, from thrombosis outpatient clinic of Maastricht University Medical Centre, the Netherlands (derivation) and Padua University hospital in Italy (validation), were included. PTS was defined as a Villalta score of ≥ 5 at least 6 months after acute thrombosis.  Variables in the baseline model in the acute phase were: age, body mass index, sex, varicose veins, history of venous thrombosis, smoking status, provoked thrombosis and thrombus location. For the secondary model, the additional variable was residual vein obstruction. Optimism-corrected area under the receiver operating characteristic curves (AUCs) were 0.71 for the baseline model and 0.60 for the secondary model. Calibration plots showed well-calibrated predictions. External validation of the derived clinical risk scores was successful: AUC, 0.66 (95% confidence interval [CI], 0.63-0.70) and 0.64 (95% CI, 0.60-0.69).  Individual risk for PTS in the acute phase of deep vein thrombosis can be predicted based on readily accessible baseline clinical and demographic characteristics. The individual risk in the sub-acute phase can be predicted with limited additional clinical characteristics. Schattauer GmbH Stuttgart.

Validation of the IHC4 Breast Cancer Prognostic Algorithm Using Multiple Approaches on the Multinational TEAM Clinical Trial.

PubMed

Bartlett, John M S; Christiansen, Jason; Gustavson, Mark; Rimm, David L; Piper, Tammy; van de Velde, Cornelis J H; Hasenburg, Annette; Kieback, Dirk G; Putter, Hein; Markopoulos, Christos J; Dirix, Luc Y; Seynaeve, Caroline; Rea, Daniel W

2016-01-01

Hormone receptors HER2/neu and Ki-67 are markers of residual risk in early breast cancer. An algorithm (IHC4) combining these markers may provide additional information on residual risk of recurrence in patients treated with hormone therapy. To independently validate the IHC4 algorithm in the multinational Tamoxifen Versus Exemestane Adjuvant Multicenter Trial (TEAM) cohort, originally developed on the trans-ATAC (Arimidex, Tamoxifen, Alone or in Combination Trial) cohort, by comparing 2 methodologies. The IHC4 biomarker expression was quantified on TEAM cohort samples (n = 2919) by using 2 independent methodologies (conventional 3,3'-diaminobezidine [DAB] immunohistochemistry with image analysis and standardized quantitative immunofluorescence [QIF] by AQUA technology). The IHC4 scores were calculated by using the same previously established coefficients and then compared with recurrence-free and distant recurrence-free survival, using multivariate Cox proportional hazards modeling. The QIF model was highly significant for prediction of residual risk (P < .001), with continuous model scores showing a hazard ratio (HR) of 1.012 (95% confidence interval [95% CI]: 1.010-1.014), which was significantly higher than that for the DAB model (HR: 1.008, 95% CI: 1.006-1.009); P < .001). Each model added significant prognostic value in addition to recognized clinical prognostic factors, including nodal status, in multivariate analyses. Quantitative immunofluorescence, however, showed more accuracy with respect to overall residual risk assessment than the DAB model. The use of the IHC4 algorithm was validated on the TEAM trial for predicting residual risk in patients with breast cancer. These data support the use of the IHC4 algorithm clinically, but quantitative and standardized approaches need to be used.

Sexual risk behavior among youth: modeling the influence of prosocial activities and socioeconomic factors.

PubMed

Ramirez-Valles, J; Zimmerman, M A; Newcomb, M D

1998-09-01

Sexual activity among high-school-aged youths has steadily increased since the 1970s, emerging as a significant public health concern. Yet, patterns of youth sexual risk behavior are shaped by social class, race, and gender. Based on sociological theories of financial deprivation and collective socialization, we develop and test a model of the relationships among neighborhood poverty; family structure and social class position; parental involvement; prosocial activities; race; and gender as they predict youth sexual risk behavior. We employ structural equation modeling to test this model on a cross-sectional sample of 370 sexually active high-school students from a midwestern city; 57 percent (n = 209) are males and 86 percent are African American. We find that family structure indirectly predicts sexual risk behavior through neighborhood poverty, parental involvement, and prosocial activities. In addition, family class position indirectly predicts sexual risk behavior through neighborhood poverty and prosocial activities. We address implications for theory and health promotion.

A measurement model of perinatal stressors: identifying risk for postnatal emotional distress in mothers of high-risk infants.

PubMed

DeMier, R L; Hynan, M T; Hatfield, R F; Varner, M W; Harris, H B; Manniello, R L

2000-01-01

A measurement model of perinatal stressors was first evaluated for reliability and then used to identify risk factors for postnatal emotional distress in high-risk mothers. In Study 1, six measures (gestational age of the baby, birthweight, length of the baby's hospitalization, a postnatal complications rating for the infant, and Apgar scores at 1 and 5 min) were obtained from chart reviews of preterm births at two different hospitals. Confirmatory factor analyses revealed that the six measures could be accounted for by three factors: (a) Infant Maturity, (b) Apgar Ratings, and (c) Complications. In Study 2, a modified measurement model indicated that Infant Maturity and Complications were significant predictors of postnatal emotional distress in an additional sample of mothers. This measurement model may also be useful in predicting (a) other measures of psychological distress in parents, and (b) measures of cognitive and motor development in infants.

Global review of open access risk assessment software packages valid for global or continental scale analysis

NASA Astrophysics Data System (ADS)

Daniell, James; Simpson, Alanna; Gunasekara, Rashmin; Baca, Abigail; Schaefer, Andreas; Ishizawa, Oscar; Murnane, Rick; Tijssen, Annegien; Deparday, Vivien; Forni, Marc; Himmelfarb, Anne; Leder, Jan

2015-04-01

Over the past few decades, a plethora of open access software packages for the calculation of earthquake, volcanic, tsunami, storm surge, wind and flood have been produced globally. As part of the World Bank GFDRR Review released at the Understanding Risk 2014 Conference, over 80 such open access risk assessment software packages were examined. Commercial software was not considered in the evaluation. A preliminary analysis was used to determine whether the 80 models were currently supported and if they were open access. This process was used to select a subset of 31 models that include 8 earthquake models, 4 cyclone models, 11 flood models, and 8 storm surge/tsunami models for more detailed analysis. By using multi-criteria analysis (MCDA) and simple descriptions of the software uses, the review allows users to select a few relevant software packages for their own testing and development. The detailed analysis evaluated the models on the basis of over 100 criteria and provides a synopsis of available open access natural hazard risk modelling tools. In addition, volcano software packages have since been added making the compendium of risk software tools in excess of 100. There has been a huge increase in the quality and availability of open access/source software over the past few years. For example, private entities such as Deltares now have an open source policy regarding some flood models (NGHS). In addition, leaders in developing risk models in the public sector, such as Geoscience Australia (EQRM, TCRM, TsuDAT, AnuGA) or CAPRA (ERN-Flood, Hurricane, CRISIS2007 etc.), are launching and/or helping many other initiatives. As we achieve greater interoperability between modelling tools, we will also achieve a future wherein different open source and open access modelling tools will be increasingly connected and adapted towards unified multi-risk model platforms and highly customised solutions. It was seen that many software tools could be improved by enabling user-defined exposure and vulnerability. Without this function, many tools can only be used regionally and not at global or continental scale. It is becoming increasingly easy to use multiple packages for a single region and/or hazard to characterize the uncertainty in the risk, or use as checks for the sensitivities in the analysis. There is a potential for valuable synergy between existing software. A number of open source software packages could be combined to generate a multi-risk model with multiple views of a hazard. This extensive review has simply attempted to provide a platform for dialogue between all open source and open access software packages and to hopefully inspire collaboration between developers, given the great work done by all open access and open source developers.

Software reliability through fault-avoidance and fault-tolerance

NASA Technical Reports Server (NTRS)

Vouk, Mladen A.; Mcallister, David F.

1993-01-01

Strategies and tools for the testing, risk assessment and risk control of dependable software-based systems were developed. Part of this project consists of studies to enable the transfer of technology to industry, for example the risk management techniques for safety-concious systems. Theoretical investigations of Boolean and Relational Operator (BRO) testing strategy were conducted for condition-based testing. The Basic Graph Generation and Analysis tool (BGG) was extended to fully incorporate several variants of the BRO metric. Single- and multi-phase risk, coverage and time-based models are being developed to provide additional theoretical and empirical basis for estimation of the reliability and availability of large, highly dependable software. A model for software process and risk management was developed. The use of cause-effect graphing for software specification and validation was investigated. Lastly, advanced software fault-tolerance models were studied to provide alternatives and improvements in situations where simple software fault-tolerance strategies break down.

The cardiovascular event reduction tool (CERT)--a simplified cardiac risk prediction model developed from the West of Scotland Coronary Prevention Study (WOSCOPS).

PubMed

L'Italien, G; Ford, I; Norrie, J; LaPuerta, P; Ehreth, J; Jackson, J; Shepherd, J

2000-03-15

The clinical decision to treat hypercholesterolemia is premised on an awareness of patient risk, and cardiac risk prediction models offer a practical means of determining such risk. However, these models are based on observational cohorts where estimates of the treatment benefit are largely inferred. The West of Scotland Coronary Prevention Study (WOSCOPS) provides an opportunity to develop a risk-benefit prediction model from the actual observed primary event reduction seen in the trial. Five-year Cox model risk estimates were derived from all WOSCOPS subjects (n = 6,595 men, aged 45 to 64 years old at baseline) using factors previously shown to be predictive of definite fatal coronary heart disease or nonfatal myocardial infarction. Model risk factors included age, diastolic blood pressure, total cholesterol/ high-density lipoprotein ratio (TC/HDL), current smoking, diabetes, family history of fatal coronary heart disease, nitrate use or angina, and treatment (placebo/ 40-mg pravastatin). All risk factors were expressed as categorical variables to facilitate risk assessment. Risk estimates were incorporated into a simple, hand-held slide rule or risk tool. Risk estimates were identified for 5-year age bands (45 to 65 years), 4 categories of TC/HDL ratio (<5.5, 5.5 to <6.5, 6.5 to <7.5, > or = 7.5), 2 levels of diastolic blood pressure (<90, > or = 90 mm Hg), from 0 to 3 additional risk factors (current smoking, diabetes, family history of premature fatal coronary heart disease, nitrate use or angina), and pravastatin treatment. Five-year risk estimates ranged from 2% in very low-risk subjects to 61% in the very high-risk subjects. Risk reduction due to pravastatin treatment averaged 31%. Thus, the Cardiovascular Event Reduction Tool (CERT) is a risk prediction model derived from the WOSCOPS trial. Its use will help physicians identify patients who will benefit from cholesterol reduction.

Health effects models for nuclear power plant accident consequence analysis: Low LET radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Evans, J.S.

1990-01-01

This report describes dose-response models intended to be used in estimating the radiological health effects of nuclear power plant accidents. Models of early and continuing effects, cancers and thyroid nodules, and genetic effects are provided. Weibull dose-response functions are recommended for evaluating the risks of early and continuing health effects. Three potentially lethal early effects -- the hematopoietic, pulmonary, and gastrointestinal syndromes -- are considered. In addition, models are included for assessing the risks of several nonlethal early and continuing effects -- including prodromal vomiting and diarrhea, hypothyroidism and radiation thyroiditis, skin burns, reproductive effects, and pregnancy losses. Linear andmore » linear-quadratic models are recommended for estimating cancer risks. Parameters are given for analyzing the risks of seven types of cancer in adults -- leukemia, bone, lung, breast, gastrointestinal, thyroid, and other.'' The category, other'' cancers, is intended to reflect the combined risks of multiple myeloma, lymphoma, and cancers of the bladder, kidney, brain, ovary, uterus and cervix. Models of childhood cancers due to in utero exposure are also developed. For most cancers, both incidence and mortality are addressed. The models of cancer risk are derived largely from information summarized in BEIR III -- with some adjustment to reflect more recent studies. 64 refs., 18 figs., 46 tabs.« less

Estimating community health needs against a Triple Aim background: What can we learn from current predictive risk models?

PubMed

Elissen, Arianne M J; Struijs, Jeroen N; Baan, Caroline A; Ruwaard, Dirk

2015-05-01

To support providers and commissioners in accurately assessing their local populations' health needs, this study produces an overview of Dutch predictive risk models for health care, focusing specifically on the type, combination and relevance of included determinants for achieving the Triple Aim (improved health, better care experience, and lower costs). We conducted a mixed-methods study combining document analyses, interviews and a Delphi study. Predictive risk models were identified based on a web search and expert input. Participating in the study were Dutch experts in predictive risk modelling (interviews; n=11) and experts in healthcare delivery, insurance and/or funding methodology (Delphi panel; n=15). Ten predictive risk models were analysed, comprising 17 unique determinants. Twelve were considered relevant by experts for estimating community health needs. Although some compositional similarities were identified between models, the combination and operationalisation of determinants varied considerably. Existing predictive risk models provide a good starting point, but optimally balancing resources and targeting interventions on the community level will likely require a more holistic approach to health needs assessment. Development of additional determinants, such as measures of people's lifestyle and social network, may require policies pushing the integration of routine data from different (healthcare) sources. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes.

PubMed

Petersen, Laura A; Pietz, Kenneth; Woodard, LeChauncy D; Byrne, Margaret

2005-01-01

Many possible methods of risk adjustment exist, but there is a dearth of comparative data on their performance. We compared the predictive validity of 2 widely used methods (Diagnostic Cost Groups [DCGs] and Adjusted Clinical Groups [ACGs]) for 2 clinical outcomes using a large national sample of patients. We studied all patients who used Veterans Health Administration (VA) medical services in fiscal year (FY) 2001 (n = 3,069,168) and assigned both a DCG and an ACG to each. We used logistic regression analyses to compare predictive ability for death or long-term care (LTC) hospitalization for age/gender models, DCG models, and ACG models. We also assessed the effect of adding age to the DCG and ACG models. Patients in the highest DCG categories, indicating higher severity of illness, were more likely to die or to require LTC hospitalization. Surprisingly, the age/gender model predicted death slightly more accurately than the ACG model (c-statistic of 0.710 versus 0.700, respectively). The addition of age to the ACG model improved the c-statistic to 0.768. The highest c-statistic for prediction of death was obtained with a DCG/age model (0.830). The lowest c-statistics were obtained for age/gender models for LTC hospitalization (c-statistic 0.593). The c-statistic for use of ACGs to predict LTC hospitalization was 0.783, and improved to 0.792 with the addition of age. The c-statistics for use of DCGs and DCG/age to predict LTC hospitalization were 0.885 and 0.890, respectively, indicating the best prediction. We found that risk adjusters based upon diagnoses predicted an increased likelihood of death or LTC hospitalization, exhibiting good predictive validity. In this comparative analysis using VA data, DCG models were generally superior to ACG models in predicting clinical outcomes, although ACG model performance was enhanced by the addition of age.

A modeling framework for exposing risks in complex systems.

PubMed

Sharit, J

2000-08-01

This article introduces and develops a modeling framework for exposing risks in the form of human errors and adverse consequences in high-risk systems. The modeling framework is based on two components: a two-dimensional theory of accidents in systems developed by Perrow in 1984, and the concept of multiple system perspectives. The theory of accidents differentiates systems on the basis of two sets of attributes. One set characterizes the degree to which systems are interactively complex; the other emphasizes the extent to which systems are tightly coupled. The concept of multiple perspectives provides alternative descriptions of the entire system that serve to enhance insight into system processes. The usefulness of these two model components derives from a modeling framework that cross-links them, enabling a variety of work contexts to be exposed and understood that would otherwise be very difficult or impossible to identify. The model components and the modeling framework are illustrated in the case of a large and comprehensive trauma care system. In addition to its general utility in the area of risk analysis, this methodology may be valuable in applications of current methods of human and system reliability analysis in complex and continually evolving high-risk systems.

Total Ionizing Dose Influence on the Single Event Effect Sensitivity in Samsung 8Gb NAND Flash Memories

NASA Astrophysics Data System (ADS)

Edmonds, Larry D.; Irom, Farokh; Allen, Gregory R.

2017-08-01

A recent model provides risk estimates for the deprogramming of initially programmed floating gates via prompt charge loss produced by an ionizing radiation environment. The environment can be a mixture of electrons, protons, and heavy ions. The model requires several input parameters. This paper extends the model to include TID effects in the control circuitry by including one additional parameter. Parameters intended to produce conservative risk estimates for the Samsung 8 Gb SLC NAND flash memory are given, subject to some qualifications.

Echocardiography and risk prediction in advanced heart failure: incremental value over clinical markers.

PubMed

Agha, Syed A; Kalogeropoulos, Andreas P; Shih, Jeffrey; Georgiopoulou, Vasiliki V; Giamouzis, Grigorios; Anarado, Perry; Mangalat, Deepa; Hussain, Imad; Book, Wendy; Laskar, Sonjoy; Smith, Andrew L; Martin, Randolph; Butler, Javed

2009-09-01

Incremental value of echocardiography over clinical parameters for outcome prediction in advanced heart failure (HF) is not well established. We evaluated 223 patients with advanced HF receiving optimal therapy (91.9% angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 92.8% beta-blockers, 71.8% biventricular pacemaker, and/or defibrillator use). The Seattle Heart Failure Model (SHFM) was used as the reference clinical risk prediction scheme. The incremental value of echocardiographic parameters for event prediction (death or urgent heart transplantation) was measured by the improvement in fit and discrimination achieved by addition of standard echocardiographic parameters to the SHFM. After a median follow-up of 2.4 years, there were 38 (17.0%) events (35 deaths; 3 urgent transplants). The SHFM had likelihood ratio (LR) chi(2) 32.0 and C statistic 0.756 for event prediction. Left ventricular end-systolic volume, stroke volume, and severe tricuspid regurgitation were independent echocardiographic predictors of events. The addition of these parameters to SHFM improved LR chi(2) to 72.0 and C statistic to 0.866 (P < .001 and P=.019, respectively). Reclassifying the SHFM-predicted risk with use of the echocardiography-added model resulted in improved prognostic separation. Addition of standard echocardiographic variables to the SHFM results in significant improvement in risk prediction for patients with advanced HF.

Personality and diabetes mellitus incidence in a national sample.

PubMed

Cukić, Iva; Weiss, Alexander

2014-09-01

To test whether personality traits were prospectively associated with type 2 diabetes incidence. The sample (n=6798) was derived from the National Health and Nutrition Examination Survey Epidemiological Follow-up Study cohort. We fit four logistic regression models to test whether neuroticism, extraversion, openness to experience, or the Type A behavior pattern predicted type 2 diabetes incidence. Model 1 included sex, age, and race/ethnicity. Model 2 added personality traits, Model 3 added depressive symptoms, and Model 4 added body mass index (BMI), hypertension, and cigarette smoking status as predictors. In Model 1 age was associated with increased risk of diabetes (2% per year); being black as opposed to white was associated with a three-fold increase in risk. In Model 2 age and being black were still significant and extraversion was associated with decreased risk (17% per standard deviation [SD]). In Model 3 age, being black, and extraversion were still significant. In addition, neuroticism was associated with decreased risk (26% per SD) and depressive symptoms were associated with increased risk (28% per SD). In Model 4 age, being black, neuroticism, and depressive symptoms were still significant. BMI was associated with increased risk (14% per SD) and extraversion was no longer significant. Higher neuroticism was associated with reduced type 2 diabetes risk even after controlling for race/ethnicity, age, depressive symptoms, and BMI. Extraversion and Type A behavior were not significant after including covariates. Copyright © 2014 Elsevier Inc. All rights reserved.

Quantifying the predictive accuracy of time-to-event models in the presence of competing risks.

PubMed

Schoop, Rotraut; Beyersmann, Jan; Schumacher, Martin; Binder, Harald

2011-02-01

Prognostic models for time-to-event data play a prominent role in therapy assignment, risk stratification and inter-hospital quality assurance. The assessment of their prognostic value is vital not only for responsible resource allocation, but also for their widespread acceptance. The additional presence of competing risks to the event of interest requires proper handling not only on the model building side, but also during assessment. Research into methods for the evaluation of the prognostic potential of models accounting for competing risks is still needed, as most proposed methods measure either their discrimination or calibration, but do not examine both simultaneously. We adapt the prediction error proposal of Graf et al. (Statistics in Medicine 1999, 18, 2529–2545) and Gerds and Schumacher (Biometrical Journal 2006, 48, 1029–1040) to handle models with competing risks, i.e. more than one possible event type, and introduce a consistent estimator. A simulation study investigating the behaviour of the estimator in small sample size situations and for different levels of censoring together with a real data application follows.

Evaluating Predictive Models of Software Quality

NASA Astrophysics Data System (ADS)

Ciaschini, V.; Canaparo, M.; Ronchieri, E.; Salomoni, D.

2014-06-01

Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

Utility of existing diabetes risk prediction tools for young black and white adults: Evidence from the Bogalusa Heart Study.

PubMed

Pollock, Benjamin D; Hu, Tian; Chen, Wei; Harville, Emily W; Li, Shengxu; Webber, Larry S; Fonseca, Vivian; Bazzano, Lydia A

2017-01-01

To evaluate several adult diabetes risk calculation tools for predicting the development of incident diabetes and pre-diabetes in a bi-racial, young adult population. Surveys beginning in young adulthood (baseline age ≥18) and continuing across multiple decades for 2122 participants of the Bogalusa Heart Study were used to test the associations of five well-known adult diabetes risk scores with incident diabetes and pre-diabetes using separate Cox models for each risk score. Racial differences were tested within each model. Predictive utility and discrimination were determined for each risk score using the Net Reclassification Index (NRI) and Harrell's c-statistic. All risk scores were strongly associated (p<.0001) with incident diabetes and pre-diabetes. The Wilson model indicated greater risk of diabetes for blacks versus whites with equivalent risk scores (HR=1.59; 95% CI 1.11-2.28; p=.01). C-statistics for the diabetes risk models ranged from 0.79 to 0.83. Non-event NRIs indicated high specificity (non-event NRIs: 76%-88%), but poor sensitivity (event NRIs: -23% to -3%). Five diabetes risk scores established in middle-aged, racially homogenous adult populations are generally applicable to younger adults with good specificity but poor sensitivity. The addition of race to these models did not result in greater predictive capabilities. A more sensitive risk score to predict diabetes in younger adults is needed. Copyright © 2017 Elsevier Inc. All rights reserved.

CONTROL FUNCTION ASSISTED IPW ESTIMATION WITH A SECONDARY OUTCOME IN CASE-CONTROL STUDIES.

PubMed

Sofer, Tamar; Cornelis, Marilyn C; Kraft, Peter; Tchetgen Tchetgen, Eric J

2017-04-01

Case-control studies are designed towards studying associations between risk factors and a single, primary outcome. Information about additional, secondary outcomes is also collected, but association studies targeting such secondary outcomes should account for the case-control sampling scheme, or otherwise results may be biased. Often, one uses inverse probability weighted (IPW) estimators to estimate population effects in such studies. IPW estimators are robust, as they only require correct specification of the mean regression model of the secondary outcome on covariates, and knowledge of the disease prevalence. However, IPW estimators are inefficient relative to estimators that make additional assumptions about the data generating mechanism. We propose a class of estimators for the effect of risk factors on a secondary outcome in case-control studies that combine IPW with an additional modeling assumption: specification of the disease outcome probability model. We incorporate this model via a mean zero control function. We derive the class of all regular and asymptotically linear estimators corresponding to our modeling assumption, when the secondary outcome mean is modeled using either the identity or the log link. We find the efficient estimator in our class of estimators and show that it reduces to standard IPW when the model for the primary disease outcome is unrestricted, and is more efficient than standard IPW when the model is either parametric or semiparametric.

Combining Knowledge and Data Driven Insights for Identifying Risk Factors using Electronic Health Records

PubMed Central

Sun, Jimeng; Hu, Jianying; Luo, Dijun; Markatou, Marianthi; Wang, Fei; Edabollahi, Shahram; Steinhubl, Steven E.; Daar, Zahra; Stewart, Walter F.

2012-01-01

Background: The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification. Methods: We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors. Results: The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003–2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist. Conclusion: We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors. PMID:23304365

Common carotid intima-media thickness does not add to Framingham risk score in individuals with diabetes mellitus: the USE-IMT initiative.

PubMed

den Ruijter, H M; Peters, S A E; Groenewegen, K A; Anderson, T J; Britton, A R; Dekker, J M; Engström, G; Eijkemans, M J; Evans, G W; de Graaf, J; Grobbee, D E; Hedblad, B; Hofman, A; Holewijn, S; Ikeda, A; Kavousi, M; Kitagawa, K; Kitamura, A; Koffijberg, H; Ikram, M A; Lonn, E M; Lorenz, M W; Mathiesen, E B; Nijpels, G; Okazaki, S; O'Leary, D H; Polak, J F; Price, J F; Robertson, C; Rembold, C M; Rosvall, M; Rundek, T; Salonen, J T; Sitzer, M; Stehouwer, C D A; Witteman, J C; Moons, K G; Bots, M L

2013-07-01

The aim of this work was to investigate whether measurement of the mean common carotid intima-media thickness (CIMT) improves cardiovascular risk prediction in individuals with diabetes. We performed a subanalysis among 4,220 individuals with diabetes in a large ongoing individual participant data meta-analysis involving 56,194 subjects from 17 population-based cohorts worldwide. We first refitted the risk factors of the Framingham heart risk score on the individuals without previous cardiovascular disease (baseline model) and then expanded this model with the mean common CIMT (CIMT model). The absolute 10 year risk for developing a myocardial infarction or stroke was estimated from both models. In individuals with diabetes we compared discrimination and calibration of the two models. Reclassification of individuals with diabetes was based on allocation to another cardiovascular risk category when mean common CIMT was added. During a median follow-up of 8.7 years, 684 first-time cardiovascular events occurred among the population with diabetes. The C statistic was 0.67 for the Framingham model and 0.68 for the CIMT model. The absolute 10 year risk for developing a myocardial infarction or stroke was 16% in both models. There was no net reclassification improvement with the addition of mean common CIMT (1.7%; 95% CI -1.8, 3.8). There were no differences in the results between men and women. There is no improvement in risk prediction in individuals with diabetes when measurement of the mean common CIMT is added to the Framingham risk score. Therefore, this measurement is not recommended for improving individual cardiovascular risk stratification in individuals with diabetes.

Applying risk and resilience models to predicting the effects of media violence on development.

PubMed

Prot, Sara; Gentile, Douglas A

2014-01-01

Although the effects of media violence on children and adolescents have been studied for over 50 years, they remain controversial. Much of this controversy is driven by a misunderstanding of causality that seeks the cause of atrocities such as school shootings. Luckily, several recent developments in risk and resilience theories offer a way out of this controversy. Four risk and resilience models are described, including the cascade model, dose-response gradients, pathway models, and turning-point models. Each is described and applied to the existing media effects literature. Recommendations for future research are discussed with regard to each model. In addition, we examine current developments in theorizing that stressors have sensitizing versus steeling effects and recent interest in biological and gene by environment interactions. We also discuss several of the cultural aspects that have supported the polarization and misunderstanding of the literature, and argue that applying risk and resilience models to the theories and data offers a more balanced way to understand the subtle effects of media violence on aggression within a multicausal perspective.

To kill a kangaroo: understanding the decision to pursue high-risk/high-gain resources.

PubMed

Jones, James Holland; Bird, Rebecca Bliege; Bird, Douglas W

2013-09-22

In this paper, we attempt to understand hunter-gatherer foraging decisions about prey that vary in both the mean and variance of energy return using an expected utility framework. We show that for skewed distributions of energetic returns, the standard linear variance discounting (LVD) model for risk-sensitive foraging can produce quite misleading results. In addition to creating difficulties for the LVD model, the skewed distributions characteristic of hunting returns create challenges for estimating probability distribution functions required for expected utility. We present a solution using a two-component finite mixture model for foraging returns. We then use detailed foraging returns data based on focal follows of individual hunters in Western Australia hunting for high-risk/high-gain (hill kangaroo) and relatively low-risk/low-gain (sand monitor) prey. Using probability densities for the two resources estimated from the mixture models, combined with theoretically sensible utility curves characterized by diminishing marginal utility for the highest returns, we find that the expected utility of the sand monitors greatly exceeds that of kangaroos despite the fact that the mean energy return for kangaroos is nearly twice as large as that for sand monitors. We conclude that the decision to hunt hill kangaroos does not arise simply as part of an energetic utility-maximization strategy and that additional social, political or symbolic benefits must accrue to hunters of this highly variable prey.

Improving the evidence base for services working with youth at-risk of involvement in the criminal justice system: developing a standardised program approach.

PubMed

Knight, Alice; Maple, Myfanwy; Shakeshaft, Anthony; Shakehsaft, Bernie; Pearce, Tania

2018-04-16

Young people who engage in multiple risk behaviour (high-risk young people) such as substance abuse, antisocial behaviour, low engagement in education and employment, self-harm or suicide ideation are more likely to experience serious harms later in life including homelessness, incarceration, violence and premature death. In addition to personal disadvantage, these harms represent an avoidable social and economic cost to society. Despite these harms, there is insufficient evidence about how to improve outcomes for high-risk young people. A key reason for this is a lack of standardisation in the way in which programs provided by services are defined and evaluated. This paper describes the development of a standardised intervention model for high-risk young people. The model can be used by service providers to achieve greater standardisation across their programs, outcomes and outcome measures. To demonstrate its feasibility, the model is applied to an existing program for high-risk young people. The development and uptake of a standardised intervention model for these programs will help to more rapidly develop a larger and more rigorous evidence-base to improve outcomes for high-risk young people.

Inclusion of Highest Glasgow Coma Scale Motor Component Score in Mortality Risk Adjustment for Benchmarking of Trauma Center Performance.

PubMed

Gomez, David; Byrne, James P; Alali, Aziz S; Xiong, Wei; Hoeft, Chris; Neal, Melanie; Subacius, Harris; Nathens, Avery B

2017-12-01

The Glasgow Coma Scale (GCS) is the most widely used measure of traumatic brain injury (TBI) severity. Currently, the arrival GCS motor component (mGCS) score is used in risk-adjustment models for external benchmarking of mortality. However, there is evidence that the highest mGCS score in the first 24 hours after injury might be a better predictor of death. Our objective was to evaluate the impact of including the highest mGCS score on the performance of risk-adjustment models and subsequent external benchmarking results. Data were derived from the Trauma Quality Improvement Program analytic dataset (January 2014 through March 2015) and were limited to the severe TBI cohort (16 years or older, isolated head injury, GCS ≤8). Risk-adjustment models were created that varied in the mGCS covariates only (initial score, highest score, or both initial and highest mGCS scores). Model performance and fit, as well as external benchmarking results, were compared. There were 6,553 patients with severe TBI across 231 trauma centers included. Initial and highest mGCS scores were different in 47% of patients (n = 3,097). Model performance and fit improved when both initial and highest mGCS scores were included, as evidenced by improved C-statistic, Akaike Information Criterion, and adjusted R-squared values. Three-quarters of centers changed their adjusted odds ratio decile, 2.6% of centers changed outlier status, and 45% of centers exhibited a ≥0.5-SD change in the odds ratio of death after including highest mGCS score in the model. This study supports the concept that additional clinical information has the potential to not only improve the performance of current risk-adjustment models, but can also have a meaningful impact on external benchmarking strategies. Highest mGCS score is a good potential candidate for inclusion in additional models. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Testing the Predictive Validity of the Hendrich II Fall Risk Model.

PubMed

Jung, Hyesil; Park, Hyeoun-Ae

2018-03-01

Cumulative data on patient fall risk have been compiled in electronic medical records systems, and it is possible to test the validity of fall-risk assessment tools using these data between the times of admission and occurrence of a fall. The Hendrich II Fall Risk Model scores assessed during three time points of hospital stays were extracted and used for testing the predictive validity: (a) upon admission, (b) when the maximum fall-risk score from admission to falling or discharge, and (c) immediately before falling or discharge. Predictive validity was examined using seven predictive indicators. In addition, logistic regression analysis was used to identify factors that significantly affect the occurrence of a fall. Among the different time points, the maximum fall-risk score assessed between admission and falling or discharge showed the best predictive performance. Confusion or disorientation and having a poor ability to rise from a sitting position were significant risk factors for a fall.

"Near-term" Natural Catastrophe Risk Management and Risk Hedging in a Changing Climate

NASA Astrophysics Data System (ADS)

Michel, Gero; Tiampo, Kristy

2014-05-01

Competing with analytics - Can the insurance market take advantage of seasonal or "near-term" forecasting and temporal changes in risk? Natural perils (re)insurance has been based on models following climatology i.e. the long-term "historical" average. This is opposed to considering the "near-term" and forecasting hazard and risk for the seasons or years to come. Variability and short-term changes in risk are deemed abundant for almost all perils. In addition to hydrometeorological perils whose changes are vastly discussed, earthquake activity might also change over various time-scales affected by earlier local (or even global) events, regional changes in the distribution of stresses and strains and more. Only recently has insurance risk modeling of (stochastic) hurricane-years or extratropical-storm-years started considering our ability to forecast climate variability herewith taking advantage of apparent correlations between climate indicators and the activity of storm events. Once some of these "near-term measures" were in the market, rating agencies and regulators swiftly adopted these concepts demanding companies to deploy a selection of more conservative "time-dependent" models. This was despite the fact that the ultimate effect of some of these measures on insurance risk was not well understood. Apparent short-term success over the last years in near-term seasonal hurricane forecasting was brought to a halt in 2013 when these models failed to forecast the exceptional shortage of hurricanes herewith contradicting an active-year forecast. The focus of earthquake forecasting has in addition been mostly on high rather than low temporal and regional activity despite the fact that avoiding losses does not by itself create a product. This presentation sheds light on new risk management concepts for over-regional and global (re)insurance portfolios that take advantage of forecasting changes in risk. The presentation focuses on the "upside" and on new opportunities in risk-taking rather than the "downside" and the general notion that catastrophes will get worse. The focus will be on the industry's ability to hedge and optimize risk more efficiently in a changing environment.

A method for scenario-based risk assessment for robust aerospace systems

NASA Astrophysics Data System (ADS)

Thomas, Victoria Katherine

In years past, aircraft conceptual design centered around creating a feasible aircraft that could be built and could fly the required missions. More recently, aircraft viability entered into conceptual design, allowing that the product's potential to be profitable should also be examined early in the design process. While examining an aerospace system's feasibility and viability early in the design process is extremely important, it is also important to examine system risk. In traditional aerospace systems risk analysis, risk is examined from the perspective of performance, schedule, and cost. Recently, safety and reliability analysis have been brought forward in the design process to also be examined during late conceptual and early preliminary design. While these analyses work as designed, existing risk analysis methods and techniques are not designed to examine an aerospace system's external operating environment and the risks present there. A new method has been developed here to examine, during the early part of concept design, the risk associated with not meeting assumptions about the system's external operating environment. The risks are examined in five categories: employment, culture, government and politics, economics, and technology. The risks are examined over a long time-period, up to the system's entire life cycle. The method consists of eight steps over three focus areas. The first focus area is Problem Setup. During problem setup, the problem is defined and understood to the best of the decision maker's ability. There are four steps in this area, in the following order: Establish the Need, Scenario Development, Identify Solution Alternatives, and Uncertainty and Risk Identification. There is significant iteration between steps two through four. Focus area two is Modeling and Simulation. In this area the solution alternatives and risks are modeled, and a numerical value for risk is calculated. A risk mitigation model is also created. The four steps involved in completing the modeling and simulation are: Alternative Solution Modeling, Uncertainty Quantification, Risk Assessment, and Risk Mitigation. Focus area three consists of Decision Support. In this area a decision support interface is created that allows for game playing between solution alternatives and risk mitigation. A multi-attribute decision making process is also implemented to aid in decision making. A demonstration problem inspired by Airbus' mid 1980s decision to break into the widebody long-range market was developed to illustrate the use of this method. The results showed that the method is able to capture additional types of risk than previous analysis methods, particularly at the early stages of aircraft design. It was also shown that the method can be used to help create a system that is robust to external environmental factors. The addition of an external environment risk analysis in the early stages of conceptual design can add another dimension to the analysis of feasibility and viability. The ability to take risk into account during the early stages of the design process can allow for the elimination of potentially feasible and viable but too-risky alternatives. The addition of a scenario-based analysis instead of a traditional probabilistic analysis enabled uncertainty to be effectively bound and examined over a variety of potential futures instead of only a single future. There is also potential for a product to be groomed for a specific future that one believes is likely to happen, or for a product to be steered during design as the future unfolds.

A Patient Risk Model of Chemotherapy-Induced Febrile Neutropenia: Lessons Learned From the ANC Study Group.

PubMed

Lyman, Gary H; Poniewierski, Marek S

2017-12-01

Neutropenia and its complications, including febrile neutropenia (FN), represent major toxicities associated with cancer chemotherapy, resulting in considerable morbidity, mortality, and costs. The myeloid growth factors such as granulocyte colony-stimulating factor (G-CSF) have been shown to reduce the risk of neutropenia complications while enabling safe and effective chemotherapy dose intensity. Concerns about the high costs of these agents along with limited physician adherence to clinical practice guidelines, resulting in both overuse and underuse, has stimulated interest in models for individual patient risk assessment to guide appropriate use of G-CSF. In a model developed and validated by the ANC Study Group, half of patients were classified as high risk and half as low risk based on patient-, disease-, and treatment-related factors. This model has been further validated in an independent patient population. Physician-assessed risk of FN, as well as the decision to use prophylactic CSF, has been shown to correlate poorly with the FN risk estimated by the model. Additional modeling efforts in both adults and children receiving cancer treatment have been reported. Identification of patients at a high individual risk for FN and its consequences may offer the potential for optimal chemotherapy delivery and patient outcomes. Likewise, identification of patients at low risk for neutropenic events may reduce costs when such supportive care is not warranted. This article reviews and summarizes FN modeling studies and the opportunities for personalizing supportive care in patients receiving chemotherapy. Copyright © 2017 by the National Comprehensive Cancer Network.

Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000-2007

NASA Astrophysics Data System (ADS)

Yin, Ping; Mu, Lan; Madden, Marguerite; Vena, John E.

2014-10-01

Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000-2007. With the census tract level as the spatial scale and the 2-year period aggregation as the temporal scale, we compare a total of seven Bayesian spatio-temporal models including two under a separate modeling framework and five under a joint modeling framework. One joint model outperforms others based on the deviance information criterion. Results show that the northwest region of Georgia has consistently high lung cancer incidence risk for all population groups during the study period. In addition, there are inverse relationships between the socioeconomic status and the lung cancer incidence risk among all Georgian population groups, and the relationships in males are stronger than those in females. By mapping more reliable variations in lung cancer incidence risk at a relatively fine spatio-temporal scale for different Georgian population groups, our study aims to better support healthcare performance assessment, etiological hypothesis generation, and health policy making.

A Longitudinal Test of the Parent-Adolescent Family Functioning Discrepancy Hypothesis: A Trend toward Increased HIV Risk Behaviors Among Immigrant Hispanic Adolescents.

PubMed

Córdova, David; Schwartz, Seth J; Unger, Jennifer B; Baezconde-Garbanati, Lourdes; Villamar, Juan A; Soto, Daniel W; Des Rosiers, Sabrina E; Lee, Tae Kyoung; Meca, Alan; Cano, Miguel Ángel; Lorenzo-Blanco, Elma I; Oshri, Assaf; Salas-Wright, Christopher P; Piña-Watson, Brandy; Romero, Andrea J

2016-10-01

Parent-adolescent discrepancies in family functioning play an important role in HIV risk behaviors among adolescents, yet longitudinal research with recent immigrant Hispanic families remains limited. This study tested the effects of trajectories of parent-adolescent family functioning discrepancies on HIV risk behaviors among recent-immigrant Hispanic adolescents. Additionally, we examined whether and to what extent trajectories of parent-adolescent family functioning discrepancies vary as a function of gender. We assessed family functioning of 302 Hispanic adolescents (47 % female) and their parent (70 % female) at six time points over a three-year period and computed latent discrepancy scores between parent and adolescent reports at each timepoint. Additionally, adolescents completed measures of sexual risk behaviors and alcohol use. We conducted a confirmatory factor analysis to determine the feasibility of collapsing parent and adolescent reported family functioning indicators onto a single latent discrepancy variable, tested model invariance over time, and conducted growth mixture modeling (GMM). GMM yielded a three-class solution for discrepancies: High-Increasing, High-Stable, and Low-Stable. Relative to the Low-Stable class, parent-adolescent dyads in the High-Increasing and High-Stable classes were at greater risk for adolescents reporting sexual debut at time 6. Additionally, the High-Stable class was at greater risk, relative to the Low-Stable class, in terms of adolescent lifetime alcohol use at 30 months post-baseline. Multiple group GMM indicated that trajectories of parent-adolescent family functioning trajectories did not vary by gender. Implications for future research and practice are discussed.

A Longitudinal Test of the Parent–Adolescent Family Functioning Discrepancy Hypothesis: A Trend toward Increased HIV Risk Behaviors among Immigrant Hispanic Adolescents

PubMed Central

Cordova, David; Schwartz, Seth J.; Unger, Jennifer B.; Baezconde-Garbanati, Lourdes; Villamar, Juan A.; Soto, Daniel W.; Des Rosiers, Sabrina E.; Lee, Tae Kyoung; Meca, Alan; Cano, Miguel Ángel; Lorenzo-Blanco, Elma I.; Oshri, Assaf; Salas-Wright, Christopher P.; Piña-Watson, Brandy M.; Romero, Andrea J.

2016-01-01

Parent-adolescent discrepancies in family functioning play an important role in HIV risk behaviors among adolescents, yet longitudinal research with recent immigrant Hispanic families remains limited. This study tested the effects of trajectories of parent–adolescent family functioning discrepancies on HIV risk behaviors among recent-immigrant Hispanic adolescents. Additionally, we examined whether and to what extent trajectories of parent-adolescent family functioning discrepancies vary as a function of gender. We assessed family functioning of 302 Hispanic adolescents (47% female) and their parent (70% female) at six time points over a three-year period and computed latent discrepancy scores between parent and adolescent reports at each timepoint. Additionally, adolescents completed measures of sexual risk behaviors and alcohol use. We conducted a confirmatory factor analysis to determine the feasibility of collapsing parent and adolescent reported family functioning indicators onto a single latent discrepancy variable, tested model invariance over time, and conducted growth mixture modeling (GMM). GMM yielded a three-class solution for discrepancies: High-Increasing, High-Stable, and Low-Stable. Relative to the Low-Stable class, parent–adolescent dyads in the High-Increasing and High-Stable classes were at greater risk for adolescents reporting sexual debut at time 6. Additionally, the High-Stable class was at greater risk, relative to the Low-Stable class, in terms of adolescent lifetime alcohol use at 30 months post-baseline. Multiple group GMM indicated that trajectories of parent-adolescent family functioning trajectories did not vary by gender. Implications for future research and practice are discussed. PMID:27216199

Number of Psychosocial Strengths Predicts Reduced HIV Sexual Risk Behaviors Above and Beyond Syndemic Problems Among Gay and Bisexual Men.

PubMed

Hart, Trevor A; Noor, Syed W; Adam, Barry D; Vernon, Julia R G; Brennan, David J; Gardner, Sandra; Husbands, Winston; Myers, Ted

2017-10-01

Syndemics research shows the additive effect of psychosocial problems on high-risk sexual behavior among gay and bisexual men (GBM). Psychosocial strengths may predict less engagement in high-risk sexual behavior. In a study of 470 ethnically diverse HIV-negative GBM, regression models were computed using number of syndemic psychosocial problems, number of psychosocial strengths, and serodiscordant condomless anal sex (CAS). The number of syndemic psychosocial problems correlated with serodiscordant CAS (RR = 1.51, 95% CI 1.18-1.92; p = 0.001). When adding the number of psychosocial strengths to the model, the effect of syndemic psychosocial problems became non-significant, but the number of strengths-based factors remained significant (RR = 0.67, 95% CI 0.53-0.86; p = 0.002). Psychosocial strengths may operate additively in the same way as syndemic psychosocial problems, but in the opposite direction. Consistent with theories of resilience, psychosocial strengths may be an important set of variables predicting sexual risk behavior that is largely missing from the current HIV behavioral literature.

Comparison of time series models for predicting campylobacteriosis risk in New Zealand.

PubMed

Al-Sakkaf, A; Jones, G

2014-05-01

Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998-2009 data and used to predict for each month of 2010. The Holt-Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt-Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt-Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic. © 2013 Blackwell Verlag GmbH.

Single-nucleotide polymorphisms of MMP2 in MMP/TIMP pathways associated with the risk of alcohol-induced osteonecrosis of the femoral head in Chinese males: A case-control study.

PubMed

Yu, Yan; Xie, Zhilan; Wang, Jihan; Chen, Chu; Du, Shuli; Chen, Peng; Li, Bin; Jin, Tianbo; Zhao, Heping

2016-12-01

The proportion of alcohol-induced osteonecrosis of the femoral head (ONFH) in all ONFH patients was 30.7%, with males prevailing among the ONFH patients in mainland China (70.1%). Matrix metalloproteinase 2 (MMP2), a member of the MMP gene family, encodes the enzyme MMP2, which can promote osteoclast migration, attachment, and bone matrix degradation. In this case-control study, we aimed to investigate the association between MMP2 and the alcohol-induced ONFH in Chinese males.In total, 299 patients with alcohol-induced ONFH and 396 healthy controls were recruited for a case-control association study. Five single-nucleotide polymorphisms within the MMP2 locus were genotyped and examined for their correlation with the risk of alcohol-induced ONFH and treatment response using Pearson χ test and unconditional logistic regression analysis. We identified 3 risk alleles for carriers: the allele "T" of rs243849 increased the risk of alcohol-induced ONFH in the allele model, the log-additive model without adjustment, and the log-additive model with adjustment for age. Conversely, the genotypes "CC" in rs7201 and "CC" in rs243832 decreased the risk of alcohol-induced ONFH, as revealed by the recessive model. After the Bonferroni multiple adjustment, no significant association was found. Furthermore, the haplotype analysis showed that the "TT" haplotype of MMP2 was more frequent among patients with alcohol-induced ONFH by unconditional logistic regression analysis adjusted for age.In conclusion, there may be an association between MMP2 and the risk of alcohol-induced ONFH in North-Chinese males. However, studies on larger populations are needed to confirm this hypothesis; these data may provide a theoretical foundation for future studies.

Development of a prototype Typhoon Risk Model over the Korean Peninsula

NASA Astrophysics Data System (ADS)

Kim, K. Y.; Cocke, S.; Shin, D. W.; CHOI, M.; Kwon, J.

2016-12-01

Risk can be defined as probability of a given hazard of a given level causing a particular level of loss of damage (Alexander, 2000). Risk management is important for mitigation and developing plans for emergencies. More effective risk management strategies can help reduce potential losses from natural disasters like typhoon, floods, earthquakes, and so on. We are developing a prototype typhoon risk model to assess the current and potentially future hazard due to typhoons in the Western Pacific. To develop the typhoon risk model, a variety of sources of data over Korea are used such as population, damage to buildings, agriculture, ships, etc. The model is based on proven concepts used in catastrophe models that have been used in the U.S. and other regions of the world. Recently, the sea surface temperatures where typhoons have occurred have tended to increase. According to recent studies of global warming, the intensity of typhoons could increase, and the frequency of typhoons may decrease in the future climate. The prototype risk model can help us determine the change in risk as a consequence of the change in typhoon activity. We focus on Korea and other regions of interest to Korean insurers, re-insurers, and related industries. The model can potentially be coupled to various damage models or emergency management systems for planning and mitigation. In addition, the assessment would be useful for emergency planners, coastal community planners, and private and governmental insurance programs. This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMIPA2016-8030.

A calibration hierarchy for risk models was defined: from utopia to empirical data.

PubMed

Van Calster, Ben; Nieboer, Daan; Vergouwe, Yvonne; De Cock, Bavo; Pencina, Michael J; Steyerberg, Ewout W

2016-06-01

Calibrated risk models are vital for valid decision support. We define four levels of calibration and describe implications for model development and external validation of predictions. We present results based on simulated data sets. A common definition of calibration is "having an event rate of R% among patients with a predicted risk of R%," which we refer to as "moderate calibration." Weaker forms of calibration only require the average predicted risk (mean calibration) or the average prediction effects (weak calibration) to be correct. "Strong calibration" requires that the event rate equals the predicted risk for every covariate pattern. This implies that the model is fully correct for the validation setting. We argue that this is unrealistic: the model type may be incorrect, the linear predictor is only asymptotically unbiased, and all nonlinear and interaction effects should be correctly modeled. In addition, we prove that moderate calibration guarantees nonharmful decision making. Finally, results indicate that a flexible assessment of calibration in small validation data sets is problematic. Strong calibration is desirable for individualized decision support but unrealistic and counter productive by stimulating the development of overly complex models. Model development and external validation should focus on moderate calibration. Copyright © 2016 Elsevier Inc. All rights reserved.

Metal-Polycyclic Aromatic Hydrocarbon Mixture Toxicity in Hyalella azteca. 1. Response Surfaces and Isoboles To Measure Non-additive Mixture Toxicity and Ecological Risk.

PubMed

Gauthier, Patrick T; Norwood, Warren P; Prepas, Ellie E; Pyle, Greg G

2015-10-06

Mixtures of metals and polycyclic aromatic hydrocarbons (PAHs) occur ubiquitously in aquatic environments, yet relatively little is known regarding their potential to produce non-additive toxicity (i.e., antagonism or potentiation). A review of the lethality of metal-PAH mixtures in aquatic biota revealed that more-than-additive lethality is as common as strictly additive effects. Approaches to ecological risk assessment do not consider non-additive toxicity of metal-PAH mixtures. Forty-eight-hour water-only binary mixture toxicity experiments were conducted to determine the additive toxic nature of mixtures of Cu, Cd, V, or Ni with phenanthrene (PHE) or phenanthrenequinone (PHQ) using the aquatic amphipod Hyalella azteca. In cases where more-than-additive toxicity was observed, we calculated the possible mortality rates at Canada's environmental water quality guideline concentrations. We used a three-dimensional response surface isobole model-based approach to compare the observed co-toxicity in juvenile amphipods to predicted outcomes based on concentration addition or effects addition mixtures models. More-than-additive lethality was observed for all Cu-PHE, Cu-PHQ, and several Cd-PHE, Cd-PHQ, and Ni-PHE mixtures. Our analysis predicts Cu-PHE, Cu-PHQ, Cd-PHE, and Cd-PHQ mixtures at the Canadian Water Quality Guideline concentrations would produce 7.5%, 3.7%, 4.4% and 1.4% mortality, respectively.

Calibrating a Rainfall-Runoff and Routing Model for the Continental United States

NASA Astrophysics Data System (ADS)

Jankowfsky, S.; Li, S.; Assteerawatt, A.; Tillmanns, S.; Hilberts, A.

2014-12-01

Catastrophe risk models are widely used in the insurance industry to estimate the cost of risk. The models consist of hazard models linked to vulnerability and financial loss models. In flood risk models, the hazard model generates inundation maps. In order to develop country wide inundation maps for different return periods a rainfall-runoff and routing model is run using stochastic rainfall data. The simulated discharge and runoff is then input to a two dimensional inundation model, which produces the flood maps. In order to get realistic flood maps, the rainfall-runoff and routing models have to be calibrated with observed discharge data. The rainfall-runoff model applied here is a semi-distributed model based on the Topmodel (Beven and Kirkby, 1979) approach which includes additional snowmelt and evapotranspiration models. The routing model is based on the Muskingum-Cunge (Cunge, 1969) approach and includes the simulation of lakes and reservoirs using the linear reservoir approach. Both models were calibrated using the multiobjective NSGA-II (Deb et al., 2002) genetic algorithm with NLDAS forcing data and around 4500 USGS discharge gauges for the period from 1979-2013. Additional gauges having no data after 1979 were calibrated using CPC rainfall data. The model performed well in wetter regions and shows the difficulty of simulating areas with sinks such as karstic areas or dry areas. Beven, K., Kirkby, M., 1979. A physically based, variable contributing area model of basin hydrology. Hydrol. Sci. Bull. 24 (1), 43-69. Cunge, J.A., 1969. On the subject of a flood propagation computation method (Muskingum method), J. Hydr. Research, 7(2), 205-230. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T., 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on evolutionary computation, 6(2), 182-197.

Risk factors for the development of heterotopic ossification in seriously burned adults: A National Institute on Disability, Independent Living and Rehabilitation Research burn model system database analysis.

PubMed

Levi, Benjamin; Jayakumar, Prakash; Giladi, Avi; Jupiter, Jesse B; Ring, David C; Kowalske, Karen; Gibran, Nicole S; Herndon, David; Schneider, Jeffrey C; Ryan, Colleen M

2015-11-01

Heterotopic ossification (HO) is a debilitating complication of burn injury; however, incidence and risk factors are poorly understood. In this study, we use a multicenter database of adults with burn injuries to identify and analyze clinical factors that predict HO formation. Data from six high-volume burn centers, in the Burn Injury Model System Database, were analyzed. Univariate logistic regression models were used for model selection. Cluster-adjusted multivariate logistic regression was then used to evaluate the relationship between clinical and demographic data and the development of HO. Of 2,979 patients in the database with information on HO that addressed risk factors for development of HO, 98 (3.5%) developed HO. Of these 98 patients, 97 had arm burns, and 96 had arm grafts. When controlling for age and sex in a multivariate model, patients with greater than 30% total body surface area burn had 11.5 times higher odds of developing HO (p < 0.001), and those with arm burns that required skin grafting had 96.4 times higher odds of developing HO (p = 0.04). For each additional time a patient went to the operating room, odds of HO increased by 30% (odds ratio, 1.32; p < 0.001), and each additional ventilator day increased odds by 3.5% (odds ratio, 1.035; p < 0.001). Joint contracture, inhalation injury, and bone exposure did not significantly increase odds of HO. Risk factors for HO development include greater than 30% total body surface area burn, arm burns, arm grafts, ventilator days, and number of trips to the operating room. Future studies can use these results to identify highest-risk patients to guide deployment of prophylactic and experimental treatments. Prognostic study, level III.

Risk Factors for the Development of Heterotopic Ossification in Seriously Burned Adults: A NIDRR Burn Model System Database Analysis

PubMed Central

Levi, Benjamin; Jayakumar, Prakash; Giladi, Avi; Jupiter, Jesse B.; Ring, David C.; Kowalske, Karen; Gibran, Nicole S.; Herndon, David; Schneider, Jeffrey C.; Ryan, Colleen M.

2015-01-01

Purpose Heterotopic ossification (HO) is a debilitating complication of burn injury; however, incidence and risk factors are poorly understood. In this study we utilize a multicenter database of adults with burn injuries to identify and analyze clinical factors that predict HO formation. Methods Data from 6 high-volume burn centers, in the Burn Injury Model System Database, were analyzed. Univariate logistic regression models were used for model selection. Cluster-adjusted multivariate logistic regression was then used to evaluate the relationship between clinical and demographic data and the development of HO. Results Of 2,979 patients in the database with information on HO that addressed risk factors for development of HO, 98 (3.5%) developed HO. Of these 98 patients, 97 had arm burns, and 96 had arm grafts. Controlling for age and sex in a multivariate model, patients with >30% total body surface area (TBSA) burn had 11.5x higher odds of developing HO (p<0.001), and those with arm burns that required skin grafting had 96.4x higher odds of developing HO (p=0.04). For each additional time a patient went to the operating room, odds of HO increased 30% (OR 1.32, p<0.001), and each additional ventilator day increase odds 3.5% (OR 1.035, p<0.001). Joint contracture, inhalation injury, and bone exposure did not significantly increase odds of HO. Conclusion Risk factors for HO development include >30% TBSA burn, arm burns, arm grafts, ventilator days, and number of trips to the operating room. Future studies can use these results to identify highest-risk patients to guide deployment of prophylactic and experimental treatments. PMID:26496115

Lunar Landing Operational Risk Model

NASA Technical Reports Server (NTRS)

Mattenberger, Chris; Putney, Blake; Rust, Randy; Derkowski, Brian

2010-01-01

Characterizing the risk of spacecraft goes beyond simply modeling equipment reliability. Some portions of the mission require complex interactions between system elements that can lead to failure without an actual hardware fault. Landing risk is currently the least characterized aspect of the Altair lunar lander and appears to result from complex temporal interactions between pilot, sensors, surface characteristics and vehicle capabilities rather than hardware failures. The Lunar Landing Operational Risk Model (LLORM) seeks to provide rapid and flexible quantitative insight into the risks driving the landing event and to gauge sensitivities of the vehicle to changes in system configuration and mission operations. The LLORM takes a Monte Carlo based approach to estimate the operational risk of the Lunar Landing Event and calculates estimates of the risk of Loss of Mission (LOM) - Abort Required and is Successful, Loss of Crew (LOC) - Vehicle Crashes or Cannot Reach Orbit, and Success. The LLORM is meant to be used during the conceptual design phase to inform decision makers transparently of the reliability impacts of design decisions, to identify areas of the design which may require additional robustness, and to aid in the development and flow-down of requirements.

Association between polymorphisms of estrogen receptor 2 and benign prostatic hyperplasia

PubMed Central

KIM, SU KANG; CHUNG, JOO-HO; PARK, HYUN CHUL; KIM, JUN HO; ANN, JAE HONG; PARK, HUN KUK; LEE, SANG HYUP; YOO, KOO HAN; LEE, BYUNG-CHEOL; KIM, YOUNG OCK

2015-01-01

Estrogens and estrogen receptors (ESRs) have been implicated in the stimulation of aberrant prostate growth and the development of prostate diseases. The aim of the present study was to investigate four single nucleotide polymorphisms (SNPs) of the ESR2 gene in order to examine whether ESR2 is a susceptibility gene for benign prostatic hyperplasia (BPH). In order to evaluate whether an association exists between ESR2 and BPH risk, four polymorphisms [rs4986938 (intron), rs17766755 (intron), rs12435857 (intron) and rs1256049 (Val328Val)] of the ESR2 gene were genotyped by direct sequencing. A total of 94 patients with BPH and 79 control subjects were examined. SNPStats and Haploview version 4.2 we used for the genetic analysis. Multiple logistic regression models (codominant1, codominant2, dominant, recessive and log-additive) were produced in order to obtain the odds ratio, 95% confidence interval and P-value. Three SNPs (rs4986938, rs17766755 and rs12435857) showed significant associations with BPH (rs4986938, P=0.015 in log-additive model; rs17766755, P=0.033 in codominant1 model, P=0.019 in dominant model and P=0.020 in log-additive model; rs12435857, P=0.023 in dominant model and P=0.011 in log-additive model). The minor alleles of these SNPs increased the risk of BPH, and the AAC haplotype showed significant association with BPH (χ2=6.34, P=0.0118). These data suggest that the ESR2 gene may be associated with susceptibility to BPH. PMID:26640585

Association between polymorphisms of estrogen receptor 2 and benign prostatic hyperplasia.

PubMed

Kim, Su Kang; Chung, Joo-Ho; Park, Hyun Chul; Kim, Jun Ho; Ann, Jae Hong; Park, Hun Kuk; Lee, Sang Hyup; Yoo, Koo Han; Lee, Byung-Cheol; Kim, Young Ock

2015-11-01

Estrogens and estrogen receptors (ESRs) have been implicated in the stimulation of aberrant prostate growth and the development of prostate diseases. The aim of the present study was to investigate four single nucleotide polymorphisms (SNPs) of the ESR2 gene in order to examine whether ESR2 is a susceptibility gene for benign prostatic hyperplasia (BPH). In order to evaluate whether an association exists between ESR2 and BPH risk, four polymorphisms [rs4986938 (intron), rs17766755 (intron), rs12435857 (intron) and rs1256049 (Val328Val)] of the ESR2 gene were genotyped by direct sequencing. A total of 94 patients with BPH and 79 control subjects were examined. SNPStats and Haploview version 4.2 we used for the genetic analysis. Multiple logistic regression models (codominant1, codominant2, dominant, recessive and log-additive) were produced in order to obtain the odds ratio, 95% confidence interval and P-value. Three SNPs (rs4986938, rs17766755 and rs12435857) showed significant associations with BPH (rs4986938, P=0.015 in log-additive model; rs17766755, P=0.033 in codominant1 model, P=0.019 in dominant model and P=0.020 in log-additive model; rs12435857, P=0.023 in dominant model and P=0.011 in log-additive model). The minor alleles of these SNPs increased the risk of BPH, and the AAC haplotype showed significant association with BPH (χ 2 =6.34, P=0.0118). These data suggest that the ESR2 gene may be associated with susceptibility to BPH.

Evaluation of Enhanced Risk Monitors for Use on Advanced Reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Veeramany, Arun; Bonebrake, Christopher A.

This study provides an overview of the methodology for integrating time-dependent failure probabilities into nuclear power reactor risk monitors. This prototypic enhanced risk monitor (ERM) methodology was evaluated using a hypothetical probabilistic risk assessment (PRA) model, generated using a simplified design of a liquid-metal-cooled advanced reactor (AR). Component failure data from industry compilation of failures of components similar to those in the simplified AR model were used to initialize the PRA model. Core damage frequency (CDF) over time were computed and analyzed. In addition, a study on alternative risk metrics for ARs was conducted. Risk metrics that quantify the normalizedmore » cost of repairs, replacements, or other operations and management (O&M) actions were defined and used, along with an economic model, to compute the likely economic risk of future actions such as deferred maintenance based on the anticipated change in CDF due to current component condition and future anticipated degradation. Such integration of conventional-risk metrics with alternate-risk metrics provides a convenient mechanism for assessing the impact of O&M decisions on safety and economics of the plant. It is expected that, when integrated with supervisory control algorithms, such integrated-risk monitors will provide a mechanism for real-time control decision-making that ensure safety margins are maintained while operating the plant in an economically viable manner.« less

Perceptions of health risks of cigarette smoking: A new measure reveals widespread misunderstanding

PubMed Central

Krosnick, Jon A.; Malhotra, Neil; Bruera, Eduardo F.; Chang, LinChiat; Pasek, Josh; Thomas, Randall K.

2017-01-01

Most Americans recognize that smoking causes serious diseases, yet many Americans continue to smoke. One possible explanation for this paradox is that perhaps Americans do not accurately perceive the extent to which smoking increases the probability of adverse health outcomes. This paper examines the accuracy of Americans’ perceptions of the absolute risk, attributable risk, and relative risk of lung cancer, and assesses which of these beliefs drive Americans’ smoking behavior. Using data from three national surveys, statistical analyses were performed by comparing means, medians, and distributions, and by employing Generalized Additive Models. Perceptions of relative risk were associated as expected with smoking onset and smoking cessation, whereas perceptions of absolute risk and attributable risk were not. Additionally, the relation of relative risk with smoking status was stronger among people who held their risk perceptions with more certainty. Most current smokers, former smokers, and never-smokers considerably underestimated the relative risk of smoking. If, as this paper suggests, people naturally think about the health consequences of smoking in terms of relative risk, smoking rates might be reduced if public understanding of the relative risks of smoking were more accurate and people held those beliefs with more confidence. PMID:28806420

Additive composite ABCG2, SLC2A9 and SLC22A12 scores of high-risk alleles with alcohol use modulate gout risk.

PubMed

Tu, Hung-Pin; Chung, Chia-Min; Min-Shan Ko, Albert; Lee, Su-Shin; Lai, Han-Ming; Lee, Chien-Hung; Huang, Chung-Ming; Liu, Chiu-Shong; Ko, Ying-Chin

2016-09-01

The aim of the present study was to evaluate the contribution of urate transporter genes and alcohol use to the risk of gout/tophi. Eight variants of ABCG2, SLC2A9, SLC22A12, SLC22A11 and SLC17A3 were genotyped in male individuals in a case-control study with 157 gout (33% tophi), 106 asymptomatic hyperuricaemia and 295 control subjects from Taiwan. The multilocus profiles of the genetic risk scores for urate gene variants were used to evaluate the risk of asymptomatic hyperuricaemia, gout and tophi. ABCG2 Q141K (T), SLC2A9 rs1014290 (A) and SLC22A12 rs475688 (C) under an additive model and alcohol use independently predicted the risk of gout (respective odds ratio for each factor=2.48, 2.03, 1.95 and 2.48). The additive composite Q141K, rs1014290 and rs475688 scores of high-risk alleles were associated with gout risk (P<0.0001). We observed the supramultiplicative interaction effect of genetic urate scores and alcohol use on gout and tophi risk (P for interaction=0.0452, 0.0033). The synergistic effect of genetic urate score 5-6 and alcohol use indicates that these combined factors correlate with gout and tophi occurrence.

Dealing With Uncertainty: Testing Risk- and Ambiguity-Attitude Across Adolescence.

PubMed

Blankenstein, Neeltje E; Crone, Eveline A; van den Bos, Wouter; van Duijvenvoorde, Anna C K

2016-01-01

Attitudes to risk (known probabilities) and attitudes to ambiguity (unknown probabilities) are separate constructs that influence decision making, but their development across adolescence remains elusive. We administered a choice task to a wide adolescent age-range (N = 157, 10-25 years) to disentangle risk- and ambiguity-attitudes using a model-based approach. Additionally, this task was played in a social context, presenting choices from a high risk-taking peer. We observed age-related changes in ambiguity-attitude, but not risk-attitude. Also, ambiguity-aversion was negatively related to real-life risk taking. Finally, the social context influenced only risk-attitudes. These results highlight the importance of disentangling risk- and ambiguity-attitudes in adolescent risk taking.

A Study of the Factors Associated with Risk for Development of Pressure Ulcers: A Longitudinal Analysis

PubMed Central

Thomas, Elizebeth; Vinodkumar, Sudhaya; Mathew, Silvia; Setia, Maninder Singh

2015-01-01

Background: Pressure ulcers (PUs) are prevalent in hospitalized patients; they may cause clinical, psychological, and economic problems in these patients. Previous studies are cross-sectional, have used pooled data, or cox-regression models to assess the risk for developing PU. However, PU risk scores change over time and models that account for time varying variables are useful for cohort analysis of data. Aims and Objectives: The present longitudinal study was conducted to compare the risk of PU between surgical and nonsurgical patients, and to evaluate the factors associated with the development of these ulcers over a period of time. Materials and Methods: We evaluated 290 hospitalized patients over a 4 months period. The main outcomes for our analysis were: (1) Score on the pressure risk assessment scale; and (2) the proportion of individuals who were at severe risk for developing PUs. We used random effects models for longitudinal analysis of the data. Results: The mean PU score was significantly higher in the nonsurgical patients compared with surgical patients at baseline (15.23 [3.86] vs. 9.33 [4.57]; P < 0.01). About 7% of the total patients had a score of >20 at baseline and were considered as being at high-risk for PU; the proportion was significantly higher among the nonsurgical patients compared with the surgical patients (14% vs. 4%, P = 0.003). In the adjusted models, there was no difference for severe risk for PU between surgical and nonsurgical patients (odds ratios [ORs]: 0.37, 95% confidence interval [CI]: 0.01–12.80). An additional day in the ward was associated with a significantly higher likelihood of being at high-risk for PU (OR: 1.47, 95% CI: 1.16–1.86). Conclusion: There were no significant differences between patients who were admitted for surgery compared with those who were not. An additional day in the ward, however, is important for developing a high-risk score for PU on the monitoring scale, and these patients require active interventions. PMID:26677269

Serum peroxiredoxin 4: a marker of oxidative stress associated with mortality in type 2 diabetes (ZODIAC-28).

PubMed

Gerrits, Esther G; Alkhalaf, Alaa; Landman, Gijs W D; van Hateren, Kornelis J J; Groenier, Klaas H; Struck, Joachim; Schulte, Janin; Gans, Reinold O B; Bakker, Stephan J L; Kleefstra, Nanne; Bilo, Henk J G

2014-01-01

Oxidative stress plays an underlying pathophysiologic role in the development of diabetes complications. The aim of this study was to investigate peroxiredoxin 4 (Prx4), a proposed novel biomarker of oxidative stress, and its association with and capability as a biomarker in predicting (cardiovascular) mortality in type 2 diabetes mellitus. Prx4 was assessed in baseline serum samples of 1161 type 2 diabetes patients. Cox proportional hazard models were used to evaluate the relationship between Prx4 and (cardiovascular) mortality. Risk prediction capabilities of Prx4 for (cardiovascular) mortality were assessed with Harrell's C statistic, the integrated discrimination improvement and net reclassification improvement. Mean age was 67 and the median diabetes duration was 4.0 years. After a median follow-up period of 5.8 years, 327 patients died; 137 cardiovascular deaths. Prx4 was associated with (cardiovascular) mortality. The Cox proportional hazard models added the variables: Prx4 (model 1); age and gender (model 2), and BMI, creatinine, smoking, diabetes duration, systolic blood pressure, cholesterol-HDL ratio, history of macrovascular complications, and albuminuria (model 3). Hazard ratios (HR) (95% CI) for cardiovascular mortality were 1.93 (1.57 - 2.38), 1.75 (1.39 - 2.20), and 1.63 (1.28 - 2.09) for models 1, 2 and 3, respectively. HR for all-cause mortality were 1.73 (1.50 - 1.99), 1.50 (1.29 - 1.75), and 1.44 (1.23 - 1.67) for models 1, 2 and 3, respectively. Addition of Prx4 to the traditional risk factors slightly improved risk prediction of (cardiovascular) mortality. Prx4 is independently associated with (cardiovascular) mortality in type 2 diabetes patients. After addition of Prx4 to the traditional risk factors, there was a slightly improvement in risk prediction of (cardiovascular) mortality in this patient group.

Health effects models for nuclear power plant accident consequence analysis: Low LET radiation: Part 2, Scientific bases for health effects models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abrahamson, S.; Bender, M.; Book, S.

1989-05-01

This report provides dose-response models intended to be used in estimating the radiological health effects of nuclear power plant accidents. Models of early and continuing effects, cancers and thyroid nodules, and genetic effects are provided. Two-parameter Weibull hazard functions are recommended for estimating the risks of early and continuing health effects. Three potentially lethal early effects -- the hematopoietic, pulmonary and gastrointestinal syndromes -- are considered. Linear and linear-quadratic models are recommended for estimating cancer risks. Parameters are given for analyzing the risks of seven types of cancer in adults -- leukemia, bone, lung, breast, gastrointestinal, thyroid and ''other''. Themore » category, ''other'' cancers, is intended to reflect the combined risks of multiple myeloma, lymphoma, and cancers of the bladder, kidney, brain, ovary, uterus and cervix. Models of childhood cancers due to in utero exposure are also provided. For most cancers, both incidence and mortality are addressed. Linear and linear-quadratic models are also recommended for assessing genetic risks. Five classes of genetic disease -- dominant, x-linked, aneuploidy, unbalanced translocation and multifactorial diseases --are considered. In addition, the impact of radiation-induced genetic damage on the incidence of peri-implantation embryo losses is discussed. The uncertainty in modeling radiological health risks is addressed by providing central, upper, and lower estimates of all model parameters. Data are provided which should enable analysts to consider the timing and severity of each type of health risk. 22 refs., 14 figs., 51 tabs.« less

Predicting Readmission at Early Hospitalization Using Electronic Clinical Data: An Early Readmission Risk Score.

PubMed

Tabak, Ying P; Sun, Xiaowu; Nunez, Carlos M; Gupta, Vikas; Johannes, Richard S

2017-03-01

Identifying patients at high risk for readmission early during hospitalization may aid efforts in reducing readmissions. We sought to develop an early readmission risk predictive model using automated clinical data available at hospital admission. We developed an early readmission risk model using a derivation cohort and validated the model with a validation cohort. We used a published Acute Laboratory Risk of Mortality Score as an aggregated measure of clinical severity at admission and the number of hospital discharges in the previous 90 days as a measure of disease progression. We then evaluated the administrative data-enhanced model by adding principal and secondary diagnoses and other variables. We examined the c-statistic change when additional variables were added to the model. There were 1,195,640 adult discharges from 70 hospitals with 39.8% male and the median age of 63 years (first and third quartile: 43, 78). The 30-day readmission rate was 11.9% (n=142,211). The early readmission model yielded a graded relationship of readmission and the Acute Laboratory Risk of Mortality Score and the number of previous discharges within 90 days. The model c-statistic was 0.697 with good calibration. When administrative variables were added to the model, the c-statistic increased to 0.722. Automated clinical data can generate a readmission risk score early at hospitalization with fair discrimination. It may have applied value to aid early care transition. Adding administrative data increases predictive accuracy. The administrative data-enhanced model may be used for hospital comparison and outcome research.

The Effects of Revealed Information on Catastrophe Loss Projection Models' Characterization of Risk: Damage Vulnerability Evidence from Florida.

PubMed

Karl, J Bradley; Medders, Lorilee A; Maroney, Patrick F

2016-06-01

We examine whether the risk characterization estimated by catastrophic loss projection models is sensitive to the revelation of new information regarding risk type. We use commercial loss projection models from two widely employed modeling firms to estimate the expected hurricane losses of Florida Atlantic University's building stock, both including and excluding secondary information regarding hurricane mitigation features that influence damage vulnerability. We then compare the results of the models without and with this revealed information and find that the revelation of additional, secondary information influences modeled losses for the windstorm-exposed university building stock, primarily evidenced by meaningful percent differences in the loss exceedance output indicated after secondary modifiers are incorporated in the analysis. Secondary risk characteristics for the data set studied appear to have substantially greater impact on probable maximum loss estimates than on average annual loss estimates. While it may be intuitively expected for catastrophe models to indicate that secondary risk characteristics hold value for reducing modeled losses, the finding that the primary value of secondary risk characteristics is in reduction of losses in the "tail" (low probability, high severity) events is less intuitive, and therefore especially interesting. Further, we address the benefit-cost tradeoffs that commercial entities must consider when deciding whether to undergo the data collection necessary to include secondary information in modeling. Although we assert the long-term benefit-cost tradeoff is positive for virtually every entity, we acknowledge short-term disincentives to such an effort. © 2015 Society for Risk Analysis.

Longitudinal associations between BMI, waist circumference, and cardiometabolic risk in US youth: monitoring implications.

PubMed

Jago, R; Mendoza, J A; Chen, T; Baranowski, T

2013-03-01

This study examined whether change in body mass index (BMI) or waist circumference (WC) is associated with change in cardiometabolic risk factors and differences between cardiovascular disease specific and diabetes specific risk factors among adolescents. We also sought to examine any differences by gender or baseline body mass status. The article is a longitudinal analysis of pre- and post-data collected in the HEALTHY trial. Participants were 4,603 ethnically diverse adolescents who provided complete data at 6th and 8th grade assessments. The main outcome measures were percent change in the following cardiometabolic risk factors: fasting triglycerides, systolic and diastolic blood pressure, high density lipoprotein cholesterol, and glucose as well as a clustered metabolic risk score. Main exposures were change in BMI or WC z-score. Models were run stratified by gender; secondary models were additionally stratified by baseline BMI group (normal, overweight, or obese). Analysis showed that when cardiometabolic risk factors were treated as continuous variables, there was strong evidence (P < 0.001) that change in BMI z-score was associated with change in the majority of the cardiovascular risk factors, except fasting glucose and the combined risk factor score for both boys and girls. There was some evidence that change in WC z-score was associated with some cardiovascular risk factors, but change in WC z-score was consistently associated with changes in fasting glucose. In conclusion, routine monitoring of BMI should be continued by health professionals, but additional information on disease risk may be provided by assessing WC. Copyright © 2013 The Obesity Society.

Climate suitability and human influences combined explain the range expansion of an invasive horticultural plant

Treesearch

Carolyn M. Beans; Francis F. Kilkenny; Laura F. Galloway

2012-01-01

Ecological niche models are commonly used to identify regions at risk of species invasions. Relying on climate alone may limit a model's success when additional variables contribute to invasion. While a climate-based model may predict the future spread of an invasive plant, we hypothesized that a model that combined climate with human influences would most...

Effects of calcium carbonate, magnesium oxide and sodium citrate bicarbonate health supplements on the urinary risk factors for kidney stone formation.

PubMed

Allie, Shameez; Rodgers, Allen

2003-01-01

We describe a model to illustrate different chemical interactions that can occur in urine following ingestion of individual and combined health supplements. Two types of interactions are defined: synergism and addition. The model was applied to eight healthy males who participated in a study to investigate the chemical interactions between calcium carbonate, magnesium oxide and sodium citrate-bicarbonate health supplements on calcium oxalate urinary stone risk factors. Subjects ingested these components individually and in combination for 7 days. Twenty-four-hour urines were collected at baseline and during the final day of supplementation. These were analysed using standard laboratory techniques. Three different chemical interactions, all involving citrate, were identified: magnesium and citrate exerted a synergistic effect on lowering the relative superaturation (RS) of brushite; the same two components produced a synergistic effect on raising pH; finally, calcium and citrate exerted an additive effect on lowering the RS of uric acid. We propose that the novel approach described in this paper allows for the evaluation of individual, additive and synergistic interactions in the assessment of the efficacy of stone-risk reducing preparations.

Use of Influenza Risk Assessment Tool for Prepandemic Preparedness

PubMed Central

Trock, Susan C.

2018-01-01

In 2010, the Centers for Disease Control and Prevention began to develop an Influenza Risk Assessment Tool (IRAT) to methodically capture and assess information relating to influenza A viruses not currently circulating among humans. The IRAT uses a multiattribute, additive model to generate a summary risk score for each virus. Although the IRAT is not intended to predict the next pandemic influenza A virus, it has provided input into prepandemic preparedness decisions. PMID:29460739

[Psychosocial stress and disease risks in occupational life. Results of international studies on the demand-control and the effort-reward imbalance models].

PubMed

Siegrist, J; Dragano, N

2008-03-01

Given the far-reaching changes of modern working life, psychosocial stress at work has received increased attention. Its influence on stress-related disease risks is analysed with the help of standardised measurements based on theoretical models. Two such models have gained special prominence in recent years, the demand-control model and the effort-reward imbalance model. The former model places its emphasis on a distinct combination of job characteristics, whereas the latter model's focus is on the imbalance between efforts spent and rewards received in turn. The predictive power of these models with respect to coronary or cardiovascular disease and depression was tested in a number of prospective epidemiological investigations. In summary, twofold elevated disease risks are observed. Effects on cardiovascular disease are particularly pronounced among men, whereas no gender differences are observed for depression. Additional evidence derived from experimental and ambulatory monitoring studies supplements this body of findings. Current scientific evidence justifies an increased awareness and assessment of these newly discovered occupational risks, in particular by occupational health professionals. Moreover, structural and interpersonal measures of stress prevention and health promotion at work are warranted, with special emphasis on gender differences.

An integrated model-based approach to the risk assessment of pesticide drift from vineyards

NASA Astrophysics Data System (ADS)

Pivato, Alberto; Barausse, Alberto; Zecchinato, Francesco; Palmeri, Luca; Raga, Roberto; Lavagnolo, Maria Cristina; Cossu, Raffaello

2015-06-01

The inhalation of pesticide in air is of particular concern for people living in close contact with intensive agricultural activities. This study aims to develop an integrated modelling methodology to assess whether pesticides pose a risk to the health of people living near vineyards, and apply this methodology in the world-renowned Prosecco DOCG (Italian label for protection of origin and geographical indication of wines) region. A sample field in Bigolino di Valdobbiadene (North-Eastern Italy) was selected to perform the pesticide fate modellization and the consequent inhalation risk assessment for people living in the area. The modellization accounts for the direct pesticide loss during the treatment of vineyards and for the volatilization from soil after the end of the treatment. A fugacity model was used to assess the volatilization flux from soil. The Gaussian puff air dispersion model CALPUFF was employed to assess the airborne concentration of the emitted pesticide over the simulation domain. The subsequent risk assessment integrates the HArmonised environmental Indicators for pesticide Risk (HAIR) and US-EPA guidelines. In this case study the modelled situation turned to be safe from the point of view of human health in the case of non-carcinogenic compounds, and additional improvements were suggested to further mitigate the effect of the most critical compound.

Chemotherapy appointment scheduling under uncertainty using mean-risk stochastic integer programming.

PubMed

Alvarado, Michelle; Ntaimo, Lewis

2018-03-01

Oncology clinics are often burdened with scheduling large volumes of cancer patients for chemotherapy treatments under limited resources such as the number of nurses and chairs. These cancer patients require a series of appointments over several weeks or months and the timing of these appointments is critical to the treatment's effectiveness. Additionally, the appointment duration, the acuity levels of each appointment, and the availability of clinic nurses are uncertain. The timing constraints, stochastic parameters, rising treatment costs, and increased demand of outpatient oncology clinic services motivate the need for efficient appointment schedules and clinic operations. In this paper, we develop three mean-risk stochastic integer programming (SIP) models, referred to as SIP-CHEMO, for the problem of scheduling individual chemotherapy patient appointments and resources. These mean-risk models are presented and an algorithm is devised to improve computational speed. Computational results were conducted using a simulation model and results indicate that the risk-averse SIP-CHEMO model with the expected excess mean-risk measure can decrease patient waiting times and nurse overtime when compared to deterministic scheduling algorithms by 42 % and 27 %, respectively.

Relationship between number of sexual intercourse partners and selected health risk behaviors among public high school adolescents.

PubMed

Valois, R F; Oeltmann, J E; Waller, J; Hussey, J R

1999-11-01

To examine the relationship between number of sexual partners and selected health risk behaviors in a statewide sample of public high school students. The Centers for Disease Control and Prevention Youth Risk Behavior Survey was used to secure usable sexual risk-taking, substance use, and violence/aggression data from 3805 respondents. Because simple polychotomous logistic regression analysis revealed a significant Race x Gender interaction, subsequent multivariate models were constructed separately for each race-gender group. Odds ratios and 95% confidence intervals was calculated from polychotomous logistic regression models for number of sexual intercourse partners and their potential risk behavior correlates. An increased number of sexual intercourse partners were correlated with a cluster of risk behaviors that place adolescents at risk for unintended pregnancy, human immunodeficiency virus/acquired immunodeficiency syndrome, and other sexually transmitted infections. For Black females, alcohol, tobacco, marijuana use, and dating violence behaviors were the strongest predictors of an increased number of sexual partners; white females had similar predictors with the addition of physical fighting. For white males, alcohol, tobacco, marijuana use, physical fighting, carrying weapons, and dating violence were the strongest predictors of an increased number of sexual intercourse partners. Black males had similar predictors with the addition of binge alcohol use. Prevention of adolescent sexual and other health risk behaviors calls for creative approaches in school and community settings and will require long-term intervention strategies focused on adolescent behavior changes and environmental modifications.

Sex similarities and differences in risk factors for recurrence of major depression.

PubMed

van Loo, Hanna M; Aggen, Steven H; Gardner, Charles O; Kendler, Kenneth S

2017-11-27

Major depression (MD) occurs about twice as often in women as in men, but it is unclear whether sex differences subsist after disease onset. This study aims to elucidate potential sex differences in rates and risk factors for MD recurrence, in order to improve prediction of course of illness and understanding of its underlying mechanisms. We used prospective data from a general population sample (n = 653) that experienced a recent episode of MD. A diverse set of potential risk factors for recurrence of MD was analyzed using Cox models subject to elastic net regularization for males and females separately. Accuracy of the prediction models was tested in same-sex and opposite-sex test data. Additionally, interactions between sex and each of the risk factors were investigated to identify potential sex differences. Recurrence rates and the impact of most risk factors were similar for men and women. For both sexes, prediction models were highly multifactorial including risk factors such as comorbid anxiety, early traumas, and family history. Some subtle sex differences were detected: for men, prediction models included more risk factors concerning characteristics of the depressive episode and family history of MD and generalized anxiety, whereas for women, models included more risk factors concerning early and recent adverse life events and socioeconomic problems. No prominent sex differences in risk factors for recurrence of MD were found, potentially indicating similar disease maintaining mechanisms for both sexes. Course of MD is a multifactorial phenomenon for both males and females.

A Hydrological Modeling Framework for Flood Risk Assessment for Japan

NASA Astrophysics Data System (ADS)

Ashouri, H.; Chinnayakanahalli, K.; Chowdhary, H.; Sen Gupta, A.

2016-12-01

Flooding has been the most frequent natural disaster that claims lives and imposes significant economic losses to human societies worldwide. Japan, with an annual rainfall of up to approximately 4000 mm is extremely vulnerable to flooding. The focus of this research is to develop a macroscale hydrologic model for simulating flooding toward an improved understanding and assessment of flood risk across Japan. The framework employs a conceptual hydrological model, known as the Probability Distributed Model (PDM), as well as the Muskingum-Cunge flood routing procedure for simulating streamflow. In addition, a Temperature-Index model is incorporated to account for snowmelt and its contribution to streamflow. For an efficient calibration of the model, in terms of computational timing and convergence of the parameters, a set of A Priori parameters is obtained based on the relationships between the model parameters and the physical properties of watersheds. In this regard, we have implemented a particle tracking algorithm and a statistical model which use high resolution Digital Terrain Models to estimate different time related parameters of the model such as time to peak of the unit hydrograph. In addition, global soil moisture and depth data are used to generate A Priori estimation of maximum soil moisture capacity, an important parameter of the PDM model. Once the model is calibrated, its performance is examined during the Typhoon Nabi which struck Japan in September 2005 and caused severe flooding throughout the country. The model is also validated for the extreme precipitation event in 2012 which affected Kyushu. In both cases, quantitative measures show that simulated streamflow depicts good agreement with gauge-based observations. The model is employed to simulate thousands of possible flood events for the entire Japan which makes a basis for a comprehensive flood risk assessment and loss estimation for the flood insurance industry.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

NASA Technical Reports Server (NTRS)

1991-01-01

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.

Cumulative impact of common genetic variants and other risk factors on colorectal cancer risk in 42,103 individuals

PubMed Central

Dunlop, Malcolm G.; Tenesa, Albert; Farrington, Susan M.; Ballereau, Stephane; Brewster, David H.; Pharoah, Paul DP.; Schafmayer, Clemens; Hampe, Jochen; Völzke, Henry; Chang-Claude, Jenny; Hoffmeister, Michael; Brenner, Hermann; von Holst, Susanna; Picelli, Simone; Lindblom, Annika; Jenkins, Mark A.; Hopper, John L.; Casey, Graham; Duggan, David; Newcomb, Polly; Abulí, Anna; Bessa, Xavier; Ruiz-Ponte, Clara; Castellví-Bel, Sergi; Niittymäki, Iina; Tuupanen, Sari; Karhu, Auli; Aaltonen, Lauri; Zanke, Brent W.; Hudson, Thomas J.; Gallinger, Steven; Barclay, Ella; Martin, Lynn; Gorman, Maggie; Carvajal-Carmona, Luis; Walther, Axel; Kerr, David; Lubbe, Steven; Broderick, Peter; Chandler, Ian; Pittman, Alan; Penegar, Steven; Campbell, Harry; Tomlinson, Ian; Houlston, Richard S.

2016-01-01

Objective Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. In a large, multi-population study, we set out to assess the feasibility of CRC risk prediction using common genetic variant data, combined with other risk factors. We built a risk prediction model and applied it to the Scottish population using available data. Design Nine populations of European descent were studied to develop and validate colorectal cancer risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence colorectal cancer risk. Risk models were generated from case-control data incorporating genotypes alone (n=39,266), and in combination with gender, age and family history (n=11,324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4,187 independent samples. 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. Results Median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10−16), confirmed in external validation sets (Sweden p=1.2×10−6, Finland p=2×10−5). Mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05–1.13). Discriminative performance was poor across the risk spectrum (area under curve (AUC) for genotypes alone - 0.57; AUC for genotype/age/gender/FH - 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. Conclusion We show that genotype data provides additional information that complements age, gender and FH as risk factors. However, individualized genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential, since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance. PMID:22490517

Stationarity is undead: Uncertainty dominates the distribution of extremes

NASA Astrophysics Data System (ADS)

Serinaldi, Francesco; Kilsby, Chris G.

2015-03-01

The increasing effort to develop and apply nonstationary models in hydrologic frequency analyses under changing environmental conditions can be frustrated when the additional uncertainty related to the model complexity is accounted for along with the sampling uncertainty. In order to show the practical implications and possible problems of using nonstationary models and provide critical guidelines, in this study we review the main tools developed in this field (such as nonstationary distribution functions, return periods, and risk of failure) highlighting advantages and disadvantages. The discussion is supported by three case studies that revise three illustrative examples reported in the scientific and technical literature referring to the Little Sugar Creek (at Charlotte, North Carolina), Red River of the North (North Dakota/Minnesota), and the Assunpink Creek (at Trenton, New Jersey). The uncertainty of the results is assessed by complementing point estimates with confidence intervals (CIs) and emphasizing critical aspects such as the subjectivity affecting the choice of the models' structure. Our results show that (1) nonstationary frequency analyses should not only be based on at-site time series but require additional information and detailed exploratory data analyses (EDA); (2) as nonstationary models imply that the time-varying model structure holds true for the entire future design life period, an appropriate modeling strategy requires that EDA identifies a well-defined deterministic mechanism leading the examined process; (3) when the model structure cannot be inferred in a deductive manner and nonstationary models are fitted by inductive inference, model structure introduces an additional source of uncertainty so that the resulting nonstationary models can provide no practical enhancement of the credibility and accuracy of the predicted extreme quantiles, whereas possible model misspecification can easily lead to physically inconsistent results; (4) when the model structure is uncertain, stationary models and a suitable assessment of the uncertainty accounting for possible temporal persistence should be retained as more theoretically coherent and reliable options for practical applications in real-world design and management problems; (5) a clear understanding of the actual probabilistic meaning of stationary and nonstationary return periods and risk of failure is required for a correct risk assessment and communication.

How TK-TD and population models for aquatic macrophytes could support the risk assessment for plant protection products.

PubMed

Hommen, Udo; Schmitt, Walter; Heine, Simon; Brock, Theo Cm; Duquesne, Sabine; Manson, Phil; Meregalli, Giovanna; Ochoa-Acuña, Hugo; van Vliet, Peter; Arts, Gertie

2016-01-01

This case study of the Society of Environmental Toxicology and Chemistry (SETAC) workshop MODELINK demonstrates the potential use of mechanistic effects models for macrophytes to extrapolate from effects of a plant protection product observed in laboratory tests to effects resulting from dynamic exposure on macrophyte populations in edge-of-field water bodies. A standard European Union (EU) risk assessment for an example herbicide based on macrophyte laboratory tests indicated risks for several exposure scenarios. Three of these scenarios are further analyzed using effect models for 2 aquatic macrophytes, the free-floating standard test species Lemna sp., and the sediment-rooted submerged additional standard test species Myriophyllum spicatum. Both models include a toxicokinetic (TK) part, describing uptake and elimination of the toxicant, a toxicodynamic (TD) part, describing the internal concentration-response function for growth inhibition, and a description of biomass growth as a function of environmental factors to allow simulating seasonal dynamics. The TK-TD models are calibrated and tested using laboratory tests, whereas the growth models were assumed to be fit for purpose based on comparisons of predictions with typical growth patterns observed in the field. For the risk assessment, biomass dynamics are predicted for the control situation and for several exposure levels. Based on specific protection goals for macrophytes, preliminary example decision criteria are suggested for evaluating the model outputs. The models refined the risk indicated by lower tier testing for 2 exposure scenarios, while confirming the risk associated for the third. Uncertainties related to the experimental and the modeling approaches and their application in the risk assessment are discussed. Based on this case study and the assumption that the models prove suitable for risk assessment once fully evaluated, we recommend that 1) ecological scenarios be developed that are also linked to the exposure scenarios, and 2) quantitative protection goals be set to facilitate the interpretation of model results for risk assessment. © 2015 SETAC.

Multimethod Prediction of Physical Parent-Child Aggression Risk in Expectant Mothers and Fathers with Social Information Processing Theory

PubMed Central

Rodriguez, Christina M.; Smith, Tamika L.; Silvia, Paul J.

2015-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants’ own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. PMID:26631420

Prospective investigation of poultry and fish intake in relation to cancer risk

PubMed Central

Daniel, Carrie R.; Cross, Amanda J.; Graubard, Barry I.; Hollenbeck, Albert R.; Park, Yikyung; Sinha, Rashmi

2011-01-01

Dietary guidelines advise consumers to limit intake of red meat and choose lean protein sources, such as poultry and fish. Poultry consumption has been steadily increasing in the U.S., but the effect on cancer risk remains unclear. In a large U.S. cohort, we prospectively investigated poultry and fish intake and cancer risk across a range of malignancies in men and women. Diet was assessed at baseline (1995–1996) with a food frequency questionnaire in 492,186 participants of the National Institutes of Health-AARP Diet and Health Study. Over a mean follow-up of 9 years, we identified 74,418 incident cancer cases. In multivariate Cox proportional hazards regression models, we estimated the substitution and addition effects of white meat (poultry and fish) intake in relation to cancer risk. In substitution models with total meat intake held constant, a 10 gram (per 1,000 kilocalories) increase in white meat intake offset by an equal decrease in red meat intake was associated with a statistically significant reduced (3–20%) risk of cancers of the esophagus, liver, colon, rectum, anus, lung, and pleura. In addition models with red meat intake held constant, poultry intake remained inversely associated with esophageal squamous cell carcinoma, liver cancer, and lung cancer, but we observed mixed findings for fish intake. As the dietary recommendations intend, the inverse association observed between white meat intake and cancer risk may be largely due to the substitution of red meat. Simply increasing fish or poultry intake, without reducing red meat intake, may be less beneficial for cancer prevention. PMID:21803982

Population Modeling of Modified Risk Tobacco Products Accounting for Smoking Reduction and Gradual Transitions of Relative Risk.

PubMed

Poland, Bill; Teischinger, Florian

2017-11-01

As suggested by the Food and Drug Administration (FDA) Modified Risk Tobacco Product (MRTP) Applications Draft Guidance, we developed a statistical model based on public data to explore the effect on population mortality of an MRTP resulting in reduced conventional cigarette smoking. Many cigarette smokers who try an MRTP persist as dual users while smoking fewer conventional cigarettes per day (CPD). Lower-CPD smokers have lower mortality risk based on large cohort studies. However, with little data on the effect of smoking reduction on mortality, predictive modeling is needed. We generalize prior assumptions of gradual, exponential decay of Excess Risk (ER) of death, relative to never-smokers, after quitting or reducing CPD. The same age-dependent slopes are applied to all transitions, including initiation to conventional cigarettes and to a second product (MRTP). A Monte Carlo simulation model generates random individual product use histories, including CPD, to project cumulative deaths through 2060 in a population with versus without the MRTP. Transitions are modeled to and from dual use, which affects CPD and cigarette quit rates, and to MRTP use only. Results in a hypothetical scenario showed high sensitivity of long-run mortality to CPD reduction levels and moderate sensitivity to ER transition rates. Models to project population effects of an MRTP should account for possible mortality effects of reduced smoking among dual users. In addition, studies should follow dual-user CPD histories and quit rates over long time periods to clarify long-term usage patterns and thereby improve health impact projections. We simulated mortality effects of a hypothetical MRTP accounting for cigarette smoking reduction by smokers who add MRTP use. Data on relative mortality risk versus CPD suggest that this reduction may have a substantial effect on mortality rates, unaccounted for in other models. This effect is weighed with additional hypothetical effects in an example. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Updating and prospective validation of a prognostic model for high sickness absence.

PubMed

Roelen, C A M; Heymans, M W; Twisk, J W R; van Rhenen, W; Pallesen, S; Bjorvatn, B; Moen, B E; Magerøy, N

2015-01-01

To further develop and validate a Dutch prognostic model for high sickness absence (SA). Three-wave longitudinal cohort study of 2,059 Norwegian nurses. The Dutch prognostic model was used to predict high SA among Norwegian nurses at wave 2. Subsequently, the model was updated by adding person-related (age, gender, marital status, children at home, and coping strategies), health-related (BMI, physical activity, smoking, and caffeine and alcohol intake), and work-related (job satisfaction, job demands, decision latitude, social support at work, and both work-to-family and family-to-work spillover) variables. The updated model was then prospectively validated for predictions at wave 3. 1,557 (77 %) nurses had complete data at wave 2 and 1,342 (65 %) at wave 3. The risk of high SA was under-estimated by the Dutch model, but discrimination between high-risk and low-risk nurses was fair after re-calibration to the Norwegian data. Gender, marital status, BMI, physical activity, smoking, alcohol intake, job satisfaction, job demands, decision latitude, support at the workplace, and work-to-family spillover were identified as potential predictors of high SA. However, these predictors did not improve the model's discriminative ability, which remained fair at wave 3. The prognostic model correctly identifies 73 % of Norwegian nurses at risk of high SA, although additional predictors are needed before the model can be used to screen working populations for risk of high SA.

Climate Change Could Increase the Geographic Extent of Hendra Virus Spillover Risk.

PubMed

Martin, Gerardo; Yanez-Arenas, Carlos; Chen, Carla; Plowright, Raina K; Webb, Rebecca J; Skerratt, Lee F

2018-03-19

Disease risk mapping is important for predicting and mitigating impacts of bat-borne viruses, including Hendra virus (Paramyxoviridae:Henipavirus), that can spillover to domestic animals and thence to humans. We produced two models to estimate areas at potential risk of HeV spillover explained by the climatic suitability for its flying fox reservoir hosts, Pteropus alecto and P. conspicillatus. We included additional climatic variables that might affect spillover risk through other biological processes (such as bat or horse behaviour, plant phenology and bat foraging habitat). Models were fit with a Poisson point process model and a log-Gaussian Cox process. In response to climate change, risk expanded southwards due to an expansion of P. alecto suitable habitat, which increased the number of horses at risk by 175-260% (110,000-165,000). In the northern limits of the current distribution, spillover risk was highly uncertain because of model extrapolation to novel climatic conditions. The extent of areas at risk of spillover from P. conspicillatus was predicted shrink. Due to a likely expansion of P. alecto into these areas, it could replace P. conspicillatus as the main HeV reservoir. We recommend: (1) HeV monitoring in bats, (2) enhancing HeV prevention in horses in areas predicted to be at risk, (3) investigate and develop mitigation strategies for areas that could experience reservoir host replacements.

Association of MTHFR C667T polymorphism with bone mineral density and fracture risk: an updated meta-analysis.

PubMed

Wang, H; Liu, C

2012-11-01

This meta-analysis investigated the association of C677T polymorphism in MTHFR gene with bone mineral density (BMD) and fracture risk. The results suggested that C677T polymorphism was marginally associated with fracture risk. In addition, this polymorphism was modestly associated with BMD of lumbar spine, femoral neck, total hip, and total body, respectively. The methylenetetrahydrofolate reductase (MTHFR) gene has been implicated in the regulation of BMD and, thus, may serve as a potential risk factor for the development of fracture. However, results have been inconsistent. In this study, a meta-analysis was performed to clarify the association of C677T polymorphism in MTHFR gene with BMD and fracture risk. Published literature from PubMed and EMBASE were searched for eligible publications. Pooled odds ratio (OR) or weighted mean difference (WMD) and 95% confidence interval (CI) were calculated using a fixed- or random-effects model. Twenty studies (3,525 cases and 17,909 controls) were included in this meta-analysis. The TT genotype of C677T polymorphism was marginally associated with an increased risk of fracture under recessive model (TT vs. TC + CC: OR = 1.23, 95% CI 1.04-1.47). Using this model, similar results were found among East Asians (OR = 1.40, 95% CI 1.07-1.83), female subpopulation (1.27, 95% CI 1.04-1.55), cohort studies (OR = 1.24, 95% CI 1.08-1.44), and subjects younger than aged 60 years (OR = 1.51, 95% CI 1.10-2.07). In addition, under homogeneous co-dominant model, there was a modest association of C677T polymorphism with BMD of lumbar spine (WMD = -0.017 g/cm(2); 95%CI, -0.030-(-0.005) g/cm(2)), femoral neck (WMD = -0.010 g/cm(2); 95% CI -0.017-(-0.003) g/cm(2)), total hip (WMD = -0.013 g/cm(2), 95% CI -0.022-(-0.004) g/cm(2)), and total body (WMD = -0.020 g/cm(2); 95% CI -0.027-(-0.013) g/cm(2)), respectively. This meta-analysis suggested that C677T polymorphism was marginally associated with fracture risk. In addition, this polymorphism was modestly associated with BMD of lumbar spine, femoral neck, total hip, and total body, respectively.

Microbial Risk Assessment

NASA Technical Reports Server (NTRS)

Ott, C. M.; Mena, K. D.; Nickerson, C.A.; Pierson, D. L.

2009-01-01

Historically, microbiological spaceflight requirements have been established in a subjective manner based upon expert opinion of both environmental and clinical monitoring results and the incidence of disease. The limited amount of data, especially from long-duration missions, has created very conservative requirements based primarily on the concentration of microorganisms. Periodic reevaluations of new data from later missions have allowed some relaxation of these stringent requirements. However, the requirements remain very conservative and subjective in nature, and the risk of crew illness due to infectious microorganisms is not well defined. The use of modeling techniques for microbial risk has been applied in the food and potable water industries and has exceptional potential for spaceflight applications. From a productivity standpoint, this type of modeling can (1) decrease unnecessary costs and resource usage and (2) prevent inadequate or inappropriate data for health assessment. In addition, a quantitative model has several advantages for risk management and communication. By identifying the variable components of the model and the knowledge associated with each component, this type of modeling can: (1) Systematically identify and close knowledge gaps, (2) Systematically identify acceptable and unacceptable risks, (3) Improve communication with stakeholders as to the reasons for resource use, and (4) Facilitate external scientific approval of the NASA requirements. The modeling of microbial risk involves the evaluation of several key factors including hazard identification, crew exposure assessment, dose-response assessment, and risk characterization. Many of these factors are similar to conditions found on Earth; however, the spaceflight environment is very specialized as the inhabitants live in a small, semi-closed environment that is often dependent on regenerative life support systems. To further complicate modeling efforts, microbial dose-response characteristics may be affected by a potentially dysfunctional crew immune system during a mission. In addition, microbial virulence has been shown to change under certain conditions during spaceflight, further complicating dose-response characterization. An initial study of the applicability of microbial risk assessment techniques was performed using Crew Health Care System (CHeCS) operational data from the International Space Station potable water systems. The risk of infection from potable water was selected as the flight systems and microbial ecology are well defined. This initial study confirmed the feasibility of using microbial risk assessment modeling for spaceflight systems. While no immediate threat was detected, the study identified several medically significant microorganisms that could pose a health risk if uncontrolled. The study also identified several specific knowledge gaps in making a risk assessment and noted that filling these knowledge gaps is essential as the risk estimates may change by orders of magnitude depending on the answers. The current phase of the microbial risk assessment studies focuses on the dose-response relationship of specific infectious agents, focusing on Salmonella enterica Typhimurium, Pseudomonas spp., and Escherichia coli, as their evaluation will provide a better baseline for determining the overall hazard characterization. The organisms were chosen as they either have been isolated on spacecraft or have an identified route of infection during a mission. The characterization will utilize dose-response models selected either from the peer-reviewed literature and/or by using statistical approaches. Development of these modeling and risk assessment techniques will help to optimize flight requirements and to protect the safety, health, and performance of the crew.

An Agent-Based Model of Evolving Community Flood Risk.

PubMed

Tonn, Gina L; Guikema, Seth D

2018-06-01

Although individual behavior plays a major role in community flood risk, traditional flood risk models generally do not capture information on how community policies and individual decisions impact the evolution of flood risk over time. The purpose of this study is to improve the understanding of the temporal aspects of flood risk through a combined analysis of the behavioral, engineering, and physical hazard aspects of flood risk. Additionally, the study aims to develop a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions. An agent-based model (ABM) is used to analyze the influence of flood protection measures, individual behavior, and the occurrence of floods and near-miss flood events on community flood risk. The ABM focuses on the following decisions and behaviors: dissemination of flood management information, installation of community flood protection, elevation of household mechanical equipment, and elevation of homes. The approach is place based, with a case study area in Fargo, North Dakota, but is focused on generalizable insights. Generally, community mitigation results in reduced future damage, and individual action, including mitigation and movement into and out of high-risk areas, can have a significant influence on community flood risk. The results of this study provide useful insights into the interplay between individual and community actions and how it affects the evolution of flood risk. This study lends insight into priorities for future work, including the development of more in-depth behavioral and decision rules at the individual and community level. © 2017 Society for Risk Analysis.

Optimal dividends in the Brownian motion risk model with interest

NASA Astrophysics Data System (ADS)

Fang, Ying; Wu, Rong

2009-07-01

In this paper, we consider a Brownian motion risk model, and in addition, the surplus earns investment income at a constant force of interest. The objective is to find a dividend policy so as to maximize the expected discounted value of dividend payments. It is well known that optimality is achieved by using a barrier strategy for unrestricted dividend rate. However, ultimate ruin of the company is certain if a barrier strategy is applied. In many circumstances this is not desirable. This consideration leads us to impose a restriction on the dividend stream. We assume that dividends are paid to the shareholders according to admissible strategies whose dividend rate is bounded by a constant. Under this additional constraint, we show that the optimal dividend strategy is formed by a threshold strategy.

Incorporating Comorbidity Within Risk Adjustment for UK Pediatric Cardiac Surgery.

PubMed

Brown, Katherine L; Rogers, Libby; Barron, David J; Tsang, Victor; Anderson, David; Tibby, Shane; Witter, Thomas; Stickley, John; Crowe, Sonya; English, Kate; Franklin, Rodney C; Pagel, Christina

2017-07-01

When considering early survival rates after pediatric cardiac surgery it is essential to adjust for risk linked to case complexity. An important but previously less well understood component of case mix complexity is comorbidity. The National Congenital Heart Disease Audit data representing all pediatric cardiac surgery procedures undertaken in the United Kingdom and Ireland between 2009 and 2014 was used to develop and test groupings for comorbidity and additional non-procedure-based risk factors within a risk adjustment model for 30-day mortality. A mixture of expert consensus based opinion and empiric statistical analyses were used to define and test the new comorbidity groups. The study dataset consisted of 21,838 pediatric cardiac surgical procedure episodes in 18,834 patients with 539 deaths (raw 30-day mortality rate, 2.5%). In addition to surgical procedure type, primary cardiac diagnosis, univentricular status, age, weight, procedure type (bypass, nonbypass, or hybrid), and era, the new risk factor groups of non-Down congenital anomalies, acquired comorbidities, increased severity of illness indicators (eg, preoperative mechanical ventilation or circulatory support) and additional cardiac risk factors (eg, heart muscle conditions and raised pulmonary arterial pressure) all independently increased the risk of operative mortality. In an era of low mortality rates across a wide range of operations, non-procedure-based risk factors form a vital element of risk adjustment and their presence leads to wide variations in the predicted risk of a given operation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Long-Term Survival Prediction for Coronary Artery Bypass Grafting: Validation of the ASCERT Model Compared With The Society of Thoracic Surgeons Predicted Risk of Mortality.

PubMed

Lancaster, Timothy S; Schill, Matthew R; Greenberg, Jason W; Ruaengsri, Chawannuch; Schuessler, Richard B; Lawton, Jennifer S; Maniar, Hersh S; Pasque, Michael K; Moon, Marc R; Damiano, Ralph J; Melby, Spencer J

2018-05-01

The recently developed American College of Cardiology Foundation-Society of Thoracic Surgeons (STS) Collaboration on the Comparative Effectiveness of Revascularization Strategy (ASCERT) Long-Term Survival Probability Calculator is a valuable addition to existing short-term risk-prediction tools for cardiac surgical procedures but has yet to be externally validated. Institutional data of 654 patients aged 65 years or older undergoing isolated coronary artery bypass grafting between 2005 and 2010 were reviewed. Predicted survival probabilities were calculated using the ASCERT model. Survival data were collected using the Social Security Death Index and institutional medical records. Model calibration and discrimination were assessed for the overall sample and for risk-stratified subgroups based on (1) ASCERT 7-year survival probability and (2) the predicted risk of mortality (PROM) from the STS Short-Term Risk Calculator. Logistic regression analysis was performed to evaluate additional perioperative variables contributing to death. Overall survival was 92.1% (569 of 597) at 1 year and 50.5% (164 of 325) at 7 years. Calibration assessment found no significant differences between predicted and actual survival curves for the overall sample or for the risk-stratified subgroups, whether stratified by predicted 7-year survival or by PROM. Discriminative performance was comparable between the ASCERT and PROM models for 7-year survival prediction (p < 0.001 for both; C-statistic = 0.815 for ASCERT and 0.781 for PROM). Prolonged ventilation, stroke, and hospital length of stay were also predictive of long-term death. The ASCERT survival probability calculator was externally validated for prediction of long-term survival after coronary artery bypass grafting in all risk groups. The widely used STS PROM performed comparably as a predictor of long-term survival. Both tools provide important information for preoperative decision making and patient counseling about potential outcomes after coronary artery bypass grafting. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

A small-area ecologic study of myocardial infarction, neighborhood deprivation, and sex: a Bayesian modeling approach.

PubMed

Deguen, Séverine; Lalloue, Benoît; Bard, Denis; Havard, Sabrina; Arveiler, Dominique; Zmirou-Navier, Denis

2010-07-01

Socioeconomic inequalities in the risk of coronary heart disease (CHD) are well documented for men and women. CHD incidence is greater for men but its association with socioeconomic status is usually found to be stronger among women. We explored the sex-specific association between neighborhood deprivation level and the risk of myocardial infarction (MI) at a small-area scale. We studied 1193 myocardial infarction events in people aged 35-74 years in the Strasbourg metropolitan area, France (2000-2003). We used a deprivation index to assess the neighborhood deprivation level. To take into account spatial dependence and the variability of MI rates due to the small number of events, we used a hierarchical Bayesian modeling approach. We fitted hierarchical Bayesian models to estimate sex-specific relative and absolute MI risks across deprivation categories. We tested departure from additive joint effects of deprivation and sex. The risk of MI increased with the deprivation level for both sexes, but was higher for men for all deprivation classes. Relative rates increased along the deprivation scale more steadily for women and followed a different pattern: linear for men and nonlinear for women. Our data provide evidence of effect modification, with departure from an additive joint effect of deprivation and sex. We document sex differences in the socioeconomic gradient of MI risk in Strasbourg. Women appear more susceptible at levels of extreme deprivation; this result is not a chance finding, given the large difference in event rates between men and women.

A Practical Probabilistic Graphical Modeling Tool for Weighing ...

EPA Pesticide Factsheets

Past weight-of-evidence frameworks for adverse ecological effects have provided soft-scoring procedures for judgments based on the quality and measured attributes of evidence. Here, we provide a flexible probabilistic structure for weighing and integrating lines of evidence for ecological risk determinations. Probabilistic approaches can provide both a quantitative weighing of lines of evidence and methods for evaluating risk and uncertainty. The current modeling structure wasdeveloped for propagating uncertainties in measured endpoints and their influence on the plausibility of adverse effects. To illustrate the approach, we apply the model framework to the sediment quality triad using example lines of evidence for sediment chemistry measurements, bioassay results, and in situ infauna diversity of benthic communities using a simplified hypothetical case study. We then combine the three lines evidence and evaluate sensitivity to the input parameters, and show how uncertainties are propagated and how additional information can be incorporated to rapidly update the probability of impacts. The developed network model can be expanded to accommodate additional lines of evidence, variables and states of importance, and different types of uncertainties in the lines of evidence including spatial and temporal as well as measurement errors. We provide a flexible Bayesian network structure for weighing and integrating lines of evidence for ecological risk determinations

Methodology for Developing a Probabilistic Risk Assessment Model of Spacecraft Rendezvous and Dockings

NASA Technical Reports Server (NTRS)

Farnham, Steven J., II; Garza, Joel, Jr.; Castillo, Theresa M.; Lutomski, Michael

2011-01-01

In 2007 NASA was preparing to send two new visiting vehicles carrying logistics and propellant to the International Space Station (ISS). These new vehicles were the European Space Agency s (ESA) Automated Transfer Vehicle (ATV), the Jules Verne, and the Japanese Aerospace and Explorations Agency s (JAXA) H-II Transfer Vehicle (HTV). The ISS Program wanted to quantify the increased risk to the ISS from these visiting vehicles. At the time, only the Shuttle, the Soyuz, and the Progress vehicles rendezvoused and docked to the ISS. The increased risk to the ISS was from an increase in vehicle traffic, thereby, increasing the potential catastrophic collision during the rendezvous and the docking or berthing of the spacecraft to the ISS. A universal method of evaluating the risk of rendezvous and docking or berthing was created by the ISS s Risk Team to accommodate the increasing number of rendezvous and docking or berthing operations due to the increasing number of different spacecraft, as well as the future arrival of commercial spacecraft. Before the first docking attempt of ESA's ATV and JAXA's HTV to the ISS, a probabilistic risk model was developed to quantitatively calculate the risk of collision of each spacecraft with the ISS. The 5 rendezvous and docking risk models (Soyuz, Progress, Shuttle, ATV, and HTV) have been used to build and refine the modeling methodology for rendezvous and docking of spacecrafts. This risk modeling methodology will be NASA s basis for evaluating the addition of future ISS visiting spacecrafts hazards, including SpaceX s Dragon, Orbital Science s Cygnus, and NASA s own Orion spacecraft. This paper will describe the methodology used for developing a visiting vehicle risk model.

Risk assessment of consuming agricultural products irrigated with reclaimed wastewater: An exposure model

NASA Astrophysics Data System (ADS)

van Ginneken, Meike; Oron, Gideon

2000-09-01

This study assesses health risks to consumers due to the use of agricultural products irrigated with reclaimed wastewater. The analysis is based on a definition of an exposure model which takes into account several parameters: (1) the quality of the applied wastewater, (2) the irrigation method, (3) the elapsed times between irrigation, harvest, and product consumption, and (4) the consumers' habits. The exposure model is used for numerical simulation of human consumers' risks using the Monte Carlo simulation method. The results of the numerical simulation show large deviations, probably caused by uncertainty (impreciseness in quality of input data) and variability due to diversity among populations. There is a 10-orders of magnitude difference in the risk of infection between the different exposure scenarios with the same water quality. This variation indicates the need for setting risk-based criteria for wastewater reclamation rather than single water quality guidelines. Extra data are required to decrease uncertainty in the risk assessment. Future research needs to include definition of acceptable risk criteria, more accurate dose-response modeling, information regarding pathogen survival in treated wastewater, additional data related to the passage of pathogens into and in the plants during irrigation, and information regarding the behavior patterns of the community of human consumers.

Improving Disease Prediction by Incorporating Family Disease History in Risk Prediction Models with Large-Scale Genetic Data.

PubMed

Gim, Jungsoo; Kim, Wonji; Kwak, Soo Heon; Choi, Hosik; Park, Changyi; Park, Kyong Soo; Kwon, Sunghoon; Park, Taesung; Won, Sungho

2017-11-01

Despite the many successes of genome-wide association studies (GWAS), the known susceptibility variants identified by GWAS have modest effect sizes, leading to notable skepticism about the effectiveness of building a risk prediction model from large-scale genetic data. However, in contrast to genetic variants, the family history of diseases has been largely accepted as an important risk factor in clinical diagnosis and risk prediction. Nevertheless, the complicated structures of the family history of diseases have limited their application in clinical practice. Here, we developed a new method that enables incorporation of the general family history of diseases with a liability threshold model, and propose a new analysis strategy for risk prediction with penalized regression analysis that incorporates both large numbers of genetic variants and clinical risk factors. Application of our model to type 2 diabetes in the Korean population (1846 cases and 1846 controls) demonstrated that single-nucleotide polymorphisms accounted for 32.5% of the variation explained by the predicted risk scores in the test data set, and incorporation of family history led to an additional 6.3% improvement in prediction. Our results illustrate that family medical history provides valuable information on the variation of complex diseases and improves prediction performance. Copyright © 2017 by the Genetics Society of America.

Managing security risks for inter-organisational information systems: a multiagent collaborative model

NASA Astrophysics Data System (ADS)

Feng, Nan; Wu, Harris; Li, Minqiang; Wu, Desheng; Chen, Fuzan; Tian, Jin

2016-09-01

Information sharing across organisations is critical to effectively managing the security risks of inter-organisational information systems. Nevertheless, few previous studies on information systems security have focused on inter-organisational information sharing, and none have studied the sharing of inferred beliefs versus factual observations. In this article, a multiagent collaborative model (MACM) is proposed as a practical solution to assess the risk level of each allied organisation's information system and support proactive security treatment by sharing beliefs on event probabilities as well as factual observations. In MACM, for each allied organisation's information system, we design four types of agents: inspection agent, analysis agent, control agent, and communication agent. By sharing soft findings (beliefs) in addition to hard findings (factual observations) among the organisations, each organisation's analysis agent is capable of dynamically predicting its security risk level using a Bayesian network. A real-world implementation illustrates how our model can be used to manage security risks in distributed information systems and that sharing soft findings leads to lower expected loss from security risks.

Risk maps for navigation in liver surgery

NASA Astrophysics Data System (ADS)

Hansen, C.; Zidowitz, S.; Schenk, A.; Oldhafer, K.-J.; Lang, H.; Peitgen, H.-O.

2010-02-01

The optimal transfer of preoperative planning data and risk evaluations to the operative site is challenging. A common practice is to use preoperative 3D planning models as a printout or as a presentation on a display. One important aspect is that these models were not developed to provide information in complex workspaces like the operating room. Our aim is to reduce the visual complexity of 3D planning models by mapping surgically relevant information onto a risk map. Therefore, we present methods for the identification and classification of critical anatomical structures in the proximity of a preoperatively planned resection surface. Shadow-like distance indicators are introduced to encode the distance from the resection surface to these critical structures on the risk map. In addition, contour lines are used to accentuate shape and spatial depth. The resulting visualization is clear and intuitive, allowing for a fast mental mapping of the current resection surface to the risk map. Preliminary evaluations by liver surgeons indicate that damage to risk structures may be prevented and patient safety may be enhanced using the proposed methods.

Does the mortality risk of social isolation depend upon socioeconomic factors?

PubMed

Patterson, Andrew C

2016-10-01

This study considers whether socioeconomic status influences the impact of social isolation on mortality risk. Using data from the Alameda County Study, Cox proportional hazard models indicate that having a high income worsens the mortality risk of social isolation. Education may offset risk, however, and the specific pattern that emerges depends on which measures for socioeconomic status and social isolation are included. Additionally, lonely people who earn high incomes suffer especially high risk of accidents and suicides as well as cancer. Further research is needed that contextualizes the health risks of social isolation within the broader social environment. © The Author(s) 2015.

A review on the removal of antibiotics by carbon nanotubes.

PubMed

Cong, Qiao; Yuan, Xing; Qu, Jiao

2013-01-01

Increasing concerns have been raised regarding the potential risks of antibiotics to human and ecological health due to their extensive use. Carbon nanotubes (CNTs) have drawn special research attention because of their unique properties and potential applications as a kind of adsorbents. This review summarizes the currently available research on the adsorption of antibiotics on CNTs, and will provide useful information for CNT application and risk assessment. Four different models, the Freundlich model (FM), Langmuir model (LM), Polanyi-Mane model (PMM), and Dubinin-Ashtakhov model (DAM), are often used to fit the adsorption isotherms. Because different mechanisms may act simultaneously, including electrostatic interactions, hydrophobic interactions, π-π bonds, and hydrogen bonds, the prediction of organic chemical adsorption on CNTs is not straightforward. Properties of CNTs, such as specific surface area, adsorption sites, and oxygen content, may influence the adsorption of antibiotics on CNTs. Adsorption heterogeneity and hysteresis are two features of antibiotic-CNT interactions. In addition, CNTs with adsorbed antibiotics may have potential risks for human health. So, further research examining how to reduce such risks is needed.

CYP gene family variants as potential protective factors in drug addiction in Han Chinese.

PubMed

Zhang, Hongxing; Yang, Qi; Zheng, Wenkai; Ouyang, Yongri; Yang, Min; Wang, Fengjiao; Jin, Tianbo; Zhang, Ji; Wang, Zhenyuan

2016-08-01

There is growing evidence that genetic factors also contribute to drug addiction. The human cytochrome P450 has shown special interest because of pharmacokinetic variation in different individuals and populations, which is largely determined by the relevant genes. The present study aimed to investigate the polymorphism of the CYP/addicts relationship. We genotyped 13 tag single-nucleotide polymorphisms (tSNPs) from three genes, including 692 cases and 700 controls. Sequenom MassARRAY RS1000 (Sequenom, Inc., San Diego, CA, USA) was used for SNP genotyping. Statistical analysis of the association between tSNPs and drug addiction was performed using the chi-squared test and SNP Stats software (http://bioinfo.iconcologia.net). The T/T genotype of rs2242480 in CYP3A4 was associated with decreased risk in the recessive model (p = 0.0002). Allele frequency at rs3743484 in CYP1A2 showed significant differences between addicts and controls (p = 0.046; odds ratio = 0.80; 95% confidence interval = 0.65-1.00). In genetic model analyses, the minor C allele of rs3743484 in CYP1A2 was associated with a reduced risk of drug addiction based on analysis using codominant and additive models (p = 0.027 dominant model; p =0.038 additive model). Our findings show that at allelic and genotypic level polymorphisms in CYP3A4 and CYP1A2 are significantly associated with a reduced risk of drug addiction in X'ian Han Chinese individuals. However, this result needs to be confirmed in additional studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Laser Scanning Systems and Techniques in Rockfall Source Identification and Risk Assessment: A Critical Review

NASA Astrophysics Data System (ADS)

Fanos, Ali Mutar; Pradhan, Biswajeet

2018-04-01

Rockfall poses risk to people, their properties and to transportation ways in mountainous and hilly regions. This catastrophe shows various characteristics such as vast distribution, sudden occurrence, variable magnitude, strong fatalness and randomicity. Therefore, prediction of rockfall phenomenon both spatially and temporally is a challenging task. Digital Terrain model (DTM) is one of the most significant elements in rockfall source identification and risk assessment. Light detection and ranging (LiDAR) is the most advanced effective technique to derive high-resolution and accurate DTM. This paper presents a critical overview of rockfall phenomenon (definition, triggering factors, motion modes and modeling) and LiDAR technique in terms of data pre-processing, DTM generation and the factors that can be obtained from this technique for rockfall source identification and risk assessment. It also reviews the existing methods that are utilized for the evaluation of the rockfall trajectories and their characteristics (frequency, velocity, bouncing height and kinetic energy), probability, susceptibility, hazard and risk. Detail consideration is given on quantitative methodologies in addition to the qualitative ones. Various methods are demonstrated with respect to their application scales (local and regional). Additionally, attention is given to the latest improvement, particularly including the consideration of the intensity of the phenomena and the magnitude of the events at chosen sites.

Cumulative estrogen exposure, number of menstrual cycles, and Alzheimer's risk in a cohort of British women.

PubMed

Fox, Molly; Berzuini, Carlo; Knapp, Leslie A

2013-12-01

The effect of estrogen on Alzheimer's Disease (AD) risk has received substantial research and media attention, especially in terms of hormone replacement therapy. But reproductive history is also an important modifier of estrogenic exposure, and deserves further investigation. Importantly, there is wide variation in reproductive patterns that modifies estrogen exposure during the reproductive span, which previous AD studies have not incorporated into their calculations. We measured degree of Alzheimer's-type dementia in a cohort of elderly British women, and collected detailed reproductive and medical history information, which we used to estimate number of months with estrogen exposure and number of months with menstrual cycles. Using Cox proportional-hazards models, we find that longer duration of estrogen exposure may have a protective effect against AD risk, such that for every additional month with estrogen, women experienced on average a 0.5% decrease in AD risk (N=89, p=0.02). More menstrual cycles may also have a protective effect against AD risk, although this result was of borderline statistical significance (p<0.10). These results build upon previous methodologies by taking into account a variety of parameters including oral contraceptive use, breastfeeding, post-partum anovulation, abortions, and miscarriages. Additionally, Cox models revealed that longer reproductive span, age>21 at first birth, and more months in lifetime spent pregnant had protective effects against AD risk. Copyright © 2013 Elsevier Ltd. All rights reserved.

An Overview of Exposure Assessment Models Used by the U.S. Environmental Protection Agency

EPA Science Inventory

Models are often used in addition to or in lieu of monitoring data to estimate environmental concentrations and exposures for use in risk assessments or epidemiological studies, and to support regulatory standards and voluntary programs (Jayjock et al., 2007; US EPA, 1989, 1992)....

Linking livestock snow disaster mortality and environmental stressors in the Qinghai-Tibetan Plateau: Quantification based on generalized additive models.

PubMed

Li, Yijia; Ye, Tao; Liu, Weihang; Gao, Yu

2018-06-01

Livestock snow disaster occurs widely in Central-to-Eastern Asian temperate and alpine grasslands. The effects of snow disaster on livestock involve a complex interaction between precipitation, vegetation, livestock, and herder communities. Quantifying the relationship among livestock mortality, snow hazard intensity, and seasonal environmental stressors is of great importance for snow disaster early warning, risk assessments, and adaptation strategies. Using a wide-spatial extent, long-time series, and event-based livestock snow disaster dataset, this study quantified those relationships and established a quantitative model of livestock mortality for prediction purpose for the Qinghai-Tibet Plateau region. Estimations using generalized additive models (GAMs) were shown to accurately predict livestock mortality and mortality rate due to snow disaster, with adjusted-R 2 up to 0.794 and 0.666, respectively. These results showed that a longer snow disaster duration, lower temperatures during the disaster, and a drier summer with less vegetation all contribute significantly and non-linearly to higher mortality (rate), after controlling for elevation and socioeconomic conditions. These results can be readily applied to risk assessment and risk-based adaptation actions. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction models for the risk of spontaneous preterm birth based on maternal characteristics: a systematic review and independent external validation.

PubMed

Meertens, Linda J E; van Montfort, Pim; Scheepers, Hubertina C J; van Kuijk, Sander M J; Aardenburg, Robert; Langenveld, Josje; van Dooren, Ivo M A; Zwaan, Iris M; Spaanderman, Marc E A; Smits, Luc J M

2018-04-17

Prediction models may contribute to personalized risk-based management of women at high risk of spontaneous preterm delivery. Although prediction models are published frequently, often with promising results, external validation generally is lacking. We performed a systematic review of prediction models for the risk of spontaneous preterm birth based on routine clinical parameters. Additionally, we externally validated and evaluated the clinical potential of the models. Prediction models based on routinely collected maternal parameters obtainable during first 16 weeks of gestation were eligible for selection. Risk of bias was assessed according to the CHARMS guidelines. We validated the selected models in a Dutch multicenter prospective cohort study comprising 2614 unselected pregnant women. Information on predictors was obtained by a web-based questionnaire. Predictive performance of the models was quantified by the area under the receiver operating characteristic curve (AUC) and calibration plots for the outcomes spontaneous preterm birth <37 weeks and <34 weeks of gestation. Clinical value was evaluated by means of decision curve analysis and calculating classification accuracy for different risk thresholds. Four studies describing five prediction models fulfilled the eligibility criteria. Risk of bias assessment revealed a moderate to high risk of bias in three studies. The AUC of the models ranged from 0.54 to 0.67 and from 0.56 to 0.70 for the outcomes spontaneous preterm birth <37 weeks and <34 weeks of gestation, respectively. A subanalysis showed that the models discriminated poorly (AUC 0.51-0.56) for nulliparous women. Although we recalibrated the models, two models retained evidence of overfitting. The decision curve analysis showed low clinical benefit for the best performing models. This review revealed several reporting and methodological shortcomings of published prediction models for spontaneous preterm birth. Our external validation study indicated that none of the models had the ability to predict spontaneous preterm birth adequately in our population. Further improvement of prediction models, using recent knowledge about both model development and potential risk factors, is necessary to provide an added value in personalized risk assessment of spontaneous preterm birth. © 2018 The Authors Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

Risk Management in Biologics Technology Transfer.

PubMed

Toso, Robert; Tsang, Jonathan; Xie, Jasmina; Hohwald, Stephen; Bain, David; Willison-Parry, Derek

Technology transfer of biological products is a complex process that is important for product commercialization. To achieve a successful technology transfer, the risks that arise from changes throughout the project must be managed. Iterative risk analysis and mitigation tools can be used to both evaluate and reduce risk. The technology transfer stage gate model is used as an example tool to help manage risks derived from both designed process change and unplanned changes that arise due to unforeseen circumstances. The strategy of risk assessment for a change can be tailored to the type of change. In addition, a cross-functional team and centralized documentation helps maximize risk management efficiency to achieve a successful technology transfer. © PDA, Inc. 2016.

Cost benefits of ergonomic intervention in a hospital: a preliminary study using Oxenburgh's productivity model.

PubMed

Busse, M; Bridger, B

1997-09-01

This case study of absenteeism amongst nurses was carried out using the productivity model of Oxenburgh (1991). Data on absenteeism amongst nurses were collected from one private hospital. Areas of high risk of injury were identified and the presence of ergonomic risk factors determined. The productivity model was used to calculate the costs of absenteeism in terms of actual rates of pay and loss of productivity. Potential benefits resulting from ergonomic improvements to the work environment were estimated using the productivity model. The model predicted that even modest reductions in injury would justify the additional expenditure in a relatively short period of time. Further investigations of injuries to nurses in both State and Private Sector Hospitals seem to be justified.

Improving long-term prediction of first cardiovascular event: the contribution of family history of coronary heart disease and social status.

PubMed

Veronesi, G; Gianfagna, F; Giampaoli, S; Chambless, L E; Mancia, G; Cesana, G; Ferrario, M M

2014-07-01

The aim of this study is to assess whether family history of coronary heart disease (CHD) and education as proxy of social status improve long-term cardiovascular disease risk prediction in a low-incidence European population. The 20-year risk of first coronary or ischemic stroke events was estimated using sex-specific Cox models in 3956 participants of three population-based surveys in northern Italy, aged 35-69 years and free of cardiovascular disease at enrollment. The additional contribution of education and positive family history of CHD was defined as change in discrimination and Net Reclassification Improvement (NRI) over the model including 7 traditional risk factors. Kaplan-Meier 20-year risk was 16.8% in men (254 events) and 6.4% in women (102 events). Low education (hazard ratio=1.35, 95%CI 0.98-1.85) and family history of CHD (1.55; 1.19-2.03) were associated with the endpoint in men, but not in women. In men, the addition of education and family history significantly improved discrimination by 1%; NRI was 6% (95%CI: 0.2%-15.2%), raising to 20% (0.5%-44%) in those at intermediate risk. NRI in women at intermediate risk was 7%. In low-incidence populations, family history of CHD and education, easily assessed in clinical practice, should be included in long-term cardiovascular disease risk scores, at least in men. Copyright © 2014 Elsevier Inc. All rights reserved.

Weighted Genetic Risk Scores and Prediction of Weight Gain in Solid Organ Transplant Populations

PubMed Central

Saigi-Morgui, Núria; Quteineh, Lina; Bochud, Pierre-Yves; Crettol, Severine; Kutalik, Zoltán; Wojtowicz, Agnieszka; Bibert, Stéphanie; Beckmann, Sonja; Mueller, Nicolas J; Binet, Isabelle; van Delden, Christian; Steiger, Jürg; Mohacsi, Paul; Stirnimann, Guido; Soccal, Paola M.; Pascual, Manuel; Eap, Chin B

2016-01-01

Background Polygenic obesity in Solid Organ Transplant (SOT) populations is considered a risk factor for the development of metabolic abnormalities and graft survival. Few studies to date have studied the genetics of weight gain in SOT recipients. We aimed to determine whether weighted genetic risk scores (w-GRS) integrating genetic polymorphisms from GWAS studies (SNP group#1 and SNP group#2) and from Candidate Gene studies (SNP group#3) influence BMI in SOT populations and if they predict ≥10% weight gain (WG) one year after transplantation. To do so, two samples (nA = 995, nB = 156) were obtained from naturalistic studies and three w-GRS were constructed and tested for association with BMI over time. Prediction of 10% WG at one year after transplantation was assessed with models containing genetic and clinical factors. Results w-GRS were associated with BMI in sample A and B combined (BMI increased by 0.14 and 0.11 units per additional risk allele in SNP group#1 and #2, respectively, p-values<0.008). w-GRS of SNP group#3 showed an effect of 0.01 kg/m2 per additional risk allele when combining sample A and B (p-value 0.04). Models with genetic factors performed better than models without in predicting 10% WG at one year after transplantation. Conclusions This is the first study in SOT evaluating extensively the association of w-GRS with BMI and the influence of clinical and genetic factors on 10% of WG one year after transplantation, showing the importance of integrating genetic factors in the final model. Genetics of obesity among SOT recipients remains an important issue and can contribute to treatment personalization and prediction of WG after transplantation. PMID:27788139

Weighted Genetic Risk Scores and Prediction of Weight Gain in Solid Organ Transplant Populations.

PubMed

Saigi-Morgui, Núria; Quteineh, Lina; Bochud, Pierre-Yves; Crettol, Severine; Kutalik, Zoltán; Wojtowicz, Agnieszka; Bibert, Stéphanie; Beckmann, Sonja; Mueller, Nicolas J; Binet, Isabelle; van Delden, Christian; Steiger, Jürg; Mohacsi, Paul; Stirnimann, Guido; Soccal, Paola M; Pascual, Manuel; Eap, Chin B

2016-01-01

Polygenic obesity in Solid Organ Transplant (SOT) populations is considered a risk factor for the development of metabolic abnormalities and graft survival. Few studies to date have studied the genetics of weight gain in SOT recipients. We aimed to determine whether weighted genetic risk scores (w-GRS) integrating genetic polymorphisms from GWAS studies (SNP group#1 and SNP group#2) and from Candidate Gene studies (SNP group#3) influence BMI in SOT populations and if they predict ≥10% weight gain (WG) one year after transplantation. To do so, two samples (nA = 995, nB = 156) were obtained from naturalistic studies and three w-GRS were constructed and tested for association with BMI over time. Prediction of 10% WG at one year after transplantation was assessed with models containing genetic and clinical factors. w-GRS were associated with BMI in sample A and B combined (BMI increased by 0.14 and 0.11 units per additional risk allele in SNP group#1 and #2, respectively, p-values<0.008). w-GRS of SNP group#3 showed an effect of 0.01 kg/m2 per additional risk allele when combining sample A and B (p-value 0.04). Models with genetic factors performed better than models without in predicting 10% WG at one year after transplantation. This is the first study in SOT evaluating extensively the association of w-GRS with BMI and the influence of clinical and genetic factors on 10% of WG one year after transplantation, showing the importance of integrating genetic factors in the final model. Genetics of obesity among SOT recipients remains an important issue and can contribute to treatment personalization and prediction of WG after transplantation.

Risk prediction models of breast cancer: a systematic review of model performances.

PubMed

Anothaisintawee, Thunyarat; Teerawattananon, Yot; Wiratkapun, Chollathip; Kasamesup, Vijj; Thakkinstian, Ammarin

2012-05-01

The number of risk prediction models has been increasingly developed, for estimating about breast cancer in individual women. However, those model performances are questionable. We therefore have conducted a study with the aim to systematically review previous risk prediction models. The results from this review help to identify the most reliable model and indicate the strengths and weaknesses of each model for guiding future model development. We searched MEDLINE (PubMed) from 1949 and EMBASE (Ovid) from 1974 until October 2010. Observational studies which constructed models using regression methods were selected. Information about model development and performance were extracted. Twenty-five out of 453 studies were eligible. Of these, 18 developed prediction models and 7 validated existing prediction models. Up to 13 variables were included in the models and sample sizes for each study ranged from 550 to 2,404,636. Internal validation was performed in four models, while five models had external validation. Gail and Rosner and Colditz models were the significant models which were subsequently modified by other scholars. Calibration performance of most models was fair to good (expected/observe ratio: 0.87-1.12), but discriminatory accuracy was poor to fair both in internal validation (concordance statistics: 0.53-0.66) and in external validation (concordance statistics: 0.56-0.63). Most models yielded relatively poor discrimination in both internal and external validation. This poor discriminatory accuracy of existing models might be because of a lack of knowledge about risk factors, heterogeneous subtypes of breast cancer, and different distributions of risk factors across populations. In addition the concordance statistic itself is insensitive to measure the improvement of discrimination. Therefore, the new method such as net reclassification index should be considered to evaluate the improvement of the performance of a new develop model.

Cost-effectiveness of additional catheter-directed thrombolysis for deep vein thrombosis.

PubMed

Enden, T; Resch, S; White, C; Wik, H S; Kløw, N E; Sandset, P M

2013-06-01

Additional treatment with catheter-directed thrombolysis (CDT) has recently been shown to reduce post-thrombotic syndrome (PTS). To estimate the cost effectiveness of additional CDT compared with standard treatment alone. Using a Markov decision model, we compared the two treatment strategies in patients with a high proximal deep vein thrombosis (DVT) and a low risk of bleeding. The model captured the development of PTS, recurrent venous thromboembolism and treatment-related adverse events within a lifetime horizon and the perspective of a third-party payer. Uncertainty was assessed with one-way and probabilistic sensitivity analyzes. Model inputs from the CaVenT study included PTS development, major bleeding from CDT and utilities for post DVT states including PTS. The remaining clinical inputs were obtained from the literature. Costs obtained from the CaVenT study, hospital accounts and the literature are expressed in US dollars ($); effects in quality adjusted life years (QALY). In base case analyzes, additional CDT accumulated 32.31 QALYs compared with 31.68 QALYs after standard treatment alone. Direct medical costs were $64,709 for additional CDT and $51,866 for standard treatment. The incremental cost-effectiveness ratio (ICER) was $20,429/QALY gained. One-way sensitivity analysis showed model sensitivity to the clinical efficacy of both strategies, but the ICER remained < $55,000/QALY over the full range of all parameters. The probability that CDT is cost effective was 82% at a willingness to pay threshold of $50,000/QALY gained. Additional CDT is likely to be a cost-effective alternative to the standard treatment for patients with a high proximal DVT and a low risk of bleeding. © 2013 International Society on Thrombosis and Haemostasis.

Cost-effectiveness of additional catheter-directed thrombolysis for deep vein thrombosis

PubMed Central

ENDEN, T.; RESCH, S.; WHITE, C.; WIK, H. S.; KLØW, N. E.; SANDSET, P. M.

2013-01-01

Summary Background Additional treatment with catheter-directed thrombolysis (CDT) has recently been shown to reduce post-thrombotic syndrome (PTS). Objectives To estimate the cost effectiveness of additional CDT compared with standard treatment alone. Methods Using a Markov decision model, we compared the two treatment strategies in patients with a high proximal deep vein thrombosis (DVT) and a low risk of bleeding. The model captured the development of PTS, recurrent venous thromboembolism and treatment-related adverse events within a lifetime horizon and the perspective of a third-party payer. Uncertainty was assessed with one-way and probabilistic sensitivity analyzes. Model inputs from the CaVenT study included PTS development, major bleeding from CDT and utilities for post DVT states including PTS. The remaining clinical inputs were obtained from the literature. Costs obtained from the CaVenT study, hospital accounts and the literature are expressed in US dollars ($); effects in quality adjusted life years (QALY). Results In base case analyzes, additional CDT accumulated 32.31 QALYs compared with 31.68 QALYs after standard treatment alone. Direct medical costs were $64 709 for additional CDT and $51 866 for standard treatment. The incremental cost-effectiveness ratio (ICER) was $20 429/QALY gained. One-way sensitivity analysis showed model sensitivity to the clinical efficacy of both strategies, but the ICER remained < $55 000/QALY over the full range of all parameters. The probability that CDT is cost effective was 82% at a willingness to pay threshold of $50 000/QALY gained. Conclusions Additional CDT is likely to be a cost-effective alternative to the standard treatment for patients with a high proximal DVT and a low risk of bleeding. PMID:23452204

In-Vivo Assessment of Femoral Bone Strength Using Finite Element Analysis (FEA) Based on Routine MDCT Imaging: A Preliminary Study on Patients with Vertebral Fractures

PubMed Central

Liebl, Hans; Garcia, Eduardo Grande; Holzner, Fabian; Noel, Peter B.; Burgkart, Rainer; Rummeny, Ernst J.; Baum, Thomas; Bauer, Jan S.

2015-01-01

Purpose To experimentally validate a non-linear finite element analysis (FEA) modeling approach assessing in-vitro fracture risk at the proximal femur and to transfer the method to standard in-vivo multi-detector computed tomography (MDCT) data of the hip aiming to predict additional hip fracture risk in subjects with and without osteoporosis associated vertebral fractures using bone mineral density (BMD) measurements as gold standard. Methods One fresh-frozen human femur specimen was mechanically tested and fractured simulating stance and clinically relevant fall loading configurations to the hip. After experimental in-vitro validation, the FEA simulation protocol was transferred to standard contrast-enhanced in-vivo MDCT images to calculate individual hip fracture risk each for 4 subjects with and without a history of osteoporotic vertebral fractures matched by age and gender. In addition, FEA based risk factor calculations were compared to manual femoral BMD measurements of all subjects. Results In-vitro simulations showed good correlation with the experimentally measured strains both in stance (R2 = 0.963) and fall configuration (R2 = 0.976). The simulated maximum stress overestimated the experimental failure load (4743 N) by 14.7% (5440 N) while the simulated maximum strain overestimated by 4.7% (4968 N). The simulated failed elements coincided precisely with the experimentally determined fracture locations. BMD measurements in subjects with a history of osteoporotic vertebral fractures did not differ significantly from subjects without fragility fractures (femoral head: p = 0.989; femoral neck: p = 0.366), but showed higher FEA based risk factors for additional incident hip fractures (p = 0.028). Conclusion FEA simulations were successfully validated by elastic and destructive in-vitro experiments. In the subsequent in-vivo analyses, MDCT based FEA based risk factor differences for additional hip fractures were not mirrored by according BMD measurements. Our data suggests, that MDCT derived FEA models may assess bone strength more accurately than BMD measurements alone, providing a valuable in-vivo fracture risk assessment tool. PMID:25723187

Comparative analysis of bleeding risk by the location and shape of arachnoid cysts: a finite element model analysis.

PubMed

Lee, Chang-Hyun; Han, In Seok; Lee, Ji Yeoun; Phi, Ji Hoon; Kim, Seung-Ki; Kim, Young-Eun; Wang, Kyu-Chang

2017-01-01

Although arachnoid cysts (ACs) are observed in various locations, only sylvian ACs are mainly regarded to be associated with bleeding. The reason for this selective association of sylvian ACs with bleeding is not understood well. This study is to investigate the effect of the location and shape of ACs on the risk of bleeding. A developed finite element model of the head/brain was modified for models of sylvian, suprasellar, and posterior fossa ACs. A spherical AC was placed at each location to compare the effect of AC location. Bowl-shaped and oval-shaped AC models were developed to compare the effect by shape. The shear force on the spot-weld elements (SFSW) was measured between the dura and the outer wall of the ACs or the comparable arachnoid membrane in the normal model. All AC models revealed higher SFSW than comparable normal models. By location, sylvian AC displayed the highest SFSW for frontal and lateral impacts. By shape, small outer wall AC models showed higher SFSW than large wall models in sylvian area and lower SFSW than large ones in posterior fossa. In regression analysis, the presence of AC was the only independent risk of bleeding. The bleeding mechanism of ACs is very complex, and the risk quantification failed to show a significant role of location and shape of ACs. The presence of AC increases shear force on impact condition and may be a risk factor of bleeding, and sylvian location of AC may not have additive risks of AC bleeding.

Quantitative Risk Assessment for African Horse Sickness in Live Horses Exported from South Africa

PubMed Central

Sergeant, Evan S.

2016-01-01

African horse sickness (AHS) is a severe, often fatal, arbovirus infection of horses, transmitted by Culicoides spp. midges. AHS occurs in most of sub-Saharan Africa and is a significant impediment to export of live horses from infected countries, such as South Africa. A stochastic risk model was developed to estimate the probability of exporting an undetected AHS-infected horse through a vector protected pre-export quarantine facility, in accordance with OIE recommendations for trade from an infected country. The model also allows for additional risk management measures, including multiple PCR tests prior to and during pre-export quarantine and optionally during post-arrival quarantine, as well as for comparison of risk associated with exports from a demonstrated low-risk area for AHS and an area where AHS is endemic. If 1 million horses were exported from the low-risk area with no post-arrival quarantine we estimate the median number of infected horses to be 5.4 (95% prediction interval 0.5 to 41). This equates to an annual probability of 0.0016 (95% PI: 0.00015 to 0.012) assuming 300 horses exported per year. An additional PCR test while in vector-protected post-arrival quarantine reduced these probabilities by approximately 12-fold. Probabilities for horses exported from an area where AHS is endemic were approximately 15 to 17 times higher than for horses exported from the low-risk area under comparable scenarios. The probability of undetected AHS infection in horses exported from an infected country can be minimised by appropriate risk management measures. The final choice of risk management measures depends on the level of risk acceptable to the importing country. PMID:26986002

Quantitative Risk Assessment for African Horse Sickness in Live Horses Exported from South Africa.

PubMed

Sergeant, Evan S; Grewar, John D; Weyer, Camilla T; Guthrie, Alan J

2016-01-01

African horse sickness (AHS) is a severe, often fatal, arbovirus infection of horses, transmitted by Culicoides spp. midges. AHS occurs in most of sub-Saharan Africa and is a significant impediment to export of live horses from infected countries, such as South Africa. A stochastic risk model was developed to estimate the probability of exporting an undetected AHS-infected horse through a vector protected pre-export quarantine facility, in accordance with OIE recommendations for trade from an infected country. The model also allows for additional risk management measures, including multiple PCR tests prior to and during pre-export quarantine and optionally during post-arrival quarantine, as well as for comparison of risk associated with exports from a demonstrated low-risk area for AHS and an area where AHS is endemic. If 1 million horses were exported from the low-risk area with no post-arrival quarantine we estimate the median number of infected horses to be 5.4 (95% prediction interval 0.5 to 41). This equates to an annual probability of 0.0016 (95% PI: 0.00015 to 0.012) assuming 300 horses exported per year. An additional PCR test while in vector-protected post-arrival quarantine reduced these probabilities by approximately 12-fold. Probabilities for horses exported from an area where AHS is endemic were approximately 15 to 17 times higher than for horses exported from the low-risk area under comparable scenarios. The probability of undetected AHS infection in horses exported from an infected country can be minimised by appropriate risk management measures. The final choice of risk management measures depends on the level of risk acceptable to the importing country.

Improving prediction of fall risk among nursing home residents using electronic medical records.

PubMed

Marier, Allison; Olsho, Lauren E W; Rhodes, William; Spector, William D

2016-03-01

Falls are physically and financially costly, but may be preventable with targeted intervention. The Minimum Data Set (MDS) is one potential source of information on fall risk factors among nursing home residents, but its limited breadth and relatively infrequent updates may limit its practical utility. Richer, more frequently updated data from electronic medical records (EMRs) may improve ability to identify individuals at highest risk for falls. The authors applied a repeated events survival model to analyze MDS 3.0 and EMR data for 5129 residents in 13 nursing homes within a single large California chain that uses a centralized EMR system from a leading vendor. Estimated regression parameters were used to project resident fall probability. The authors examined the proportion of observed falls within each projected fall risk decile to assess improvements in predictive power from including EMR data. In a model incorporating fall risk factors from the MDS only, 28.6% of observed falls occurred among residents in the highest projected risk decile. In an alternative specification incorporating more frequently updated measures for the same risk factors from the EMR data, 32.3% of observed falls occurred among residents in the highest projected risk decile, a 13% increase over the base MDS-only specification. Incorporating EMR data improves ability to identify those at highest risk for falls relative to prediction using MDS data alone. These improvements stem chiefly from the greater frequency with which EMR data are updated, with minimal additional gains from availability of additional risk factor variables. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Dynamical modeling approach to risk assessment for radiogenic leukemia among astronauts engaged in interplanetary space missions.

PubMed

Smirnova, Olga A; Cucinotta, Francis A

2018-02-01

A recently developed biologically motivated dynamical model of the assessment of the excess relative risk (ERR) for radiogenic leukemia among acutely/continuously irradiated humans (Smirnova, 2015, 2017) is applied to estimate the ERR for radiogenic leukemia among astronauts engaged in long-term interplanetary space missions. Numerous scenarios of space radiation exposure during space missions are used in the modeling studies. The dependence of the ERR for leukemia among astronauts on several mission parameters including the dose equivalent rates of galactic cosmic rays (GCR) and large solar particle events (SPEs), the number of large SPEs, the time interval between SPEs, mission duration, the degree of astronaut's additional shielding during SPEs, the degree of their additional 12-hour's daily shielding, as well as the total mission dose equivalent, is examined. The results of the estimation of ERR for radiogenic leukemia among astronauts, which are obtained in the framework of the developed dynamical model for various scenarios of space radiation exposure, are compared with the corresponding results, computed by the commonly used linear model. It is revealed that the developed dynamical model along with the linear model can be applied to estimate ERR for radiogenic leukemia among astronauts engaged in long-term interplanetary space missions in the range of applicability of the latter. In turn, the developed dynamical model is capable of predicting the ERR for leukemia among astronauts for the irradiation regimes beyond the applicability range of the linear model in emergency cases. As a supplement to the estimations of cancer incidence and death (REIC and REID) (Cucinotta et al., 2013, 2017), the developed dynamical model for the assessment of the ERR for leukemia can be employed on the pre-mission design phase for, e.g., the optimization of the regimes of astronaut's additional shielding in the course of interplanetary space missions. The developed model can also be used on the phase of the real-time responses during the space mission to make the decisions on the operational application of appropriate countermeasures to minimize the risks of occurrences of leukemia, especially, for emergency cases. Copyright © 2017 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.

Predictors of incident heart failure in patients after an acute coronary syndrome: The LIPID heart failure risk-prediction model.

PubMed

Driscoll, Andrea; Barnes, Elizabeth H; Blankenberg, Stefan; Colquhoun, David M; Hunt, David; Nestel, Paul J; Stewart, Ralph A; West, Malcolm J; White, Harvey D; Simes, John; Tonkin, Andrew

2017-12-01

Coronary heart disease is a major cause of heart failure. Availability of risk-prediction models that include both clinical parameters and biomarkers is limited. We aimed to develop such a model for prediction of incident heart failure. A multivariable risk-factor model was developed for prediction of first occurrence of heart failure death or hospitalization. A simplified risk score was derived that enabled subjects to be grouped into categories of 5-year risk varying from <5% to >20%. Among 7101 patients from the LIPID study (84% male), with median age 61years (interquartile range 55-67years), 558 (8%) died or were hospitalized because of heart failure. Older age, history of claudication or diabetes mellitus, body mass index>30kg/m 2 , LDL-cholesterol >2.5mmol/L, heart rate>70 beats/min, white blood cell count, and the nature of the qualifying acute coronary syndrome (myocardial infarction or unstable angina) were associated with an increase in heart failure events. Coronary revascularization was associated with a lower event rate. Incident heart failure increased with higher concentrations of B-type natriuretic peptide >50ng/L, cystatin C>0.93nmol/L, D-dimer >273nmol/L, high-sensitivity C-reactive protein >4.8nmol/L, and sensitive troponin I>0.018μg/L. Addition of biomarkers to the clinical risk model improved the model's C statistic from 0.73 to 0.77. The net reclassification improvement incorporating biomarkers into the clinical model using categories of 5-year risk was 23%. Adding a multibiomarker panel to conventional parameters markedly improved discrimination and risk classification for future heart failure events. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

From pest data to abundance-based risk maps combining eco-physiological knowledge, weather, and habitat variability.

PubMed

Lacasella, Federica; Marta, Silvio; Singh, Aditya; Stack Whitney, Kaitlin; Hamilton, Krista; Townsend, Phil; Kucharik, Christopher J; Meehan, Timothy D; Gratton, Claudio

2017-03-01

Noxious species, i.e., crop pest or invasive alien species, are major threats to both natural and managed ecosystems. Invasive pests are of special importance, and knowledge about their distribution and abundance is fundamental to minimize economic losses and prioritize management activities. Occurrence models are a common tool used to identify suitable zones and map priority areas (i.e., risk maps) for noxious species management, although they provide a simplified description of species dynamics (i.e., no indication on species density). An alternative is to use abundance models, but translating abundance data into risk maps is often challenging. Here, we describe a general framework for generating abundance-based risk maps using multi-year pest data. We used an extensive data set of 3968 records collected between 2003 and 2013 in Wisconsin during annual surveys of soybean aphid (SBA), an exotic invasive pest in this region. By using an integrative approach, we modelled SBA responses to weather, seasonal, and habitat variability using generalized additive models (GAMs). Our models showed good to excellent performance in predicting SBA occurrence and abundance (TSS = 0.70, AUC = 0.92; R 2  = 0.63). We found that temperature, precipitation, and growing degree days were the main drivers of SBA trends. In addition, a significant positive relationship between SBA abundance and the availability of overwintering habitats was observed. Our models showed aphid populations were also sensitive to thresholds associated with high and low temperatures, likely related to physiological tolerances of the insects. Finally, the resulting aphid predictions were integrated using a spatial prioritization algorithm ("Zonation") to produce an abundance-based risk map for the state of Wisconsin that emphasized the spatiotemporal consistency and magnitude of past infestation patterns. This abundance-based risk map can provide information on potential foci of pest outbreaks where scouting efforts and prophylactic measures should be concentrated. The approach we took is general, relatively simple, and can be applied to other species, habitats and geographical areas for which species abundance data and biotic and abiotic data are available. © 2016 by the Ecological Society of America.

Animal models of polycystic ovary syndrome: a focused review of rodent models in relationship to clinical phenotypes and cardiometabolic risk.

PubMed

Shi, Danni; Vine, Donna F

2012-07-01

To review rodent animal models of polycystic ovary syndrome (PCOS), with a focus on those associated with the metabolic syndrome and cardiovascular disease risk factors. Review. Rodent models of PCOS. Description and comparison of animal models. Comparison of animal models to clinical phenotypes of PCOS. Animals used to study PCOS include rodents, mice, rhesus monkeys, and ewes. Major methods to induce PCOS in these models include subcutaneous injection or implantation of androgens, estrogens, antiprogesterone, letrozole, prenatal exposure to excess androgens, and exposure to constant light. In addition, transgenic mice models and spontaneous PCOS-like rodent models have also been developed. Rodents are the most economical and widely used animals to study PCOS and ovarian dysfunction. The model chosen to study the development of PCOS and other metabolic parameters remains dependent on the specific etiologic hypotheses being investigated. Rodent models have been shown to demonstrate changes in insulin metabolism, with or without induction of hyperandrogenemia, and limited studies have investigated cardiometabolic risk factors for type 2 diabetes and cardiovascular disease. Given the clinical heterogeneity of PCOS, the utilization of different animal models may be the best approach to further our understanding of the pathophysiologic mechanisms associated with the early etiology of PCOS and cardiometabolic risk. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Surrogate modeling of joint flood risk across coastal watersheds

NASA Astrophysics Data System (ADS)

Bass, Benjamin; Bedient, Philip

2018-03-01

This study discusses the development and performance of a rapid prediction system capable of representing the joint rainfall-runoff and storm surge flood response of tropical cyclones (TCs) for probabilistic risk analysis. Due to the computational demand required for accurately representing storm surge with the high-fidelity ADvanced CIRCulation (ADCIRC) hydrodynamic model and its coupling with additional numerical models to represent rainfall-runoff, a surrogate or statistical model was trained to represent the relationship between hurricane wind- and pressure-field characteristics and their peak joint flood response typically determined from physics based numerical models. This builds upon past studies that have only evaluated surrogate models for predicting peak surge, and provides the first system capable of probabilistically representing joint flood levels from TCs. The utility of this joint flood prediction system is then demonstrated by improving upon probabilistic TC flood risk products, which currently account for storm surge but do not take into account TC associated rainfall-runoff. Results demonstrate the source apportionment of rainfall-runoff versus storm surge and highlight that slight increases in flood risk levels may occur due to the interaction between rainfall-runoff and storm surge as compared to the Federal Emergency Management Association's (FEMAs) current practices.

Probabilistic pharmacokinetic models of decompression sickness in humans, part 1: Coupled perfusion-limited compartments.

PubMed

Murphy, F Gregory; Hada, Ethan A; Doolette, David J; Howle, Laurens E

2017-07-01

Decompression sickness (DCS) is a disease caused by gas bubbles forming in body tissues following a reduction in ambient pressure, such as occurs in scuba diving. Probabilistic models for quantifying the risk of DCS are typically composed of a collection of independent, perfusion-limited theoretical tissue compartments which describe gas content or bubble volume within these compartments. It has been previously shown that 'pharmacokinetic' gas content models, with compartments coupled in series, show promise as predictors of the incidence of DCS. The mechanism of coupling can be through perfusion or diffusion. This work examines the application of five novel pharmacokinetic structures with compartments coupled by perfusion to the prediction of the probability and time of onset of DCS in humans. We optimize these models against a training set of human dive trial data consisting of 4335 exposures with 223 DCS cases. Further, we examine the extrapolation quality of the models on an additional set of human dive trial data consisting of 3140 exposures with 147 DCS cases. We find that pharmacokinetic models describe the incidence of DCS for single air bounce dives better than a single-compartment, perfusion-limited model. We further find the U.S. Navy LEM-NMRI98 is a better predictor of DCS risk for the entire training set than any of our pharmacokinetic models. However, one of the pharmacokinetic models we consider, the CS2T3 model, is a better predictor of DCS risk for single air bounce dives and oxygen decompression dives. Additionally, we find that LEM-NMRI98 outperforms CS2T3 on the extrapolation data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimizing spacecraft design - optimization engine development : progress and plans

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Feather, Martin S.; Dunphy, Julia R; Salcedo, Jose; Menzies, Tim

2003-01-01

At JPL and NASA, a process has been developed to perform life cycle risk management. This process requires users to identify: goals and objectives to be achieved (and their relative priorities), the various risks to achieving those goals and objectives, and options for risk mitigation (prevention, detection ahead of time, and alleviation). Risks are broadly defined to include the risk of failing to design a system with adequate performance, compatibility and robustness in addition to more traditional implementation and operational risks. The options for mitigating these different kinds of risks can include architectural and design choices, technology plans and technology back-up options, test-bed and simulation options, engineering models and hardware/software development techniques and other more traditional risk reduction techniques.

Therapies for treatment of osteoporosis in US women: cost-effectiveness and budget impact considerations.

PubMed

Tosteson, Anna N A; Burge, Russel T; Marshall, Deborah A; Lindsay, Robert

2008-09-01

To evaluate the cost-effectiveness of osteoporosis treatments for women at high fracture risk and estimate the population-level impact of providing bisphosphonate therapy to all eligible high-risk US women. Fractures, healthcare costs, and quality-adjusted life-years (QALYs) were estimated over 10 years using a Markov model. No therapy, risedronate, alendronate, ibandronate, and teriperatide (PTH) were compared among 4 risk groups. Sensitivity analyses examined the robustness of model results for 65-year-old women with low bone density and previous vertebral fracture. Women treated with a bisphosphonate experienced fewer fractures and more QALYs compared with no therapy or PTH. Total costs were lowest for the untreated cohort, followed by risedronate, alendronate, ibandronate, and PTH in all risk groups except women aged 75 years with previous fracture. The incremental cost-effectiveness of risedronate compared with no therapy ranged from cost saving for the base case to $66,722 per QALY for women aged 65 years with no previous fracture. Ibandronate and PTH were dominated in all risk groups. (A dominated treatment has a higher cost and poorer outcome.) Treating all eligible women with a bisphosphonate would cost an estimated additional $5563 million (21% total increase) and would result in 390,049 fewer fractures (35% decrease). In the highest risk group, the additional cost of therapy was offset by other healthcare cost savings. Osteoporosis treatment of high-risk women is cost-effective, with bisphosphonates providing the most benefit at lowest cost. For highest risk women, costs are offset by savings from fracture prevention.

Predicting herbicide mixture effects on multiple algal species using mixture toxicity models.

PubMed

Nagai, Takashi

2017-10-01

The validity of the application of mixture toxicity models, concentration addition and independent action, to a species sensitivity distribution (SSD) for calculation of a multisubstance potentially affected fraction was examined in laboratory experiments. Toxicity assays of herbicide mixtures using 5 species of periphytic algae were conducted. Two mixture experiments were designed: a mixture of 5 herbicides with similar modes of action and a mixture of 5 herbicides with dissimilar modes of action, corresponding to the assumptions of the concentration addition and independent action models, respectively. Experimentally obtained mixture effects on 5 algal species were converted to the fraction of affected (>50% effect on growth rate) species. The predictive ability of the concentration addition and independent action models with direct application to SSD depended on the mode of action of chemicals. That is, prediction was better for the concentration addition model than the independent action model for the mixture of herbicides with similar modes of action. In contrast, prediction was better for the independent action model than the concentration addition model for the mixture of herbicides with dissimilar modes of action. Thus, the concentration addition and independent action models could be applied to SSD in the same manner as for a single-species effect. The present study to validate the application of the concentration addition and independent action models to SSD supports the usefulness of the multisubstance potentially affected fraction as the index of ecological risk. Environ Toxicol Chem 2017;36:2624-2630. © 2017 SETAC. © 2017 SETAC.

Spatial Distribution of the Risk of Dengue and the Entomological Indicators in Sumaré, State of São Paulo, Brazil

PubMed Central

Barbosa, Gerson Laurindo; Donalísio, Maria Rita; Stephan, Celso; Lourenço, Roberto Wagner; Andrade, Valmir Roberto; Arduino, Marylene de Brito; de Lima, Virgilia Luna Castor

2014-01-01

Dengue fever is a major public health problem worldwide, caused by any of four virus (DENV-1, DENV-2, DENV-3 and DENV-4; Flaviviridae: Flavivirus), transmitted by Aedes aegypti mosquito. Reducing the levels of infestation by A. aegypti is one of the few current strategies to control dengue fever. Entomological indicators are used by dengue national control program to measure the infestation of A. aegypti, but little is known about predictive power of these indicators to measure dengue risk. In this spatial case-control study, we analyzed the spatial distribution of the risk of dengue and the influence of entomological indicators of A. aegypti in its egg, larva-pupa and adult stages occurring in a mid-size city in the state of São Paulo. The dengue cases were those confirmed by the city's epidemiological surveillance system and the controls were obtained through random selection of points within the perimeter of the inhabited area. The values of the entomological indicators were extrapolated for the entire study area through the geostatistical ordinary kriging technique. For each case and control, the respective indicator values were obtained, according with its geographical coordinates and analyzed by using a generalized additive model. Dengue incidence demonstrated a seasonal behavior, as well as the entomological indicators of all mosquito's evolutionary stages. The infestation did not present a significant variation in intensity and was not a limiting or determining factor of the occurrence of cases in the municipality. The risk maps of the disease from crude and adjusted generalized additive models did not present differences, suggesting that areas with the highest values of entomological indicators were not associated with the incidence of dengue. The inclusion of other variables in the generalized additive models may reveal the modulatory effect for the risk of the disease, which is not found in this study. PMID:24831806

Spatial distribution of the risk of dengue and the entomological indicators in Sumaré, state of São Paulo, Brazil.

PubMed

Barbosa, Gerson Laurindo; Donalísio, Maria Rita; Stephan, Celso; Lourenço, Roberto Wagner; Andrade, Valmir Roberto; Arduino, Marylene de Brito; de Lima, Virgilia Luna Castor

2014-05-01

Dengue fever is a major public health problem worldwide, caused by any of four virus (DENV-1, DENV-2, DENV-3 and DENV-4; Flaviviridae: Flavivirus), transmitted by Aedes aegypti mosquito. Reducing the levels of infestation by A. aegypti is one of the few current strategies to control dengue fever. Entomological indicators are used by dengue national control program to measure the infestation of A. aegypti, but little is known about predictive power of these indicators to measure dengue risk. In this spatial case-control study, we analyzed the spatial distribution of the risk of dengue and the influence of entomological indicators of A. aegypti in its egg, larva-pupa and adult stages occurring in a mid-size city in the state of São Paulo. The dengue cases were those confirmed by the city's epidemiological surveillance system and the controls were obtained through random selection of points within the perimeter of the inhabited area. The values of the entomological indicators were extrapolated for the entire study area through the geostatistical ordinary kriging technique. For each case and control, the respective indicator values were obtained, according with its geographical coordinates and analyzed by using a generalized additive model. Dengue incidence demonstrated a seasonal behavior, as well as the entomological indicators of all mosquito's evolutionary stages. The infestation did not present a significant variation in intensity and was not a limiting or determining factor of the occurrence of cases in the municipality. The risk maps of the disease from crude and adjusted generalized additive models did not present differences, suggesting that areas with the highest values of entomological indicators were not associated with the incidence of dengue. The inclusion of other variables in the generalized additive models may reveal the modulatory effect for the risk of the disease, which is not found in this study.

Double jeopardy: interaction effects of marital and poverty status on the risk of mortality.

PubMed

Smith, K R; Waitzman, N J

1994-08-01

The purpose of this paper is to examine the hypothesis that marital and poverty status interact in their effects on mortality risks beyond their main effects. This study examines the epidemiological bases for applying an additive rather than a multiplicative specification when testing for interaction between two discrete risk factors. We specifically predict that risks associated with being nonmarried and with being poor interact to produce mortality risks that are greater than each risk acting independently. The analysis is based on men and women who were ages 25-74 during the 1971-1975 National Health and Nutrition Examination Survey I (NHANES I) and who were traced successfully in the NHANES I Epidemiologic Follow-Up Study in 1982-1984. Overall, being both poor and nonmarried places nonelderly (ages 25-64) men, but not women, at risk of mortality greater than that expected from the main effects. This study shows that for all-cause mortality, marital and poverty status interact for men but less so for women; these findings exist when interaction is assessed with either a multiplicative or an additive standard. This difference is most pronounced for poor, widowed men and (to a lesser degree) poor, divorced men. For violent/accidental deaths among men, the interaction effects are large on the basis of an additive model. Weak main and interaction effects were detected for the elderly (age 65+).

Utility of genetic and non-genetic risk factors in predicting coronary heart disease in Singaporean Chinese.

PubMed

Chang, Xuling; Salim, Agus; Dorajoo, Rajkumar; Han, Yi; Khor, Chiea-Chuen; van Dam, Rob M; Yuan, Jian-Min; Koh, Woon-Puay; Liu, Jianjun; Goh, Daniel Yt; Wang, Xu; Teo, Yik-Ying; Friedlander, Yechiel; Heng, Chew-Kiat

2017-01-01

Background Although numerous phenotype based equations for predicting risk of 'hard' coronary heart disease are available, data on the utility of genetic information for such risk prediction is lacking in Chinese populations. Design Case-control study nested within the Singapore Chinese Health Study. Methods A total of 1306 subjects comprising 836 men (267 incident cases and 569 controls) and 470 women (128 incident cases and 342 controls) were included. A Genetic Risk Score comprising 156 single nucleotide polymorphisms that have been robustly associated with coronary heart disease or its risk factors ( p < 5 × 10 -8 ) in at least two independent cohorts of genome-wide association studies was built. For each gender, three base models were used: recalibrated Adult Treatment Panel III (ATPIII) Model (M 1 ); ATP III model fitted using Singapore Chinese Health Study data (M 2 ) and M 3 : M 2 + C-reactive protein + creatinine. Results The Genetic Risk Score was significantly associated with incident 'hard' coronary heart disease ( p for men: 1.70 × 10 -10 -1.73 × 10 -9 ; p for women: 0.001). The inclusion of the Genetic Risk Score in the prediction models improved discrimination in both genders (c-statistics: 0.706-0.722 vs. 0.663-0.695 from base models for men; 0.788-0.790 vs. 0.765-0.773 for women). In addition, the inclusion of the Genetic Risk Score also improved risk classification with a net gain of cases being reclassified to higher risk categories (men: 12.4%-16.5%; women: 10.2% (M 3 )), while not significantly reducing the classification accuracy in controls. Conclusions The Genetic Risk Score is an independent predictor for incident 'hard' coronary heart disease in our ethnic Chinese population. Inclusion of genetic factors into coronary heart disease prediction models could significantly improve risk prediction performance.

Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture

NASA Astrophysics Data System (ADS)

Kim, K. H.; Lee, S.; Han, E.; Ines, A. V. M.

2017-12-01

Climate-Agriculture-Modeling and Decision Tool (CAMDT) is a decision support system (DSS) tool that aims to facilitate translations of probabilistic seasonal climate forecasts (SCF) to crop responses such as yield and water stress. Since CAMDT is a software framework connecting different models and algorithms with SCF information, it can be easily customized for different types of agriculture models. In this study, we replaced the DSSAT-CSM-Rice model originally incorporated in CAMDT with a generic epidemiological model, EPIRICE, to generate a seasonal pest outlook. The resulting CAMDT-Disease generates potential risks for selected fungal, viral, and bacterial diseases of rice over the next months by translating SCFs into agriculturally-relevant risk information. The integrated modeling procedure of CAMDT-Disease first disaggregates a given SCF using temporal downscaling methods (predictWTD or FResampler1), runs EPIRICE with the downscaled weather inputs, and finally visualizes the EPIRICE outputs as disease risk compared to that of the previous year and the 30-year-climatological average. In addition, the easy-to-use graphical user interface adopted from CAMDT allows users to simulate "what-if" scenarios of disease risks over different planting dates with given SCFs. Our future work includes the simulation of the effect of crop disease on yields through the disease simulation models with the DSSAT-CSM-Rice model, as disease remains one of the most critical yield-reducing factors in the field.

Interaction between nonsynonymous polymorphisms in PLA2G7 gene and smoking on the risk of coronary heart disease in a Chinese population.

PubMed

Chi, Yunpeng; Shi, Conghong; Zhang, Xiaojiang; Xi, Yang

2018-05-04

To investigate the impact of PLA2G7 polymorphism, and additional their interactions with smoking and drinking on coronary heart disease (CHD) risk based on Chinese population. GMDR model was used to screen the best gene-smoking and gene-drinking interaction combinations. Logistic regression was performed to investigate association between 4 SNPs and CHD, and the interaction effect between rs1805017 and smoking. For CHD patient-control haplotype analyses, the SHEsis online haplotype analysis software ( http://analysis.bio-x.cn/myAnalysis.php ) was employed. CHD risks were higher in carriers of homozygous mutant of rs1805017 and rs1805018 than those with wild-type homozygotes, OR (95% CI) were 1.45 (1.16-1.92) and 1.51 (1.23-1.97), respectively, but the other two SNPs, rs16874954 and rs1051931 were not significant associated with CHD risks. GMDR analysis indicated that there was a significant two-locus model (p = 0.0107) involving rs1805017 and smoking, indicating a potential gene-environment interaction between rs1805017 and smoking. But we did not found any gene-drinking and gene-gene interaction combinations in GMDR models. The haplotype R-I was observed most frequently in two groups, with 47.43 and 54.38% in the case and control group of the population, respectively. The results also indicated that the haplotype containing the rs1805017-H and rs1805018-T alleles were associated with a statistically increased CHD risk, OR (95% CI) 1.43 (1.10-1.86), p = 0.0021. Polymorphisms in rs1805017 and rs1805018, additional interaction between rs1805017 and smoking, and haplotype containing the rs1805017-H and rs1805018-T alleles were associated with increased CHD risk.

State transition model: vorapaxar added to standard antiplatelet therapy to prevent thrombosis post myocardial infarction or peripheral artery disease.

PubMed

Du, Mark; Chase, Monica; Oguz, Mustafa; Davies, Glenn

2017-09-01

To evaluate long-term health benefits and risks of adding vorapaxar (VOR) to the standard care antiplatelet therapy (SC) of aspirin and/or clopidogrel, among a population with a recent myocardial infarction (MI) and/or peripheral artery disease (PAD). In a state-transition model, patients transition between health states (event-free, recurrent MI, stroke, death), while at risk of experiencing non-transition-related revascularization and non-fatal bleeding events. Risk equations developed from the TRA 2°P-TIMI 50 trial's patient-level data were used to predict cardiovascular (CV) outcomes over longer time horizons. Additional sources, including trials and US-based observational studies, informed the inputs for short-term CV risk, non-CV death, and health-related quality of life. Survival and quality-adjusted life-years (QALYs) were estimated over a lifetime horizon, discounted at 3% per year. Within a cohort of 7361 patients with recent MI and/or PAD, VOR + SC relative to SC alone yielded 176 fewer CV events (MIs, strokes, or CV deaths), but 27 more major bleeding events. VOR + SC was associated with increased life expectancy and health benefits (19.93 undiscounted life-years [LYs], 9.57 discounted QALYs vs. 19.61 undiscounted LYs, 9.41 discounted QALYs). The results were most sensitive to scenarios varying time of vorapaxar initiation, and the assumptions in the 90 day period post-MI. Additional analyses showed that add-on vorapaxar provides consistent incremental benefits in high-risk subgroups. This study contributes to the growing literature on secondary prevention add-on therapy, as results from these modeling analyses suggest that adding vorapaxar to SC for patients at high atherothrombotic risk can provide long-term health benefits.

High-risk sexual activity in the House and Ball community: influence of social networks.

PubMed

Schrager, Sheree M; Latkin, Carl A; Weiss, George; Kubicek, Katrina; Kipke, Michele D

2014-02-01

We investigated the roles of House membership and the influence of social and sexual network members on the sexual risk behavior of men in the Los Angeles House and Ball community. From February 2009 to January 2010, male participants (n = 233) completed interviewer-assisted surveys during a House meeting or Ball event. We used logistic regression to model the effects of sexual network size, influence of sexual network members, House membership status, and their interactions on high-risk sex. Significant predictors of high-risk sex included number of sexual partners in the nominated social network, multiethnicity, and previous diagnosis of sexually transmitted infection. House membership was protective against high-risk sex. Additionally, a 3-way interaction emerged between number of sexual partners in the network, influence, and network members' House membership. Future research should assess network members' attitudes and behavior in detail to provide a greater understanding of the dynamics of social influence and to identify additional avenues for intervention.

Measurement of ECG abnormalities and cardiovascular risk classification: a cohort study of primary care patients in the Netherlands

PubMed Central

Groot, Anne; Bots, Michiel L; Rutten, Frans H; den Ruijter, Hester M; Numans, Mattijs E; Vaartjes, Ilonca

2015-01-01

Background GPs need accurate tools for cardiovascular (CV) risk assessment. Abnormalities in resting electrocardiograms (ECGs) relate to increased CV risk. Aim To determine whether measurement of ECG abnormalities on top of established risk estimation (SCORE) improves CV risk classification in a primary care population. Design and setting A cohort study of patients enlisted with academic general practices in the Netherlands (the Utrecht Health Project [UHP]). Method Incident CV events were extracted from the GP records. MEANS algorithm was used to assess ECG abnormalities. Cox proportional hazards modelling was applied to relate ECG abnormalities to CV events. For a prediction model only with SCORE variables, and a model with SCORE+ECG abnormalities, the discriminative value (area under the receiver operator curve [AUC]) and the net reclassification improvement (NRI) were estimated. Results A total of 2370 participants aged 38–74 years were included, all eligible for CV risk assessment. During a mean follow-up of 7.8 years, 172 CV events occurred. In 19% of the participants at least one ECG abnormality was found (Lausanne criteria). Presence of atrial fibrillation/flutter (AF) and myocardial infarction (MI) were significantly related to CV events. The AUC of the SCORE risk factors was 0.75 (95% CI = 0.71 to 0.79). Addition of MI or AF resulted in an AUC of 0.76 (95% CI = 0.72 to 0.79) and 0.75 (95% CI = 0.72 to 0.79), respectively. The NRI with the addition of ECG abnormalities was small (MI 1.0%; 95% CI = −3.2% to 6.9%; AF 0.5%; 95% CI = −3.5% to 3.3%). Conclusion Performing a resting ECG in a primary care population does not seem to improve risk classification when SCORE information — age, sex, smoking, systolic blood pressure, and total cholesterol/HDL ratio — is already available. PMID:25548311

Measurement of ECG abnormalities and cardiovascular risk classification: a cohort study of primary care patients in the Netherlands.

PubMed

Groot, Anne; Bots, Michiel L; Rutten, Frans H; den Ruijter, Hester M; Numans, Mattijs E; Vaartjes, Ilonca

2015-01-01

GPs need accurate tools for cardiovascular (CV) risk assessment. Abnormalities in resting electrocardiograms (ECGs) relate to increased CV risk. To determine whether measurement of ECG abnormalities on top of established risk estimation (SCORE) improves CV risk classification in a primary care population. A cohort study of patients enlisted with academic general practices in the Netherlands (the Utrecht Health Project [UHP]). Incident CV events were extracted from the GP records. MEANS algorithm was used to assess ECG abnormalities. Cox proportional hazards modelling was applied to relate ECG abnormalities to CV events. For a prediction model only with SCORE variables, and a model with SCORE+ECG abnormalities, the discriminative value (area under the receiver operator curve [AUC]) and the net reclassification improvement (NRI) were estimated. A total of 2370 participants aged 38-74 years were included, all eligible for CV risk assessment. During a mean follow-up of 7.8 years, 172 CV events occurred. In 19% of the participants at least one ECG abnormality was found (Lausanne criteria). Presence of atrial fibrillation/flutter (AF) and myocardial infarction (MI) were significantly related to CV events. The AUC of the SCORE risk factors was 0.75 (95% CI = 0.71 to 0.79). Addition of MI or AF resulted in an AUC of 0.76 (95% CI = 0.72 to 0.79) and 0.75 (95% CI = 0.72 to 0.79), respectively. The NRI with the addition of ECG abnormalities was small (MI 1.0%; 95% CI = -3.2% to 6.9%; AF 0.5%; 95% CI = -3.5% to 3.3%). Performing a resting ECG in a primary care population does not seem to improve risk classification when SCORE information - age, sex, smoking, systolic blood pressure, and total cholesterol/HDL ratio - is already available. © British Journal of General Practice 2015.

Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study.

PubMed

Hippisley-Cox, Julia; Coupland, Carol

2017-11-20

Objectives  To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 year risk of type 2 diabetes in men and women, taking account of potential new risk factors, and to compare their performance with current approaches. Design  Prospective open cohort study. Setting  Routinely collected data from 1457 general practices in England contributing to the QResearch database: 1094 were used to develop the scores and a separate set of 363 were used to validate the scores. Participants  11.5 million people aged 25-84 and free of diabetes at baseline: 8.87 million in the derivation cohort and 2.63 million in the validation cohort. Methods  Cox proportional hazards models were used in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QDiabetes (age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids) and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, gestational diabetes, and polycystic ovary syndrome. Additional models included fasting blood glucose and glycated haemoglobin (HBA1c). Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status. Main outcome measure  Incident type 2 diabetes recorded on the general practice record. Results  In the derivation cohort, 178 314 incident cases of type 2 diabetes were identified during follow-up arising from 42.72 million person years of observation. In the validation cohort, 62 326 incident cases of type 2 diabetes were identified from 14.32 million person years of observation. All new risk factors considered met our model inclusion criteria. Model A included age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids, and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, and gestational diabetes and polycystic ovary syndrome in women. Model B included the same variables as model A plus fasting blood glucose. Model C included HBA1c instead of fasting blood glucose. All three models had good calibration and high levels of explained variation and discrimination. In women, model B explained 63.3% of the variation in time to diagnosis of type 2 diabetes (R 2 ), the D statistic was 2.69 and the Harrell's C statistic value was 0.89. The corresponding values for men were 58.4%, 2.42, and 0.87. Model B also had the highest sensitivity compared with current recommended practice in the National Health Service based on bands of either fasting blood glucose or HBA1c. However, only 16% of patients had complete data for blood glucose measurements, smoking, and body mass index. Conclusions  Three updated QDiabetes risk models to quantify the absolute risk of type 2 diabetes were developed and validated: model A does not require a blood test and can be used to identify patients for fasting blood glucose (model B) or HBA1c (model C) testing. Model B had the best performance for predicting 10 year risk of type 2 diabetes to identify those who need interventions and more intensive follow-up, improving on current approaches. Additional external validation of models B and C in datasets with more completely collected data on blood glucose would be valuable before the models are used in clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

The Pittsburgh Cervical Cancer Screening Model: a risk assessment tool.

PubMed

Austin, R Marshall; Onisko, Agnieszka; Druzdzel, Marek J

2010-05-01

Evaluation of cervical cancer screening has grown increasingly complex with the introduction of human papillomavirus (HPV) vaccination and newer screening technologies approved by the US Food and Drug Administration. To create a unique Pittsburgh Cervical Cancer Screening Model (PCCSM) that quantifies risk for histopathologic cervical precancer (cervical intraepithelial neoplasia [CIN] 2, CIN3, and adenocarcinoma in situ) and cervical cancer in an environment predominantly using newer screening technologies. The PCCSM is a dynamic Bayesian network consisting of 19 variables available in the laboratory information system, including patient history data (most recent HPV vaccination data), Papanicolaou test results, high-risk HPV results, procedure data, and histopathologic results. The model's graphic structure was based on the published literature. Results from 375 441 patient records from 2005 through 2008 were used to build and train the model. Additional data from 45 930 patients were used to test the model. The PCCSM compares risk quantitatively over time for histopathologically verifiable CIN2, CIN3, adenocarcinoma in situ, and cervical cancer in screened patients for each current cytology result category and for each HPV result. For each current cytology result, HPV test results affect risk; however, the degree of cytologic abnormality remains the largest positive predictor of risk. Prior history also alters the CIN2, CIN3, adenocarcinoma in situ, and cervical cancer risk for patients with common current cytology and HPV test results. The PCCSM can also generate negative risk projections, estimating the likelihood of the absence of histopathologic CIN2, CIN3, adenocarcinoma in situ, and cervical cancer in screened patients. The PCCSM is a dynamic Bayesian network that computes quantitative cervical disease risk estimates for patients undergoing cervical screening. Continuously updatable with current system data, the PCCSM provides a new tool to monitor cervical disease risk in the evolving postvaccination era.

Validation of a new mortality risk prediction model for people 65 years and older in northwest Russia: The Crystal risk score.

PubMed

Turusheva, Anna; Frolova, Elena; Bert, Vaes; Hegendoerfer, Eralda; Degryse, Jean-Marie

2017-07-01

Prediction models help to make decisions about further management in clinical practice. This study aims to develop a mortality risk score based on previously identified risk predictors and to perform internal and external validations. In a population-based prospective cohort study of 611 community-dwelling individuals aged 65+ in St. Petersburg (Russia), all-cause mortality risks over 2.5 years follow-up were determined based on the results obtained from anthropometry, medical history, physical performance tests, spirometry and laboratory tests. C-statistic, risk reclassification analysis, integrated discrimination improvement analysis, decision curves analysis, internal validation and external validation were performed. Older adults were at higher risk for mortality [HR (95%CI)=4.54 (3.73-5.52)] when two or more of the following components were present: poor physical performance, low muscle mass, poor lung function, and anemia. If anemia was combined with high C-reactive protein (CRP) and high B-type natriuretic peptide (BNP) was added the HR (95%CI) was slightly higher (5.81 (4.73-7.14)) even after adjusting for age, sex and comorbidities. Our models were validated in an external population of adults 80+. The extended model had a better predictive capacity for cardiovascular mortality [HR (95%CI)=5.05 (2.23-11.44)] compared to the baseline model [HR (95%CI)=2.17 (1.18-4.00)] in the external population. We developed and validated a new risk prediction score that may be used to identify older adults at higher risk for mortality in Russia. Additional studies need to determine which targeted interventions improve the outcomes of these at-risk individuals. Copyright © 2017 Elsevier B.V. All rights reserved.

Development and Validation of Osteoporosis Risk-Assessment Model for Korean Men

PubMed Central

Oh, Sun Min; Song, Bo Mi; Nam, Byung-Ho; Rhee, Yumie; Moon, Seong-Hwan; Kim, Deog Young; Kang, Dae Ryong

2016-01-01

Purpose The aim of the present study was to develop an osteoporosis risk-assessment model to identify high-risk individuals among Korean men. Materials and Methods The study used data from 1340 and 1110 men ≥50 years who participated in the 2009 and 2010 Korean National Health and Nutrition Examination Survey, respectively, for development and validation of an osteoporosis risk-assessment model. Osteoporosis was defined as T score ≤-2.5 at either the femoral neck or lumbar spine. Performance of the candidate models and the Osteoporosis Self-assessment Tool for Asian (OSTA) was compared with sensitivity, specificity, and area under the receiver operating characteristics curve (AUC). A net reclassification improvement was further calculated to compare the developed Korean Osteoporosis Risk-Assessment Model for Men (KORAM-M) with OSTA. Results In the development dataset, the prevalence of osteoporosis was 8.1%. KORAM-M, consisting of age and body weight, had a sensitivity of 90.8%, a specificity of 42.4%, and an AUC of 0.666 with a cut-off score of -9. In the validation dataset, similar results were shown: sensitivity 87.9%, specificity 39.7%, and AUC 0.638. Additionally, risk categorization with KORAM-M showed improved reclassification over that of OSTA up to 22.8%. Conclusion KORAM-M can be simply used as a pre-screening tool to identify candidates for dual energy X-ray absorptiometry tests. PMID:26632400

The relationship of family characteristics and bipolar disorder using causal-pie models.

PubMed

Chen, Y-C; Kao, C-F; Lu, M-K; Yang, Y-K; Liao, S-C; Jang, F-L; Chen, W J; Lu, R-B; Kuo, P-H

2014-01-01

Many family characteristics were reported to increase the risk of bipolar disorder (BPD). The development of BPD may be mediated through different pathways, involving diverse risk factor profiles. We evaluated the associations of family characteristics to build influential causal-pie models to estimate their contributions on the risk of developing BPD at the population level. We recruited 329 clinically diagnosed BPD patients and 202 healthy controls to collect information in parental psychopathology, parent-child relationship, and conflict within family. Other than logistic regression models, we applied causal-pie models to identify pathways involved with different family factors for BPD. The risk of BPD was significantly increased with parental depression, neurosis, anxiety, paternal substance use problems, and poor relationship with parents. Having a depressed mother further predicted early onset of BPD. Additionally, a greater risk for BPD was observed with higher numbers of paternal/maternal psychopathologies. Three significant risk profiles were identified for BPD, including paternal substance use problems (73.0%), maternal depression (17.6%), and through poor relationship with parents and conflict within the family (6.3%). Our findings demonstrate that different aspects of family characteristics elicit negative impacts on bipolar illness, which can be utilized to target specific factors to design and employ efficient intervention programs. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Multimethod prediction of physical parent-child aggression risk in expectant mothers and fathers with Social Information Processing theory.

PubMed

Rodriguez, Christina M; Smith, Tamika L; Silvia, Paul J

2016-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants' own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Carotid Artery End-Diastolic Velocity and Future Cerebro-Cardiovascular Events in Asymptomatic High Risk Patients.

PubMed

Chung, Hyemoon; Jung, Young Hak; Kim, Ki-Hyun; Kim, Jong-Youn; Min, Pil-Ki; Yoon, Young Won; Lee, Byoung Kwon; Hong, Bum-Kee; Rim, Se-Joong; Kwon, Hyuck Moon; Choi, Eui-Young

2016-01-01

Prognostic value of additional carotid Doppler evaluations to carotid intima-media thickness (IMT) and plaque has not been completely evaluated. A total of 1119 patients with risk factors for, but without, overt coronary artery disease (CAD), who underwent both carotid ultrasound and Doppler examination were included in the present study. Parameters of interest included peak systolic and end-diastolic velocities, resistive indices of the carotid arteries, IMT, and plaque measurements. The primary end-point was all-cause cerebro-cardiovascular events (CVEs) including acute myocardial infarction, coronary revascularization therapy, heart failure admission, stroke, and cardiovascular death. Model 1 covariates comprised age and sex; Model 2 also included hypertension, diabetes and smoking; Model 3 also had use of aspirin and statin; and Model 4 also included IMT and plaque. The mean follow-up duration was 1386±461 days and the mean age of the study population was 60±12 years. Amongst 1119 participants, 43% were women, 57% had a history of hypertension, and 23% had diabetes. During follow-up, 6.6% of patients experienced CVEs. Among carotid Doppler parameters, average common carotid artery end-diastolic velocity was the independent predictor for future CVEs after adjustments for all models variables (HR 0.95 per cm/s, 95% confident interval 0.91-0.99, p=0.034 in Model 4) and significantly increased the predictive value of Model 4 (global χ(2)=59.0 vs. 62.8, p=0.029). Carotid Doppler measurements in addition to IMT and plaque evaluation are independently associated with future CVEs in asymptomatic patients at risk for CAD.

The relationship between the effect of pravastatin and risk factors for coronary heart disease in Japanese patients with hypercholesterolemia.

PubMed

Ishikawa, Toshitsugu; Mizuno, Kyoichi; Nakaya, Noriaki; Ohashi, Yasuo; Tajima, Naoko; Kushiro, Toshio; Teramoto, Tamio; Uchiyama, Shinichiro; Nakamura, Haruo

2008-10-01

Several epidemiologic studies in Japan have shown the risk factors for coronary heart disease (CHD) in the general population. The present analysis determined the risk factors for CHD in the MEGA Study, a large primary prevention trial with pravastatin in Japanese with hypercholesterolemia. The relationship between each baseline characteristic and the risk of CHD for the 5-year study period were evaluated using the Cox proportional hazard model. The multivariable predictors of CHD were sex, age, high-density lipoprotein-cholesterol (HDL-C), diabetes mellitus (DM), hypertension (HT), and history of smoking. Serum total and low-density lipoprotein-cholesterol were not independent risk factors for CHD in the current analysis. In addition, the effect of pravastatin was evaluated by subgroups in each risk factor using the interaction in a Cox model. Diet plus pravastatin treatment reduced CHD risk by 14-43% compared with diet alone, regardless of the presence or absence of risk factors. The risk factors for CHD were sex, age, DM, HT, smoking, and low HDL-C in the MEGA Study. The pravastatin treatment was effective for reducing the risk of CHD, regardless of the presence of risk factors.

Breast Cancer Risk Prediction and Mammography Biopsy Decisions

PubMed Central

Armstrong, Katrina; Handorf, Elizabeth A.; Chen, Jinbo; Demeter, Mirar N. Bristol

2012-01-01

Background Controversy continues about screening mammography, in part because of the risk of false-negative and false-positive mammograms. Pre-test breast cancer risk factors may improve the positive and negative predictive value of screening. Purpose To create a model that estimates the potential impact of pre-test risk prediction using clinical and genomic information on the reclassification of women with abnormal mammograms (BI-RADS3 and BI-RADS4 [Breast Imaging-Reporting and Data System]) above and below the threshold for breast biopsy. Methods The current study modeled 1-year breast cancer risk in women with abnormal screening mammograms using existing data on breast cancer risk factors, 12 validated breast cancer single nucleotide polymorphisms (SNPs), and probability of cancer given the BI-RADS category. Examination was made of reclassification of women above and below biopsy thresholds of 1%, 2%, and 3% risk. The Breast Cancer Surveillance Consortium data were collected from 1996 to 2002. Data analysis was conducted in 2010 and 2011. Results Using a biopsy risk threshold of 2% and the standard risk factor model, 5% of women with a BI-RADS3 mammogram had a risk above the threshold, and 3% of women with BIRADS4A mammograms had a risk below the threshold. The addition of 12 SNPs in the model resulted in 8% of women with a BI-RADS3 mammogram above the threshold for biopsy and 7% of women with BI-RADS4A mammograms below the threshold. Conclusions The incorporation of pre-test breast cancer risk factors could change biopsy decisions for a small proportion of women with abnormal mammograms. The greatest impact comes from standard breast cancer risk factors. PMID:23253645

Household-level disparities in cancer risks from vehicular air pollution in Miami

NASA Astrophysics Data System (ADS)

Collins, Timothy W.; Grineski, Sara E.; Chakraborty, Jayajit

2015-09-01

Environmental justice (EJ) research has relied on ecological analyses of socio-demographic data from areal units to determine if particular populations are disproportionately burdened by toxic risks. This article advances quantitative EJ research by (a) examining whether statistical associations found for geographic units translate to relationships at the household level; (b) testing alternative explanations for distributional injustices never before investigated; and (c) applying a novel statistical technique appropriate for geographically-clustered data. Our study makes these advances by using generalized estimating equations to examine distributive environmental inequities in the Miami (Florida) metropolitan area, based on primary household-level survey data and census block-level cancer risk estimates of hazardous air pollutant (HAP) exposure from on-road mobile emission sources. In addition to modeling determinants of on-road HAP cancer risk among all survey participants, two subgroup models are estimated to examine whether determinants of risk differ based on disadvantaged minority (Hispanic and non-Hispanic Black) versus non-Hispanic white racial/ethnic status. Results reveal multiple determinants of risk exposure disparities. In the model including all survey participants, renter-occupancy, Hispanic and non-Hispanic black race/ethnicity, the desire to live close to work/urban services or public transportation, and higher risk perception are associated with greater on-road HAP cancer risk; the desire to live in an amenity-rich environment is associated with less risk. Divergent subgroup model results shed light on the previously unexamined role of racial/ethnic status in shaping determinants of risk exposures. While lower socioeconomic status and higher risk perception predict significantly greater on-road HAP cancer risk among disadvantaged minorities, the desire to live near work/urban services or public transport predict significantly greater risk among non-Hispanic whites. Findings have important implications for EJ research and practice in Miami and elsewhere.

Space Radiation Risks for Astronauts on Multiple International Space Station Missions

PubMed Central

Cucinotta, Francis A.

2014-01-01

Mortality and morbidity risks from space radiation exposure are an important concern for astronauts participating in International Space Station (ISS) missions. NASA’s radiation limits set a 3% cancer fatality probability as the upper bound of acceptable risk and considers uncertainties in risk predictions using the upper 95% confidence level (CL) of the assessment. In addition to risk limitation, an important question arises as to the likelihood of a causal association between a crew-members’ radiation exposure in the past and a diagnosis of cancer. For the first time, we report on predictions of age and sex specific cancer risks, expected years of life-loss for specific diseases, and probability of causation (PC) at different post-mission times for participants in 1-year or multiple ISS missions. Risk projections with uncertainty estimates are within NASA acceptable radiation standards for mission lengths of 1-year or less for likely crew demographics. However, for solar minimum conditions upper 95% CL exceed 3% risk of exposure induced death (REID) by 18 months or 24 months for females and males, respectively. Median PC and upper 95%-confidence intervals are found to exceed 50% for several cancers for participation in two or more ISS missions of 18 months or longer total duration near solar minimum, or for longer ISS missions at other phases of the solar cycle. However, current risk models only consider estimates of quantitative differences between high and low linear energy transfer (LET) radiation. We also make predictions of risk and uncertainties that would result from an increase in tumor lethality for highly ionizing radiation reported in animal studies, and the additional risks from circulatory diseases. These additional concerns could further reduce the maximum duration of ISS missions within acceptable risk levels, and will require new knowledge to properly evaluate. PMID:24759903

Space radiation risks for astronauts on multiple International Space Station missions.

PubMed

Cucinotta, Francis A

2014-01-01

Mortality and morbidity risks from space radiation exposure are an important concern for astronauts participating in International Space Station (ISS) missions. NASA's radiation limits set a 3% cancer fatality probability as the upper bound of acceptable risk and considers uncertainties in risk predictions using the upper 95% confidence level (CL) of the assessment. In addition to risk limitation, an important question arises as to the likelihood of a causal association between a crew-members' radiation exposure in the past and a diagnosis of cancer. For the first time, we report on predictions of age and sex specific cancer risks, expected years of life-loss for specific diseases, and probability of causation (PC) at different post-mission times for participants in 1-year or multiple ISS missions. Risk projections with uncertainty estimates are within NASA acceptable radiation standards for mission lengths of 1-year or less for likely crew demographics. However, for solar minimum conditions upper 95% CL exceed 3% risk of exposure induced death (REID) by 18 months or 24 months for females and males, respectively. Median PC and upper 95%-confidence intervals are found to exceed 50% for several cancers for participation in two or more ISS missions of 18 months or longer total duration near solar minimum, or for longer ISS missions at other phases of the solar cycle. However, current risk models only consider estimates of quantitative differences between high and low linear energy transfer (LET) radiation. We also make predictions of risk and uncertainties that would result from an increase in tumor lethality for highly ionizing radiation reported in animal studies, and the additional risks from circulatory diseases. These additional concerns could further reduce the maximum duration of ISS missions within acceptable risk levels, and will require new knowledge to properly evaluate.

Additive effects of PNPLA3 and TM6SF2 on the histological severity of non-alcoholic fatty liver disease.

PubMed

Koo, Bo Kyung; Joo, Sae Kyung; Kim, Donghee; Bae, Jeong Mo; Park, Jeong Hwan; Kim, Jung Ho; Kim, Won

2017-11-29

We investigated the effects of PNPLA3 rs738409, TM6SF2 rs58542926, and MBOAT7-TMC4 rs641738 variants on metabolic phenotypes and their combined effects on the histological severity of non-alcoholic fatty liver disease (NAFLD). We genotyped rs738409, rs58542926, and rs641738 in biopsy-proven NAFLD patients (n = 416) and healthy controls (n = 109). Homeostasis model assessment of insulin resistance and adipose tissue insulin resistance were calculated. The rs738409 and rs58542926 variants, but not rs641738, were associated not only with non-alcoholic steatohepatitis (NASH) (odds ratio [OR], 2.00; 95% confidence interval [CI], 1.46-2.73 and OR, 1.91; 95% CI, 1.04-3.51) but also with significant fibrosis (≥ F2) (OR, 1.53; 95% CI, 1.11-2.11 and OR, 1.88; 95% CI, 1.02-3.46) in NAFLD, even after adjustment for metabolic risk factors. Of both variants, only rs738409 was associated with homeostasis model assessment of insulin resistance and adipose tissue insulin resistance even in healthy controls (P = 0.046 and 0.002, respectively) as well as in the entire study cohort (P = 0.016 and 0.048, respectively). PNPLA3 and TM6SF2 risk variants additively increased the risk of NASH and significant fibrosis (OR per risk allele, 2.03; 95% CI, 1.50-2.73 and 1.61; 95% CI, 1.19-2.17). Even in subjects with low insulin resistance, the risk of NASH or significant fibrosis increased as the number of risk alleles increased (P = 0.008 and 0.020, respectively). PNPLA3 and TM6SF2 determine the risk of NASH and significant fibrosis, even after adjustment for insulin resistance, and exert an additive effect on NASH and significant fibrosis. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Agency Problems and Airport Security: Quantitative and Qualitative Evidence on the Impact of Security Training.

PubMed

de Gramatica, Martina; Massacci, Fabio; Shim, Woohyun; Turhan, Uğur; Williams, Julian

2017-02-01

We analyze the issue of agency costs in aviation security by combining results from a quantitative economic model with a qualitative study based on semi-structured interviews. Our model extends previous principal-agent models by combining the traditional fixed and varying monetary responses to physical and cognitive effort with nonmonetary welfare and potentially transferable value of employees' own human capital. To provide empirical evidence for the tradeoffs identified in the quantitative model, we have undertaken an extensive interview process with regulators, airport managers, security personnel, and those tasked with training security personnel from an airport operating in a relatively high-risk state, Turkey. Our results indicate that the effectiveness of additional training depends on the mix of "transferable skills" and "emotional" buy-in of the security agents. Principals need to identify on which side of a critical tipping point their agents are to ensure that additional training, with attached expectations of the burden of work, aligns the incentives of employees with the principals' own objectives. © 2016 Society for Risk Analysis.

Risk adjustment alternatives in paying for behavioral health care under Medicaid.

PubMed Central

Ettner, S L; Frank, R G; McGuire, T G; Hermann, R C

2001-01-01

OBJECTIVE: To compare the performance of various risk adjustment models in behavioral health applications such as setting mental health and substance abuse (MH/SA) capitation payments or overall capitation payments for populations including MH/SA users. DATA SOURCES/STUDY DESIGN: The 1991-93 administrative data from the Michigan Medicaid program were used. We compared mean absolute prediction error for several risk adjustment models and simulated the profits and losses that behavioral health care carve outs and integrated health plans would experience under risk adjustment if they enrolled beneficiaries with a history of MH/SA problems. Models included basic demographic adjustment, Adjusted Diagnostic Groups, Hierarchical Condition Categories, and specifications designed for behavioral health. PRINCIPAL FINDINGS: Differences in predictive ability among risk adjustment models were small and generally insignificant. Specifications based on relatively few MH/SA diagnostic categories did as well as or better than models controlling for additional variables such as medical diagnoses at predicting MH/SA expenditures among adults. Simulation analyses revealed that among both adults and minors considerable scope remained for behavioral health care carve outs to make profits or losses after risk adjustment based on differential enrollment of severely ill patients. Similarly, integrated health plans have strong financial incentives to avoid MH/SA users even after adjustment. CONCLUSIONS: Current risk adjustment methodologies do not eliminate the financial incentives for integrated health plans and behavioral health care carve-out plans to avoid high-utilizing patients with psychiatric disorders. PMID:11508640

Space Radiation Cancer, Circulatory Disease and CNS Risks for Near Earth Asteroid and Mars Missions: Uncertainty Estimates for Never-Smokers

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Chappell, Lori J.; Wang, Minli; Kim, Myung-Hee

2011-01-01

The uncertainties in estimating the health risks from galactic cosmic rays (GCR) and solar particle events (SPE) are a major limitation to the length of space missions and the evaluation of potential risk mitigation approaches. NASA limits astronaut exposures to a 3% risk of exposure induced cancer death (REID), and protects against uncertainties in risks projections using an assessment of 95% confidence intervals after propagating the error from all model factors (environment and organ exposure, risk coefficients, dose-rate modifiers, and quality factors). Because there are potentially significant late mortality risks from diseases of the circulatory system and central nervous system (CNS) which are less well defined than cancer risks, the cancer REID limit is not necessarily conservative. In this report, we discuss estimates of lifetime risks from space radiation and new estimates of model uncertainties are described. The key updates to the NASA risk projection model are: 1) Revised values for low LET risk coefficients for tissue specific cancer incidence, with incidence rates transported to an average U.S. population to estimate the probability of Risk of Exposure Induced Cancer (REIC) and REID. 2) An analysis of smoking attributable cancer risks for never-smokers that shows significantly reduced lung cancer risk as well as overall cancer risks from radiation compared to risk estimated for the average U.S. population. 3) Derivation of track structure based quality functions depends on particle fluence, charge number, Z and kinetic energy, E. 4) The assignment of a smaller maximum in quality function for leukemia than for solid cancers. 5) The use of the ICRP tissue weights is shown to over-estimate cancer risks from SPEs by a factor of 2 or more. Summing cancer risks for each tissue is recommended as a more accurate approach to estimate SPE cancer risks. 6) Additional considerations on circulatory and CNS disease risks. Our analysis shows that an individual s history of smoking exposure has a larger impact on GCR risk estimates than amounts of radiation shielding or age at exposure (amongst adults). Risks for never-smokers compared to the average U.S. population are estimated to be reduced between 30% and 60% dependent on model assumptions. Lung cancer is the major contributor to the reduction for never-smokers, with additional contributions from circulatory diseases and cancers of the stomach, liver, bladder, oral cavity and esophagus, and leukemia. The relative contribution of CNS risks to the overall space radiation detriment is potentially increased for never-smokers such as most astronauts. Problems in estimating risks for former smokers and the influence of second-hand smoke are discussed. Compared to the LET approximation, the new track structure derived radiation quality functions lead to a reduced risk for relativistic energy particles and increased risks for intermediate energy particles. Revised estimates for the number of safe days in space at solar minimum for heavy shielding conditions are described for never-smokers and the average U.S. population. Results show that missions to near Earth asteroids (NEA) or Mars violate NASA's radiation safety standards with the current levels of uncertainties. Greater improvements in risk estimates for never-smokers are possible, and would be dependent on improved understanding of risk transfer models, and elucidating the role of space radiation on the various stages of disease formation (e.g. initiation, promotion, and progression).

Comparison of direct measures of adiposity with indirect measures for assessing cardiometabolic risk factors in preadolescent girls.

PubMed

Hetherington-Rauth, Megan; Bea, Jennifer W; Lee, Vinson R; Blew, Robert M; Funk, Janet; Lohman, Timothy G; Going, Scott B

2017-02-23

Childhood overweight and obesity remains high, contributing to cardiometabolic risk factors at younger ages. It is unclear which measures of adiposity serve as the best proxies for identifying children at metabolic risk. This study assessed whether DXA-derived direct measures of adiposity are more strongly related to cardiometabolic risk factors in children than indirect measures. Anthropometric and DXA measures of adiposity and a comprehensive assessment of cardiometabolic risk factors were obtained in 288, 9-12 year old girls, most being of Hispanic ethnicity. Multiple regression models for each metabolic parameter were run against each adiposity measure while controlling for maturation and ethnicity. In addition, regression models including both indirect and direct measures were developed to assess whether using direct measures of adiposity could provide a better prediction of the cardiometabolic risk factors beyond that of using indirect measures alone. Measures of adiposity were significantly correlated with cardiometabolic risk factors (p < 0.05) except fasting glucose. After adjusting for maturation and ethnicity, indirect measures of adiposity accounted for 29-34% in HOMA-IR, 10-13% in TG, 14-17% in HDL-C, and 5-8% in LDL-C while direct measures accounted for 29-34% in HOMA-IR, 10-12% in TG, 13-16% in HDL-C, and 5-6% in LDL-C. The addition of direct measures of adiposity to indirect measures added significantly to the variance explained for HOMA-IR (p = 0.04). Anthropometric measures may perform as well as the more precise direct DXA-derived measures of adiposity for assessing most CVD risk factors in preadolescent girls. The use of DXA-derived adiposity measures together with indirect measures may be advantageous for predicting insulin resistance risk. NCT02654262 . Retrospectively registered 11 January 2016.

An Expert Map of Gambling Risk Perception.

PubMed

Spurrier, Michael; Blaszczynski, Alexander; Rhodes, Paul

2015-12-01

The purpose of the current study was to investigate the moderating or mediating role played by risk perception in decision-making, gambling behaviour, and disordered gambling aetiology. Eleven gambling expert clinicians and researchers completed a semi-structured interview derived from mental models and grounded theory methodologies. Expert interview data was used to construct a comprehensive expert mental model 'map' detailing risk-perception related factors contributing to harmful or safe gambling. Systematic overlapping processes of data gathering and analysis were used to iteratively extend, saturate, test for exception, and verify concepts and emergent themes. Findings indicated that experts considered idiosyncratic beliefs among gamblers result in overall underestimates of risk and loss, insufficient prioritization of needs, and planning and implementation of risk management strategies. Additional contextual factors influencing use of risk information (reinforcement and learning; mental states, environmental cues, ambivalence; and socio-cultural and biological variables) acted to shape risk perceptions and increase vulnerabilities to harm or disordered gambling. It was concluded that understanding the nature, extent and processes by which risk perception predisposes an individual to maintain gambling despite adverse consequences can guide the content of preventative educational responsible gambling campaigns.

Intraoperative adaptation and visualization of preoperative risk analyses for oncologic liver surgery

NASA Astrophysics Data System (ADS)

Hansen, Christian; Schlichting, Stefan; Zidowitz, Stephan; Köhn, Alexander; Hindennach, Milo; Kleemann, Markus; Peitgen, Heinz-Otto

2008-03-01

Tumor resections from the liver are complex surgical interventions. With recent planning software, risk analyses based on individual liver anatomy can be carried out preoperatively. However, additional tumors within the liver are frequently detected during oncological interventions using intraoperative ultrasound. These tumors are not visible in preoperative data and their existence may require changes to the resection strategy. We propose a novel method that allows an intraoperative risk analysis adaptation by merging newly detected tumors with a preoperative risk analysis. To determine the exact positions and sizes of these tumors we make use of a navigated ultrasound-system. A fast communication protocol enables our application to exchange crucial data with this navigation system during an intervention. A further motivation for our work is to improve the visual presentation of a moving ultrasound plane within a complex 3D planning model including vascular systems, tumors, and organ surfaces. In case the ultrasound plane is located inside the liver, occlusion of the ultrasound plane by the planning model is an inevitable problem for the applied visualization technique. Our system allows the surgeon to focus on the ultrasound image while perceiving context-relevant planning information. To improve orientation ability and distance perception, we include additional depth cues by applying new illustrative visualization algorithms. Preliminary evaluations confirm that in case of intraoperatively detected tumors a risk analysis adaptation is beneficial for precise liver surgery. Our new GPU-based visualization approach provides the surgeon with a simultaneous visualization of planning models and navigated 2D ultrasound data while minimizing occlusion problems.

Risk assessment models to predict caries recurrence after oral rehabilitation under general anaesthesia: a pilot study.

PubMed

Lin, Yai-Tin; Kalhan, Ashish Chetan; Lin, Yng-Tzer Joseph; Kalhan, Tosha Ashish; Chou, Chein-Chin; Gao, Xiao Li; Hsu, Chin-Ying Stephen

2018-05-08

Oral rehabilitation under general anaesthesia (GA), commonly employed to treat high caries-risk children, has been associated with high economic and individual/family burden, besides high post-GA caries recurrence rates. As there is no caries prediction model available for paediatric GA patients, this study was performed to build caries risk assessment/prediction models using pre-GA data and to explore mid-term prognostic factors for early identification of high-risk children prone to caries relapse post-GA oral rehabilitation. Ninety-two children were identified and recruited with parental consent before oral rehabilitation under GA. Biopsychosocial data collection at baseline and the 6-month follow-up were conducted using questionnaire (Q), microbiological assessment (M) and clinical examination (C). The prediction models constructed using data collected from Q, Q + M and Q + M + C demonstrated an accuracy of 72%, 78% and 82%, respectively. Furthermore, of the 83 (90.2%) patients recalled 6 months after GA intervention, recurrent caries was identified in 54.2%, together with reduced bacterial counts, lower plaque index and increased percentage of children toothbrushing for themselves (all P < 0.05). Additionally, meal-time and toothbrushing duration were shown, through bivariate analyses, to be significant prognostic determinants for caries recurrence (both P < 0.05). Risk assessment/prediction models built using pre-GA data may be promising in identifying high-risk children prone to post-GA caries recurrence, although future internal and external validation of predictive models is warranted. © 2018 FDI World Dental Federation.

Developing a suitable model for supplier selection based on supply chain risks: an empirical study from Iranian pharmaceutical companies.

PubMed

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts' opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry.

Using the Job Demands-Resources model to investigate risk perception, safety climate and job satisfaction in safety critical organizations.

PubMed

Nielsen, Morten Birkeland; Mearns, Kathryn; Matthiesen, Stig Berge; Eid, Jarle

2011-10-01

Using the Job Demands-Resources model (JD-R) as a theoretical framework, this study investigated the relationship between risk perception as a job demand and psychological safety climate as a job resource with regard to job satisfaction in safety critical organizations. In line with the JD-R model, it was hypothesized that high levels of risk perception is related to low job satisfaction and that a positive perception of safety climate is related to high job satisfaction. In addition, it was hypothesized that safety climate moderates the relationship between risk perception and job satisfaction. Using a sample of Norwegian offshore workers (N = 986), all three hypotheses were supported. In summary, workers who perceived high levels of risk reported lower levels of job satisfaction, whereas this effect diminished when workers perceived their safety climate as positive. Follow-up analyses revealed that this interaction was dependent on the type of risks in question. The results of this study supports the JD-R model, and provides further evidence for relationships between safety-related concepts and work-related outcomes indicating that organizations should not only develop and implement sound safety procedures to reduce the effects of risks and hazards on workers, but can also enhance other areas of organizational life through a focus on safety. © 2011 The Authors. Scandinavian Journal of Psychology © 2011 The Scandinavian Psychological Associations.

Developing a Suitable Model for Supplier Selection Based on Supply Chain Risks: An Empirical Study from Iranian Pharmaceutical Companies

PubMed Central

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts’ opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry. PMID:24250442

Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus.

PubMed

Cohen, Mark E; Ko, Clifford Y; Bilimoria, Karl Y; Zhou, Lynn; Huffman, Kristopher; Wang, Xue; Liu, Yaoming; Kraemer, Kari; Meng, Xiangju; Merkow, Ryan; Chow, Warren; Matel, Brian; Richards, Karen; Hart, Amy J; Dimick, Justin B; Hall, Bruce L

2013-08-01

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) collects detailed clinical data from participating hospitals using standardized data definitions, analyzes these data, and provides participating hospitals with reports that permit risk-adjusted comparisons with a surgical quality standard. Since its inception, the ACS NSQIP has worked to refine surgical outcomes measurements and enhance statistical methods to improve the reliability and validity of this hospital profiling. From an original focus on controlling for between-hospital differences in patient risk factors with logistic regression, ACS NSQIP has added a variable to better adjust for the complexity and risk profile of surgical procedures (procedure mix adjustment) and stabilized estimates derived from small samples by using a hierarchical model with shrinkage adjustment. New models have been developed focusing on specific surgical procedures (eg, "Procedure Targeted" models), which provide opportunities to incorporate indication and other procedure-specific variables and outcomes to improve risk adjustment. In addition, comparative benchmark reports given to participating hospitals have been expanded considerably to allow more detailed evaluations of performance. Finally, procedures have been developed to estimate surgical risk for individual patients. This article describes the development of, and justification for, these new statistical methods and reporting strategies in ACS NSQIP. Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Predicting cancer risk knowledge and information seeking: the role of social and cognitive factors.

PubMed

Hovick, Shelly R; Liang, Ming-Ching; Kahlor, Leeann

2014-01-01

This study tests an expanded Structural Influence Model (SIM) to gain a greater understanding of the social and cognitive factors that contribute to disparities in cancer risk knowledge and information seeking. At the core of this expansion is the planned risk information seeking model (PRISM). This study employed an online sample (N = 1,007) of African American, Hispanic, and non-Hispanic White adults. The addition of four cognitive predictors to the SIM substantially increased variance explained in cancer risk knowledge (R(2) = .29) and information seeking (R(2) = .56). Health literacy mediated the effects of social determinants (socioeconomic status [SES] and race/ethnicity) on cancer risk knowledge, while subjective norms mediated their effects on cancer risk information seeking. Social capital and perceived seeking control were also shown to be important mediators of the relationships between SES and cancer communication outcomes. Our results illustrate the social and cognitive mechanisms by which social determinants impact cancer communication outcomes, as well as several points of intervention to reduce communication disparities.

Interaction of reward seeking and self-regulation in the prediction of risk taking: A cross-national test of the dual systems model.

PubMed

Duell, Natasha; Steinberg, Laurence; Chein, Jason; Al-Hassan, Suha M; Bacchini, Dario; Lei, Chang; Chaudhary, Nandita; Di Giunta, Laura; Dodge, Kenneth A; Fanti, Kostas A; Lansford, Jennifer E; Malone, Patrick S; Oburu, Paul; Pastorelli, Concetta; Skinner, Ann T; Sorbring, Emma; Tapanya, Sombat; Uribe Tirado, Liliana Maria; Alampay, Liane Peña

2016-10-01

In the present analysis, we test the dual systems model of adolescent risk taking in a cross-national sample of over 5,200 individuals aged 10 through 30 (M = 17.05 years, SD = 5.91) from 11 countries. We examine whether reward seeking and self-regulation make independent, additive, or interactive contributions to risk taking, and ask whether these relations differ as a function of age and culture. To compare across cultures, we conduct 2 sets of analyses: 1 comparing individuals from Asian and Western countries, and 1 comparing individuals from low- and high-GDP countries. Results indicate that reward seeking and self-regulation have largely independent associations with risk taking and that the influences of each variable on risk taking are not unique to adolescence, but that their link to risk taking varies across cultures. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Cumulative Risk, Negative Emotionality, and Emotion Regulation as Predictors of Social Competence in Transition to School: A Mediated Moderation Model

ERIC Educational Resources Information Center

Chang, Hyein; Shelleby, Elizabeth C.; Cheong, JeeWon; Shaw, Daniel S.

2012-01-01

The goals of this study were to examine the additive and interactive effects of cumulative risk and child negative emotionality on children's social competence in the transition from preschool to school and to test whether these associations were mediated by child emotion regulation within a sample of 310 low-income, ethnically diverse boys.…

Radiation Measurements Performed with Active Detectors Relevant for Human Space Exploration

PubMed Central

Narici, Livio; Berger, Thomas; Matthiä, Daniel; Reitz, Günther

2015-01-01

A reliable radiation risk assessment in space is a mandatory step for the development of countermeasures and long-duration mission planning in human spaceflight. Research in radiobiology provides information about possible risks linked to radiation. In addition, for a meaningful risk evaluation, the radiation exposure has to be assessed to a sufficient level of accuracy. Consequently, both the radiation models predicting the risks and the measurements used to validate such models must have an equivalent precision. Corresponding measurements can be performed both with passive and active devices. The former is easier to handle, cheaper, lighter, and smaller but they measure neither the time dependence of the radiation environment nor some of the details useful for a comprehensive radiation risk assessment. Active detectors provide most of these details and have been extensively used in the International Space Station. To easily access such an amount of data, a single point access is becoming essential. This review presents an ongoing work on the development of a tool that allows obtaining information about all relevant measurements performed with active detectors providing reliable inputs for radiation model validation. PMID:26697408

Radiation Measurements Performed with Active Detectors Relevant for Human Space Exploration.

PubMed

Narici, Livio; Berger, Thomas; Matthiä, Daniel; Reitz, Günther

2015-01-01

A reliable radiation risk assessment in space is a mandatory step for the development of countermeasures and long-duration mission planning in human spaceflight. Research in radiobiology provides information about possible risks linked to radiation. In addition, for a meaningful risk evaluation, the radiation exposure has to be assessed to a sufficient level of accuracy. Consequently, both the radiation models predicting the risks and the measurements used to validate such models must have an equivalent precision. Corresponding measurements can be performed both with passive and active devices. The former is easier to handle, cheaper, lighter, and smaller but they measure neither the time dependence of the radiation environment nor some of the details useful for a comprehensive radiation risk assessment. Active detectors provide most of these details and have been extensively used in the International Space Station. To easily access such an amount of data, a single point access is becoming essential. This review presents an ongoing work on the development of a tool that allows obtaining information about all relevant measurements performed with active detectors providing reliable inputs for radiation model validation.

RESILIENCE THEORY AND ITS IMPLICATIONS FOR CHINESE ADOLESCENTS.

PubMed

Wang, Jin-Liang; Zhang, Da-Jun; Zimmerman, Marc A

2015-10-01

Over the past 20 years, resilience theory has attracted great attention from both researchers and mental health practitioners. Resilience is defined as a process of overcoming the negative effects of risk exposure, coping successfully with traumatic experiences, or avoiding the negative trajectories associated with risks. Three basic models of resilience have been proposed to account for the mechanism whereby promotive factors operate to alter the trajectory from risk exposure to negative consequences: compensatory model, protective model, and inoculation model. Assets and resources are two types of promotive factors found to be effective in decreasing internalizing and externalizing problems. Considering the protective or compensatory role of assets and resources in helping youth be resilient against negative effects of adversity, resilience could be applied to Chinese migrant and left-behind children who are at risk for internalizing (e.g., depression, anxiety) and externalizing problems (e.g., delinquent behaviors, cigarette and alcohol use). Additionally, psychological suzhi-based interventions, a mental health construct for individuals that focuses on a strengths-based approach, can be integrated with resilience-based approach to develop more balanced programs for positive youth development.

The Perils of Picky Eating: Dietary Breadth Is Related to Extinction Risk in Insectivorous Bats

PubMed Central

Boyles, Justin G.; Storm, Jonathan J.

2007-01-01

Several recent papers evaluate the relationship between ecological characteristics and extinction risk in bats. These studies report that extinction risk is negatively related to geographic range size and positively related to habitat specialization. Here, we evaluate the hypothesis that extinction risk is also related to dietary specialization in insectivorous vespertilionid bats using both traditional and phylogenetically-controlled analysis of variance. We collected dietary data and The World Conservation Union (IUCN) rankings for 44 Australian, European, and North American bat species. Our results indicate that species of conservation concern (IUCN ranking near threatened or above) are more likely to have a specialized diet than are species of least concern. Additional analyses show that dietary breadth is not correlated to geographic range size or wing morphology, characteristics previously found to correlate with extinction risk. Therefore, there is likely a direct relationship between dietary specialization and extinction risk; however, the large variation in dietary breadth within species of least concern suggests that diet alone cannot explain extinction risk. Our results may have important implications for the development of predictive models of extinction risk and for the assignment of extinction risk to insectivorous bat species. Similar analyses should be conducted on additional bat families to assess the generality of this relationship between niche breadth and extinction risk. PMID:17653286

Risk Preferences and the Timing of Marriage and Childbearing

PubMed Central

SCHMIDT, LUCIE

2008-01-01

The existing literature on marriage and fertility decisions pays little attention to the roles played by risk preferences and uncertainty. However, given uncertainty regarding the availability of suitable marriage partners, the ability to contracept, and the ability to conceive, women’s risk preferences might be expected to play an important role in marriage and fertility timing decisions. By using data from the Panel Study of Income Dynamics (PSID), I find that measured risk preferences have a significant effect on the timing of both marriage and fertility. Highly risk-tolerant women are more likely to delay marriage, consistent with either a search model of marriage or a risk-pooling explanation. In addition, risk preferences affect fertility timing in a way that differs by marital status and education, and that varies over the life cycle. Greater tolerance for risk leads to earlier births at young ages, consistent with these women being less likely to contracept effectively. In addition, as the subgroup of college-educated, unmarried women nears the end of their fertile periods, highly risk-tolerant women are likely to delay childbearing relative to their more risk-averse counterparts and are therefore less likely to become mothers. These findings may have broader implications for both individual and societal well-being. PMID:18613489

Association Between Four Polymorphisms in lncRNA and Risk of Lung Cancer in a Chinese Never-Smoking Female Population.

PubMed

Gao, Min; Li, Hang; Lv, Xiaoting; Zhou, Baosen; Yin, Zhihua

2018-06-07

Long noncoding RNAs (lncRNAs) play important roles in the development of human cancers. This is the first case-control study of the association between specific polymorphisms in lncRNA genes and the risk of lung cancer, as well as the gene-environment interaction between the polymorphisms and cooking oil fume exposure in Chinese never-smoking females. A hospital-based case-control study was carried out in Shenyang, Liaoning province. The study included 395 cases and 556 controls. The polymorphisms of rs4785367, rs3803662, rs10750417, and rs1814343 in lncRNA genes were analyzed. The gene-environment interactions were explored on both additive and multiplicative scale. In addition, the results were listed as follows: for rs3803662, compared with the individuals carrying homozygous TT genotype, those with homozygous CC genotype had the decreased risk of lung cancer (adjusted odds ratio [OR] = 0.61, 95% confidence interval [CI] = 0.40-0.92, p = 0.018). As for rs4785367, compared with homozygous TT, homozygous CC could lessen the risk of lung cancer (adjusted OR = 0.54, 95% CI = 0.33-0.89, p = 0.016). The recessive models of rs3803662 and rs4785367 showed significant association (adjusted OR = 0.65, 95% CIs = 0.44-0.97, p = 0.033; adjusted OR = 0.54, 95% CIs = 0.33-0.88, p = 0.014). The C allele of rs3803662 was suggested to be protective allele of lung cancer (adjusted OR = 0.80, 95% CI = 0.66-0.97, p = 0.023). However, rs10750417 and rs1814343 polymorphisms were not significantly associated with lung cancer risks. The measures of additive interaction and logistic models suggested that the gene-environment interactions were not statistically significant on both additive and multiplicative scales.

Non-additive and epistatic effects of HLA polymorphisms contributing to risk of adult glioma.

PubMed

Zhang, Chenan; de Smith, Adam J; Smirnov, Ivan V; Wiencke, John K; Wiemels, Joseph L; Witte, John S; Walsh, Kyle M

2017-11-01

Although genome-wide association studies have identified several susceptibility loci for adult glioma, little is known regarding the potential contribution of genetic variation in the human leukocyte antigen (HLA) region to glioma risk. HLA associations have been reported for various malignancies, with many studies investigating selected candidate HLA polymorphisms. However, no systematic analysis has been conducted in glioma patients, and no investigation into potential non-additive effects has been described. We conducted comprehensive genetic analyses of HLA variants among 1746 adult glioma patients and 2312 controls of European-ancestry from the GliomaScan Consortium. Genotype data were generated with the Illumina 660-Quad array, and we imputed HLA alleles using a reference panel of 5225 individuals in the Type 1 Diabetes Genetics Consortium who underwent high-resolution HLA typing via next-generation sequencing. Case-control comparisons were adjusted for population stratification using ancestry-informative principal components. Because alleles in different loci across the HLA region are linked, we created multigene haplotypes consisting of the genes DRB1, DQA1, and DQB1. Although none of the haplotypes were associated with glioma in additive models, inclusion of a dominance term significantly improved the model for multigene haplotype HLA-DRB1*1501-DQA1*0102-DQB1*0602 (P = 0.002). Heterozygous carriers of the haplotype had an increased risk of glioma [odds ratio (OR) 1.23; 95% confidence interval (CI) 1.01-1.49], while homozygous carriers were at decreased risk compared with non-carriers (OR 0.64; 95% CI 0.40-1.01). Our results suggest that the DRB1*1501-DQA1*0102-DQB1*0602 haplotype may contribute to the risk of glioma in a non-additive manner, with the positive dominance effect partly explained by an epistatic interaction with HLA-DRB1*0401-DQA1*0301-DQB1*0301.

Improved understanding of geologic CO{sub 2} storage processes requires risk-driven field experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oldenburg, C.M.

2011-06-01

The need for risk-driven field experiments for CO{sub 2} geologic storage processes to complement ongoing pilot-scale demonstrations is discussed. These risk-driven field experiments would be aimed at understanding the circumstances under which things can go wrong with a CO{sub 2} capture and storage (CCS) project and cause it to fail, as distinguished from accomplishing this end using demonstration and industrial scale sites. Such risk-driven tests would complement risk-assessment efforts that have already been carried out by providing opportunities to validate risk models. In addition to experimenting with high-risk scenarios, these controlled field experiments could help validate monitoring approaches to improvemore » performance assessment and guide development of mitigation strategies.« less

Identifying high-risk areas for sporadic measles outbreaks: lessons from South Africa.

PubMed

Sartorius, Benn; Cohen, C; Chirwa, T; Ntshoe, G; Puren, A; Hofman, K

2013-03-01

To develop a model for identifying areas at high risk for sporadic measles outbreaks based on an analysis of factors associated with a national outbreak in South Africa between 2009 and 2011. Data on cases occurring before and during the national outbreak were obtained from the South African measles surveillance programme, and data on measles immunization and population size, from the District Health Information System. A Bayesian hierarchical Poisson model was used to investigate the association between the risk of measles in infants in a district and first-dose vaccination coverage, population density, background prevalence of human immunodeficiency virus (HIV) infection and expected failure of seroconversion. Model projections were used to identify emerging high-risk areas in 2012. A clear spatial pattern of high-risk areas was noted, with many interconnected (i.e. neighbouring) areas. An increased risk of measles outbreak was significantly associated with both the preceding build-up of a susceptible population and population density. The risk was also elevated when more than 20% of infants in a populous area had missed a first vaccine dose. The model was able to identify areas at high risk of experiencing a measles outbreak in 2012 and where additional preventive measures could be undertaken. The South African measles outbreak was associated with the build-up of a susceptible population (owing to poor vaccine coverage), high prevalence of HIV infection and high population density. The predictive model developed could be applied to other settings susceptible to sporadic outbreaks of measles and other vaccine-preventable diseases.

A prediction model for colon cancer surveillance data.

PubMed

Good, Norm M; Suresh, Krithika; Young, Graeme P; Lockett, Trevor J; Macrae, Finlay A; Taylor, Jeremy M G

2015-08-15

Dynamic prediction models make use of patient-specific longitudinal data to update individualized survival probability predictions based on current and past information. Colonoscopy (COL) and fecal occult blood test (FOBT) results were collected from two Australian surveillance studies on individuals characterized as high-risk based on a personal or family history of colorectal cancer. Motivated by a Poisson process, this paper proposes a generalized nonlinear model with a complementary log-log link as a dynamic prediction tool that produces individualized probabilities for the risk of developing advanced adenoma or colorectal cancer (AAC). This model allows predicted risk to depend on a patient's baseline characteristics and time-dependent covariates. Information on the dates and results of COLs and FOBTs were incorporated using time-dependent covariates that contributed to patient risk of AAC for a specified period following the test result. These covariates serve to update a person's risk as additional COL, and FOBT test information becomes available. Model selection was conducted systematically through the comparison of Akaike information criterion. Goodness-of-fit was assessed with the use of calibration plots to compare the predicted probability of event occurrence with the proportion of events observed. Abnormal COL results were found to significantly increase risk of AAC for 1 year following the test. Positive FOBTs were found to significantly increase the risk of AAC for 3 months following the result. The covariates that incorporated the updated test results were of greater significance and had a larger effect on risk than the baseline variables. Copyright © 2015 John Wiley & Sons, Ltd.

Self-reported clothing size as a proxy measure for body size.

PubMed

Hughes, Laura A E; Schouten, Leo J; Goldbohm, R Alexandra; van den Brandt, Piet A; Weijenberg, Matty P

2009-09-01

Few studies have considered the potential utility of clothing size as a predictor of diseases associated with body weight. We used data on weight-stable men and women from a subcohort of the Netherlands Cohort Study to assess the correlation of clothing size with other anthropometric variables. Cox regression using the case-cohort approach was performed to establish whether clothing size can predict cancer risk after 13.3 years of follow-up, and if additionally considering body mass index (BMI) in the model improves the prediction. Trouser and skirt size correlated well with circumference measurements. Skirt size predicted endometrial cancer risk, and this effect was slightly attenuated when BMI was added to the model. Trouser size predicted risk of renal cell carcinoma, regardless of whether BMI was in the model. Clothing size appears to predict cancer risk independently of BMI, suggesting that clothing size is a useful measure to consider in epidemiologic studies when waist circumference is not available.

Ensemble Flow Forecasts for Risk Based Reservoir Operations of Lake Mendocino in Mendocino County, California

NASA Astrophysics Data System (ADS)

Delaney, C.; Hartman, R. K.; Mendoza, J.; Evans, K. M.; Evett, S.

2016-12-01

Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation or flow forecasts to inform the flood operations of reservoirs. Previous research and modeling for flood control reservoirs has shown that FIRO can reduce flood risk and increase water supply for many reservoirs. The risk-based method of FIRO presents a unique approach that incorporates flow forecasts made by NOAA's California-Nevada River Forecast Center (CNRFC) to model and assess risk of meeting or exceeding identified management targets or thresholds. Forecasted risk is evaluated against set risk tolerances to set reservoir flood releases. A water management model was developed for Lake Mendocino, a 116,500 acre-foot reservoir located near Ukiah, California. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United State Army Corps of Engineers and is operated by the Sonoma County Water Agency for water supply. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has been plagued with water supply reliability issues since 2007. FIRO is applied to Lake Mendocino by simulating daily hydrologic conditions from 1985 to 2010 in the Upper Russian River from Lake Mendocino to the City of Healdsburg approximately 50 miles downstream. The risk-based method is simulated using a 15-day, 61 member streamflow hindcast by the CNRFC. Model simulation results of risk-based flood operations demonstrate a 23% increase in average end of water year (September 30) storage levels over current operations. Model results show no increase in occurrence of flood damages for points downstream of Lake Mendocino. This investigation demonstrates that FIRO may be a viable flood control operations approach for Lake Mendocino and warrants further investigation through additional modeling and analysis.

Making predictions of mangrove deforestation: a comparison of two methods in Kenya.

PubMed

Rideout, Alasdair J R; Joshi, Neha P; Viergever, Karin M; Huxham, Mark; Briers, Robert A

2013-11-01

Deforestation of mangroves is of global concern given their importance for carbon storage, biogeochemical cycling and the provision of other ecosystem services, but the links between rates of loss and potential drivers or risk factors are rarely evaluated. Here, we identified key drivers of mangrove loss in Kenya and compared two different approaches to predicting risk. Risk factors tested included various possible predictors of anthropogenic deforestation, related to population, suitability for land use change and accessibility. Two approaches were taken to modelling risk; a quantitative statistical approach and a qualitative categorical ranking approach. A quantitative model linking rates of loss to risk factors was constructed based on generalized least squares regression and using mangrove loss data from 1992 to 2000. Population density, soil type and proximity to roads were the most important predictors. In order to validate this model it was used to generate a map of losses of Kenyan mangroves predicted to have occurred between 2000 and 2010. The qualitative categorical model was constructed using data from the same selection of variables, with the coincidence of different risk factors in particular mangrove areas used in an additive manner to create a relative risk index which was then mapped. Quantitative predictions of loss were significantly correlated with the actual loss of mangroves between 2000 and 2010 and the categorical risk index values were also highly correlated with the quantitative predictions. Hence, in this case the relatively simple categorical modelling approach was of similar predictive value to the more complex quantitative model of mangrove deforestation. The advantages and disadvantages of each approach are discussed, and the implications for mangroves are outlined. © 2013 Blackwell Publishing Ltd.

Couple resilience to economic pressure.

PubMed

Conger, R D; Rueter, M A; Elder, G H

1999-01-01

Over 400 married couples participated in a 3-year prospective study of economic pressure and marital relations. The research (a) empirically evaluated the family stress model of economic stress influences on marital distress and (b) extended the model to include specific interactional characteristics of spouses hypothesized to protect against economic pressure. Findings provided support for the basic mediational model, which proposes that economic pressure increases risk for emotional distress, which, in turn, increases risk for marital conflict and subsequent marital distress. Regarding resilience to economic stress, high marital support reduced the association between economic pressure and emotional distress. In addition, effective couple problem solving reduced the adverse influence of marital conflict on marital distress. Overall, the findings provided substantial support for the extended family stress model.

12 CFR Appendix H to Part 222 - Appendix H-Model Forms for Risk-Based Pricing and Credit Score Disclosure Exception Notices

Code of Federal Regulations, 2014 CFR

2014-01-01

... addresses that may change over time. ii. The addition of graphics or icons, such as the person's corporate... rate. All forms contained in this appendix are models; their use is optional. 3. A person may change... required to conduct consumer testing when rearranging the format of the model forms. a. Acceptable changes...

Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.

PubMed

Razavian, Narges; Blecker, Saul; Schmidt, Ann Marie; Smith-McLallen, Aaron; Nigam, Somesh; Sontag, David

2015-12-01

We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative claims, pharmacy records, healthcare utilization, and laboratory results of 4.1 million individuals between 2005 and 2009, an initial set of 42,000 variables were derived that together describe the full health status and history of every individual. Machine learning was then used to methodically enhance predictive variable set and fit models predicting onset of type 2 diabetes in 2009-2011, 2010-2012, and 2011-2013. We compared the enhanced model with a parsimonious model consisting of known diabetes risk factors in a real-world environment, where missing values are common and prevalent. Furthermore, we analyzed novel and known risk factors emerging from the model at different age groups at different stages before the onset. Parsimonious model using 21 classic diabetes risk factors resulted in area under ROC curve (AUC) of 0.75 for diabetes prediction within a 2-year window following the baseline. The enhanced model increased the AUC to 0.80, with about 900 variables selected as predictive (p < 0.0001 for differences between AUCs). Similar improvements were observed for models predicting diabetes onset 1-3 years and 2-4 years after baseline. The enhanced model improved positive predictive value by at least 50% and identified novel surrogate risk factors for type 2 diabetes, such as chronic liver disease (odds ratio [OR] 3.71), high alanine aminotransferase (OR 2.26), esophageal reflux (OR 1.85), and history of acute bronchitis (OR 1.45). Liver risk factors emerge later in the process of diabetes development compared with obesity-related factors such as hypertension and high hemoglobin A1c. In conclusion, population-level risk prediction for type 2 diabetes using readily available administrative data is feasible and has better prediction performance than classical diabetes risk prediction algorithms on very large populations with missing data. The new model enables intervention allocation at national scale quickly and accurately and recovers potentially novel risk factors at different stages before the disease onset.

Modelling West Nile virus transmission risk in Europe: effect of temperature and mosquito biotypes on the basic reproduction number.

PubMed

Vogels, Chantal B F; Hartemink, Nienke; Koenraadt, Constantianus J M

2017-07-10

West Nile virus (WNV) is a mosquito-borne flavivirus which has caused repeated outbreaks in humans in southern and central Europe, but thus far not in northern Europe. The main mosquito vector for WNV, Culex pipiens, consists of two behaviourally distinct biotypes, pipiens and molestus, which can form hybrids. Differences between biotypes, such as vector competence and host preference, could be important in determining the risk of WNV outbreaks. Risks for WNV establishment can be modelled with basic reproduction number (R 0 ) models. However, existing R 0 models have not differentiated between biotypes. The aim of this study was, therefore, to explore the role of temperature-dependent and biotype-specific effects on the risk of WNV establishment in Europe. We developed an R 0 model with temperature-dependent and biotype-specific parameters, and calculated R 0 values using the next-generation matrix for several scenarios relevant for Europe. In addition, elasticity analysis was done to investigate the contribution of each biotype to R 0 . Global warming and increased mosquito-to-host ratios can possibly result in more intense WNV circulation in birds and spill-over to humans in northern Europe. Different contributions of the Cx. pipiens biotypes to R 0 shows the importance of including biotype-specific parameters in models for reliable WNV risk assessments.

Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.

PubMed

Fortner, Renée T; Hüsing, Anika; Kühn, Tilman; Konar, Meric; Overvad, Kim; Tjønneland, Anne; Hansen, Louise; Boutron-Ruault, Marie-Christine; Severi, Gianluca; Fournier, Agnès; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vasiliki; Orfanos, Philippos; Masala, Giovanna; Agnoli, Claudia; Mattiello, Amalia; Tumino, Rosario; Sacerdote, Carlotta; Bueno-de-Mesquita, H B As; Peeters, Petra H M; Weiderpass, Elisabete; Gram, Inger T; Gavrilyuk, Oxana; Quirós, J Ramón; Maria Huerta, José; Ardanaz, Eva; Larrañaga, Nerea; Lujan-Barroso, Leila; Sánchez-Cantalejo, Emilio; Butt, Salma Tunå; Borgquist, Signe; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Allen, Naomi E; Rinaldi, Sabina; Dossus, Laure; Gunter, Marc; Merritt, Melissa A; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf

2017-03-15

Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination. © 2016 UICC.

Issues in the Pharmacokinetics of Trichloroethylene and Its Metabolites

PubMed Central

Chiu, Weihsueh A.; Okino, Miles S.; Lipscomb, John C.; Evans, Marina V.

2006-01-01

Much progress has been made in understanding the complex pharmacokinetics of trichloroethylene (TCE). Qualitatively, it is clear that TCE is metabolized to multiple metabolites either locally or into systemic circulation. Many of these metabolites are thought to have toxicologic importance. In addition, efforts to develop physiologically based pharmacokinetic (PBPK) models have led to a better quantitative assessment of the dosimetry of TCE and several of its metabolites. As part of a mini-monograph on key issues in the health risk assessment of TCE, this article is a review of a number of the current scientific issues in TCE pharmacokinetics and recent PBPK modeling efforts with a focus on literature published since 2000. Particular attention is paid to factors affecting PBPK modeling for application to risk assessment. Recent TCE PBPK modeling efforts, coupled with methodologic advances in characterizing uncertainty and variability, suggest that rigorous application of PBPK modeling to TCE risk assessment appears feasible at least for TCE and its major oxidative metabolites trichloroacetic acid and trichloroethanol. However, a number of basic structural hypotheses such as enterohepatic recirculation, plasma binding, and flow- or diffusion-limited treatment of tissue distribution require additional evaluation and analysis. Moreover, there are a number of metabolites of potential toxicologic interest, such as chloral, dichloroacetic acid, and those derived from glutathione conjugation, for which reliable pharmacokinetic data is sparse because of analytical difficulties or low concentrations in systemic circulation. It will be a challenge to develop reliable dosimetry for such cases. PMID:16966104

Association between TLR2 and TLR4 Gene Polymorphisms and the Susceptibility to Inflammatory Bowel Disease: A Meta-Analysis.

PubMed

Cheng, Yang; Zhu, Yun; Huang, Xiuping; Zhang, Wei; Han, Zelong; Liu, Side

2015-01-01

The associations between toll-like receptor 2 (TLR2) and toll-like receptor 4(TLR4) polymorphisms and inflammatory bowel disease (IBD) susceptibility remain controversial. A meta-analysis was performed to assess these associations. A systematic search was performed to identify all relevant studies relating TLR2 and TLR4 polymorphisms and IBD susceptibility. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Subgroup analyses were performed by ethnicity and publication quality. Thirty-eight eligible studies, assessing 10970 cases and 7061 controls were included. No TLR2 Arg677Trp polymorphism was found. No significant association was observed between TLR2 Arg753Gln polymorphism and Crohn's disease (CD) or ulcerative colitis (UC) in all genetic models. Interestingly, TLR4 Asp299Gly polymorphism was significantly associated with increased risk of CD and UC in all genetic models, except for the additive one in CD. In addition, a statistically significant association between TLR4 Asp299Gly polymorphism and IBD was observed among high quality studies evaluating Caucasians, but not Asians. Associations between TLR4 Thr399Ile polymorphisms and CD risk were found only in the allele and dominant models. The TLR4 Thr399Ile polymorphism was associated with UC risk in pooled results as well as subgroup analysis of high quality publications assessing Caucasians, in allele and dominant models. The meta-analysis provides evidence that TLR2 Arg753Gln is not associated with CD and UC susceptibility in Asians; TLR4 Asp299Gly is associated with CD and UC susceptibility in Caucasians, but not Asians. TLR4 Thr399Ile may be associated with IBD susceptibility in Caucasians only. Additional well-powered studies of Asp299Gly and other TLR4 variants are warranted.

Placenta previa and placental abruption after assisted reproductive technology in patients with endometriosis: a systematic review and meta-analysis.

PubMed

Gasparri, Maria Luisa; Nirgianakis, Konstantinos; Taghavi, Katayoun; Papadia, Andrea; Mueller, Michael D

2018-07-01

Recent evidence suggests that assisted reproductive technology (ART) increases the risk of adverse pregnancy outcomes, including placental disorders. Similarly, endometriosis resulted detrimental on placenta previa. However, up to 50% of women with endometriosis suffer from infertility, thus requiring ART. The aim of our metanalysis is to compare women with and without endometriosis undergoing ART in terms of placenta disorders events, to establish if ART itself or endometriosis, as an indication to ART, increases the risk of placenta previa. Literature searches were conducted in January 2018 using electronic databases (PubMed, Medline, Scopus, Embase, Science Direct, and the Cochrane Library Scopus). Series comparing pregnancy outcome after ART in women with and without endometriosis were screened and data on placenta previa and placental abruption were extracted. Five retrospective case-control studies met the inclusion criteria. The meta-analysis revealed that endometriosis is associated with an increased risk of placenta previa in pregnancies achieved through ART (OR 2.96 (95% CI 1.25-7.03); p = 0.01, I 2  =69%, random-effect model). No differences in placental abruption incidence were found (OR 0.44 (95% CI 0.10-1.87); p = 0.26, I 2  = 0%, fixed-effect model). Patients with endometriosis undergoing ART may have additional risk of placenta previa. Despite the inability to determine if endometriosis alone or endometriosis plus ART increase the risk, physicians should be aware of the potential additional risk that endometriosis patients undergoing ART harbor.

Quantitative microbial risk assessment for Escherichia coli O157:H7, Salmonella enterica, and Listeria monocytogenes in leafy green vegetables consumed at salad bars, based on modeling supply chain logistics.

PubMed

Tromp, S O; Rijgersberg, H; Franz, E

2010-10-01

Quantitative microbial risk assessments do not usually account for the planning and ordering mechanisms (logistics) of a food supply chain. These mechanisms and consumer demand determine the storage and delay times of products. The aim of this study was to quantitatively assess the difference between simulating supply chain logistics (MOD) and assuming fixed storage times (FIX) in microbial risk estimation for the supply chain of fresh-cut leafy green vegetables destined for working-canteen salad bars. The results of the FIX model were previously published (E. Franz, S. O. Tromp, H. Rijgersberg, and H. J. van der Fels-Klerx, J. Food Prot. 73:274-285, 2010). Pathogen growth was modeled using stochastic discrete-event simulation of the applied logistics concept. The public health effects were assessed by conducting an exposure assessment and risk characterization. The relative growths of Escherichia coli O157 (17%) and Salmonella enterica (15%) were identical in the MOD and FIX models. In contrast, the relative growth of Listeria monocytogenes was considerably higher in the MOD model (1,156%) than in the FIX model (194%). The probability of L. monocytogenes infection in The Netherlands was higher in the MOD model (5.18×10(-8)) than in the FIX model (1.23×10(-8)). The risk of listeriosis-induced fetal mortality in the perinatal population increased from 1.24×10(-4) (FIX) to 1.66×10(-4) (MOD). Modeling the probabilistic nature of supply chain logistics is of additional value for microbial risk assessments regarding psychrotrophic pathogens in food products for which time and temperature are the postharvest preventive measures in guaranteeing food safety.

Association of ARID5B gene variants with acute lymphoblastic leukemia in Yemeni children.

PubMed

Al-Absi, Boshra; Noor, Suzita M; Saif-Ali, Riyadh; Salem, Sameer D; Ahmed, Radwan H; Razif, Muhammad Fm; Muniandy, Sekaran

2017-04-01

Studies have shown an association between ARID5B gene polymorphisms and childhood acute lymphoblastic leukemia. However, the association between ARID5B variants and acute lymphoblastic leukemia among the Arab population still needs to be studied. The aim of this study was to investigate the association between ARID5B variants with acute lymphoblastic leukemia in Yemeni children. A total of 14 ARID5B gene single nucleotide polymorphisms (SNPs) were genotyped in 289 Yemeni children, of whom 136 had acute lymphoblastic leukemia and 153 were controls, using the nanofluidic Dynamic Array (Fluidigm 192.24 Dynamic Array). Using logistic regression adjusted for age and gender, the risks of acute lymphoblastic leukemia were presented as odds ratios and 95% confidence intervals. We found that nine SNPs were associated with acute lymphoblastic leukemia under additive genetic models: rs7073837, rs10740055, rs7089424, rs10821936, rs4506592, rs10994982, rs7896246, rs10821938, and rs7923074. Furthermore, the recessive models revealed that six SNPs were risk factors for acute lymphoblastic leukemia: rs10740055, rs7089424, rs10994982, rs7896246, rs10821938, and rs7923074. The gender-specific impact of these SNPs under the recessive genetic model revealed that SNPs rs10740055, rs10994982, and rs6479779 in females, and rs10821938 and rs7923074 in males were significantly associated with acute lymphoblastic leukemia risk. Under the dominant model, SNPs rs7073837, rs10821936, rs7896246, and rs6479778 in males only showed striking association with acute lymphoblastic leukemia. The additive model revealed that SNPs with significant association with acute lymphoblastic leukemia were rs10821936 (both males and females); rs7073837, rs10740055, rs10994982, and rs4948487 (females only); and rs7089424, rs7896246, rs10821938, and rs7923074 (males only). In addition, the ARID5B haplotype block (CGAACACAA) showed a higher risk for acute lymphoblastic leukemia. The haplotype (CCCGACTGC) was associated with protection against acute lymphoblastic leukemia. In conclusion, our study has shown that ARID5B variants are associated with acute lymphoblastic leukemia in Yemeni children with several gender biases of ARID5B single nucleotide polymorphisms reported.

A mediator model to predict workplace influenza vaccination behaviour--an application of the health action process approach.

PubMed

Ernsting, Anna; Gellert, Paul; Schneider, Michael; Lippke, Sonia

2013-01-01

Applying the health action process approach (HAPA) to vaccination behaviour as a single-event health behaviour to study vaccination adherence and its predictors in a worksite flu vaccination programme. A total of N = 823 employees participated in a longitudinal survey. Predictors (risk perception, self-efficacy, positive and negative outcome expectancies, intention and planning) were assessed at Time 1, and behaviour was assessed five months later at Time 2. Intention and planning were specified as mediators in a path analytical logistic regression model. Risk perception, self-efficacy and positive as well as negative outcome expectancies predicted intention (R² = .76). Intention and planning predicted subsequent behaviour, and planning mediated the relation between intention and vaccination behaviour (R² = .67). In addition, results suggested the adjustment of the theoretical model: risk perception and negative outcome expectancies showed direct effects on behaviour resulting in a significantly better model fit. Findings support the general applicability of the HAPA to vaccination behaviour and the importance of planning for translating intentions into behaviour. However, the adjusted model was superior and underlined the particular role of risk perception and negative outcome expectancies for vaccination behaviour to explain underlying mechanisms in vaccination behaviour.

Large-scale application of the flood damage model RAilway Infrastructure Loss (RAIL)

NASA Astrophysics Data System (ADS)

Kellermann, Patric; Schönberger, Christine; Thieken, Annegret H.

2016-11-01

Experience has shown that river floods can significantly hamper the reliability of railway networks and cause extensive structural damage and disruption. As a result, the national railway operator in Austria had to cope with financial losses of more than EUR 100 million due to flooding in recent years. Comprehensive information on potential flood risk hot spots as well as on expected flood damage in Austria is therefore needed for strategic flood risk management. In view of this, the flood damage model RAIL (RAilway Infrastructure Loss) was applied to estimate (1) the expected structural flood damage and (2) the resulting repair costs of railway infrastructure due to a 30-, 100- and 300-year flood in the Austrian Mur River catchment. The results were then used to calculate the expected annual damage of the railway subnetwork and subsequently analysed in terms of their sensitivity to key model assumptions. Additionally, the impact of risk aversion on the estimates was investigated, and the overall results were briefly discussed against the background of climate change and possibly resulting changes in flood risk. The findings indicate that the RAIL model is capable of supporting decision-making in risk management by providing comprehensive risk information on the catchment level. It is furthermore demonstrated that an increased risk aversion of the railway operator has a marked influence on flood damage estimates for the study area and, hence, should be considered with regard to the development of risk management strategies.

Developing a Screening Model to Establish Human Risk from Glacial Meltwater Release of Legacy Organochlorine Pollutants at the Silvretta Glacier in the Swiss Alps

NASA Astrophysics Data System (ADS)

Miner, K. R.

2017-12-01

Organochlorine pollutants (OCPs) banned globally by the Stockholm Convention in 2004 are reemerging from melting glaciers in numerous alpine ecosystems. Despite the known OCP influx from glaciers, a study of human risk from uptake of pesticides in glacial meltwater has never been attempted. Our study qualifies human uptake routes and quantifies risk utilizing published meltwater data from the Silvretta Glacier in the Swiss Alps in combination with methodology established by the US Environmental Protection Agency (EPA). Relatively high concentrations of OCPs in Silvretta glacier meltwater reflect proximity to use near high density populations and provide the best estimate of a 95th percentile human risk scenario. This screening level model assesses direct PCB risk to humans through consumption of fish tissue and meltwater. Our model shows a risk for both cancer and non-cancer disease impacts to children with lifetime exposure to glacial meltwater and an average local fish consumption. For adults with an abbreviated 30 year exposure timeframe, the risk for non-cancer effects is negligible and cancer effects are only barely above screening level. Populations that consume higher quantities of local fish are at greater risk, with additional challenges borne by children. Further direct study into the individual level risk to Swiss residents from glacial meltwater pollution is deemed necessary by our screening study.

Increased genetic risk for obesity in premature coronary artery disease.

PubMed

Cole, Christopher B; Nikpay, Majid; Stewart, Alexandre F R; McPherson, Ruth

2016-04-01

There is ongoing controversy as to whether obesity confers risk for CAD independently of associated risk factors including diabetes mellitus. We have carried out a Mendelian randomization study using a genetic risk score (GRS) for body mass index (BMI) based on 35 risk alleles to investigate this question in a population of 5831 early onset CAD cases without diabetes mellitus and 3832 elderly healthy control subjects, all of strictly European ancestry, with adjustment for traditional risk factors (TRFs). We then estimated the genetic correlation between these BMI and CAD (rg) by relating the pairwise genetic similarity matrix to a phenotypic covariance matrix between these two traits. GRSBMI significantly (P=2.12 × 10(-12)) associated with CAD status in a multivariate model adjusted for TRFs, with a per allele odds ratio (OR) of 1.06 (95% CI 1.042-1.076). The addition of GRSBMI to TRFs explained 0.75% of CAD variance and yielded a continuous net recombination index of 16.54% (95% CI=11.82-21.26%, P<0.0001). To test whether GRSBMI explained CAD status when adjusted for measured BMI, separate models were constructed in which the score and BMI were either included as covariates or not. The addition of BMI explained ~1.9% of CAD variance and GRSBMI plus BMI explained 2.65% of CAD variance. Finally, using bivariate restricted maximum likelihood analysis, we provide strong evidence of genome-wide pleiotropy between obesity and CAD. This analysis supports the hypothesis that obesity is a causal risk factor for CAD.

Explaining the low risk of preterm birth among arab americans in the United States: an analysis of 617451 births.

PubMed

El-Sayed, Abdulrahman M; Galea, Sandro

2009-03-01

Arab Americans have a lower risk for preterm birth than white Americans. We assessed factors that may contribute to the association between ethnicity and preterm birth risk in Michigan, the state with the largest concentration of Arab Americans in the United States. Factors assessed as potential contributors to the ethnicity/preterm birth risk association were maternal age, parity, education, marital status, tobacco use, and maternal birthplace. Data were collected about all births in Michigan between 2000 and 2005. Stratified analyses, trivariate analyses, and manual stepwise logistic regression model building were used to assess potential contributors to the ethnicity/preterm birth risk association. Arab ethnicity was associated with lower preterm birth risk compared with non-Arab white subjects in the unadjusted model. Maternal birthplace inside or outside the United States explained 0.17 of the difference in preterm birth risk between Arab ethnicity and non-Arab white mothers; ethnic differences in marital status and tobacco use explained less of the observed ethnic difference in preterm birth risk. In the final model adjusted for all explanatory variables, Arab ethnicity was no longer associated with preterm birth risk. Maternal birthplace, marital status, and tobacco use may contribute to the preterm birth risk difference between Arab ethnicity and non-Arab white mothers. Additional work is needed to consider the mechanisms relating factors such as maternal birthplace and marital status to ethnic differences in preterm birth risk.

A flexible count data regression model for risk analysis.

PubMed

Guikema, Seth D; Coffelt, Jeremy P; Goffelt, Jeremy P

2008-02-01

In many cases, risk and reliability analyses involve estimating the probabilities of discrete events such as hardware failures and occurrences of disease or death. There is often additional information in the form of explanatory variables that can be used to help estimate the likelihood of different numbers of events in the future through the use of an appropriate regression model, such as a generalized linear model. However, existing generalized linear models (GLM) are limited in their ability to handle the types of variance structures often encountered in using count data in risk and reliability analysis. In particular, standard models cannot handle both underdispersed data (variance less than the mean) and overdispersed data (variance greater than the mean) in a single coherent modeling framework. This article presents a new GLM based on a reformulation of the Conway-Maxwell Poisson (COM) distribution that is useful for both underdispersed and overdispersed count data and demonstrates this model by applying it to the assessment of electric power system reliability. The results show that the proposed COM GLM can provide as good of fits to data as the commonly used existing models for overdispered data sets while outperforming these commonly used models for underdispersed data sets.

Peer rejection, aggressive or withdrawn behavior, and psychological maladjustment from ages 5 to 12: an examination of four predictive models.

PubMed

Ladd, Gary W

2006-01-01

Findings yielded a comprehensive portrait of the predictive relations among children's aggressive or withdrawn behaviors, peer rejection, and psychological maladjustment across the 5-12 age period. Examination of peer rejection in different variable contexts and across repeated intervals throughout childhood revealed differences in the timing, strength, and consistency of this risk factor as a distinct (additive) predictor of externalizing versus internalizing problems. In conjunction with aggressive behavior, peer rejection proved to be a stronger additive predictor of externalizing problems during early rather than later childhood. Relative to withdrawn behavior, rejection's efficacy as a distinct predictor of internalizing problems was significant early in childhood and increased progressively thereafter. These additive path models fit the data better than did disorder-driven or transactional models.

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

Impact of wall thickness and saccular geometry on the computational wall stress of descending thoracic aortic aneurysms.

PubMed

Shang, Eric K; Nathan, Derek P; Sprinkle, Shanna R; Fairman, Ronald M; Bavaria, Joseph E; Gorman, Robert C; Gorman, Joseph H; Jackson, Benjamin M

2013-09-10

Wall stress calculated using finite element analysis has been used to predict rupture risk of aortic aneurysms. Prior models often assume uniform aortic wall thickness and fusiform geometry. We examined the effects of including local wall thickness, intraluminal thrombus, calcifications, and saccular geometry on peak wall stress (PWS) in finite element analysis of descending thoracic aortic aneurysms. Computed tomographic angiography of descending thoracic aortic aneurysms (n=10 total, 5 fusiform and 5 saccular) underwent 3-dimensional reconstruction with custom algorithms. For each aneurysm, an initial model was constructed with uniform wall thickness. Experimental models explored the addition of variable wall thickness, calcifications, and intraluminal thrombus. Each model was loaded with 120 mm Hg pressure, and von Mises PWS was computed. The mean PWS of uniform wall thickness models was 410 ± 111 kPa. The imposition of variable wall thickness increased PWS (481 ± 126 kPa, P<0.001). Although the addition of calcifications was not statistically significant (506 ± 126 kPa, P=0.07), the addition of intraluminal thrombus to variable wall thickness (359 ± 86 kPa, P ≤ 0.001) reduced PWS. A final model incorporating all features also reduced PWS (368 ± 88 kPa, P<0.001). Saccular geometry did not increase diameter-normalized stress in the final model (77 ± 7 versus 67 ± 12 kPa/cm, P=0.22). Incorporation of local wall thickness can significantly increase PWS in finite element analysis models of thoracic aortic aneurysms. Incorporating variable wall thickness, intraluminal thrombus, and calcifications significantly impacts computed PWS of thoracic aneurysms; sophisticated models may, therefore, be more accurate in assessing rupture risk. Saccular aneurysms did not demonstrate a significantly higher normalized PWS than fusiform aneurysms.

Bankruptcy prediction for credit risk using neural networks: a survey and new results.

PubMed

Atiya, A F

2001-01-01

The prediction of corporate bankruptcies is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. This work presents two contributions. First we review the topic of bankruptcy prediction, with emphasis on neural-network (NN) models. Second, we develop an NN bankruptcy prediction model. Inspired by one of the traditional credit risk models developed by Merton (1974), we propose novel indicators for the NN system. We show that the use of these indicators in addition to traditional financial ratio indicators provides a significant improvement in the (out-of-sample) prediction accuracy (from 81.46% to 85.5% for a three-year-ahead forecast).

Software risk management through independent verification and validation

NASA Technical Reports Server (NTRS)

Callahan, John R.; Zhou, Tong C.; Wood, Ralph

1995-01-01

Software project managers need tools to estimate and track project goals in a continuous fashion before, during, and after development of a system. In addition, they need an ability to compare the current project status with past project profiles to validate management intuition, identify problems, and then direct appropriate resources to the sources of problems. This paper describes a measurement-based approach to calculating the risk inherent in meeting project goals that leverages past project metrics and existing estimation and tracking models. We introduce the IV&V Goal/Questions/Metrics model, explain its use in the software development life cycle, and describe our attempts to validate the model through the reverse engineering of existing projects.

Risk Assessment in Relation to the Effect of Climate Change on Water Shortage in the Taichung Area

NASA Astrophysics Data System (ADS)

Hsiao, J.; Chang, L.; Ho, C.; Niu, M.

2010-12-01

Rapid economic development has stimulated a worldwide greenhouse effect and induced global climate change. Global climate change has increased the range of variation in the quantity of regional river flows between wet and dry seasons, which effects the management of regional water resources. Consequently, the influence of climate change has become an important issue in the management of regional water resources. In this study, the Monte Carlo simulation method was applied to risk analysis of shortage of water supply in the Taichung area. This study proposed a simulation model that integrated three models: weather generator model, surface runoff model, and water distribution model. The proposed model was used to evaluate the efficiency of the current water supply system and the potential effectiveness of two additional plans for water supply: the “artificial lakes” plan and the “cross-basin water transport” plan. A first-order Markov Chain method and two probability distribution models, exponential distribution and normal distribution, were used in the weather generator model. In the surface runoff model, researchers selected the Generalized Watershed Loading Function model (GWLF) to simulate the relationship between quantity of rainfall and basin outflow. A system dynamics model (SD) was applied to the water distribution model. Results of the simulation indicated that climate change could increase the annual quantity of river flow in the Dachia River and Daan River basins. However, climate change could also increase the difference in the quantity of river flow between wet and dry seasons. Simulation results showed that in current system case or in the additional plan cases, shortage status of water for both public and agricultural uses with conditions of climate change will be mostly worse than that without conditions of climate change except for the shortage status for the public use in the current system case. With or without considering the effect of climate change, the additional plans, especially the “cross-basin water transport” plan, for water supply could significantly increase the supply of water for public use. The proposed simulation model and results of analysis in this study could provide valuable reference for decision-makers in regards to risk analysis of regional water supply.

Default risk modeling beyond the first-passage approximation: extended Black-Cox model.

PubMed

Katz, Yuri A; Shokhirev, Nikolai V

2010-07-01

We develop a generalization of the Black-Cox structural model of default risk. The extended model captures uncertainty related to firm's ability to avoid default even if company's liabilities momentarily exceeding its assets. Diffusion in a linear potential with the radiation boundary condition is used to mimic a company's default process. The exact solution of the corresponding Fokker-Planck equation allows for derivation of analytical expressions for the cumulative probability of default and the relevant hazard rate. Obtained closed formulas fit well the historical data on global corporate defaults and demonstrate the split behavior of credit spreads for bonds of companies in different categories of speculative-grade ratings with varying time to maturity. Introduction of the finite rate of default at the boundary improves valuation of credit risk for short time horizons, which is the key advantage of the proposed model. We also consider the influence of uncertainty in the initial distance to the default barrier on the outcome of the model and demonstrate that this additional source of incomplete information may be responsible for nonzero credit spreads for bonds with very short time to maturity.

Hierarchical dose response of E. coli O157:H7 from human outbreaks incorporating heterogeneity in exposure.

PubMed

Teunis, P F M; Ogden, I D; Strachan, N J C

2008-06-01

The infectivity of pathogenic microorganisms is a key factor in the transmission of an infectious disease in a susceptible population. Microbial infectivity is generally estimated from dose-response studies in human volunteers. This can only be done with mildly pathogenic organisms. Here a hierarchical Beta-Poisson dose-response model is developed utilizing data from human outbreaks. On the lowest level each outbreak is modelled separately and these are then combined at a second level to produce a group dose-response relation. The distribution of foodborne pathogens often shows strong heterogeneity and this is incorporated by introducing an additional parameter to the dose-response model, accounting for the degree of overdispersion relative to Poisson distribution. It was found that heterogeneity considerably influences the shape of the dose-response relationship and increases uncertainty in predicted risk. This uncertainty is greater than previously reported surrogate and outbreak models using a single level of analysis. Monte Carlo parameter samples (alpha, beta of the Beta-Poisson model) can be readily incorporated in risk assessment models built using tools such as S-plus and @ Risk.

Air pollution and health risks due to vehicle traffic.

PubMed

Zhang, Kai; Batterman, Stuart

2013-04-15

Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed-volume relationship, the California Line Source Dispersion Model, an empirical NO2-NOx relationship, estimated travel time changes during congestion, and concentration-response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, "U" shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2-NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties. Copyright © 2013 Elsevier B.V. All rights reserved.

Air pollution and health risks due to vehicle traffic

PubMed Central

Zhang, Kai; Batterman, Stuart

2014-01-01

Traffic congestion increases vehicle emissions and degrades ambient air quality, and recent studies have shown excess morbidity and mortality for drivers, commuters and individuals living near major roadways. Presently, our understanding of the air pollution impacts from congestion on roads is very limited. This study demonstrates an approach to characterize risks of traffic for on- and near-road populations. Simulation modeling was used to estimate on- and near-road NO2 concentrations and health risks for freeway and arterial scenarios attributable to traffic for different traffic volumes during rush hour periods. The modeling used emission factors from two different models (Comprehensive Modal Emissions Model and Motor Vehicle Emissions Factor Model version 6.2), an empirical traffic speed–volume relationship, the California Line Source Dispersion Model, an empirical NO2–NOx relationship, estimated travel time changes during congestion, and concentration–response relationships from the literature, which give emergency doctor visits, hospital admissions and mortality attributed to NO2 exposure. An incremental analysis, which expresses the change in health risks for small increases in traffic volume, showed non-linear effects. For a freeway, “U” shaped trends of incremental risks were predicted for on-road populations, and incremental risks are flat at low traffic volumes for near-road populations. For an arterial road, incremental risks increased sharply for both on- and near-road populations as traffic increased. These patterns result from changes in emission factors, the NO2–NOx relationship, the travel delay for the on-road population, and the extended duration of rush hour for the near-road population. This study suggests that health risks from congestion are potentially significant, and that additional traffic can significantly increase risks, depending on the type of road and other factors. Further, evaluations of risk associated with congestion must consider travel time, the duration of rush-hour, congestion-specific emission estimates, and uncertainties. PMID:23500830

Price returns efficiency of the Shanghai A-Shares

NASA Astrophysics Data System (ADS)

Long, Wang Jiang; Jaaman, Saiful Hafizah; Samsudin, Humaida Banu

2014-06-01

Beta measured from the capital asset pricing model (CAPM) is the most widely used risk to estimate expected return. In this paper factors that influence Shanghai A-share stock return based on CAPM are explored and investigated. Price data of 312 companies listed on Shanghai Stock Exchange (SSE) from the year 2000 to 2011 are investigated. This study employed the Fama-MacBeth cross-sectional method to avoid weakness of traditional CAPM. In addition, this study improves the model by adjusting missing data. Findings of this study justifies that systematic risk can explain the portfolios' returns of China SSE stock market.

Modelling of individual subject ozone exposure response kinetics.

PubMed

Schelegle, Edward S; Adams, William C; Walby, William F; Marion, M Susan

2012-06-01

A better understanding of individual subject ozone (O(3)) exposure response kinetics will provide insight into how to improve models used in the risk assessment of ambient ozone exposure. To develop a simple two compartment exposure-response model that describes individual subject decrements in forced expiratory volume in one second (FEV(1)) induced by the acute inhalation of O(3) lasting up to 8 h. FEV(1) measurements of 220 subjects who participated in 14 previously completed studies were fit to the model using both particle swarm and nonlinear least squares optimization techniques to identify three subject-specific coefficients producing minimum "global" and local errors, respectively. Observed and predicted decrements in FEV(1) of the 220 subjects were used for validation of the model. Further validation was provided by comparing the observed O(3)-induced FEV(1) decrements in an additional eight studies with predicted values obtained using model coefficients estimated from the 220 subjects used in cross validation. Overall the individual subject measured and modeled FEV(1) decrements were highly correlated (mean R(2) of 0.69 ± 0.24). In addition, it was shown that a matrix of individual subject model coefficients can be used to predict the mean and variance of group decrements in FEV(1). This modeling approach provides insight into individual subject O(3) exposure response kinetics and provides a potential starting point for improving the risk assessment of environmental O(3) exposure.

Quantifying introgression risk with realistic population genetics.

PubMed

Ghosh, Atiyo; Meirmans, Patrick G; Haccou, Patsy

2012-12-07

Introgression is the permanent incorporation of genes from the genome of one population into another. This can have severe consequences, such as extinction of endemic species, or the spread of transgenes. Quantification of the risk of introgression is an important component of genetically modified crop regulation. Most theoretical introgression studies aimed at such quantification disregard one or more of the most important factors concerning introgression: realistic genetical mechanisms, repeated invasions and stochasticity. In addition, the use of linkage as a risk mitigation strategy has not been studied properly yet with genetic introgression models. Current genetic introgression studies fail to take repeated invasions and demographic stochasticity into account properly, and use incorrect measures of introgression risk that can be manipulated by arbitrary choices. In this study, we present proper methods for risk quantification that overcome these difficulties. We generalize a probabilistic risk measure, the so-called hazard rate of introgression, for application to introgression models with complex genetics and small natural population sizes. We illustrate the method by studying the effects of linkage and recombination on transgene introgression risk at different population sizes.

Quantifying introgression risk with realistic population genetics

PubMed Central

Ghosh, Atiyo; Meirmans, Patrick G.; Haccou, Patsy

2012-01-01

Introgression is the permanent incorporation of genes from the genome of one population into another. This can have severe consequences, such as extinction of endemic species, or the spread of transgenes. Quantification of the risk of introgression is an important component of genetically modified crop regulation. Most theoretical introgression studies aimed at such quantification disregard one or more of the most important factors concerning introgression: realistic genetical mechanisms, repeated invasions and stochasticity. In addition, the use of linkage as a risk mitigation strategy has not been studied properly yet with genetic introgression models. Current genetic introgression studies fail to take repeated invasions and demographic stochasticity into account properly, and use incorrect measures of introgression risk that can be manipulated by arbitrary choices. In this study, we present proper methods for risk quantification that overcome these difficulties. We generalize a probabilistic risk measure, the so-called hazard rate of introgression, for application to introgression models with complex genetics and small natural population sizes. We illustrate the method by studying the effects of linkage and recombination on transgene introgression risk at different population sizes. PMID:23055068

Tourism sector preparedness in zones with a high seismic risk: Case study of the Capital Region of Japan

NASA Astrophysics Data System (ADS)

Lihui, W.; Wang, D.

2017-12-01

Japan is a country highly vulnerable to natural disasters, especially earthquakes. Tourism, as a strategic industry in Japan, is especially vulnerable to destructive earthquake disasters owing to the characteristics of vulnerability, sensitivity and substitutability. Here we aim to provide theoretical understanding of the perception and responses of tourism managers towards damaging disasters in tourism destinations with high seismic risks. We conducted surveys among the mangers of tourism businesses in the capital area of Japan in 2014 and applied structural equation modeling techniques to empirically test the proposed model with four latent variables, which are risk perception, threat knowledge, disaster preparedness and earthquake preparedness. Our results show that threat knowledge affects risk perception and disaster preparedness positively. In addition, disaster preparedness positively affects earthquake preparedness. However, the proposed paths from risk perception to disaster preparedness, risk perception to earthquake preparedness, and threat knowledge to earthquake preparedness were not statistically significant. Our results may provide references for policymakers in promoting crisis planning in tourism destination with high seismic risks.

Risk-trading in flood management: An economic model.

PubMed

Chang, Chiung Ting

2017-09-15

Although flood management is no longer exclusively a topic of engineering, flood mitigation continues to be associated with hard engineering options. Flood adaptation or the capacity to adapt to flood risk, as well as a demand for internalizing externalities caused by flood risk between regions, complicate flood management activities. Even though integrated river basin management has long been recommended to resolve the above issues, it has proven difficult to apply widely, and sometimes even to bring into existence. This article explores how internalization of externalities as well as the realization of integrated river basin management can be encouraged via the use of a market-based approach, namely a flood risk trading program. In addition to maintaining efficiency of optimal resource allocation, a flood risk trading program may also provide a more equitable distribution of benefits by facilitating decentralization. This article employs a graphical analysis to show how flood risk trading can be implemented to encourage mitigation measures that increase infiltration and storage capacity. A theoretical model is presented to demonstrate the economic conditions necessary for flood risk trading. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estrogen in cardiovascular disease during systemic lupus erythematosus.

PubMed

Gilbert, Emily L; Ryan, Michael J

2014-12-01

Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease that disproportionately affects women during their childbearing years. Cardiovascular disease is the leading cause of mortality in this patient population at an age when women often have low cardiovascular risk. Hypertension is a major cardiovascular disease risk factor, and its prevalence is markedly increased in women with SLE. Estrogen has traditionally been implicated in SLE disease progression because of the prevalence of the disease in women; however, its role in cardiovascular risk factors such as hypertension is unclear. The objective of this review is to discuss evidence for the role of estrogen in both human and murine SLE with emphasis on the effect of estrogen on cardiovascular risk factors, including hypertension. PubMed was used to search for articles with terms related to estradiol and SLE. The references of retrieved publications were also reviewed. The potential permissive role of estrogen in SLE development is supported by studies from experimental animal models of lupus in which early removal of estrogen or its effects leads to attenuation of SLE disease parameters, including autoantibody production and renal injury. However, data about the role of estrogens in human SLE are much less clear, with most studies not reaching firm conclusions about positive or negative outcomes after hormonal manipulations involving estrogen during SLE (ie, oral contraceptives, hormone therapy). Significant gaps in knowledge remain about the effect of estrogen on cardiovascular risk factors during SLE. Studies in women with SLE were not designed to determine the effect of estrogen or hormone therapy on blood pressure even though hypertension is highly prevalent, and risk of premature ovarian failure could necessitate use of hormone therapy in women with SLE. Recent evidence from an experimental animal model of lupus found that estrogen may protect against cardiovascular risk factors in adulthood. In addition, increasing evidence suggests that estrogen may have distinct temporal effects on cardiovascular risk factors during SLE. Data from experimental models of lupus suggest that estrogens may have an important permissive role for developing SLE early in life. However, their role in adulthood remains unclear, particularly for the effect on cardiovascular disease and its risk factors. Additional work is needed to understand the effect of estrogens in human SLE, and preclinical studies in experimental models of SLE may contribute important mechanistic insight to further advance the field. Copyright © 2014 Elsevier HS Journals, Inc. All rights reserved.

Estrogen in Cardiovascular Disease during Systemic Lupus Erythematosus

PubMed Central

Gilbert, Emily L.; Ryan, Michael J.

2015-01-01

Purpose Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease that disproportionately affects women during their childbearing years. Cardiovascular disease is the leading cause of mortality in this patient population at an age when women often have low cardiovascular risk. Hypertension is a major cardiovascular disease risk factor, and its prevalence is markedly increased in women with SLE. Estrogen has traditionally been implicated in SLE disease progression because of the prevalence of the disease in women; however, its role in cardiovascular risk factors such as hypertension is unclear. The objective of this review is to discuss evidence for the role of estrogen in both human and murine SLE with emphasis on the effect of estrogen on cardiovascular risk factors, including hypertension. Methods PubMed was used to search for articles with terms related to estradiol and SLE. The references of retrieved publications were also reviewed. Findings The potential permissive role of estrogen in SLE development is supported by studies from experimental animal models of lupus in which early removal of estrogen or its effects leads to attenuation of SLE disease parameters, including autoantibody production and renal injury. However, data about the role of estrogens in human SLE are much less clear, with most studies not reaching firm conclusions about positive or negative outcomes after hormonal manipulations involving estrogen during SLE (ie, oral contraceptives, hormone therapy). Significant gaps in knowledge remain about the effect of estrogen on cardiovascular risk factors during SLE. Studies in women with SLE were not designed to determine the effect of estrogen or hormone therapy on blood pressure even though hypertension is highly prevalent, and risk of premature ovarian failure could necessitate use of hormone therapy in women with SLE. Recent evidence from an experimental animal model of lupus found that estrogen may protect against cardiovascular risk factors in adulthood. In addition, increasing evidence suggests that estrogen may have distinct temporal effects on cardiovascular risk factors during SLE. Implications Data from experimental models of lupus suggest that estrogens may have an important permissive role for developing SLE early in life. However, their role in adulthood remains unclear, particularly for the effect on cardiovascular disease and its risk factors. Additional work is needed to understand the effect of estrogens in human SLE, and preclinical studies in experimental models of SLE may contribute important mechanistic insight to further advance the field. PMID:25194860

Methamphetamine Use among Rural White and Native American Adolescents: An Application of the Stress Process Model

ERIC Educational Resources Information Center

Eitle, David J.; Eitle, Tamela McNulty

2013-01-01

Methamphetamine use has been identified as having significant adverse health consequences, yet we know little about the correlates of its use. Additionally, research has found that Native Americans are at the highest risk for methamphetamine use. Our exploratory study, informed by the stress process model, examines stress and stress buffering…

How are flood risk estimates affected by the choice of return-periods?

NASA Astrophysics Data System (ADS)

Ward, P. J.; de Moel, H.; Aerts, J. C. J. H.

2011-12-01

Flood management is more and more adopting a risk based approach, whereby flood risk is the product of the probability and consequences of flooding. One of the most common approaches in flood risk assessment is to estimate the damage that would occur for floods of several exceedance probabilities (or return periods), to plot these on an exceedance probability-loss curve (risk curve) and to estimate risk as the area under the curve. However, there is little insight into how the selection of the return-periods (which ones and how many) used to calculate risk actually affects the final risk calculation. To gain such insights, we developed and validated an inundation model capable of rapidly simulating inundation extent and depth, and dynamically coupled this to an existing damage model. The method was applied to a section of the River Meuse in the southeast of the Netherlands. Firstly, we estimated risk based on a risk curve using yearly return periods from 2 to 10 000 yr (€ 34 million p.a.). We found that the overall risk is greatly affected by the number of return periods used to construct the risk curve, with over-estimations of annual risk between 33% and 100% when only three return periods are used. In addition, binary assumptions on dike failure can have a large effect (a factor two difference) on risk estimates. Also, the minimum and maximum return period considered in the curve affects the risk estimate considerably. The results suggest that more research is needed to develop relatively simple inundation models that can be used to produce large numbers of inundation maps, complementary to more complex 2-D-3-D hydrodynamic models. It also suggests that research into flood risk could benefit by paying more attention to the damage caused by relatively high probability floods.

Suicide Risk Among College Student. The Intersection of Sexual Orientation and Race.

PubMed

Shadick, Richard; Backus Dagirmanjian, Faedra; Barbot, Baptiste

2015-01-01

Research on young adults in the general population has identified a relationship between sexual minority identification and risk for suicide. Differential rates of suicidal ideation and attempts have also been found across racial and ethnic groups. This study examined risk for suicide among university students, based on membership in one or more marginalized groups (sexual minority and racial minority identification). Data were collected from first-year college students (N = 4,345) at an urban university. Structural equation modeling was employed to model a suicidality construct, based on which a "risk for suicide" category system was derived. Chi-square and logistic regression analyses were then conducted to estimate the relationship between the background variables of interest and suicide risk. Students who identified as lesbian, gay, or bisexual (LGB) were associated with higher suicide risk than their heterosexual peers. Students of color were slightly less at risk than their heterosexual peers. However, LGB students of color were associated with elevated suicide risk relative to heterosexual peers. Results indicate that belonging to multiple marginalized groups may increase one's risk for suicide, though these effects are not simply additive. Findings highlight the complexity of the intersection between marginalized identities and suicidality.

Gender-Dependent Association of FTO Polymorphisms with Body Mass Index in Mexicans

PubMed Central

Saldaña-Alvarez, Yolanda; Salas-Martínez, María Guadalupe; García-Ortiz, Humberto; Luckie-Duque, Angélica; García-Cárdenas, Gustavo; Vicenteño-Ayala, Hermenegildo; Cordova, Emilio J.; Esparza-Aguilar, Marcelino; Contreras-Cubas, Cecilia; Carnevale, Alessandra; Chávez-Saldaña, Margarita; Orozco, Lorena

2016-01-01

To evaluate the associations between six single-nucleotide polymorphisms (SNPs) in intron 1 of FTO and body mass index (BMI), a case-control association study of 2314 unrelated Mexican-Mestizo adult subjects was performed. The association between each SNP and BMI was tested using logistic and linear regression adjusted for age, gender, and ancestry and assuming additive, recessive, and dominant effects of the minor allele. Association analysis after BMI stratification showed that all five FTO SNPs (rs1121980, rs17817449, rs3751812, rs9930506, and rs17817449), were significantly associated with obesity class II/III under an additive model (P<0.05). Interestingly, we also documented a genetic model-dependent influence of gender on the effect of FTO variants on increased BMI. Two SNPs were specifically associated in males under a dominant model, while the remainder were associated with females under additive and recessive models (P<0.05). The SNP rs9930506 showed the highest increased in obesity risk in females (odds ratio = 4.4). Linear regression using BMI as a continuous trait also revealed differential FTO SNP contributions. Homozygous individuals for the risk alleles of rs17817449, rs3751812, and rs9930506 were on average 2.18 kg/m2 heavier than homozygous for the wild-type alleles; rs1121980 and rs8044769 showed significant but less-strong effects on BMI (1.54 kg/m2 and 0.9 kg/m2, respectively). Remarkably, rs9930506 also exhibited positive interactions with age and BMI in a gender-dependent manner. Women carrying the minor allele of this variant have a significant increase in BMI by year (0.42 kg/m2, P = 1.17 x 10−10). Linear regression haplotype analysis under an additive model, confirmed that the TGTGC haplotype harboring all five minor alleles, increased the BMI of carriers by 2.36 kg/m2 (P = 1.15 x 10−5). Our data suggest that FTO SNPs make differential contributions to obesity risk and support the hypothesis that gender differences in the mechanisms involving these variants may contribute to disease development. PMID:26726774

Dynamical insurance models with investment: Constrained singular problems for integrodifferential equations

NASA Astrophysics Data System (ADS)

Belkina, T. A.; Konyukhova, N. B.; Kurochkin, S. V.

2016-01-01

Previous and new results are used to compare two mathematical insurance models with identical insurance company strategies in a financial market, namely, when the entire current surplus or its constant fraction is invested in risky assets (stocks), while the rest of the surplus is invested in a risk-free asset (bank account). Model I is the classical Cramér-Lundberg risk model with an exponential claim size distribution. Model II is a modification of the classical risk model (risk process with stochastic premiums) with exponential distributions of claim and premium sizes. For the survival probability of an insurance company over infinite time (as a function of its initial surplus), there arise singular problems for second-order linear integrodifferential equations (IDEs) defined on a semiinfinite interval and having nonintegrable singularities at zero: model I leads to a singular constrained initial value problem for an IDE with a Volterra integral operator, while II model leads to a more complicated nonlocal constrained problem for an IDE with a non-Volterra integral operator. A brief overview of previous results for these two problems depending on several positive parameters is given, and new results are presented. Additional results are concerned with the formulation, analysis, and numerical study of "degenerate" problems for both models, i.e., problems in which some of the IDE parameters vanish; moreover, passages to the limit with respect to the parameters through which we proceed from the original problems to the degenerate ones are singular for small and/or large argument values. Such problems are of mathematical and practical interest in themselves. Along with insurance models without investment, they describe the case of surplus completely invested in risk-free assets, as well as some noninsurance models of surplus dynamics, for example, charity-type models.

Do Parents and Peers Matter? A Prospective Socio-Ecological Examination of Substance Use and Sexual Risk among African American Youth

ERIC Educational Resources Information Center

Elkington, Katherine S.; Bauermeister, Jose A.; Zimmerman, Marc A.

2011-01-01

We examined the direct contribution of parent and peer risk and promotive factors on youth condom use trajectories, in addition to the indirect influence of these factors via youth's substance use over four years in a sample of urban, African American youth (N = 679; 51% female; M = 14.86 years; SD = 0.65). Growth curve modeling was used to…

The role of fine-grained annotations in supervised recognition of risk factors for heart disease from EHRs.

PubMed

Roberts, Kirk; Shooshan, Sonya E; Rodriguez, Laritza; Abhyankar, Swapna; Kilicoglu, Halil; Demner-Fushman, Dina

2015-12-01

This paper describes a supervised machine learning approach for identifying heart disease risk factors in clinical text, and assessing the impact of annotation granularity and quality on the system's ability to recognize these risk factors. We utilize a series of support vector machine models in conjunction with manually built lexicons to classify triggers specific to each risk factor. The features used for classification were quite simple, utilizing only lexical information and ignoring higher-level linguistic information such as syntax and semantics. Instead, we incorporated high-quality data to train the models by annotating additional information on top of a standard corpus. Despite the relative simplicity of the system, it achieves the highest scores (micro- and macro-F1, and micro- and macro-recall) out of the 20 participants in the 2014 i2b2/UTHealth Shared Task. This system obtains a micro- (macro-) precision of 0.8951 (0.8965), recall of 0.9625 (0.9611), and F1-measure of 0.9276 (0.9277). Additionally, we perform a series of experiments to assess the value of the annotated data we created. These experiments show how manually-labeled negative annotations can improve information extraction performance, demonstrating the importance of high-quality, fine-grained natural language annotations. Copyright © 2015 Elsevier Inc. All rights reserved.

A Regularized Deep Learning Approach for Clinical Risk Prediction of Acute Coronary Syndrome Using Electronic Health Records.

PubMed

Huang, Zhengxing; Dong, Wei; Duan, Huilong; Liu, Jiquan

2018-05-01

Acute coronary syndrome (ACS), as a common and severe cardiovascular disease, is a leading cause of death and the principal cause of serious long-term disability globally. Clinical risk prediction of ACS is important for early intervention and treatment. Existing ACS risk scoring models are based mainly on a small set of hand-picked risk factors and often dichotomize predictive variables to simplify the score calculation. This study develops a regularized stacked denoising autoencoder (SDAE) model to stratify clinical risks of ACS patients from a large volume of electronic health records (EHR). To capture characteristics of patients at similar risk levels, and preserve the discriminating information across different risk levels, two constraints are added on SDAE to make the reconstructed feature representations contain more risk information of patients, which contribute to a better clinical risk prediction result. We validate our approach on a real clinical dataset consisting of 3464 ACS patient samples. The performance of our approach for predicting ACS risk remains robust and reaches 0.868 and 0.73 in terms of both AUC and accuracy, respectively. The obtained results show that the proposed approach achieves a competitive performance compared to state-of-the-art models in dealing with the clinical risk prediction problem. In addition, our approach can extract informative risk factors of ACS via a reconstructive learning strategy. Some of these extracted risk factors are not only consistent with existing medical domain knowledge, but also contain suggestive hypotheses that could be validated by further investigations in the medical domain.

Heat Waves and Climate Change: Applying the Health Belief Model to Identify Predictors of Risk Perception and Adaptive Behaviours in Adelaide, Australia

PubMed Central

Akompab, Derick A.; Bi, Peng; Williams, Susan; Grant, Janet; Walker, Iain A.; Augoustinos, Martha

2013-01-01

Heat waves are considered a health risk and they are likely to increase in frequency, intensity and duration as a consequence of climate change. The effects of heat waves on human health could be reduced if individuals recognise the risks and adopt healthy behaviours during a heat wave. The purpose of this study was to determine the predictors of risk perception using a heat wave scenario and identify the constructs of the health belief model that could predict adaptive behaviours during a heat wave. A cross-sectional study was conducted during the summer of 2012 among a sample of persons aged between 30 to 69 years in Adelaide. Participants’ perceptions were assessed using the health belief model as a conceptual frame. Their knowledge about heat waves and adaptive behaviours during heat waves was also assessed. Logistic regression analyses were performed to determine the predictors of risk perception to a heat wave scenario and adaptive behaviours during a heat wave. Of the 267 participants, about half (50.9%) had a high risk perception to heat waves while 82.8% had good adaptive behaviours during a heat wave. Multivariate models found that age was a significant predictor of risk perception. In addition, participants who were married (OR = 0.21; 95% CI, 0.07–0.62), who earned a gross annual household income of ≥$60,000 (OR = 0.41; 95% CI, 0.17–0.94) and without a fan (OR = 0.29; 95% CI, 0.11–0.79) were less likely to have a high risk perception to heat waves. Those who were living with others (OR = 2.87; 95% CI, 1.19–6.90) were more likely to have a high risk perception to heat waves. On the other hand, participants with a high perceived benefit (OR = 2.14; 95% CI, 1.00–4.58), a high “cues to action” (OR = 3.71; 95% CI, 1.63–8.43), who had additional training or education after high school (OR = 2.65; 95% CI, 1.25–5.58) and who earned a gross annual household income of ≥$60,000 (OR = 2.66; 95% CI, 1.07–6.56) were more likely to have good adaptive behaviours during a heat wave. The health belief model could be useful to guide the design and implementation of interventions to promote adaptive behaviours during heat waves. PMID:23759952

A real-time heat strain risk classifier using heart rate and skin temperature.

PubMed

Buller, Mark J; Latzka, William A; Yokota, Miyo; Tharion, William J; Moran, Daniel S

2008-12-01

Heat injury is a real concern to workers engaged in physically demanding tasks in high heat strain environments. Several real-time physiological monitoring systems exist that can provide indices of heat strain, e.g. physiological strain index (PSI), and provide alerts to medical personnel. However, these systems depend on core temperature measurement using expensive, ingestible thermometer pills. Seeking a better solution, we suggest the use of a model which can identify the probability that individuals are 'at risk' from heat injury using non-invasive measures. The intent is for the system to identify individuals who need monitoring more closely or who should apply heat strain mitigation strategies. We generated a model that can identify 'at risk' (PSI 7.5) workers from measures of heart rate and chest skin temperature. The model was built using data from six previously published exercise studies in which some subjects wore chemical protective equipment. The model has an overall classification error rate of 10% with one false negative error (2.7%), and outperforms an earlier model and a least squares regression model with classification errors of 21% and 14%, respectively. Additionally, the model allows the classification criteria to be adjusted based on the task and acceptable level of risk. We conclude that the model could be a valuable part of a multi-faceted heat strain management system.

Extending the Strategy Based Risk Model Using the Delphi Method: An Application to the Validation Process for Research and Developmental (R&D) Satellites

DTIC Science & Technology

2009-12-01

correctly Risk before validation step: 41-60% - Is this too high/ low ? Why? Risk 8: Operational or data latency impacts based on relationship between...too high, too low , or correct. We also asked them to comment on why they felt this way. Finally, we left additional space on the survey for any...cost of each validation effort was too high, too low , or acceptable. They then gave us rationale for their beliefs. The second cost associated with

Considerations in deriving quantitative cancer criteria for inorganic arsenic exposure via inhalation.

PubMed

Lewis, Ari S; Beyer, Leslie A; Zu, Ke

2015-01-01

The inhalation unit risk (IUR) that currently exists in the United States Environmental Protection Agency's (US EPA's) Integrated Risk Information System was developed in 1984 based on studies examining the relationship between respiratory cancer and arsenic exposure in copper smelters from two US locations: the copper smelter in Anaconda, Montana, and the American Smelting And Refining COmpany (ASARCO) smelter in Tacoma, Washington. Since US EPA last conducted its assessment, additional data have become available from epidemiology and mechanistic studies. In addition, the California Air Resources Board, Texas Commission of Environmental Quality, and Dutch Expert Committee on Occupational Safety have all conducted new risk assessments. All three analyses, which calculated IURs based on respiratory/lung cancer mortality, generated IURs that are lower (i.e., less restrictive) than the current US EPA value of 4.3×10(-3) (μg/m(3))(-1). The IURs developed by these agencies, which vary more than 20-fold, are based on somewhat different studies and use different methodologies to address uncertainties in the underlying datasets. Despite these differences, all were developed based on a cumulative exposure metric assuming a low-dose linear dose-response relationship. In this paper, we contrast and compare the analyses conducted by these agencies and critically evaluate strengths and limitations inherent in the data and methodologies used to develop quantitative risk estimates. In addition, we consider how these data could be best used to assess risk at much lower levels of arsenic in air, such as those experienced by the general public. Given that the mode of action for arsenic supports a threshold effect, and epidemiological evidence suggests that the arsenic concentration in air is a reliable predictor of lung/respiratory cancer risk, we developed a quantitative cancer risk analysis using a nonlinear threshold model. Applying a nonlinear model to occupational data, we established points of departure based on both cumulative exposure (μg/m(3)-years) to arsenic and arsenic concentration (μg/m(3)) via inhalation. Using these values, one can assess the lifetime risk of respiratory cancer mortality associated with ambient air concentrations of arsenic for the general US population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Semi-Markov Approach to the Shipping Safety Modelling

NASA Astrophysics Data System (ADS)

Guze, Sambor; Smolarek, Leszek

2012-02-01

In the paper the navigational safety model of a ship on the open area has been studied under conditions of incomplete information. Moreover the structure of semi-Markov processes is used to analyse the stochastic ship safety according to the subjective acceptance of risk by the navigator. In addition, the navigator’s behaviour can be analysed by using the numerical simulation to estimate the probability of collision in the safety model.

Lifetime and 5 years risk of breast cancer and attributable risk factor according to Gail model in Iranian women

PubMed Central

Mohammadbeigi, Abolfazl; Mohammadsalehi, Narges; Valizadeh, Razieh; Momtaheni, Zeinab; Mokhtari, Mohsen; Ansari, Hossein

2015-01-01

Introduction: Breast cancer is the most commonly diagnosed cancers in women worldwide and in Iran. It is expected to account for 29% of all new cancers in women at 2015. This study aimed to assess the 5 years and lifetime risk of breast cancer according to Gail model, and to evaluate the effect of other additional risk factors on the Gail risk. Materials and Methods: A cross sectional study conducted on 296 women aged more than 34-year-old in Qom, Center of Iran. Breast Cancer Risk Assessment Tool calculated the Gail risk for each subject. Data were analyzed by paired t-test, independent t-test, and analysis of variance in bivariate approach to evaluate the effect of each factor on Gail risk. Multiple linear regression models with stepwise method were used to predict the effect of each variable on the Gail risk. Results: The mean age of the participants was 47.8 ± 8.8-year-old and 47% have Fars ethnicity. The 5 years and lifetime risk was 0.37 ± 0.18 and 4.48 ± 0.925%, respectively. It was lower than the average risk in same race and age women (P < 0.001). Being single, positive family history of breast cancer, positive history of biopsy, and radiotherapy as well as using nonhormonal contraceptives were related to higher lifetime risk (P < 0.05). Moreover, a significant direct correlation observed between lifetime risk and body mass index, age of first live birth, and menarche age. While an inversely correlation observed between lifetimes risk of breast cancer and total month of breast feeding duration and age. Conclusion: Based on our results, the 5 years and lifetime risk of breast cancer according to Gail model was lower than the same race and age. Moreover, by comparison with national epidemiologic indicators about morbidity and mortality of breast cancer, it seems that the Gail model overestimate the risk of breast cancer in Iranian women. PMID:26229355

Applying Latent Class Analysis to Risk Stratification for Perioperative Mortality in Patients Undergoing Intraabdominal General Surgery.

PubMed

Kim, Minjae; Wall, Melanie M; Li, Guohua

2016-07-01

Perioperative risk stratification is often performed using individual risk factors without consideration of the syndemic of these risk factors. We used latent class analysis (LCA) to identify the classes of comorbidities and risk factors associated with perioperative mortality in patients presenting for intraabdominal general surgery. The 2005 to 2010 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a cohort of patients undergoing intraabdominal general surgery. Risk factors and comorbidities were entered into LCA models to identify the latent classes, and individuals were assigned to a class based on the highest posterior probability of class membership. Relative risk regression was used to determine the associations between the latent classes and 30-day mortality, with adjustments for procedure. A 9-class model was fit using LCA on 466,177 observations. After combining classes with similar adjusted mortality risks, 5 risk classes were obtained. Compared with the class with average mortality risk (class 4), the risk ratios (95% confidence interval) ranged from 0.020 (0.014-0.027) in the lowest risk class (class 1) to 6.75 (6.46-7.02) in the highest risk class. After adjusting for procedure and ASA physical status, the latent classes remained significantly associated with 30-day mortality. The addition of the risk class variable to a model containing ASA physical status and surgical procedure demonstrated a significant increase in the area under the receiver operator characteristic curve (0.892 vs 0.915; P < 0.0001). Latent classes of risk factors and comorbidities in patients undergoing intraabdominal surgery are predictive of 30-day mortality independent of the ASA physical status and improve risk prediction with the ASA physical status.

The effect of binary mixtures of zinc, copper, cadmium, and nickel on the growth of the freshwater diatom Navicula pelliculosa and comparison with mixture toxicity model predictions.

PubMed

Nagai, Takashi; De Schamphelaere, Karel A C

2016-11-01

The authors investigated the effect of binary mixtures of zinc (Zn), copper (Cu), cadmium (Cd), and nickel (Ni) on the growth of a freshwater diatom, Navicula pelliculosa. A 7 × 7 full factorial experimental design (49 combinations in total) was used to test each binary metal mixture. A 3-d fluorescence microplate toxicity assay was used to test each combination. Mixture effects were predicted by concentration addition and independent action models based on a single-metal concentration-response relationship between the relative growth rate and the calculated free metal ion activity. Although the concentration addition model predicted the observed mixture toxicity significantly better than the independent action model for the Zn-Cu mixture, the independent action model predicted the observed mixture toxicity significantly better than the concentration addition model for the Cd-Zn, Cd-Ni, and Cd-Cu mixtures. For the Zn-Ni and Cu-Ni mixtures, it was unclear which of the 2 models was better. Statistical analysis concerning antagonistic/synergistic interactions showed that the concentration addition model is generally conservative (with the Zn-Ni mixture being the sole exception), indicating that the concentration addition model would be useful as a method for a conservative first-tier screening-level risk analysis of metal mixtures. Environ Toxicol Chem 2016;35:2765-2773. © 2016 SETAC. © 2016 SETAC.

Applying Additive Hazards Models for Analyzing Survival in Patients with Colorectal Cancer in Fars Province, Southern Iran

PubMed

Madadizadeh, Farzan; Ghanbarnejad, Amin; Ghavami, Vahid; Zare Bandamiri, Mohammad; Mohammadianpanah, Mohammad

2017-04-01

Introduction: Colorectal cancer (CRC) is a commonly fatal cancer that ranks as third worldwide and third and the fifth in Iranian women and men, respectively. There are several methods for analyzing time to event data. Additive hazards regression models take priority over the popular Cox proportional hazards model if the absolute hazard (risk) change instead of hazard ratio is of primary concern, or a proportionality assumption is not made. Methods: This study used data gathered from medical records of 561 colorectal cancer patients who were admitted to Namazi Hospital, Shiraz, Iran, during 2005 to 2010 and followed until December 2015. The nonparametric Aalen’s additive hazards model, semiparametric Lin and Ying’s additive hazards model and Cox proportional hazards model were applied for data analysis. The proportionality assumption for the Cox model was evaluated with a test based on the Schoenfeld residuals and for test goodness of fit in additive models, Cox-Snell residual plots were used. Analyses were performed with SAS 9.2 and R3.2 software. Results: The median follow-up time was 49 months. The five-year survival rate and the mean survival time after cancer diagnosis were 59.6% and 68.1±1.4 months, respectively. Multivariate analyses using Lin and Ying’s additive model and the Cox proportional model indicated that the age of diagnosis, site of tumor, stage, and proportion of positive lymph nodes, lymphovascular invasion and type of treatment were factors affecting survival of the CRC patients. Conclusion: Additive models are suitable alternatives to the Cox proportionality model if there is interest in evaluation of absolute hazard change, or no proportionality assumption is made. Creative Commons Attribution License

The Effects of Floods on the Incidence of Bacillary Dysentery in Baise (Guangxi Province, China) from 2004 to 2012.

PubMed

Liu, Xuena; Liu, Zhidong; Zhang, Ying; Jiang, Baofa

2017-02-12

Research shows potential effects of floods on intestinal infections. Baise, a city in Guangxi Province (China) had experienced several floods between 2004 and 2012 due to heavy and constant precipitation. This study aimed to examine the relationship between floods and the incidence of bacillary dysentery in Baise. A mixed generalized additive model and Spearman correlation were applied to analyze the relationship between monthly incidence of bacillary dysentery and 14 flood events with two severity levels. Data collected from 2004 to 2010 were utilized to estimate the parameters, whereas data from 2011 to 2012 were used to validate the model. There were in total 9255 cases of bacillary dysentery included in our analyses. According to the mixed generalized additive model, the relative risks (RR) of moderate and severe floods on the incidence of bacillary dysentery were 1.40 (95% confidence interval (CI): 1.16-1.69) and 1.78 (95% CI: 1.61-1.97), respectively. The regression analysis also indicated that the flood duration was negatively associated with the incidence of bacillary dysentery (with RR: 0.57, 95% CI: 0.40-0.86). Therfore, this research suggests that floods exert a significant part in enhancing the risk of bacillary dysentery in Baise. Moreover, severe floods have a higher proportional contribution to the incidence of bacillary dysentery than moderate floods. In addition, short-term floods may contribute more to the incidence of bacillary dysentery than a long-term flood. The findings from this research will provide more evidence to reduce health risks related to floods.

The Effects of Floods on the Incidence of Bacillary Dysentery in Baise (Guangxi Province, China) from 2004 to 2012

PubMed Central

Liu, Xuena; Liu, Zhidong; Zhang, Ying; Jiang, Baofa

2017-01-01

Research shows potential effects of floods on intestinal infections. Baise, a city in Guangxi Province (China) had experienced several floods between 2004 and 2012 due to heavy and constant precipitation. This study aimed to examine the relationship between floods and the incidence of bacillary dysentery in Baise. A mixed generalized additive model and Spearman correlation were applied to analyze the relationship between monthly incidence of bacillary dysentery and 14 flood events with two severity levels. Data collected from 2004 to 2010 were utilized to estimate the parameters, whereas data from 2011 to 2012 were used to validate the model. There were in total 9255 cases of bacillary dysentery included in our analyses. According to the mixed generalized additive model, the relative risks (RR) of moderate and severe floods on the incidence of bacillary dysentery were 1.40 (95% confidence interval (CI): 1.16–1.69) and 1.78 (95% CI: 1.61–1.97), respectively. The regression analysis also indicated that the flood duration was negatively associated with the incidence of bacillary dysentery (with RR: 0.57, 95% CI: 0.40–0.86). Therfore, this research suggests that floods exert a significant part in enhancing the risk of bacillary dysentery in Baise. Moreover, severe floods have a higher proportional contribution to the incidence of bacillary dysentery than moderate floods. In addition, short-term floods may contribute more to the incidence of bacillary dysentery than a long-term flood. The findings from this research will provide more evidence to reduce health risks related to floods. PMID:28208681

Psychosocial work environment and the risk of coronary heart disease.

PubMed

Peter, R; Siegrist, J

2000-06-01

Remarkable changes in the working situation have led to the increasing importance of psychomentally and socio-emotionally demanding conditions at work. With the help of theoretical models, those highly prevalent psychosocial work environments were conceptualized which influence the risk of coronary heart disease by enhanced activation of the autonomic nervous system. One of the most prominent theoretical approaches, the job strain model, and a more recent approach, the effort-reward imbalance model, are discussed in the paper. Findings from prospective and cross-sectional studies indicate that job strain and effort-reward imbalance at work define specific conditions of chronic work stress that are associated with an elevated risk of coronary heart disease (CHD). Respective multivariate odds-ratios range from 1.2 to 5.0 with respect to job strain, and from 1.5 to 6.1 with respect to effort-reward imbalance. These associations are explained neither by established behavioral or biomedical risk factors nor by physical and chemical hazards at work, rather they define independent, new work-related risk conditions. There is additional evidence that effort-reward imbalance may mediate the association of some traditional occupational exposures, such as shift work, with cardiovascular risk: in a cross-sectional study, prevalence odds ratios of hypertension and atherogenic lipids attributable to effort-reward imbalance were relatively highest among shiftworkers as compared to daytime workers. Preliminary results from intervention programs based on the theoretical models document favorable effects on health. Information derived from theoretical models on psychosocial work environment may help to better identify populations at risk and to develop and apply specific, theory-guided preventive activities in the future.

Integrating copper toxicity and climate change to understand extinction risk to two species of pond-breeding anurans.

PubMed

Weir, Scott M; Scott, David E; Salice, Christopher J; Lance, Stacey L

2016-09-01

Chemical contamination is often suggested as an important contributing factor to amphibian population declines, but direct links are rarely reported. Population modeling provides a quantitative method to integrate toxicity data with demographic data to understand the long-term effects of contaminants on population persistence. In this study we use laboratory-derived embryo and larval toxicity data for two anuran species to investigate the potential for toxicity to contribute to population declines. We use the southern toad (Anaxyrus terrestris) and the southern leopard frog (Lithobates sphenocephalus) as model species to investigate copper (Cu) toxicity. We use matrix models to project populations through time and quantify extinction risk (the probability of quasi-extinction in 35 yr). Life-history parameters for toads and frogs were obtained from previously published literature or unpublished data from a long-term (>35 yr) data set. In addition to Cu toxicity, we investigate the role of climate change on amphibian populations by including the probability of early pond drying that results in catastrophic reproductive failure (CRF, i.e., complete mortality of all larval individuals). Our models indicate that CRF is an important parameter for both species as both were unable to persist when CRF probability was >50% for toads or 40% for frogs. Copper toxicity alone did not result in significant effects on extinction risk unless toxicity was very high (>50% reduction in survival parameters). For toads, Cu toxicity and high probability of CRF both resulted in high extinction risk but no synergistic (or greater than additive) effects between the two stressors occurred. For leopard frogs, in the absence of CRF survival was high even under Cu toxicity, but with CRF Cu toxicity increased extinction risk. Our analyses highlight the importance of considering multiple stressors as well as species differences in response to those stressors. Our models were consistently most sensitive to juvenile and adult survival, further suggesting the importance of terrestrial stages to population persistence. Future models will incorporate multiple wetlands with different combinations of stressors to understand if our results for a single wetland result in a population sink within the landscape. © 2016 by the Ecological Society of America.

Hazard perception, risk perception, and the need for decontamination by residents exposed to soil pollution: the role of sustainability and the limits of expert knowledge.

PubMed

Vandermoere, Frédéric

2008-04-01

This case study examines the hazard and risk perception and the need for decontamination according to people exposed to soil pollution. Using an ecological-symbolic approach (ESA), a multidisciplinary model is developed that draws upon psychological and sociological perspectives on risk perception and includes ecological variables by using data from experts' risk assessments. The results show that hazard perception is best predicted by objective knowledge, subjective knowledge, estimated knowledge of experts, and the assessed risks. However, experts' risk assessments induce an increase in hazard perception only when residents know the urgency of decontamination. Risk perception is best predicted by trust in the risk management. Additionally, need for decontamination relates to hazard perception, risk perception, estimated knowledge of experts, and thoughts about sustainability. In contrast to the knowledge deficit model, objective and subjective knowledge did not significantly relate to risk perception and need for decontamination. The results suggest that residents can make a distinction between hazards in terms of the seriousness of contamination on the one hand, and human health risks on the other hand. Moreover, next to the importance of social determinants of environmental risk perception, this study shows that the output of experts' risk assessments-or the objective risks-can create a hazard awareness rather than an alarming risk consciousness, despite residents' distrust of scientific knowledge.

Psychosocial work environment and myocardial infarction: improving risk estimation by combining two complementary job stress models in the SHEEP Study

PubMed Central

Peter, R; Siegrist, J; Hallqvist, J; Reuterwall, C; Theorell, T

2002-01-01

Objectives: Associations between two alternative formulations of job stress derived from the effort-reward imbalance and the job strain model and first non-fatal acute myocardial infarction were studied. Whereas the job strain model concentrates on situational (extrinsic) characteristics the effort-reward imbalance model analyses distinct person (intrinsic) characteristics in addition to situational ones. In view of these conceptual differences the hypothesis was tested that combining information from the two models improves the risk estimation of acute myocardial infarction. Methods: 951 male and female myocardial infarction cases and 1147 referents aged 45–64 years of The Stockholm Heart Epidemiology (SHEEP) case-control study underwent a clinical examination. Information on job stress and health adverse behaviours was derived from standardised questionnaires. Results: Multivariate analysis showed moderately increased odds ratios for either model. Yet, with respect to the effort-reward imbalance model gender specific effects were found: in men the extrinsic component contributed to risk estimation, whereas this was the case with the intrinsic component in women. Controlling each job stress model for the other in order to test the independent effect of either approach did not show systematically increased odds ratios. An improved estimation of acute myocardial infarction risk resulted from combining information from the two models by defining groups characterised by simultaneous exposure to effort-reward imbalance and job strain (men: odds ratio 2.02 (95% confidence intervals (CI) 1.34 to 3.07); women odds ratio 2.19 (95% CI 1.11 to 4.28)). Conclusions: Findings show an improved risk estimation of acute myocardial infarction by combining information from the two job stress models under study. Moreover, gender specific effects of the two components of the effort-reward imbalance model were observed. PMID:11896138

The role of retinopathy distribution and other lesion types for the definition of examination intervals during screening for diabetic retinopathy.

PubMed

Ometto, Giovanni; Erlandsen, Mogens; Hunter, Andrew; Bek, Toke

2017-06-01

It has previously been shown that the intervals between screening examinations for diabetic retinopathy can be optimized by including individual risk factors for the development of the disease in the risk assessment. However, in some cases, the risk model calculating the screening interval may recommend a different interval than an experienced clinician. The purpose of this study was to evaluate the influence of factors unrelated to diabetic retinopathy and the distribution of lesions for discrepancies between decisions made by the clinician and the risk model. Therefore, fundus photographs from 90 screening examinations where the recommendations of the clinician and a risk model had been discrepant were evaluated. Forty features were defined to describe the type and location of the lesions, and classification and ranking techniques were used to assess whether the features could predict the discrepancy between the grader and the risk model. Suspicion of tumours, retinal degeneration and vascular diseases other than diabetic retinopathy could explain why the clinician recommended shorter examination intervals than the model. Additionally, the regional distribution of microaneurysms/dot haemorrhages was important for defining a photograph as belonging to the group where both the clinician and the risk model had recommended a short screening interval as opposed to the other decision alternatives. Features unrelated to diabetic retinopathy and the regional distribution of retinal lesions may affect the recommendation of the examination interval during screening for diabetic retinopathy. The development of automated computerized algorithms for extracting information about the type and location of retinal lesions could be expected to further optimize examination intervals during screening for diabetic retinopathy. © 2016 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Influence of Methylenetetrahydrofolate Reductase C677T Polymorphism on the Risk of Lung Cancer and the Clinical Response to Platinum-Based Chemotherapy for Advanced Non-Small Cell Lung Cancer: An Updated Meta-Analysis

PubMed Central

Zhu, Ning; Gong, Yi; He, Jian; Xia, Jingwen

2013-01-01

Purpose Methylenetetrahydrofolate reductase (MTHFR) has been implicated in lung cancer risk and response to platinum-based chemotherapy in advanced non-small cell lung cancer (NSCLC). However, the results are controversial. We performed meta-analysis to investigate the effect of MTHFR C677T polymorphism on lung cancer risk and response to platinum-based chemotherapy in advanced NSCLC. Materials and Methods The databases of PubMed, Ovid, Wanfang and Chinese Biomedicine were searched for eligible studies. Nineteen studies on MTHFR C677T polymorphism and lung cancer risk and three articles on C677T polymorphism and response to platinum-based chemotherapy in advanced NSCLC, were identified. Results The results indicated that the allelic contrast, homozygous contrast and recessive model of the MTHFR C677T polymorphism were associated significantly with increased lung cancer risk. In the subgroup analysis, the C677T polymorphism was significantly correlated with an increased risk of NSCLC, with the exception of the recessive model. The dominant model and the variant T allele showed a significant association with lung cancer susceptibility of ever smokers. Male TT homozygote carriers had a higher susceptibility, but the allelic contrast and homozygote model had a protective effect in females. No relationship was observed for SCLC in any comparison model. In addition, MTHFR 677TT homozygote carriers had a better response to platinum-based chemotherapy in advanced NSCLC in the recessive model. Conclusion The MTHFR C677T polymorphism might be a genetic marker for lung cancer risk or response to platinum-based chemotherapy in advanced NSCLC. However, our results require further verification. PMID:24142642

Joint association between body fat and its distribution with all-cause mortality: A data linkage cohort study based on NHANES (1988-2011)

PubMed Central

Peng, Yang; Wang, Zhiqiang; Adegbija, Odewumi; Hu, Jie; Ma, Jun; Ma, Ying-Hua

2018-01-01

Objective Although obesity is recognized as an important risk of mortality, how the amount and distribution of body fat affect mortality risk is unclear. Furthermore, whether fat distribution confers any additional risk of mortality in addition to fat amount is not understood. Methods This data linkage cohort study included 16415 participants (8554 females) aged 18 to 89 years from National Health and Nutrition Examination Survey III (1988–1994) and its linked mortality data (31 December 2011). Cox proportional hazard models and parametric survival models were used to estimate the association between body fat percentage (BF%), based on bioelectrical impedance analysis, and waist-hip ratio (WHR) with mortality. Results A total of 4999 deaths occurred during 19-year follow-up. A U-shaped association between BF% and mortality was found in both sexes, with the adjusted hazard ratios for other groups between 1.02 (95% confidence interval: 0.89, 1.18) and 2.10 (1.47, 3.01) when BF% groups of 25–30% in males and 30–35% in females were used as references. A non-linear relationship between WHR and mortality was detected in males, with the adjusted hazard ratios among other groups ranging from 1.05 (0.94, 1.18) to 1.52 (1.15, 2.00) compared with the WHR category of 0.95–1.0. However in females, the death risk constantly increased across the WHR spectrum. Joint impact of BF% and WHR suggested males with BF% of 25–30% and WHR of 0.95–1.0 and females with BF% of 30–35% and WHR <0.9 were associated with the lowest mortality risk and longest survival age compared with their counterparts in other categories. Conclusions This study supported the use of body fat distribution in addition to fat amount in assessing the risk of all-cause mortality. PMID:29474498

Joint association between body fat and its distribution with all-cause mortality: A data linkage cohort study based on NHANES (1988-2011).

PubMed

Dong, Bin; Peng, Yang; Wang, Zhiqiang; Adegbija, Odewumi; Hu, Jie; Ma, Jun; Ma, Ying-Hua

2018-01-01

Although obesity is recognized as an important risk of mortality, how the amount and distribution of body fat affect mortality risk is unclear. Furthermore, whether fat distribution confers any additional risk of mortality in addition to fat amount is not understood. This data linkage cohort study included 16415 participants (8554 females) aged 18 to 89 years from National Health and Nutrition Examination Survey III (1988-1994) and its linked mortality data (31 December 2011). Cox proportional hazard models and parametric survival models were used to estimate the association between body fat percentage (BF%), based on bioelectrical impedance analysis, and waist-hip ratio (WHR) with mortality. A total of 4999 deaths occurred during 19-year follow-up. A U-shaped association between BF% and mortality was found in both sexes, with the adjusted hazard ratios for other groups between 1.02 (95% confidence interval: 0.89, 1.18) and 2.10 (1.47, 3.01) when BF% groups of 25-30% in males and 30-35% in females were used as references. A non-linear relationship between WHR and mortality was detected in males, with the adjusted hazard ratios among other groups ranging from 1.05 (0.94, 1.18) to 1.52 (1.15, 2.00) compared with the WHR category of 0.95-1.0. However in females, the death risk constantly increased across the WHR spectrum. Joint impact of BF% and WHR suggested males with BF% of 25-30% and WHR of 0.95-1.0 and females with BF% of 30-35% and WHR <0.9 were associated with the lowest mortality risk and longest survival age compared with their counterparts in other categories. This study supported the use of body fat distribution in addition to fat amount in assessing the risk of all-cause mortality.

A biopsychosocial model of body image concerns and disordered eating in early adolescent girls.

PubMed

Rodgers, Rachel F; Paxton, Susan J; McLean, Siân A

2014-05-01

Body image and eating concerns are prevalent among early adolescent girls, and associated with biological, psychological and sociocultural risk factors. To date, explorations of biopsychosocial models of body image concerns and disordered eating in early adolescent girls are lacking. A sample of 488 early adolescent girls, mean age = 12.35 years (SD = 0.53), completed a questionnaire assessing depressive symptoms, self-esteem, body mass index (BMI), sociocultural appearance pressures, thin-ideal internalization, appearance comparison, body image concerns and disordered eating. Structural equation modelling was conducted to test a hypothetical model in which internalization and comparison were mediators of the effect of both negative affect and sociocultural influences on body image concerns and disordered eating. In addition, the model proposed that BMI would impact body image concerns. Although the initial model was a poor fit to the data, the fit was improved after the addition of a direct pathway between negative affect and bulimic symptoms. The final model explained a large to moderate proportion of the variance in body image and eating concerns. This study supports the role of negative affect in biopsychosocial models of the development of body image concerns and disordered eating in early adolescent girls. Interventions including strategies to address negative affect as well as sociocultural appearance pressures may help decrease the risk for body image concerns and disordered eating among this age group.

Risk and the physics of clinical prediction.

PubMed

McEvoy, John W; Diamond, George A; Detrano, Robert C; Kaul, Sanjay; Blaha, Michael J; Blumenthal, Roger S; Jones, Steven R

2014-04-15

The current paradigm of primary prevention in cardiology uses traditional risk factors to estimate future cardiovascular risk. These risk estimates are based on prediction models derived from prospective cohort studies and are incorporated into guideline-based initiation algorithms for commonly used preventive pharmacologic treatments, such as aspirin and statins. However, risk estimates are more accurate for populations of similar patients than they are for any individual patient. It may be hazardous to presume that the point estimate of risk derived from a population model represents the most accurate estimate for a given patient. In this review, we exploit principles derived from physics as a metaphor for the distinction between predictions regarding populations versus patients. We identify the following: (1) predictions of risk are accurate at the level of populations but do not translate directly to patients, (2) perfect accuracy of individual risk estimation is unobtainable even with the addition of multiple novel risk factors, and (3) direct measurement of subclinical disease (screening) affords far greater certainty regarding the personalized treatment of patients, whereas risk estimates often remain uncertain for patients. In conclusion, shifting our focus from prediction of events to detection of disease could improve personalized decision-making and outcomes. We also discuss innovative future strategies for risk estimation and treatment allocation in preventive cardiology. Copyright © 2014 Elsevier Inc. All rights reserved.

Application of Probabilistic Modeling to Quantify the Reduction Levels of Hepatocellular Carcinoma Risk Attributable to Chronic Aflatoxins Exposure.

PubMed

Wambui, Joseph M; Karuri, Edward G; Ojiambo, Julia A; Njage, Patrick M K

2017-01-01

Epidemiological studies show a definite connection between areas of high aflatoxin content and a high occurrence of human hepatocellular carcinoma (HCC). Hepatitis B virus in individuals further increases the risk of HCC. The two risk factors are prevalent in rural Kenya and continuously predispose the rural populations to HCC. A quantitative cancer risk assessment therefore quantified the levels at which potential pre- and postharvest interventions reduce the HCC risk attributable to consumption of contaminated maize and groundnuts. The assessment applied a probabilistic model to derive probability distributions of HCC cases and percentage reductions levels of the risk from secondary data. Contaminated maize and groundnuts contributed to 1,847 ± 514 and 158 ± 52 HCC cases per annum, respectively. The total contribution of both foods to the risk was additive as it resulted in 2,000 ± 518 cases per annum. Consumption and contamination levels contributed significantly to the risk whereby lower age groups were most affected. Nonetheless, pre- and postharvest interventions might reduce the risk by 23.0-83.4% and 4.8-95.1%, respectively. Therefore, chronic exposure to aflatoxins increases the HCC risk in rural Kenya, but a significant reduction of the risk can be achieved by applying specific pre- and postharvest interventions.

Therapeutic risk management of the suicidal patient: augmenting clinical suicide risk assessment with structured instruments.

PubMed

Homaifar, Beeta; Matarazzo, Bridget; Wortzel, Hal S

2013-09-01

This column is the second in a series presenting a model for therapeutic risk management of the suicidal patient. As discussed in the first part of the series, the model involves several elements including augmenting clinical risk assessment with structured instruments, stratifying risk in terms of both severity and temporality, and developing and documenting a safety plan. This column explores in more detail how to augment clinical risk assessment with structured instruments. Unstructured clinical interviews have the potential to miss important aspects of suicide risk assessment. By augmenting the free-form clinical interview with structured instruments that demonstrate reliability and validity, a more nuanced and multifaceted approach to suicide risk assessment is achieved. Incorporating structured instruments into practice also serves a medicolegal function, since these instruments may become a living part of the medical record, establishing baseline levels of suicidal thoughts and behaviors and facilitating future clinical determinations regarding safety needs. We describe several instruments used in a multidisciplinary suicide consultation service, each of which has demonstrated relevance to suicide risk assessment and screening, ease of administration, and strong psychometric properties. In addition, we emphasize the importance of viewing suicide risk assessment as an ongoing process rather than as a singular event. Finally, we discuss special considerations in the evolving practice of risk assessment.

Cardiac Complications, Earlier Treatment, and Initial Disease Severity in Kawasaki Disease.

PubMed

Abrams, Joseph Y; Belay, Ermias D; Uehara, Ritei; Maddox, Ryan A; Schonberger, Lawrence B; Nakamura, Yosikazu

2017-09-01

To assess if observed higher observed risks of cardiac complications for patients with Kawasaki disease (KD) treated earlier may reflect bias due to confounding from initial disease severity, as opposed to any negative effect of earlier treatment. We used data from Japanese nationwide KD surveys from 1997 to 2004. Receipt of additional intravenous immunoglobulin (IVIG) (data available all years) or any additional treatment (available for 2003-2004) were assessed as proxies for initial disease severity. We determined associations between earlier or later IVIG treatment (defined as receipt of IVIG on days 1-4 vs days 5-10 of illness) and cardiac complications by stratifying by receipt of additional treatment or by using logistic modeling to control for the effect of receiving additional treatment. A total of 48 310 patients with KD were included in the analysis. In unadjusted analysis, earlier IVIG treatment was associated with a higher risk for 4 categories of cardiac complications, including all major cardiac complications (risk ratio, 1.10; 95% CI, 1.06-1.15). Stratifying by receipt of additional treatment removed this association, and earlier IVIG treatment became protective against all major cardiac complications when controlling for any additional treatment in logistic regressions (OR, 0.90; 95% CI, 0.80-1.00). Observed higher risks of cardiac complications among patients with KD receiving IVIG treatment on days 1-4 of the illness are most likely due to underlying higher initial disease severity, and patients with KD should continue to be treated with IVIG as early as possible. Published by Elsevier Inc.

Urothelial cancer of the upper urinary tract: emerging biomarkers and integrative models for risk stratification.

PubMed

Mathieu, Romain; Vartolomei, Mihai D; Mbeutcha, Aurélie; Karakiewicz, Pierre I; Briganti, Alberto; Roupret, Morgan; Shariat, Shahrokh F

2016-08-01

The aim of this review was to provide an overview of current biomarkers and risk stratification models in urothelial cancer of the upper urinary tract (UTUC). A non-systematic Medline/PubMed literature search was performed using the terms "biomarkers", "preoperative models", "postoperative models", "risk stratification", together with "upper tract urothelial carcinoma". Original articles published between January 2003 and August 2015 were included based on their clinical relevance. Additional references were collected by cross referencing the bibliography of the selected articles. Various promising predictive and prognostic biomarkers have been identified in UTUC thanks to the increasing knowledge of the different biological pathways involved in UTUC tumorigenesis. These biomarkers may help identify tumors with aggressive biology and worse outcomes. Current tools aim at predicting muscle invasive or non-organ confined disease, renal failure after radical nephroureterectomy and survival outcomes. These models are still mainly based on imaging and clinicopathological feature and none has integrated biomarkers. Risk stratification in UTUC is still suboptimal, especially in the preoperative setting due to current limitations in staging and grading. Identification of novel biomarkers and external validation of current prognostic models may help improve risk stratification to allow evidence-based counselling for kidney-sparing approaches, perioperative chemotherapy and/or risk-based surveillance. Despite growing understanding of the biology underlying UTUC, management of this disease remains difficult due to the lack of validated biomarkers and the limitations of current predictive and prognostic tools. Further efforts and collaborations are necessaryry to allow their integration in daily practice.

Nonstandard Lumbar Region in Predicting Fracture Risk.

PubMed

Alajlouni, Dima; Bliuc, Dana; Tran, Thach; Pocock, Nicholas; Nguyen, Tuan V; Eisman, John A; Center, Jacqueline R

Femoral neck (FN) bone mineral density (BMD) is the most commonly used skeletal site to estimate fracture risk. The role of lumbar spine (LS) BMD in fracture risk prediction is less clear due to osteophytes that spuriously increase LS BMD, particularly at lower levels. The aim of this study was to compare fracture predictive ability of upper L1-L2 BMD with standard L2-L4 BMD and assess whether the addition of either LS site could improve fracture prediction over FN BMD. This study comprised a prospective cohort of 3016 women and men over 60 yr from the Dubbo Osteoporosis Epidemiology Study followed up for occurrence of minimal trauma fractures from 1989 to 2014. Dual-energy X-ray absorptiometry was used to measure BMD at L1-L2, L2-L4, and FN at baseline. Fracture risks were estimated using Cox proportional hazards models separately for each site. Predictive performances were compared using receiver operating characteristic curve analyses. There were 565 women and 179 men with a minimal trauma fracture during a mean of 11 ± 7 yr. L1-L2 BMD T-score was significantly lower than L2-L4 T-score in both genders (p < 0.0001). L1-L2 and L2-L4 BMD models had a similar fracture predictive ability. LS BMD was better than FN BMD in predicting vertebral fracture risk in women [area under the curve 0.73 (95% confidence interval, 0.68-0.79) vs 0.68 (95% confidence interval, 0.62-0.74), but FN was superior for hip fractures prediction in both women and men. The addition of L1-L2 or L2-L4 to FN BMD in women increased overall and vertebral predictive power compared with FN BMD alone by 1% and 4%, respectively (p < 0.05). In an elderly population, L1-L2 is as good as but not better than L2-L4 site in predicting fracture risk. The addition of LS BMD to FN BMD provided a modest additional benefit in overall fracture risk. Further studies in individuals with spinal degenerative disease are needed. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

The current contribution of molecular factors to risk estimation in neuroblastoma patients.

PubMed

Berthold, F; Sahin, K; Hero, B; Christiansen, H; Gehring, M; Harms, D; Horz, S; Lampert, F; Schwab, M; Terpe, J

1997-10-01

The association of molecular characteristics with prognosis has been reported, but not their relationship with each other and their impact in the context of known clinical risk factors. In this study, data of 1249 consecutive intent-to-treat-neuroblastoma patients with more than 1 year follow-up were examined by multivariate analysis using loglinear and Cox proportional hazard regression models on a stage-related basis (stages 1-3: 600, 4S: 116, 4: 533). In a first step, risk factors were identified from 18 selected clinical variables, and risk groups defined. The second step investigated whether molecular characteristics (MYCN, LOH 1p, del 1p, CD44, N-ras, NGF-R, bcl-2, APO-1 (CD95)) contributed additional prognostic information to the model. The loglinear model demonstrated several interactions between clinical factors. By the Cox regression model, seven independent clinical risk factors were found for stages 1-3, seven for stage 4 and two for stage 4S. By subsequent introduction of all molecular variables, MYCN amplification only added significant prognostic information to the clinical factors in localised and stage 4 neuroblastoma. The models allowed the definition of risk groups for stages 1-3 patients by age (e beta = 5.09) and MYCN (e beta = 4.26), for stage 4 by MYCN (e beta = 2.78) and number of symptoms (e beta = 2.44) and for stage 4S by platelet count (e beta = 3.91) and general condition (e beta = 2.99). Molecular factors and in particular MYCN contribute significantly to risk estimation. In conjunction with clinical factors, they are powerful tools to define risk groups in neuroblastoma.

Anaemia to predict outcome in patients with acute coronary syndromes.

PubMed

Ennezat, Pierre Vladimir; Maréchaux, Sylvestre; Pinçon, Claire; Finzi, Jonathan; Barrailler, Stéphanie; Bouabdallaoui, Nadia; Van Belle, Eric; Montalescot, Gilles; Collet, Jean-Philippe

2013-01-01

Owing to the heterogeneous population of patients with acute coronary syndromes (ACS), risk stratification with tools such as the GRACE risk score is recommended to guide therapeutic management and improve outcome. To evaluate whether anaemia refines the value of the GRACE risk model to predict midterm outcome after an ACS. A prospective registry of 1064 ACS patients (63 ± 14 years; 73% men; 57% ST-segment elevation myocardial infarction [MI]) was studied. Anaemia was defined as haemoglobin less than 13 mg/dL in men or less than 12 mg/dL in women. The primary endpoint was 6-month death or rehospitalization for MI. The primary endpoint was reached in 132 patients, including 68 deaths. Anaemia was associated with adverse clinical outcomes (hazard ratio 3.008, 95% confidence interval 2.137-4.234; P<0.0001) in univariate analysis and remained independently associated with outcome after adjustment for the Global Registry of Acute Coronary Events (GRACE) risk score (hazard ratio 2.870, 95% confidence interval 1.815-4.538; P<0.0001). Anaemia provided additional prognostic information to the GRACE score as demonstrated by a systematic improvement in global model fit and discrimination (c-statistic increasing from 0.633 [0.571;0.696] to 0.697 [0.638;0.755]). Subsequently, adding anaemia to the GRACE score led to reclassification of 595 patients into different risk categories; 16.5% patients at low risk (≤ 5% risk of death or rehospitalization for MI) were upgraded to intermediate (>5-10%) or high risk (>10%); 79.5% patients at intermediate risk were reclassified as low (55%) or high risk (24%); and 45.5% patients at high risk were downgraded to intermediate risk. Overall, 174 patients were reclassified into a higher risk category (17.3%) and 421 into a lower risk category (41.9%). Anaemia provides independent additional prognostic information to the GRACE score. Combining anaemia with the GRACE score refines its predictive value, which often overestimates the risk. Copyright © 2013. Published by Elsevier Masson SAS.

A comparison of imputation techniques for handling missing predictor values in a risk model with a binary outcome.

PubMed

Ambler, Gareth; Omar, Rumana Z; Royston, Patrick

2007-06-01

Risk models that aim to predict the future course and outcome of disease processes are increasingly used in health research, and it is important that they are accurate and reliable. Most of these risk models are fitted using routinely collected data in hospitals or general practices. Clinical outcomes such as short-term mortality will be near-complete, but many of the predictors may have missing values. A common approach to dealing with this is to perform a complete-case analysis. However, this may lead to overfitted models and biased estimates if entire patient subgroups are excluded. The aim of this paper is to investigate a number of methods for imputing missing data to evaluate their effect on risk model estimation and the reliability of the predictions. Multiple imputation methods, including hotdecking and multiple imputation by chained equations (MICE), were investigated along with several single imputation methods. A large national cardiac surgery database was used to create simulated yet realistic datasets. The results suggest that complete case analysis may produce unreliable risk predictions and should be avoided. Conditional mean imputation performed well in our scenario, but may not be appropriate if using variable selection methods. MICE was amongst the best performing multiple imputation methods with regards to the quality of the predictions. Additionally, it produced the least biased estimates, with good coverage, and hence is recommended for use in practice.

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks.

PubMed

Jamei, Mehdi; Nisnevich, Aleksandr; Wetchler, Everett; Sudat, Sylvia; Liu, Eric

2017-01-01

Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for patients. Large scale adoption of Electronic Health Records (EHR) has created the opportunity to proactively identify patients with high risk of hospital readmission, and apply effective interventions to mitigate that risk. To that end, in the past, numerous machine-learning models have been employed to predict the risk of 30-day hospital readmission. However, the need for an accurate and real-time predictive model, suitable for hospital setting applications still exists. Here, using data from more than 300,000 hospital stays in California from Sutter Health's EHR system, we built and tested an artificial neural network (NN) model based on Google's TensorFlow library. Through comparison with other traditional and non-traditional models, we demonstrated that neural networks are great candidates to capture the complexity and interdependency of various data fields in EHRs. LACE, the current industry standard, showed a precision (PPV) of 0.20 in identifying high-risk patients in our database. In contrast, our NN model yielded a PPV of 0.24, which is a 20% improvement over LACE. Additionally, we discussed the predictive power of Social Determinants of Health (SDoH) data, and presented a simple cost analysis to assist hospitalists in implementing helpful and cost-effective post-discharge interventions.

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks

PubMed Central

2017-01-01

Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for patients. Large scale adoption of Electronic Health Records (EHR) has created the opportunity to proactively identify patients with high risk of hospital readmission, and apply effective interventions to mitigate that risk. To that end, in the past, numerous machine-learning models have been employed to predict the risk of 30-day hospital readmission. However, the need for an accurate and real-time predictive model, suitable for hospital setting applications still exists. Here, using data from more than 300,000 hospital stays in California from Sutter Health’s EHR system, we built and tested an artificial neural network (NN) model based on Google’s TensorFlow library. Through comparison with other traditional and non-traditional models, we demonstrated that neural networks are great candidates to capture the complexity and interdependency of various data fields in EHRs. LACE, the current industry standard, showed a precision (PPV) of 0.20 in identifying high-risk patients in our database. In contrast, our NN model yielded a PPV of 0.24, which is a 20% improvement over LACE. Additionally, we discussed the predictive power of Social Determinants of Health (SDoH) data, and presented a simple cost analysis to assist hospitalists in implementing helpful and cost-effective post-discharge interventions. PMID:28708848

Performance Measures in Neurosurgical Patient Care: Differing Applications of Patient Safety Indicators.

PubMed

Moghavem, Nuriel; McDonald, Kathryn; Ratliff, John K; Hernandez-Boussard, Tina

2016-04-01

Patient Safety Indicators (PSIs) are administratively coded identifiers of potentially preventable adverse events. These indicators are used for multiple purposes, including benchmarking and quality improvement efforts. Baseline PSI evaluation in high-risk surgeries is fundamental to both purposes. Determine PSI rates and their impact on other outcomes in patients undergoing cranial neurosurgery compared with other surgeries. The Agency for Healthcare Research and Quality (AHRQ) PSI software was used to flag adverse events and determine risk-adjusted rates (RAR). Regression models were built to assess the association between PSIs and important patient outcomes. We identified cranial neurosurgeries based on International Classification of Diseases, Ninth Revision, Clinical Modification codes in California, Florida, New York, Arkansas, and Mississippi State Inpatient Databases, AHRQ, 2010-2011. PSI development, 30-day all-cause readmission, length of stay, hospital costs, and inpatient mortality. A total of 48,424 neurosurgical patients were identified. Procedure indication was strongly associated with PSI development. The neurosurgical population had significantly higher RAR of most PSIs evaluated compared with other surgical patients. Development of a PSI was strongly associated with increased length of stay and hospital cost and, in certain PSIs, increased inpatient mortality and 30-day readmission. In this population-based study, certain accountability measures proposed for use as value-based payment modifiers show higher RAR in neurosurgery patients compared with other surgical patients and were subsequently associated with poor outcomes. Our results indicate that for quality improvement efforts, the current AHRQ risk-adjustment models should be viewed in clinically meaningful stratified subgroups: for profiling and pay-for-performance applications, additional factors should be included in the risk-adjustment models. Further evaluation of PSIs in additional high-risk surgeries is needed to better inform the use of these metrics.

SNCA polymorphisms, smoking, and sporadic Parkinson's disease in Japanese.

PubMed

Miyake, Yoshihiro; Tanaka, Keiko; Fukushima, Wakaba; Kiyohara, Chikako; Sasaki, Satoshi; Tsuboi, Yoshio; Yamada, Tatsuo; Oeda, Tomoko; Shimada, Hiroyuki; Kawamura, Nobutoshi; Sakae, Nobutaka; Fukuyama, Hidenao; Hirota, Yoshio; Nagai, Masaki

2012-06-01

Several case-control studies and genome-wide association studies have examined the relationships between single nucleotide polymorphisms (SNPs) in the SNCA gene and Parkinson's disease (PD), and have provided inconsistent results. We investigated the relationships between SNPs rs356229, rs356219, rs356220, rs7684318, and rs2736990 and the risk of sporadic PD in Japan using data from a multicenter hospital-based case-control study. Included were 229 cases within 6 years of onset of PD as defined according to the UK PD Society Brain Bank clinical diagnostic criteria. Controls were 357 inpatients and outpatients without neurodegenerative disease. Adjustment was made for sex, age, region of residence, and smoking. Based on the recessive model, compared with subjects with the CC or CT genotype of SNP rs356220, those with the TT genotype had a significantly increased risk of sporadic PD: the adjusted OR was 1.42 (95% CI: 1.002-2.02). In the additive model, SNP rs2736990 was significantly related to the risk of sporadic PD: the adjusted OR was 1.30 (95% CI: 1.002-1.68). There were no significant relationships between SNP rs356229, rs356219, or rs7684318 and the risk of sporadic PD in any genetic model. The additive interactions between SNPs rs356219 and rs356220 and smoking with respect to sporadic PD were significant although the multiplicative interactions were not significant. This study suggests that SNCA SNPs rs356220 and rs2736990 are significantly associated with the risk of sporadic PD in Japanese. We also present new evidence for biological interactions between SNPs rs356219 and rs356220 and smoking that affect sporadic PD. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mediators of the Relation between Childhood Sexual Abuse and Women’s Sexual Risk Behavior: A Comparison of Two Theoretical Frameworks

PubMed Central

Senn, Theresa E.; Carey, Michael P.; Coury-Doniger, Patricia

2012-01-01

Childhood sexual abuse (CSA) is associated with sexual risk behavior in adulthood, but little research has investigated processes that might mediate this relation. The purpose of this study was to investigate whether constructs suggested by the traumagenic dynamics (TD) model (a theory of the effects of CSA) or constructs suggested by the Information-Motivation-Behavioral skills (IMB) model (a theory of the antecedents of sexual risk behavior) better mediated the relation between CSA and sexual risk behavior in adulthood. Participants were 481 women attending an STI clinic (66% African American) who completed a computerized survey as well as behavioral simulations assessing condom application and sexual assertiveness skills. Forty-five percent of the sample met criteria for CSA and CSA was associated with sexual risk behavior in adulthood. In multiple mediator models, the TD constructs mediated the relation between CSA and the number of sexual partners whereas the IMB constructs mediated the relation between CSA and unprotected sex. In addition, the TD constructs better mediated the relation between CSA and the number of sexual partners; the TD and IMB constructs did not differ in their ability to mediate the relation between CSA and unprotected sex. Sexual risk reduction interventions for women who were sexually abused should target not only the constructs from health behavior models (e.g., motivation and skills to reduce sexual risk), but also constructs that are specific to sexual abuse (e.g., traumatic sexualization and guilt). PMID:22282323

Association of RTEL1 gene polymorphisms with stroke risk in a Chinese Han population.

PubMed

Cai, Yi; Zeng, Chaosheng; Su, Qingjie; Zhou, Jingxia; Li, Pengxiang; Dai, Mingming; Wang, Desheng; Long, Faqing

2017-12-29

We investigated the associations between single nucleotide polymorphisms (SNPs) in the regulator of telomere elongation helicase 1 ( RTEL1 ) gene and stroke in the Chinese population. A total of 400 stroke patients and 395 healthy participants were included in this study. Five SNPs in RTEL1 were genotyped and the association with stroke risk was analyzed. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using unconditional logistic regression analysis. Multivariate logistic regression analysis was used to identify SNPs that correlated with stroke. Rs2297441 was associated with an increased risk of stroke in an allele model (odds ratio [OR] = 1.24, 95% confidence interval [95% CI] = 1.01-1.52, p = 0.043). Rs6089953 was associated with an increased risk of stroke under the genotype model ([OR] = 1.862, [CI] = 1.123-3.085, p = 0.016). Rs2297441 was associated with an increased risk of stroke in an additive model (OR = 1.234, 95% CI = 1.005, p = 0.045, Rs6089953, Rs6010620 and Rs6010621 were associated with an increased risk of stroke in the recessive model (Rs6089953:OR = 1.825, 95% CI = 1.121-2.969, p =0.01546; Rs6010620: OR = 1.64, 95% CI = 1.008-2.669, p =0.04656;Rs6010621:OR = 1.661, 95% CI = 1.014-2.722, p =0.04389). Our findings reveal a possible association between SNPs in the RTEL1 gene and stroke risk in Chinese population.

HIV RISK REDUCTION INTERVENTIONS AMONG SUBSTANCE-ABUSING REPRODUCTIVE-AGE WOMEN: A SYSTEMATIC REVIEW

PubMed Central

Weissman, Jessica; Kanamori, Mariano; Dévieux, Jessy G.; Trepka, Mary Jo; De La Rosa, Mario

2017-01-01

HIV/AIDS is one of the leading causes of death among reproductive-age women throughout the world, and substance abuse plays a major role in HIV infection. We conducted a systematic review, in accordance with the 2015 Preferred Items for Reporting Systematic Reviews and Meta-analysis tool, to assess HIV risk-reduction intervention studies among reproductive-age women who abuse substances. We initially identified 6,506 articles during our search and, after screening titles and abstracts, examining articles in greater detail, and finally excluding those rated methodologically weak, a total of 10 studies were included in this review. Studies that incorporated behavioral skills training into the intervention and were based on theoretical model(s) were the most effective in general at decreasing sex and drug risk behaviors. Additional HIV risk-reduction intervention research with improved methodological designs is warranted to determine the most efficacious HIV risk-reduction intervention for reproductive-age women who abuse substances. PMID:28467160

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

NASA Astrophysics Data System (ADS)

Champion, Billy Ray

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. . Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. . The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of "of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency's traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Public perceptions of the risks of an unfamiliar technology: The case of using nuclear energy sources for space missions

NASA Astrophysics Data System (ADS)

Maharik, Michael

This thesis addresses the public perception of the risk of a technology not widely known to laypeople. Its aims were (1) to characterize public perceptions of the risk of using nuclear energy in space and decisions related to this risk, and (2) to extend the 'mental model' methodology to studying public perception of unfamiliar, risky technologies. A model of the physical processes capable of creating risks from using nuclear energy sources in space was first constructed. Then, knowledge and beliefs related to this topic were elicited from three different groups of people. The generality of the findings was examined in a constructive replication with environmentally-oriented people. The possibility of involving the public in decision-making processes related to engineering macro-design was then investigated. Finally, a communication regarding these risk processes was developed and evaluated in an experiment comparing it with communications produced by NASA. Although they included large portions of the expert model, people's beliefs also had gaps and misconceptions. Respondents often used scientific terms without a clear understanding of what they meant. Respondents' mental models sometimes contained scattered and inconsistent entries. The impact of pre-existing mental models was clearly seen. Different groups of people had different patterns of knowledge and beliefs. Nevertheless, respondents expressed reasonable and coherent opinions on choices among engineering options. The CMU brochure, derived from the study of readers' existing mental models, provided a better risk communication tool than NASA's material, reflecting primarily experts' perspective. The better performance of subjects reading either brochure generally reflected adding knowledge on issues that they had not previously known, rather than correcting wrong beliefs. The communication study confirmed a hypothesis that improving knowledge on risk processes related to the use of a technology causes a more favorable attitude towards that technology. Recommendations related to the design and targeting of risk communication, and to public participation in decision-making on using new and risky technologies, are derived. Additional studies that will elicit laypeople's definitions of risk related to specific technologies, and link their detailed understanding of risk-development processes to the perceived dimensions of risk, are suggested.

A Web-Based System for Bayesian Benchmark Dose Estimation.

PubMed

Shao, Kan; Shapiro, Andrew J

2018-01-11

Benchmark dose (BMD) modeling is an important step in human health risk assessment and is used as the default approach to identify the point of departure for risk assessment. A probabilistic framework for dose-response assessment has been proposed and advocated by various institutions and organizations; therefore, a reliable tool is needed to provide distributional estimates for BMD and other important quantities in dose-response assessment. We developed an online system for Bayesian BMD (BBMD) estimation and compared results from this software with U.S. Environmental Protection Agency's (EPA's) Benchmark Dose Software (BMDS). The system is built on a Bayesian framework featuring the application of Markov chain Monte Carlo (MCMC) sampling for model parameter estimation and BMD calculation, which makes the BBMD system fundamentally different from the currently prevailing BMD software packages. In addition to estimating the traditional BMDs for dichotomous and continuous data, the developed system is also capable of computing model-averaged BMD estimates. A total of 518 dichotomous and 108 continuous data sets extracted from the U.S. EPA's Integrated Risk Information System (IRIS) database (and similar databases) were used as testing data to compare the estimates from the BBMD and BMDS programs. The results suggest that the BBMD system may outperform the BMDS program in a number of aspects, including fewer failed BMD and BMDL calculations and estimates. The BBMD system is a useful alternative tool for estimating BMD with additional functionalities for BMD analysis based on most recent research. Most importantly, the BBMD has the potential to incorporate prior information to make dose-response modeling more reliable and can provide distributional estimates for important quantities in dose-response assessment, which greatly facilitates the current trend for probabilistic risk assessment. https://doi.org/10.1289/EHP1289.

Beyond classic risk adjustment: Socioeconomic status and hospital performance in urologic oncology surgery.

PubMed

Odisho, Anobel Y; Etzioni, Ruth; Gore, John L

2018-06-15

Safety-net hospitals (SNHs) care for more patients of low socioeconomic status (SES) than non-SNHs and are disproportionately punished under SES-naive Medicare readmission risk-adjustment models. This study was designed to develop a risk-adjustment framework that incorporates SES and to assess the impact on readmission rates. California Office of Statewide Health Planning and Development data from 2007 to 2011 were used to identify patients undergoing radical cystectomy (RC) for bladder cancer (n = 3771) or partial nephrectomy (PN; n = 5556) or radical nephrectomy (RN; n = 13,136) for kidney cancer. Unadjusted hospital rankings and predicted rankings under models simulating the Medicare Hospital Readmissions Reduction Program were compared with predicted rankings under models incorporating SES and hospital factors. SES, derived from a multifactorial neighborhood score, was calculated from US Census data. The 30-day readmission rate was 26.1% for RC, 8.3% for RN, and 9.5% for PN. The addition of SES, geographic, and hospital factors changed hospital rankings significantly in comparison with the base model (P < .01) except for SES for RC (P = .07) and SES and rural factors for PN (P = .12). For RN and PN, the addition of SES predicted lower percentile ranks for SNHs and thus improved observed-to-expected rankings (P < .01). For RC, there were no changes in hospital rankings. SES is important for risk adjustments for complex surgical procedures such as RC. Patient SES affects overall hospital rankings across cohorts, and critically, it differentially and punitively affects rankings for SNHs for some procedures. Cancer 2018. © 2018 American Cancer Society. © 2018 American Cancer Society.

A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

PubMed

Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

2012-04-01

A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the 'Gail 2' model showed the average C statistic was 0.63 (95% CI 0.59-0.67), and the expected/observed ratio of events varied considerably across studies (95% prediction interval for E/O ratio when the model was applied in practice was 0.75-1.19). There is a need for models with better predictive performance but, given the large amount of work already conducted, further improvement of existing models based on conventional risk factors is perhaps unlikely. Research to identify new risk factors with large additionally predictive ability is therefore needed, alongside clearer reporting and continual validation of new models as they develop.

Assessment and management of human health risk from toxic metals and polycyclic aromatic hydrocarbons in urban stormwater arising from anthropogenic activities and traffic congestion.

PubMed

Ma, Yukun; Liu, An; Egodawatta, Prasanna; McGree, James; Goonetilleke, Ashantha

2017-02-01

Toxic metals (TMs) and polycyclic aromatic hydrocarbons (PAHs) in urban stormwater pose risk to human health, thereby constraining its reuse potential. Based on the hypothesis that stormwater quality is primarily influenced by anthropogenic activities and traffic congestion, the primary focus of the research study was to analyse the impacts on human health risk from TMs and PAHs in urban stormwater and thereby develop a quantitative risk assessment model. The study found that anthropogenic activities and traffic congestion exert influence on the risk posed by TMs and PAHs in stormwater from commercial and residential areas. Motor vehicle related businesses (FVS) and traffic congestion (TC) were identified as two parameters which need to be included as independent variables to improve the model. Based on the study outcomes, approaches for mitigating the risk associated with TMs and PAHs in urban stormwater are discussed. Additionally, a roadmap is presented for the assessment and management of the risk arising from these pollutants. The study outcomes are expected to contribute to reducing the human health risk associated urban stormwater pollution and thereby enhance its reuse potential. Copyright © 2016 Elsevier B.V. All rights reserved.

Predation Risk within Fishing Gear and Implications for South Australian Rock Lobster Fisheries.

PubMed

Briceño, Felipe; Linnane, Adrian Joseph; Quiroz, Juan Carlos; Gardner, Caleb; Pecl, Gretta Tatyana

2015-01-01

Depredation of southern rock lobster (Jasus edwardsii) within fishing gear by the Maori octopus (Pinnoctopus cordiformis) has economic and ecological impacts on valuable fisheries in South Australia. In addition, depredation rates can be highly variable resulting in uncertainties for the fishery. We examined how in-pot lobster predation was influenced by factors such as lobster size and sex, season, fishing zone, and catch rate. Using mixed modelling techniques, we found that in-pot predation risk increased with lobster size and was higher for male lobsters. In addition, the effect of catch rate of lobsters on predation risk by octopus differed among fishing zones. There was both a seasonal and a spatial component to octopus predation, with an increased risk within discrete fishing grounds in South Australia at certain times of the year. Information about predation within lobster gear can assist fishery management decision-making, potentially leading to significant reduction in economic losses to the fishery.

Predation Risk within Fishing Gear and Implications for South Australian Rock Lobster Fisheries

PubMed Central

Briceño, Felipe; Linnane, Adrian Joseph; Quiroz, Juan Carlos; Gardner, Caleb; Pecl, Gretta Tatyana

2015-01-01

Depredation of southern rock lobster (Jasus edwardsii) within fishing gear by the Maori octopus (Pinnoctopus cordiformis) has economic and ecological impacts on valuable fisheries in South Australia. In addition, depredation rates can be highly variable resulting in uncertainties for the fishery. We examined how in-pot lobster predation was influenced by factors such as lobster size and sex, season, fishing zone, and catch rate. Using mixed modelling techniques, we found that in-pot predation risk increased with lobster size and was higher for male lobsters. In addition, the effect of catch rate of lobsters on predation risk by octopus differed among fishing zones. There was both a seasonal and a spatial component to octopus predation, with an increased risk within discrete fishing grounds in South Australia at certain times of the year. Information about predation within lobster gear can assist fishery management decision-making, potentially leading to significant reduction in economic losses to the fishery. PMID:26489035

Assessing groundwater vulnerability in the Kinshasa region, DR Congo, using a calibrated DRASTIC model

NASA Astrophysics Data System (ADS)

Mfumu Kihumba, Antoine; Vanclooster, Marnik; Ndembo Longo, Jean

2017-02-01

This study assessed the vulnerability of groundwater against pollution in the Kinshasa region, DR Congo, as a support of a groundwater protection program. The parametric vulnerability model (DRASTIC) was modified and calibrated to predict the intrinsic vulnerability as well as the groundwater pollution risk. The method uses groundwater body specific parameters for the calibration of the factor ratings and weightings of the original DRASTIC model. These groundwater specific parameters are inferred from the statistical relation between the original DRASTIC model and observed nitrate pollution for a specific period. In addition, site-specific land use parameters are integrated into the method. The method is fully embedded in a Geographic Information System (GIS). Following these modifications, the correlation coefficient between groundwater pollution risk and observed nitrate concentrations for the 2013-2014 survey improved from r = 0.42, for the original DRASTIC model, to r = 0.61 for the calibrated model. As a way to validate this pollution risk map, observed nitrate concentrations from another survey (2008) are compared to pollution risk indices showing a good degree of coincidence with r = 0.51. The study shows that a calibration of a vulnerability model is recommended when vulnerability maps are used for groundwater resource management and land use planning at the regional scale and that it is adapted to a specific area.

Environmental fate and exposure models: advances and challenges in 21st century chemical risk assessment.

PubMed

Di Guardo, Antonio; Gouin, Todd; MacLeod, Matthew; Scheringer, Martin

2018-01-24

Environmental fate and exposure models are a powerful means to integrate information on chemicals, their partitioning and degradation behaviour, the environmental scenario and the emissions in order to compile a picture of chemical distribution and fluxes in the multimedia environment. A 1995 pioneering book, resulting from a series of workshops among model developers and users, reported the main advantages and identified needs for research in the field of multimedia fate models. Considerable efforts were devoted to their improvement in the past 25 years and many aspects were refined; notably the inclusion of nanomaterials among the modelled substances, the development of models at different spatial and temporal scales, the estimation of chemical properties and emission data, the incorporation of additional environmental media and processes, the integration of sensitivity and uncertainty analysis in the simulations. However, some challenging issues remain and require research efforts and attention: the need of methods to estimate partition coefficients for polar and ionizable chemical in the environment, a better description of bioavailability in different environments as well as the requirement of injecting more ecological realism in exposure predictions to account for the diversity of ecosystem structures and functions in risk assessment. Finally, to transfer new scientific developments into the realm of regulatory risk assessment, we propose the formation of expert groups that compare, discuss and recommend model modifications and updates and help develop practical tools for risk assessment.

Efficient GIS-based model-driven method for flood risk management and its application in central China

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhou, J.; Song, L.; Zou, Q.; Guo, J.; Wang, Y.

2014-02-01

In recent years, an important development in flood management has been the focal shift from flood protection towards flood risk management. This change greatly promoted the progress of flood control research in a multidisciplinary way. Moreover, given the growing complexity and uncertainty in many decision situations of flood risk management, traditional methods, e.g., tight-coupling integration of one or more quantitative models, are not enough to provide decision support for managers. Within this context, this paper presents a beneficial methodological framework to enhance the effectiveness of decision support systems, through the dynamic adaptation of support regarding the needs of the decision-maker. In addition, we illustrate a loose-coupling technical prototype for integrating heterogeneous elements, such as multi-source data, multidisciplinary models, GIS tools and existing systems. The main innovation is the application of model-driven concepts, which put the system in a state of continuous iterative optimization. We define the new system as a model-driven decision support system (MDSS ). Two characteristics that differentiate the MDSS are as follows: (1) it is made accessible to non-technical specialists; and (2) it has a higher level of adaptability and compatibility. Furthermore, the MDSS was employed to manage the flood risk in the Jingjiang flood diversion area, located in central China near the Yangtze River. Compared with traditional solutions, we believe that this model-driven method is efficient, adaptable and flexible, and thus has bright prospects of application for comprehensive flood risk management.

Changes in the living arrangement and risk of stroke in Japan; does it matter who lives in the household? Who among the family matters?

PubMed

Eshak, Ehab Salah; Iso, Hiroyasu; Honjo, Kaori; Noda, Ai; Sawada, Norie; Tsugane, Shoichiro

2017-01-01

Previous studies have suggested associations of family composition with morbidity and mortality; however, the evidence of associations with risk of stroke is limited. We sought to examine the impact of changes in the household composition on risk of stroke and its types in Japanese population. Cox proportional hazard modelling was used to assess the risk of incident stroke and stroke types within a cohort of 77,001 Japanese men and women aged 45-74 years who experienced addition and/or loss of family members [spouse, child(ren), parent(s) and others] to their households over a five years interval (between 1990-1993 and 1995-1998). During 1,043,446 person-years of the follow-up for 35,247 men and 41,758 women, a total of 3,858 cases of incident stroke (1485 hemorrhagic and 2373 ischemic) were documented. When compared with a stable family composition, losing at least one family member was associated with 11-15% increased risk of stroke in women and men; hazard ratios (95% confidence interval) were 1.11 (1.01-1.22) and 1.15 (1.05-1.26), respectively. The increased risk was associated with the loss of a spouse, and was evident for ischemic stroke in men and hemorrhagic stroke in women. The addition of any family members to the household was not associated with risk of stroke in men, whereas the addition of a parent (s) to the household was associated with increased risk in women: 1.49 (1.09-2.28). When the loss of a spouse was accompanied by the addition of other family members to the household, the increased risk of stroke disappeared in men: 1.18 (0.85-1.63), but exacerbated in women: 1.58 (1.19-2.10). In conclusion, men who have lost family members, specifically a spouse have higher risk of ischemic stroke, and women who gained family members; specifically a parent (s) had the higher risk of hemorrhagic stroke than those with a stable family composition.

Development of a claims-based risk score to identify obese individuals.

PubMed

Clark, Jeanne M; Chang, Hsien-Yen; Bolen, Shari D; Shore, Andrew D; Goodwin, Suzanne M; Weiner, Jonathan P

2010-08-01

Obesity is underdiagnosed, hampering system-based health promotion and research. Our objective was to develop and validate a claims-based risk model to identify obese persons using medical diagnosis and prescription records. We conducted a cross-sectional analysis of de-identified claims data from enrollees of 3 Blue Cross Blue Shield plans who completed a health risk assessment capturing height and weight. The final sample of 71,057 enrollees was randomly split into 2 subsamples for development and validation of the obesity risk model. Using the Johns Hopkins Adjusted Clinical Groups case-mix/predictive risk methodology, we categorized study members' diagnosis (ICD) codes. Logistic regression was used to determine which claims-based risk markers were associated with a body mass index (BMI) > or = 35 kg/m(2). The sensitivities of the scores > or =90(th) percentile to detect obesity were 26% to 33%, while the specificities were >90%. The areas under the receiver operator curve ranged from 0.67 to 0.73. In contrast, a diagnosis of obesity or an obesity medication alone had very poor sensitivity (10% and 1%, respectively); the obesity risk model identified an additional 22% of obese members. Varying the percentile cut-point from the 70(th) to the 99(th) percentile resulted in positive predictive values ranging from 15.5 to 59.2. An obesity risk score was highly specific for detecting a BMI > or = 35 kg/m(2) and substantially increased the detection of obese members beyond a provider-coded obesity diagnosis or medication claim. This model could be used for obesity care management and health promotion or for obesity-related research.

Groundwater arsenic contamination throughout China.

PubMed

Rodríguez-Lado, Luis; Sun, Guifan; Berg, Michael; Zhang, Qiang; Xue, Hanbin; Zheng, Quanmei; Johnson, C Annette

2013-08-23

Arsenic-contaminated groundwater used for drinking in China is a health threat that was first recognized in the 1960s. However, because of the sheer size of the country, millions of groundwater wells remain to be tested in order to determine the magnitude of the problem. We developed a statistical risk model that classifies safe and unsafe areas with respect to geogenic arsenic contamination in China, using the threshold of 10 micrograms per liter, the World Health Organization guideline and current Chinese standard for drinking water. We estimate that 19.6 million people are at risk of being affected by the consumption of arsenic-contaminated groundwater. Although the results must be confirmed with additional field measurements, our risk model identifies numerous arsenic-affected areas and highlights the potential magnitude of this health threat in China.

Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH-EVT-Copula model

NASA Astrophysics Data System (ADS)

Wang, Zong-Run; Chen, Xiao-Hong; Jin, Yan-Bo; Zhou, Yan-Ju

2010-11-01

This paper introduces GARCH-EVT-Copula model and applies it to study the risk of foreign exchange portfolio. Multivariate Copulas, including Gaussian, t and Clayton ones, were used to describe a portfolio risk structure, and to extend the analysis from a bivariate to an n-dimensional asset allocation problem. We apply this methodology to study the returns of a portfolio of four major foreign currencies in China, including USD, EUR, JPY and HKD. Our results suggest that the optimal investment allocations are similar across different Copulas and confidence levels. In addition, we find that the optimal investment concentrates on the USD investment. Generally speaking, t Copula and Clayton Copula better portray the correlation structure of multiple assets than Normal Copula.

Risk factors for keratinocyte skin cancer in patients diagnosed with melanoma, a large retrospective study.

PubMed

Espinosa, Pablo; Pfeiffer, Ruth M; García-Casado, Zaida; Requena, Celia; Landi, Maria Teresa; Kumar, Rajiv; Nagore, Eduardo

2016-01-01

Melanoma survivors are at an increased risk of developing other malignancies, including keratinocyte skin cancer (KSC). While it is known that many risk factors for melanoma also impact risk of KSC in the general population, no previous study has investigated risk factors for KSC development in melanoma patients. We assessed associations of personal and clinical characteristics, including skin phenotype and variations in the melanocortin 1 receptor (MC1R) gene, with KSC risk in melanoma patients. We used prospective follow-up information on 1200 patients treated for melanoma at the Instituto Valenciano de Oncología, Spain, between 2000 and 2011. We computed hazard ratios and 95% confidence intervals (CIs) for the association of clinical, personal and genetic characteristics with risk of KSC, squamous cell carcinoma (SCC), or basal cell carcinoma (BCC) from Cox proportional hazard models. Five-year cumulative incidence based on competing risk models of SCC, BCC or KSC overall was computed using multivariate subdistribution hazard models. To assess predictive performance of the models, we computed areas under the receiver-operating characteristic curves (AUCs, discriminatory power) using cross-validation. Median follow-up was 57.2 months; a KSC was detected in 163 patients (13.6%). In multivariable Cox models, age, sex, sunburns, chronic sun exposure, past personal history of non-melanoma skin cancer or other non-cutaneous neoplasia, and the MC1R variants p.D294H and p.R163Q were significantly associated with KSC risk. A cumulative incidence model including age, sex, personal history of KSC, and of other non-cutaneous neoplasia had an AUC of 0.76 (95% CI: 0.71-0.80). When p.D294H and p.R163Q variants were added to the model, the AUC increased to 0.81 (95% CI: 0.77-0.84) (p-value for difference <0.0001). In addition to age, sex, skin characteristics, and sun exposure, p.R163Q and p.D294H MC1R variants significantly increased KSC risk among melanoma patients. Our findings may help identify patients who could benefit most from preventive measures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling survival and mortality risk to 15 years of age for a national cohort of children with serious congenital heart defects diagnosed in infancy.

PubMed

Knowles, Rachel L; Bull, Catherine; Wren, Christopher; Wade, Angela; Goldstein, Harvey; Dezateux, Carol

2014-01-01

Congenital heart defects (CHDs) are a significant cause of death in infancy. Although contemporary management ensures that 80% of affected children reach adulthood, post-infant mortality and factors associated with death during childhood are not well-characterised. Using data from a UK-wide multicentre birth cohort of children with serious CHDs, we observed survival and investigated independent predictors of mortality up to age 15 years. Data were extracted retrospectively from hospital records and death certificates of 3,897 children (57% boys) in a prospectively identified cohort, born 1992-1995 with CHDs requiring intervention or resulting in death before age one year. A discrete-time survival model accounted for time-varying predictors; hazards ratios were estimated for mortality. Incomplete data were addressed through multilevel multiple imputation. By age 15 years, 932 children had died; 144 died without any procedure. Survival to one year was 79.8% (95% confidence intervals [CI] 78.5, 81.1%) and to 15 years was 71.7% (63.9, 73.4%), with variation by cardiac diagnosis. Importantly, 20% of cohort deaths occurred after age one year. Models using imputed data (including all children from birth) demonstrated higher mortality risk as independently associated with cardiac diagnosis, female sex, preterm birth, having additional cardiac defects or non-cardiac malformations. In models excluding children who had no procedure, additional predictors of higher mortality were younger age at first procedure, lower weight or height, longer cardiopulmonary bypass or circulatory arrest duration, and peri-procedural complications; non-cardiac malformations were no longer significant. We confirm the high mortality risk associated with CHDs in the first year of life and demonstrate an important persisting risk of death throughout childhood. Late mortality may be underestimated by procedure-based audit focusing on shorter-term surgical outcomes. National monitoring systems should emphasise the importance of routinely capturing longer-term survival and exploring the mechanisms of mortality risk in children with serious CHDs.

Predictive Models of Acute Mountain Sickness after Rapid Ascent to Various Altitudes

DTIC Science & Technology

2013-01-01

unclassified relational mountain medicine database containing individ- ual ascent profiles, demographic and physiologic subject descriptors, and...course of AMS, and define the baseline demographics and physiologic descriptors that increase the risk of AMS. In addition, these models provide...substantiated this finding in un- acclimatized women (24). Other physiologic differences between men and women (i.e., differences in endothelial

Large registry analysis to accurately define second malignancy rates and risks in a well-characterized cohort of 744 consecutive multiple myeloma patients followed-up for 25 years

PubMed Central

Engelhardt, Monika; Ihorst, Gabriele; Landgren, Ola; Pantic, Milena; Reinhardt, Heike; Waldschmidt, Johannes; May, Annette M.; Schumacher, Martin; Kleber, Martina; Wäsch, Ralph

2015-01-01

Additional malignancies in multiple myeloma patients after first-line and maintenance treatment have been observed, questioning whether specific risks exist. Second primary malignancies have also gained attention since randomized data showed associations to newer drugs. We have conducted this large registry analysis in 744 consecutive patients and analyzed: 1) frequency and onset of additional malignancies; and 2) second primary malignancy- and myeloma-specific risks. We assessed the frequency of additional malignancies in terms of host-, myeloma- and treatment-specific characteristics. To compare these risks, we estimated cumulative incidence rates for second malignancies and myeloma with Fine and Gray regression models taking into account competing risks. Additional malignancies were found in 118 patients: prior or synchronous malignancies in 63% and subsequent in 37%. Cumulative incidence rates for second malignancies were increased in IgG-myeloma and decreased in bortezomib-treated patients (P<0.05). Cumulative incidence rates for myeloma death were increased with higher stage and age, but decreased in IgG-subtypes and due to anti-myeloma treatment (P<0.05). Cytogenetics in patients acquiring second primary malignancies were predominantly favorable, suggesting that indolent myeloma and long disease latency may allow the manifestation of additional malignancies. An assessment of the Surveillance, Epidemiology, and End Result Program of the National Cancer Institute and our data with long-term follow up of 25 years confirmed a prevalence of second malignancy of 10% at 25 years, whereas death from myeloma decreased from 90% to 83%, respectively. Our important findings widen our knowledge of second malignancies and show that they are of increasing relevance as the prognosis in myeloma improves and mortality rates decrease. PMID:26160877

On the Effectiveness of Security Countermeasures for Critical Infrastructures.

PubMed

Hausken, Kjell; He, Fei

2016-04-01

A game-theoretic model is developed where an infrastructure of N targets is protected against terrorism threats. An original threat score is determined by the terrorist's threat against each target and the government's inherent protection level and original protection. The final threat score is impacted by the government's additional protection. We investigate and verify the effectiveness of countermeasures using empirical data and two methods. The first is to estimate the model's parameter values to minimize the sum of the squared differences between the government's additional resource investment predicted by the model and the empirical data. The second is to develop a multivariate regression model where the final threat score varies approximately linearly relative to the original threat score, sectors, and threat scenarios, and depends nonlinearly on the additional resource investment. The model and method are offered as tools, and as a way of thinking, to determine optimal resource investments across vulnerable targets subject to terrorism threats. © 2014 Society for Risk Analysis.

Epidemiological Implications of Host Biodiversity and Vector Biology: Key Insights from Simple Models.

PubMed

Dobson, Andrew D M; Auld, Stuart K J R

2016-04-01

Models used to investigate the relationship between biodiversity change and vector-borne disease risk often do not explicitly include the vector; they instead rely on a frequency-dependent transmission function to represent vector dynamics. However, differences between classes of vector (e.g., ticks and insects) can cause discrepancies in epidemiological responses to environmental change. Using a pair of disease models (mosquito- and tick-borne), we simulated substitutive and additive biodiversity change (where noncompetent hosts replaced or were added to competent hosts, respectively), while considering different relationships between vector and host densities. We found important differences between classes of vector, including an increased likelihood of amplified disease risk under additive biodiversity change in mosquito models, driven by higher vector biting rates. We also draw attention to more general phenomena, such as a negative relationship between initial infection prevalence in vectors and likelihood of dilution, and the potential for a rise in density of infected vectors to occur simultaneously with a decline in proportion of infected hosts. This has important implications; the density of infected vectors is the most valid metric for primarily zoonotic infections, while the proportion of infected hosts is more relevant for infections where humans are a primary host.

The two-dimensional exposure rainfall-runoff assessment (TERRA)watershed model and its use in the FIFRA ecological risk assessment for antimicrobial uses of copper. FIFRA Scientific Advisory Panel Meeting; October 25-26.

USDA-ARS?s Scientific Manuscript database

The USEPA Office of Pesticide Programs (OPP) presented preliminary risk assessments of the two antimicrobial uses of copper during a public hearing held October 25-26, 2011 in Arlington, VA to a Scientific Advisory Panel convened the by the agency. In addition presentations were made on use of the ...

Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States

PubMed Central

Maas, Paige; Barrdahl, Myrto; Joshi, Amit D.; Auer, Paul L.; Gaudet, Mia M.; Milne, Roger L.; Schumacher, Fredrick R.; Anderson, William F.; Check, David; Chattopadhyay, Subham; Baglietto, Laura; Berg, Christine D.; Chanock, Stephen J.; Cox, David G.; Figueroa, Jonine D.; Gail, Mitchell H.; Graubard, Barry I.; Haiman, Christopher A.; Hankinson, Susan E.; Hoover, Robert N.; Isaacs, Claudine; Kolonel, Laurence N.; Le Marchand, Loic; Lee, I-Min; Lindström, Sara; Overvad, Kim; Romieu, Isabelle; Sanchez, Maria-Jose; Southey, Melissa C.; Stram, Daniel O.; Tumino, Rosario; VanderWeele, Tyler J.; Willett, Walter C.; Zhang, Shumin; Buring, Julie E.; Canzian, Federico; Gapstur, Susan M.; Henderson, Brian E.; Hunter, David J.; Giles, Graham G; Prentice, Ross L.; Ziegler, Regina G.; Kraft, Peter; Garcia-Closas, Montse; Chatterjee, Nilanjan

2017-01-01

IMPORTANCE An improved model for risk stratification can be useful for guiding public health strategies of breast cancer prevention. OBJECTIVE To evaluate combined risk stratification utility of common low penetrant single nucleotide polymorphisms (SNPs) and epidemiologic risk factors. DESIGN, SETTING, AND PARTICIPANTS Using a total of 17 171 cases and 19 862 controls sampled from the Breast and Prostate Cancer Cohort Consortium (BPC3) and 5879 women participating in the 2010 National Health Interview Survey, a model for predicting absolute risk of breast cancer was developed combining information on individual level data on epidemiologic risk factors and 24 genotyped SNPs from prospective cohort studies, published estimate of odds ratios for 68 additional SNPs, population incidence rate from the National Cancer Institute-Surveillance, Epidemiology, and End Results Program cancer registry and data on risk factor distribution from nationally representative health survey. The model is used to project the distribution of absolute risk for the population of white women in the United States after adjustment for competing cause of mortality. EXPOSURES Single nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive factors, and lifestyle factors. MAIN OUTCOMES AND MEASURES Degree of stratification of absolute risk owing to nonmodifiable (SNPs, family history, height, and some components of menstrual and/or reproductive history) and modifiable factors (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], menopausal hormone therapy [MHT], alcohol, and smoking). RESULTS The average absolute risk for a 30-year-old white woman in the United States developing invasive breast cancer by age 80 years is 11.3%. A model that includes all risk factors provided a range of average absolute risk from 4.4% to 23.5% for women in the bottom and top deciles of the risk distribution, respectively. For women who were at the lowest and highest deciles of nonmodifiable risks, the 5th and 95th percentile range of the risk distribution associated with 4 modifiable factors was 2.9% to 5.0% and 15.5% to 25.0%, respectively. For women in the highest decile of risk owing to nonmodifiable factors, those who had low BMI, did not drink or smoke, and did not use MHT had risks comparable to an average woman in the general population. CONCLUSIONS AND RELEVANCE This model for absolute risk of breast cancer including SNPs can provide stratification for the population of white women in the United States. The model can also identify subsets of the population at an elevated risk that would benefit most from risk-reduction strategies based on altering modifiable factors. The effectiveness of this model for individual risk communication needs further investigation. PMID:27228256

Association between regulator of telomere elongation helicase1 (RTEL1) gene and HAPE risk: A case-control study.

PubMed

Rong, Hao; He, Xue; Zhu, Linhao; Zhu, Xikai; Kang, Longli; Wang, Li; He, Yongjun; Yuan, Dongya; Jin, Tianbo

2017-09-01

High altitude pulmonary edema (HAPE) is a paradigm of pulmonary edema. Mutations in regulator of telomere elongation helicase1 (RTEL1) represent an important contributor to risk for pulmonary fibrosis. However, little information is found about the association between RTEL1 and HAPE risk. The present study was undertaken to tentatively explore the potential relation between single-nucleotide polymorphisms (SNPs) in RTEL1 and HAPE risk in Chinese Han population. A total of 265 HAPE patients and 303 healthy controls were included in our case-control study. Four SNPs in RTEL1 were selected and genotyped using the Sequenom MassARRAY method. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated by unconditional logistic regression with adjustment for gender and age. All P values were Bonferroni corrected, and statistical significance was set at P < .0025 (.05/20). In allelic model analysis, we found that the allele "G" of rs6089953 and rs6010621 and the allele "A" of rs2297441 were associated with decreased risk of HAPE. In the genetic model analysis, we found that rs6010621, rs6089953, and rs2297441 were relevant to decreased HAPE risk under dominant model (rs6010621: OR = 0.55; 95% CI = 0.39-0.78; P = .001; rs6089953: OR = 0.68; 95% CI = 0.48-0.96; P = .027; rs2297441: OR = 0.63; 95% CI = 0.45-0.89; P = .008, respectively) and additive model (rs6010621: OR = 0.51; 95% CI = 0.46-0.81; P < .001; rs6089953: OR = 0.72; 95% CI = 0.55-0.95; P = .022; rs2297441: OR = 0.73; 95% CI = 0.57-0.95; P = .019, respectively). SNPs rs6010621 remained significant after Bonferroni correction (P < .0025). In addition, haplotype "GG, GT, AT" of rs6089953-rs6010621 were detected significantly associated with HAPE risk (P < .05), haplotype "GG" remained significant after Bonferroni correction (P < .0025). Our findings provide new evidence for the association between SNPs in RTEL1 and a decreased risk HAPE in the Chinese population. The results need further confirmation.

Association between regulator of telomere elongation helicase1 (RTEL1) gene and HAPE risk

PubMed Central

Rong, Hao; He, Xue; Zhu, Linhao; Zhu, Xikai; Kang, Longli; Wang, Li; He, Yongjun; Yuan, Dongya; Jin, Tianbo

2017-01-01

Abstract High altitude pulmonary edema (HAPE) is a paradigm of pulmonary edema. Mutations in regulator of telomere elongation helicase1 (RTEL1) represent an important contributor to risk for pulmonary fibrosis. However, little information is found about the association between RTEL1 and HAPE risk. The present study was undertaken to tentatively explore the potential relation between single-nucleotide polymorphisms (SNPs) in RTEL1 and HAPE risk in Chinese Han population. A total of 265 HAPE patients and 303 healthy controls were included in our case-control study. Four SNPs in RTEL1 were selected and genotyped using the Sequenom MassARRAY method. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated by unconditional logistic regression with adjustment for gender and age. All P values were Bonferroni corrected, and statistical significance was set at P < .0025 (.05/20). In allelic model analysis, we found that the allele “G” of rs6089953 and rs6010621 and the allele “A” of rs2297441 were associated with decreased risk of HAPE. In the genetic model analysis, we found that rs6010621, rs6089953, and rs2297441 were relevant to decreased HAPE risk under dominant model (rs6010621: OR = 0.55; 95% CI = 0.39–0.78; P = .001; rs6089953: OR = 0.68; 95% CI = 0.48–0.96; P = .027; rs2297441: OR = 0.63; 95% CI = 0.45–0.89; P = .008, respectively) and additive model (rs6010621: OR = 0.51; 95% CI = 0.46–0.81; P < .001; rs6089953: OR = 0.72; 95% CI = 0.55–0.95; P = .022; rs2297441: OR = 0.73; 95% CI = 0.57–0.95; P = .019, respectively). SNPs rs6010621 remained significant after Bonferroni correction (P < .0025). In addition, haplotype “GG, GT, AT” of rs6089953-rs6010621 were detected significantly associated with HAPE risk (P < .05), haplotype “GG” remained significant after Bonferroni correction (P < .0025). Our findings provide new evidence for the association between SNPs in RTEL1 and a decreased risk HAPE in the Chinese population. The results need further confirmation. PMID:28953687

Effects of cumulative stress and impulsivity on smoking status.

PubMed

Ansell, Emily B; Gu, Peihua; Tuit, Keri; Sinha, Rajita

2012-03-01

The stress-vulnerability model of addiction predicts that environmental factors, such as cumulative stress, will result in individual adaptations that decrease self-control, increase impulsivity, and increase risk for addiction. Impulsivity and cumulative stress are risk factors for tobacco smoking that are rarely examined simultaneously in research. We examined the indirect and direct effects of cumulative adversity in a community sample consisting of 291 men and women who participated in an assessment of cumulative stress, self-reported impulsivity, and smoking history. Data were analyzed using bootstrapping techniques to estimate indirect effects of stress on smoking via impulsivity. Cumulative adversity is associated with smoking status via direct effects and indirect effects through impulsivity scores. Additional models examining specific types of stress indicate contributions of traumatic stress and recent life events as well as chronic relationship stressors. Overall, cumulative stress is associated with increased risk of smoking via increased impulsivity and via pathways independent of impulsivity. These findings support the stress-vulnerability model and highlight the utility of mediation models in assessing how, and for whom, cumulative stress increases risk of current cigarette smoking. Increasing self-control is a target for interventions with individuals who have experienced cumulative adversity. Copyright © 2012 John Wiley & Sons, Ltd.

Effects of cumulative stress and impulsivity on smoking status

PubMed Central

Ansell, Emily B.; Gu, Peihua; Tuit, Keri; Sinha, Rajita

2013-01-01

Objective The stress-vulnerability model of addiction predicts that environmental factors, such as cumulative stress, will result in individual adaptations that decrease self-control, increase impulsivity, and increase risk for addiction. Impulsivity and cumulative stress are risk factors for tobacco smoking that are rarely examined simultaneously in research. Methods We examined the indirect and direct effects of cumulative adversity in a community sample consisting of 291 men and women who participated in an assessment of cumulative stress, self-reported impulsivity, and smoking history. Data were analyzed using bootstrapping techniques to estimate indirect effects of stress on smoking via impulsivity. Results Cumulative adversity is associated with smoking status via direct effects and indirect effects through impulsivity scores. Additional models examining specific types of stress indicate contributions of traumatic stress and recent life events as well as chronic relationship stressors. Conclusions Overall, cumulative stress is associated with increased risk of smoking via increased impulsivity and via pathways independent of impulsivity. These findings support the stress-vulnerability model and highlight the utility of mediation models in assessing how, and for whom, cumulative stress increases risk of current cigarette smoking. Increasing self-control is a target for interventions with individuals who have experienced cumulative adversity. PMID:22389084

Polymorphisms in Telomere Length Associated TERC and TERT predispose for Ischemic Stroke in a Chinese Han population.

PubMed

Zhang, Shuo; Ji, Guofa; Liang, Yiqian; Zhang, Rui; Shi, Puyu; Guo, Dangshe; Li, Chunqi; Feng, Jing; Liu, Feng; Peng, Rong; Chen, Mingwei

2017-01-06

The role of telomere in genomic stability is an established fact. Variation in leukocyte telomere length (LTL) has been considered a crucial factor that associated with age-associated diseases. To elucidate the association between LTL variation and ischemic stroke (IS) risk, we selected ten single nucleotide polymorphisms (SNPs) in three genes (TERC, TERT and RTEL1) that previously reported link to LTL, and genotyped SNPs of these genes in a case-control study. The association between polymorphisms and IS risk were tested by Chi squared test and haplotype analysis. In allele association analysis, allele "C" in rs10936599 of TERC gene and allele "G" in rs2853677 of TERT gene were found to have an increased risk of IS when compared with allele "T" and "A", respectively. Model association analysis showed that genotype "G/A" in the overdominant model and genotypes "G/A" and "A/A" in the dominant model of rs2242652 presented a more likelihood to have IS. Another TERT locus (rs2853677) with genotype "G" was also found IS-related risky in the log-additive model. Taken together, our results suggest a potential association between LTL related TERC, TERT gene variants and ischemic stroke risk.

Modeling combination HCV prevention among HIV-infected men who have sex with men and people who inject drugs

PubMed Central

Martin, Natasha K.; Skaathun, Britt; Vickerman, Peter; Stuart, David

2017-01-01

Background People who inject drugs (PWID) and HIV-infected men who have sex with men (MSM) are key risk groups for hepatitis C virus (HCV) transmission. Mathematical modeling studies can help elucidate what level and combination of prevention intervention scale-up is required to control or eliminate epidemics among these key populations. Methods We discuss the evidence surrounding HCV prevention interventions and provide an overview of the mathematical modeling literature projecting the impact of scaled-up HCV prevention among PWID and HIV-infected MSM. Results Harm reduction interventions such as opiate substitution therapy and needle and syringe programs are effective in reducing HCV incidence among PWID. Modeling and limited empirical data indicate HCV treatment could additionally be used for prevention. No studies have evaluated the effectiveness of behavior change interventions to reduce HCV incidence among MSM, but existing interventions to reduce HIV risk could be effective. Mathematical modeling and empirical data indicates that scale-up of harm reduction could reduce HCV transmission, but in isolation is unlikely to eliminate HCV among PWID. By contrast, elimination is possibly achievable through combination scale-up of harm reduction and HCV treatment. Similarly, among HIV-infected MSM, eliminating the emerging epidemics will likely require HCV treatment scale-up in combination with additional interventions to reduce HCV-related risk behaviors. Conclusions Elimination of HCV will likely require combination prevention efforts among both PWID and HIV-infected MSM populations. Further empirical research is required to validate HCV treatment as prevention among these populations, and to identify effective behavioral interventions to reduce HCV incidence among MSM. PMID:28534885

Radiobiological foundation of crew radiation risk for mars mission

NASA Astrophysics Data System (ADS)

Shafirkin, A.

The results of a comprehensive clinico-physiological study of 250 dogs after 22 hours per day chronic exposure to gamma -radiation throughout their life are presented. The exposure duration was 3 and 6 years. The dose rate varied between 25 and 150 cSv/year to simulate galactic cosmic ray dose of crew members during mars mission. Several groups of the dogs received an additional acute dose of 10 and 50 cSv during a day three times per year to simulate stochastic irradiation caused by solar cosmic rays. Data on the status of regulatory systems of organism, exchange processes dynamics, organism reaction on additional functional loads are also presented. Organism reaction and dynamics of kinetic relations are considered in detail for most radiosensitive and regenerating tissue systems of the organism, namely, bloodforming system and spermatogenic epithelium. The results on life span reduction of the dogs and dog race characteristics after the radiation exposure are discussed. Based on the results obtained in this study and in model experiments realized with big amount of small laboratory animals that were exposed to a wide dose range, using other published data, mathematical models were developed, e. g. a model of radiation damage forming as dependent on time with taking into account recovery processes, and a model of radiation mortality rate of mammals. Based on these models and analysis of radiation environment behind various shielding on the route to Mars, crew radiation risk was calculated for space missions of various durations. Total radiation risk values for cosmonaut lifetime after the missions were also estimated together with expected life span reduction.

Radiobiological foundation of crew radiation risk for Mars mission

NASA Astrophysics Data System (ADS)

Aleksandr, Shafirkin; Grigoriev, Yurj

The results of a comprehensive clinico-physiological study of 250 dogs after 22 hours per day chronic exposure to gamma-radiation throughout their life are presented. The exposure duration was 3 and 6 years. The dose rate varied between 25 and 150 cSv/year to simulate galactic cosmic ray dose of crew members during mars mission. Several groups of the dogs received an additional acute dose of 10 and 50 cSv during a day three times per year to simulate stochastic irradiation caused by solar cosmic rays. Data on the status of regulatory systems of organism, exchange processes dynamics, organism reaction on additional functional loads are also presented. Organism reaction and dynamics of kinetic relations are considered in detail for most radiosensitive and regenerating tissue systems of the organism, namely, bloodforming system and spermatogenic epithelium. The results on life span reduction of the dogs and dog race characteristics after the radiation exposure are discussed. Based on the results obtained in this study and in model experiments realized with big amount of small laboratory animals that were exposed to a wide dose range, using other published data, mathematical models were developed, e. g. a model of radiation damage forming as dependent on time with taking into account recovery processes, and a model of radiation mortality rate of mammals. Based on these models and analysis of radiation environment behind various shielding on the route to Mars, crew radiation risk was calculated for space missions of various durations. Total radiation risk values for cosmonaut lifetime after the missions were also estimated together with expected life span reduction.

Mortality and economic instability: detailed analyses for Britain and comparative analyses for selected industrialized countries.

PubMed

Brenner, M H

1983-01-01

This paper discusses a first-stage analysis of the link of unemployment rates, as well as other economic, social and environmental health risk factors, to mortality rates in postwar Britain. The results presented represent part of an international study of the impact of economic change on mortality patterns in industrialized countries. The mortality patterns examined include total and infant mortality and (by cause) cardiovascular (total), cerebrovascular and heart disease, cirrhosis of the liver, and suicide, homicide and motor vehicle accidents. Among the most prominent factors that beneficially influence postwar mortality patterns in England/Wales and Scotland are economic growth and stability and health service availability. A principal detrimental factor to health is a high rate of unemployment. Additional factors that have an adverse influence on mortality rates are cigarette consumption and heavy alcohol use and unusually cold winter temperatures (especially in Scotland). The model of mortality that includes both economic changes and behavioral and environmental risk factors was successfully applied to infant mortality rates in the interwar period. In addition, the "simple" economic change model of mortality (using only economic indicators) was applied to other industrialized countries. In Canada, the United States, the United Kingdom, and Sweden, the simple version of the economic change model could be successfully applied only if the analysis was begun before World War II; for analysis beginning in the postwar era, the more sophisticated economic change model, including behavioral and environmental risk factors, was required. In France, West Germany, Italy, and Spain, by contrast, some success was achieved using the simple economic change model.

Assessment of NHTSA’s Report “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 2004-2011 Passenger Cars and LTVs” (LBNL Phase 1)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wenzel, Tom P.

In its 2012 report NHTSA simulated the effect four fleetwide mass reduction scenarios would have on the change in annual fatalities. NHTSA estimated that the most aggressive of these scenarios (reducing mass 5.2% in heavier light trucks and 2.6% in all other vehicles types except lighter cars) would result in a small reduction in societal fatalities. LBNL replicated the methodology NHTSA used to simulate six mass reduction scenarios, including the mass reductions recommended in the 2015 NRC committee report, and estimated in 2021 and 2025 by EPA in the TAR, using the updated data through 2012. The analysis indicates thatmore » the estimated x change in fatalities under each scenario based on the updated analysis is comparable to that in the 2012 analysis, but less beneficial or more detrimental than that in the 2016 analysis. For example, an across the board 100-lb reduction in mass would result in an estimated 157 additional annual fatalities based on the 2012 analysis, but would result in only an estimated 91 additional annual fatalities based on the 2016 analysis, and an additional 87 fatalities based on the current analysis. The mass reductions recommended by the 2015 NRC committee report6 would result in a 224 increase in annual fatalities in the 2012 analysis, a 344 decrease in annual fatalities in the 2016 analysis, and a 141 increase in fatalities in the current analysis. The mass reductions EPA estimated for 2025 in the TAR7 would result in a 203 decrease in fatalities based on the 2016 analysis, but an increase of 39 fatalities based on the current analysis. These results support NHTSA’s conclusion from its 2012 study that, when footprint is held fixed, “no judicious combination of mass reductions in the various classes of vehicles results in a statistically significant fatality increase and many potential combinations are safety-neutral as point estimates.”Like the previous NHTSA studies, this updated report concludes that the estimated effect of mass reduction while maintaining footprint on societal U.S. fatality risk is small, and not statistically significant at the 95% or 90% confidence level for all vehicle types based on the jack-knife method NHTSA used. This report also finds that the estimated effects of other control variables, such as vehicle type, specific safety technologies, and crash conditions such as whether the crash occurred at night, in a rural county, or on a high-speed road, on risk are much larger, in some cases two orders of magnitude larger, than the estimated effect of mass or footprint reduction on risk. Finally, this report shows that after accounting for the many vehicle, driver, and crash variables NHTSA used in its regression analyses, there remains a wide variation in risk by vehicle make and model, and this variation is unrelated to vehicle mass. Although the purpose of the NHTSA and LBNL reports is to estimate the effect of vehicle mass reduction on societal risk, this is not exactly what the regression models are estimating. Rather, they are estimating the recent historical relationship between mass and risk, after accounting for most measurable differences between vehicles, drivers, and crash times and locations. In essence, the regression models are comparing the risk of a 2600-lb Dodge Neon with that of a 2500-lb Honda Civic, after attempting to account for all other differences between the two vehicles. The models are not estimating the effect of literally removing 100 pounds from the Neon, leaving everything else unchanged. In addition, the analyses are based on the relationship of vehicle mass and footprint on risk for recent vehicle designs (model year 2004 to 2011). These relationships may or may not continue into the future as manufacturers utilize new vehicle designs and incorporate new technologies, such as more extensive use of strong lightweight materials and specific safety technologies. Therefore, throughout this report we use the phrase “the estimated effect of mass (or footprint) reduction on risk” as shorthand for “the estimated change in risk as a function of its relationship to mass (or footprint) for vehicle models of recent design.”« less

A regularized variable selection procedure in additive hazards model with stratified case-cohort design.

PubMed

Ni, Ai; Cai, Jianwen

2018-07-01

Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.

Development and Validation of Perioperative Risk-Adjustment Models for Hip Fracture Repair, Total Hip Arthroplasty, and Total Knee Arthroplasty.

PubMed

Schilling, Peter L; Bozic, Kevin J

2016-01-06

Comparing outcomes across providers requires risk-adjustment models that account for differences in case mix. The burden of data collection from the clinical record can make risk-adjusted outcomes difficult to measure. The purpose of this study was to develop risk-adjustment models for hip fracture repair (HFR), total hip arthroplasty (THA), and total knee arthroplasty (TKA) that weigh adequacy of risk adjustment against data-collection burden. We used data from the American College of Surgeons National Surgical Quality Improvement Program to create derivation cohorts for HFR (n = 7000), THA (n = 17,336), and TKA (n = 28,661). We developed logistic regression models for each procedure using age, sex, American Society of Anesthesiologists (ASA) physical status classification, comorbidities, laboratory values, and vital signs-based comorbidities as covariates, and validated the models with use of data from 2012. The derivation models' C-statistics for mortality were 80%, 81%, 75%, and 92% and for adverse events were 68%, 68%, 60%, and 70% for HFR, THA, TKA, and combined procedure cohorts. Age, sex, and ASA classification accounted for a large share of the explained variation in mortality (50%, 58%, 70%, and 67%) and adverse events (43%, 45%, 46%, and 68%). For THA and TKA, these three variables were nearly as predictive as models utilizing all covariates. HFR model discrimination improved with the addition of comorbidities and laboratory values; among the important covariates were functional status, low albumin, high creatinine, disseminated cancer, dyspnea, and body mass index. Model performance was similar in validation cohorts. Risk-adjustment models using data from health records demonstrated good discrimination and calibration for HFR, THA, and TKA. It is possible to provide adequate risk adjustment using only the most predictive variables commonly available within the clinical record. This finding helps to inform the trade-off between model performance and data-collection burden as well as the need to define priorities for data capture from electronic health records. These models can be used to make fair comparisons of outcome measures intended to characterize provider quality of care for value-based-purchasing and registry initiatives. Copyright © 2016 by The Journal of Bone and Joint Surgery, Incorporated.

New developments in exposure assessment: the impact on the practice of health risk assessment and epidemiological studies.

PubMed

Nieuwenhuijsen, Mark; Paustenbach, Dennis; Duarte-Davidson, Raquel

2006-12-01

The field of exposure assessment has matured significantly over the past 10-15 years. Dozens of studies have measured the concentrations of numerous chemicals in many media to which humans are exposed. Others have catalogued the various exposure pathways and identified typical values which can be used in the exposure calculations for the general population such as amount of water or soil ingested per day or the percent of a chemical than can pass through the skin. In addition, studies of the duration of exposure for many tasks (e.g. showering, jogging, working in the office) have been conducted which allow for more general descriptions of the likely range of exposures. All of this information, as well as the development of new and better models (e.g. air dispersion or groundwater models), allow for better estimates of exposure. In addition to identifying better exposure factors, and better mathematical models for predicting the aerial distribution of chemicals, the conduct of simulation studies and dose-reconstruction studies can offer extraordinary opportunities for filling in data gaps regarding historical exposures which are critical to improving the power of epidemiology studies. The use of probabilistic techniques such as Monte Carlo analysis and Bayesian statistics have revolutionized the practice of exposure assessment and has greatly enhanced the quality of the risk characterization. Lastly, the field of epidemiology is about to undergo a sea change with respect to the exposure component because each year better environmental and exposure models, statistical techniques and new biological monitoring techniques are being introduced. This paper reviews these techniques and discusses where additional research is likely to pay a significant dividend. Exposure assessment techniques are now available which can significantly improve the quality of epidemiology and health risk assessment studies and vastly improve their usefulness. As more quantitative exposure components can now be incorporated into these studies, they can be better used to identify safe levels of exposure using customary risk assessment methodologies. Examples are drawn from both environmental and occupational studies illustrating how these techniques have been used to better understand exposure to specific chemicals. Some thoughts are also presented on what lessons have been learned about conducting exposure assessment for health risk assessments and epidemiological studies.

Gene variants in the folate-mediated one-carbon metabolism (FOCM) pathway as risk factors for conotruncal heart defects.

PubMed

Zhu, Huiping; Yang, Wei; Lu, Wei; Etheredge, Analee J; Lammer, Edward J; Finnell, Richard H; Carmichael, Suzan L; Shaw, Gary M

2012-05-01

We evaluated 35 variants among four folate-mediated one-carbon metabolism pathway genes, MTHFD1, SHMT1, MTHFR, and DHFR as risk factors for conotruncal heart defects. Cases with a diagnosis of single gene disorders or chromosomal aneusomies were excluded. Controls were randomly selected from area hospitals in proportion to their contribution to the total population of live-born infants. Odds ratios (OR) and the 95% confidence intervals (CI) were computed for each genotype (homozygous variant or heterozygote, vs. homozygous wildtype) and for increase of each less common allele (log-additive model). Interactions between each variant and three folate intake variables (maternal multivitamin use, maternal dietary folate intake, and combined maternal folate intake) were also evaluated under the log-additive model. In general, we did not identify notable associations. The A allele of MTHFD1 rs11627387 was associated with a 1.7-fold increase in conotruncal defects risk in both Hispanic mothers (OR = 1.7, 95% CI = 1.1-2.5) and Hispanic infants (OR = 1.7, 95% CI = 1.2-2.3). The T allele of MTHFR rs1801133 was associated with a 2.8-fold increase of risk among Hispanic women whose dietary folate intake was ≤ 25th centile. The C allele of MTHFR rs1801131 was associated with a two-fold increase of risk (OR = 2.0, 95% CI = 1.0-3.9) only among those whose dietary folate intake was >25th centile. Our study suggested that MTHFD1 rs11627387 may be associated with risk of conotruncal defects through both maternal and offspring genotype effect among the Hispanics. Maternal functional variants in MTHFR gene may interact with dietary folate intake and modify the conotruncal defects risk in the offspring. Copyright © 2012 Wiley Periodicals, Inc.

Cardiovascular outcomes after pharmacologic stress myocardial perfusion imaging.

PubMed

Lee, Douglas S; Husain, Mansoor; Wang, Xuesong; Austin, Peter C; Iwanochko, Robert M

2016-04-01

While pharmacologic stress single photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) is used for noninvasive evaluation of patients who are unable to perform treadmill exercise, its impact on net reclassification improvement (NRI) of prognosis is unknown. We evaluated the prognostic value of pharmacologic stress MPI for prediction of cardiovascular death or non-fatal myocardial infarction (MI) within 1 year at a single-center, university-based laboratory. We examined continuous and categorical NRI of pharmacologic SPECT-MPI for prediction of outcomes beyond clinical factors alone. Six thousand two hundred forty patients (median age 66 years [IQR 56-74], 3466 men) were studied and followed for 5963 person-years. SPECT-MPI variables associated with increased risk of cardiovascular death or non-fatal MI included summed stress score, stress ST-shift, and post-stress resting left ventricular ejection fraction ≤50%. Compared to a clinical model which included age, sex, cardiovascular disease, risk factors, and medications, model χ(2) (210.5 vs. 281.9, P < .001) and c-statistic (0.74 vs. 0.78, P < .001) were significantly increased by addition of SPECT-MPI predictors (summed stress score, stress ST-shift and stress resting left ventricular ejection fraction). SPECT-MPI predictors increased continuous NRI by 49.4% (P < .001), reclassifying 66.5% of patients as lower risk and 32.8% as higher risk of cardiovascular death or non-fatal MI. Addition of MPI predictors to clinical factors using risk categories, defined as <1%, 1% to 3%, and >3% annualized risk of cardiovascular death or non-fatal MI, yielded a 15.0% improvement in NRI (95% CI 7.6%-27.6%, P < .001). Pharmacologic stress MPI substantially improved net reclassification of cardiovascular death or MI risk beyond that afforded by clinical factors. Copyright © 2016 Elsevier Inc. All rights reserved.

CHALLENGES IN CONSTRUCTING STATISTICALLY-BASED SAR MODELS FOR DEVELOPMENTAL TOXICITY

EPA Science Inventory

Regulatory agencies are increasingly called upon to review large numbers of environmental contaminants that have not been characterized for their potential to pose a health risk. Additionally, there is special interest in protecting potentially sensitive subpopulations and identi...

[Uncertainty analysis of ecological risk assessment caused by heavy-metals deposition from MSWI emission].

PubMed

Liao, Zhi-Heng; Sun, Jia-Ren; Wu, Dui; Fan, Shao-Jia; Ren, Ming-Zhong; Lü, Jia-Yang

2014-06-01

The CALPUFF model was applied to simulate the ground-level atmospheric concentrations of Pb and Cd from municipal solid waste incineration (MSWI) plants, and the soil concentration model was used to estimate soil concentration increments after atmospheric deposition based on Monte Carlo simulation, then ecological risk assessment was conducted by the potential ecological risk index method. The results showed that the largest atmospheric concentrations of Pb and Cd were 5.59 x 109-3) microg x m(-3) and 5.57 x 10(-4) microg x m(-3), respectively, while the maxima of soil concentration incremental medium of Pb and Cd were 2.26 mg x kg(-1) and 0.21 mg x kg(-1), respectively; High risk areas were located next to the incinerators, Cd contributed the most to the ecological risk, and Pb was basically free of pollution risk; Higher ecological hazard level was predicted at the most polluted point in urban areas with a 55.30% probability, while in rural areas, the most polluted point was assessed to moderate ecological hazard level with a 72.92% probability. In addition, sensitivity analysis of calculation parameters in the soil concentration model was conducted, which showed the simulated results of urban and rural area were most sensitive to soil mix depth and dry deposition rate, respectively.

In-hive Pesticide Exposome: Assessing risks to migratory honey bees from in-hive pesticide contamination in the Eastern United States

NASA Astrophysics Data System (ADS)

Traynor, Kirsten S.; Pettis, Jeffery S.; Tarpy, David R.; Mullin, Christopher A.; Frazier, James L.; Frazier, Maryann; Vanengelsdorp, Dennis

2016-09-01

This study measured part of the in-hive pesticide exposome by analyzing residues from live in-hive bees, stored pollen, and wax in migratory colonies over time and compared exposure to colony health. We summarized the pesticide burden using three different additive methods: (1) the hazard quotient (HQ), an estimate of pesticide exposure risk, (2) the total number of pesticide residues, and (3) the number of relevant residues. Despite being simplistic, these models attempt to summarize potential risk from multiple contaminations in real-world contexts. Colonies performing pollination services were subject to increased pesticide exposure compared to honey-production and holding yards. We found clear links between an increase in the total number of products in wax and colony mortality. In particular, we found that fungicides with particular modes of action increased disproportionally in wax within colonies that died. The occurrence of queen events, a significant risk factor for colony health and productivity, was positively associated with all three proxies of pesticide exposure. While our exposome summation models do not fully capture the complexities of pesticide exposure, they nonetheless help elucidate their risks to colony health. Implementing and improving such models can help identify potential pesticide risks, permitting preventative actions to improve pollinator health.

A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)

PubMed Central

2018-01-01

Qualitative risk assessment frameworks, such as the Productivity Susceptibility Analysis (PSA), have been developed to rapidly evaluate the risks of fishing to marine populations and prioritize management and research among species. Despite being applied to over 1,000 fish populations, and an ongoing debate about the most appropriate method to convert biological and fishery characteristics into an overall measure of risk, the assumptions and predictive capacity of these approaches have not been evaluated. Several interpretations of the PSA were mapped to a conventional age-structured fisheries dynamics model to evaluate the performance of the approach under a range of assumptions regarding exploitation rates and measures of biological risk. The results demonstrate that the underlying assumptions of these qualitative risk-based approaches are inappropriate, and the expected performance is poor for a wide range of conditions. The information required to score a fishery using a PSA-type approach is comparable to that required to populate an operating model and evaluating the population dynamics within a simulation framework. In addition to providing a more credible characterization of complex system dynamics, the operating model approach is transparent, reproducible and can evaluate alternative management strategies over a range of plausible hypotheses for the system. PMID:29856869

In-hive Pesticide Exposome: Assessing risks to migratory honey bees from in-hive pesticide contamination in the Eastern United States

PubMed Central

Traynor, Kirsten S.; Pettis, Jeffery S.; Tarpy, David R.; Mullin, Christopher A.; Frazier, James L.; Frazier, Maryann; vanEngelsdorp, Dennis

2016-01-01

This study measured part of the in-hive pesticide exposome by analyzing residues from live in-hive bees, stored pollen, and wax in migratory colonies over time and compared exposure to colony health. We summarized the pesticide burden using three different additive methods: (1) the hazard quotient (HQ), an estimate of pesticide exposure risk, (2) the total number of pesticide residues, and (3) the number of relevant residues. Despite being simplistic, these models attempt to summarize potential risk from multiple contaminations in real-world contexts. Colonies performing pollination services were subject to increased pesticide exposure compared to honey-production and holding yards. We found clear links between an increase in the total number of products in wax and colony mortality. In particular, we found that fungicides with particular modes of action increased disproportionally in wax within colonies that died. The occurrence of queen events, a significant risk factor for colony health and productivity, was positively associated with all three proxies of pesticide exposure. While our exposome summation models do not fully capture the complexities of pesticide exposure, they nonetheless help elucidate their risks to colony health. Implementing and improving such models can help identify potential pesticide risks, permitting preventative actions to improve pollinator health. PMID:27628343

Applying a weed risk assessment approach to GM crops.

PubMed

Keese, Paul K; Robold, Andrea V; Myers, Ruth C; Weisman, Sarah; Smith, Joe

2014-12-01

Current approaches to environmental risk assessment of genetically modified (GM) plants are modelled on chemical risk assessment methods, which have a strong focus on toxicity. There are additional types of harms posed by plants that have been extensively studied by weed scientists and incorporated into weed risk assessment methods. Weed risk assessment uses robust, validated methods that are widely applied to regulatory decision-making about potentially problematic plants. They are designed to encompass a broad variety of plant forms and traits in different environments, and can provide reliable conclusions even with limited data. The knowledge and experience that underpin weed risk assessment can be harnessed for environmental risk assessment of GM plants. A case study illustrates the application of the Australian post-border weed risk assessment approach to a representative GM plant. This approach is a valuable tool to identify potential risks from GM plants.

Managing risk: clinical decision-making in mental health services.

PubMed

Muir-Cochrane, Eimear; Gerace, Adam; Mosel, Krista; O'Kane, Debra; Barkway, Patricia; Curren, David; Oster, Candice

2011-01-01

Risk assessment and management is a major component of contemporary mental health practice. Risk assessment in health care exists within contemporary perspectives of management and risk aversive practices in health care. This has led to much discussion about the best approach to assessing possible risks posed by people with mental health problems. In addition, researchers and commentators have expressed concern that clinical practice is being dominated by managerial models of risk management at the expense of meeting the patient's health and social care needs. The purpose of the present study is to investigate the risk assessment practices of a multidisciplinary mental health service. Findings indicate that mental health professionals draw on both managerial and therapeutic approaches to risk management, integrating these approaches into their clinical practice. Rather than being dominated by managerial concerns regarding risk, the participants demonstrate professional autonomy and concern for the needs of their clients.

Next-generation prognostic assessment for diffuse large B-cell lymphoma

PubMed Central

Staton, Ashley D; Kof, Jean L; Chen, Qiushi; Ayer, Turgay; Flowers, Christopher R

2015-01-01

Current standard of care therapy for diffuse large B-cell lymphoma (DLBCL) cures a majority of patients with additional benefit in salvage therapy and autologous stem cell transplant for patients who relapse. The next generation of prognostic models for DLBCL aims to more accurately stratify patients for novel therapies and risk-adapted treatment strategies. This review discusses the significance of host genetic and tumor genomic alterations seen in DLBCL, clinical and epidemiologic factors, and how each can be integrated into risk stratification algorithms. In the future, treatment prediction and prognostic model development and subsequent validation will require data from a large number of DLBCL patients to establish sufficient statistical power to correctly predict outcome. Novel modeling approaches can augment these efforts. PMID:26289217

Next-generation prognostic assessment for diffuse large B-cell lymphoma.

PubMed

Staton, Ashley D; Koff, Jean L; Chen, Qiushi; Ayer, Turgay; Flowers, Christopher R

2015-01-01

Current standard of care therapy for diffuse large B-cell lymphoma (DLBCL) cures a majority of patients with additional benefit in salvage therapy and autologous stem cell transplant for patients who relapse. The next generation of prognostic models for DLBCL aims to more accurately stratify patients for novel therapies and risk-adapted treatment strategies. This review discusses the significance of host genetic and tumor genomic alterations seen in DLBCL, clinical and epidemiologic factors, and how each can be integrated into risk stratification algorithms. In the future, treatment prediction and prognostic model development and subsequent validation will require data from a large number of DLBCL patients to establish sufficient statistical power to correctly predict outcome. Novel modeling approaches can augment these efforts.

Radiation Physics for Space and High Altitude Air Travel

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Wilson, J. W.; Goldhagen, P.; Saganti, P.; Shavers, M. R.; McKay, Gordon A. (Technical Monitor)

2000-01-01

Galactic cosmic rays (GCR) are of extra-solar origin consisting of high-energy hydrogen, helium, and heavy ions. The GCR are modified by physical processes as they traverse through the solar system, spacecraft shielding, atmospheres, and tissues producing copious amounts of secondary radiation including fragmentation products, neutrons, mesons, and muons. We discuss physical models and measurements relevant for estimating biological risks in space and high-altitude air travel. Ambient and internal spacecraft computational models for the International Space Station and a Mars mission are discussed. Risk assessment is traditionally based on linear addition of components. We discuss alternative models that include stochastic treatments of columnar damage by heavy ion tracks and multi-cellular damage following nuclear fragmentation in tissue.

Angiogenic factors combined with clinical risk factors to predict preterm pre-eclampsia in nulliparous women: a predictive test accuracy study.

PubMed

Myers, J E; Kenny, L C; McCowan, L M E; Chan, E H Y; Dekker, G A; Poston, L; Simpson, N A B; North, R A

2013-09-01

To assess the performance of clinical risk factors, uterine artery Doppler and angiogenic markers to predict preterm pre-eclampsia in nulliparous women. Predictive test accuracy study. Prospective multicentre cohort study Screening for Pregnancy Endpoints (SCOPE). Low-risk nulliparous women with a singleton pregnancy were recruited. Clinical risk factor data were obtained and plasma placental growth factor (PlGF), soluble endoglin and soluble fms-like tyrosine kinase-1 (sFlt-1) were measured at 14-16 weeks of gestation. Prediction models were developed using multivariable stepwise logistic regression. Preterm pre-eclampsia (delivered before 37(+0)  weeks of gestation). Of the 3529 women recruited, 187 (5.3%) developed pre-eclampsia of whom 47 (1.3%) delivered preterm. Controls (n = 188) were randomly selected from women without preterm pre-eclampsia and included women who developed other pregnancy complications. An area under a receiver operating characteristic curve (AUC) of 0.76 (95% CI 0.67-0.84) was observed using previously reported clinical risk variables. The AUC improved following the addition of PlGF measured at 14-16 weeks (0.84; 95% CI 0.77-0.91), but no further improvement was observed with the addition of uterine artery Doppler or the other angiogenic markers. A sensitivity of 45% (95% CI 0.31-0.59) (5% false-positive rate) and post-test probability of 11% (95% CI 9-13) were observed using clinical risk variables and PlGF measurement. Addition of plasma PlGF at 14-16 weeks of gestation to clinical risk assessment improved the identification of nulliparous women at increased risk of developing preterm pre-eclampsia, but the performance is not sufficient to warrant introduction as a clinical screening test. These findings are marker dependent, not assay dependent; additional markers are needed to achieve clinical utility. © 2013 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2013 RCOG.

Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach.

PubMed

Ho, Hung Chak; Lau, Kevin Ka-Lun; Yu, Ruby; Wang, Dan; Woo, Jean; Kwok, Timothy Chi Yui; Ng, Edward

2017-08-31

Previous studies found a relationship between geriatric depression and social deprivation. However, most studies did not include environmental factors in the statistical models, introducing a bias to estimate geriatric depression risk because the urban environment was found to have significant associations with mental health. We developed a cross-sectional study with a binomial logistic regression to examine the geriatric depression risk of a high-density city based on five social vulnerability factors and four environmental measures. We constructed a socio-environmental vulnerability index by including the significant variables to map the geriatric depression risk in Hong Kong, a high-density city characterized by compact urban environment and high-rise buildings. Crude and adjusted odds ratios (ORs) of the variables were significantly different, indicating that both social and environmental variables should be included as confounding factors. For the comprehensive model controlled by all confounding factors, older adults who were of lower education had the highest geriatric depression risks (OR: 1.60 (1.21, 2.12)). Higher percentage of residential area and greater variation in building height within the neighborhood also contributed to geriatric depression risk in Hong Kong, while average building height had negative association with geriatric depression risk. In addition, the socio-environmental vulnerability index showed that higher scores were associated with higher geriatric depression risk at neighborhood scale. The results of mapping and cross-section model suggested that geriatric depression risk was associated with a compact living environment with low socio-economic conditions in historical urban areas in Hong Kong. In conclusion, our study found a significant difference in geriatric depression risk between unadjusted and adjusted models, suggesting the importance of including environmental factors in estimating geriatric depression risk. We also developed a framework to map geriatric depression risk across a city, which can be used for identifying neighborhoods with higher risk for public health surveillance and sustainable urban planning.

Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach

PubMed Central

Lau, Kevin Ka-Lun; Yu, Ruby; Wang, Dan; Kwok, Timothy Chi Yui; Ng, Edward

2017-01-01

Previous studies found a relationship between geriatric depression and social deprivation. However, most studies did not include environmental factors in the statistical models, introducing a bias to estimate geriatric depression risk because the urban environment was found to have significant associations with mental health. We developed a cross-sectional study with a binomial logistic regression to examine the geriatric depression risk of a high-density city based on five social vulnerability factors and four environmental measures. We constructed a socio-environmental vulnerability index by including the significant variables to map the geriatric depression risk in Hong Kong, a high-density city characterized by compact urban environment and high-rise buildings. Crude and adjusted odds ratios (ORs) of the variables were significantly different, indicating that both social and environmental variables should be included as confounding factors. For the comprehensive model controlled by all confounding factors, older adults who were of lower education had the highest geriatric depression risks (OR: 1.60 (1.21, 2.12)). Higher percentage of residential area and greater variation in building height within the neighborhood also contributed to geriatric depression risk in Hong Kong, while average building height had negative association with geriatric depression risk. In addition, the socio-environmental vulnerability index showed that higher scores were associated with higher geriatric depression risk at neighborhood scale. The results of mapping and cross-section model suggested that geriatric depression risk was associated with a compact living environment with low socio-economic conditions in historical urban areas in Hong Kong. In conclusion, our study found a significant difference in geriatric depression risk between unadjusted and adjusted models, suggesting the importance of including environmental factors in estimating geriatric depression risk. We also developed a framework to map geriatric depression risk across a city, which can be used for identifying neighborhoods with higher risk for public health surveillance and sustainable urban planning. PMID:28858265

TCF7L2 polymorphisms and the risk of schizophrenia in the Chinese Han population

PubMed Central

Liu, Lijun; Li, Jingjie; Yan, Mengdan; Li, Jing; Chen, Junyu; Zhang, Yi; Zhu, Xikai; Wang, Li; Kang, Longli; Yuan, Dongya; Jin, Tianbo

2017-01-01

Single nucleotide polymorphisms (SNPs) in TCF7L2 (Transcription Factor 7-Like 2) reportedly affect susceptibility to schizophrenia (SCZ). We examined the association between TCF7L2 polymorphisms and SCZ susceptibility in a Chinese Han population. Six SNPs were genotyped in 499 SCZ patients and 500 healthy individuals, after which their associations with SCZ were evaluated using the Chi-squared test and genetic model analyses. We observed that the allele A of rs12573128 is associated with an increased SCZ risk (odds ratio [OR] = 1.33, 95% confidence interval [CI]: 1.08-1.63, P = 0.006, adjusted P = 0.030). The AA genotype of rs12573128 was associated with a higher SCZ risk than the GG genotype, before and after adjustment for sex and age (adjusted OR = 2.97, 95% CI: 1.49-5.92, P = 0.002). In addition, SNP rs12573128 was associated with 1.47-fold, 2.64-fold and 1.50-fold increases in SCZ risk of in dominant, recessive and additive model, respectively (adjusted OR = 1.47, 95% CI = 1.09-1.99, P = 0.012; Bonferroni adjusted P = 0.030). adjusted OR = 2.64, 95% CI = 1.34-5.18, P = 0.005 and adjusted OR = 1.50, 95% CI = 1.17-1.93, P = 0.002, respectively). These results suggest rs12573128 is significantly associated with an increased risk of SCZ in the Chinese Han population. PMID:28404897

Characterizing uncertainty when evaluating risk management metrics: risk assessment modeling of Listeria monocytogenes contamination in ready-to-eat deli meats.

PubMed

Gallagher, Daniel; Ebel, Eric D; Gallagher, Owen; Labarre, David; Williams, Michael S; Golden, Neal J; Pouillot, Régis; Dearfield, Kerry L; Kause, Janell

2013-04-01

This report illustrates how the uncertainty about food safety metrics may influence the selection of a performance objective (PO). To accomplish this goal, we developed a model concerning Listeria monocytogenes in ready-to-eat (RTE) deli meats. This application used a second order Monte Carlo model that simulates L. monocytogenes concentrations through a series of steps: the food-processing establishment, transport, retail, the consumer's home and consumption. The model accounted for growth inhibitor use, retail cross contamination, and applied an FAO/WHO dose response model for evaluating the probability of illness. An appropriate level of protection (ALOP) risk metric was selected as the average risk of illness per serving across all consumed servings-per-annum and the model was used to solve for the corresponding performance objective (PO) risk metric as the maximum allowable L. monocytogenes concentration (cfu/g) at the processing establishment where regulatory monitoring would occur. Given uncertainty about model inputs, an uncertainty distribution of the PO was estimated. Additionally, we considered how RTE deli meats contaminated at levels above the PO would be handled by the industry using three alternative approaches. Points on the PO distribution represent the probability that - if the industry complies with a particular PO - the resulting risk-per-serving is less than or equal to the target ALOP. For example, assuming (1) a target ALOP of -6.41 log10 risk of illness per serving, (2) industry concentrations above the PO that are re-distributed throughout the remaining concentration distribution and (3) no dose response uncertainty, establishment PO's of -4.98 and -4.39 log10 cfu/g would be required for 90% and 75% confidence that the target ALOP is met, respectively. The PO concentrations from this example scenario are more stringent than the current typical monitoring level of an absence in 25 g (i.e., -1.40 log10 cfu/g) or a stricter criteria of absence in 125 g (i.e., -2.1 log10 cfu/g). This example, and others, demonstrates that a PO for L. monocytogenes would be far below any current monitoring capabilities. Furthermore, this work highlights the demands placed on risk managers and risk assessors when applying uncertain risk models to the current risk metric framework. Copyright © 2013 Elsevier B.V. All rights reserved.

Cryptosporidiosis susceptibility and risk: a case study.

PubMed

Makri, Anna; Modarres, Reza; Parkin, Rebecca

2004-02-01

Regional estimates of cryptosporidiosis risks from drinking water exposure were developed and validated, accounting for AIDS status and age. We constructed a model with probability distributions and point estimates representing Cryptosporidium in tap water, tap water consumed per day (exposure characterization); dose response, illness given infection, prolonged illness given illness; and three conditional probabilities describing the likelihood of case detection by active surveillance (health effects characterization). The model predictions were combined with population data to derive expected case numbers and incidence rates per 100,000 population, by age and AIDS status, borough specific and for New York City overall in 2000 (risk characterization). They were compared with same-year surveillance data to evaluate predictive ability, assumed to represent true incidence of waterborne cryptosporidiosis. The predicted mean risks, similar to previously published estimates for this region, overpredicted observed incidence-most extensively when accounting for AIDS status. The results suggest that overprediction may be due to conservative parameters applied to both non-AIDS and AIDS populations, and that biological differences for children need to be incorporated. Interpretations are limited by the unknown accuracy of available surveillance data, in addition to variability and uncertainty of model predictions. The model appears sensitive to geographical differences in AIDS prevalence. The use of surveillance data for validation and model parameters pertinent to susceptibility are discussed.

Does influence at work modify the relation between high occupational physical activity and risk of heart disease in women?

PubMed

Allesøe, Karen; Holtermann, Andreas; Rugulies, Reiner; Aadahl, Mette; Boyle, Eleanor; Søgaard, Karen

2017-07-01

To investigate whether influence at work modifies the association between demanding and strenuous occupational physical activity (OPA) and risk of ischaemic heart disease (IHD). A sample of 12,093 nurses aged 45-64 years from the Danish Nurse Cohort Study was followed for 20.6 years by individual linkage to incident IHD in the Danish National Patient Registry. Information on OPA, influence at work, other occupational factors and known risk factors for IHD was collected by self-report in 1993. During follow-up 869 nurses were hospitalised with incident IHD. Nurses exposed to strenuous OPA and low influence at work had a 46% increased risk of IHD [hazard ratio (HR) 1.46 (95% confidence interval (CI) 1.02-2.09)] compared to the reference group of nurses with moderate OPA and high influence at work. Nurses exposed to strenuous OPA and high influence at work were not at an increased risk of IHD [HR 1.10 (95% CI 0.59-2.06)]. An additive hazards model showed there were 18.0 (95% CI -0.01 to 36.0) additional cases of IHD per 10,000 person years among nurses with strenuous OPA and low influence at work compared to nurses with moderate OPA and high influence at work. A detrimental additive interaction between strenuous OPA and low influence at work that could explain the additional cases of IHD among nurses with strenuous OPA and low influence at work was indicated. The findings suggest that high influence at work may buffer some of the adverse effects of strenuous OPA on risk of IHD.

Estimating Risk from Ambient Concentrations of Acrolein across the United States

PubMed Central

Woodruff, Tracey J.; Wells, Ellen M.; Holt, Elizabeth W.; Burgin, Deborah E.; Axelrad, Daniel A.

2007-01-01

Background Estimated ambient concentrations of acrolein, a hazardous air pollutant, are greater than the U.S. Environmental Protection Agency (EPA) reference concentration throughout the United States, making it a concern for human health. However, there is no method for assessing the extent of risk under the U.S. EPA noncancer risk assessment framework. Objectives We estimated excess risks from ambient concentrations of acrolein based on dose–response modeling of a study in rats with a relationship between acrolein and residual volume/total lung capacity ratio (RV/TLC) and specific compliance (sCL), markers for altered lung function. Methods Based on existing literature, we defined values above the 90th percentile for controls as “adverse.” We estimated the increase over baseline response that would occur in the human population from estimated ambient concentrations of acrolein, taken from the U.S. EPA’s National-Scale Air Toxics Assessment for 1999, after standard animal-to-human conversions and extrapolating to doses below the experimental data. Results The estimated median additional number of adverse sCL outcomes across the United States was approximately 2.5 cases per 1,000 people. The estimated range of additional outcomes from the 5th to the 95th percentile of acrolein concentration levels across census tracts was 0.28–14 cases per 1,000. For RV/TLC, the median additional outcome was 0.002 per 1,000, and the additional outcome at the 95th percentile was 0.13 per 1,000. Conclusions Although there are uncertainties in estimating human risks from animal data, this analysis demonstrates a method for estimating health risks for noncancer effects and suggests that acrolein could be associated with decreased respiratory function in the United States. PMID:17431491

The influence of rear turn-signal characteristics on crash risk.

PubMed

Sullivan, John M; Flannagan, Michael J

2012-02-01

The relationship between the relative risk of a rear-end collision during a turn, merge, or lane change maneuver and the characteristics of the rear turn-signal configuration was examined using crash data from seven states in the United States. Rear turn-signal characteristics-including color, optics, separation, and light source-were identified for 55 vehicle models and used in a logistic regression analysis to model the odds of a rear-end collision. Additional variables including driver demographics (gender, age), vehicle age, and light condition were also modeled. Risk was assessed using a contrast group of striking vehicles in similar collisions. The results suggest that the odds of being the struck vehicle were 3% to 28% lower among vehicles equipped with amber versus red turn signals. Although the analysis suggests that there may be a safety benefit associated with amber rear turn signals, it is unclear whether turn-signal color alone is responsible. The results suggest that aspects of a vehicle's rear signal characteristics may influence crash risk. Copyright © 2012 Elsevier Ltd. All rights reserved.

Calculating excess lifetime risk in relative risk models.

PubMed Central

Vaeth, M; Pierce, D A

1990-01-01

When assessing the impact of radiation exposure it is common practice to present the final conclusions in terms of excess lifetime cancer risk in a population exposed to a given dose. The present investigation is mainly a methodological study focusing on some of the major issues and uncertainties involved in calculating such excess lifetime risks and related risk projection methods. The age-constant relative risk model used in the recent analyses of the cancer mortality that was observed in the follow-up of the cohort of A-bomb survivors in Hiroshima and Nagasaki is used to describe the effect of the exposure on the cancer mortality. In this type of model the excess relative risk is constant in age-at-risk, but depends on the age-at-exposure. Calculation of excess lifetime risks usually requires rather complicated life-table computations. In this paper we propose a simple approximation to the excess lifetime risk; the validity of the approximation for low levels of exposure is justified empirically as well as theoretically. This approximation provides important guidance in understanding the influence of the various factors involved in risk projections. Among the further topics considered are the influence of a latent period, the additional problems involved in calculations of site-specific excess lifetime cancer risks, the consequences of a leveling off or a plateau in the excess relative risk, and the uncertainties involved in transferring results from one population to another. The main part of this study relates to the situation with a single, instantaneous exposure, but a brief discussion is also given of the problem with a continuous exposure at a low-dose rate. PMID:2269245

Calculating excess lifetime risk in relative risk models.

PubMed

Vaeth, M; Pierce, D A

1990-07-01

When assessing the impact of radiation exposure it is common practice to present the final conclusions in terms of excess lifetime cancer risk in a population exposed to a given dose. The present investigation is mainly a methodological study focusing on some of the major issues and uncertainties involved in calculating such excess lifetime risks and related risk projection methods. The age-constant relative risk model used in the recent analyses of the cancer mortality that was observed in the follow-up of the cohort of A-bomb survivors in Hiroshima and Nagasaki is used to describe the effect of the exposure on the cancer mortality. In this type of model the excess relative risk is constant in age-at-risk, but depends on the age-at-exposure. Calculation of excess lifetime risks usually requires rather complicated life-table computations. In this paper we propose a simple approximation to the excess lifetime risk; the validity of the approximation for low levels of exposure is justified empirically as well as theoretically. This approximation provides important guidance in understanding the influence of the various factors involved in risk projections. Among the further topics considered are the influence of a latent period, the additional problems involved in calculations of site-specific excess lifetime cancer risks, the consequences of a leveling off or a plateau in the excess relative risk, and the uncertainties involved in transferring results from one population to another. The main part of this study relates to the situation with a single, instantaneous exposure, but a brief discussion is also given of the problem with a continuous exposure at a low-dose rate.

Normalisation theory: Does it accurately describe temporal changes in adolescent drunkenness and smoking?

PubMed

Sznitman, Sharon R; Zlotnick, Cheryl; Harel-Fisch, Yossi

2016-07-01

The multiple risk model postulates that accumulating risk factors increase adolescent drunkenness and smoking. The normalisation theory adds to this by arguing that the relation between accumulative risk and drunkenness and smoking is dependent on the distribution of these behaviours in the larger population. More concretely, normalisation theory predicts that: (i) when population level use increases, low risk adolescents will be more likely to use alcohol and cigarettes; and (ii) adolescents facing multiple risk factors will be equally likely to use alcohol and cigarettes, regardless of trends in population level use. The current study empirically tests these assumptions on five waves of nationally representative samples of Israeli Jewish youth. Five cross-sectional waves of data from the Israeli Health Behaviour in School-aged Children survey for Jewish 10th graders were used. Logistic regression models measured the impact of changes in population level use across waves on drunkenness and smoking, and their association with differing levels of risk factors. Between zero and two risk factors, the risk of drunkenness and smoking increases for each additional risk factor. When reaching two risk factors, added risk does not significantly increase the likelihood of smoking and drunkenness. Changes in population level drunkenness and smoking did not systematically relate to changes in the individual level relationship between risk factors and smoking and drunkenness. The pattern of results in this study provides strong evidence for the multiple risk factor model and inconsistent evidence for the normalisation theory. [Sznitman SR, Zlotnick C, Harel-Fisch Y. Normalisation theory: Does it accurately describe temporal changes in adolescent drunkenness and smoking? Drug Alcohol Rev 2016;35:424-432]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

PubMed

Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

2011-12-01

This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

Validation of visualized transgenic zebrafish as a high throughput model to assay bradycardia related cardio toxicity risk candidates.

PubMed

Wen, Dingsheng; Liu, Aiming; Chen, Feng; Yang, Julin; Dai, Renke

2012-10-01

Drug-induced QT prolongation usually leads to torsade de pointes (TdP), thus for drugs in the early phase of development this risk should be evaluated. In the present study, we demonstrated a visualized transgenic zebrafish as an in vivo high-throughput model to assay the risk of drug-induced QT prolongation. Zebrafish larvae 48 h post-fertilization expressing green fluorescent protein in myocardium were incubated with compounds reported to induce QT prolongation or block the human ether-a-go-go-related gene (hERG) K⁺ current. The compounds sotalol, indapaminde, erythromycin, ofoxacin, levofloxacin, sparfloxacin and roxithromycin were additionally administrated by microinjection into the larvae yolk sac. The ventricle heart rate was recorded using the automatic monitoring system after incubation or microinjection. As a result, 14 out of 16 compounds inducing dog QT prolongation caused bradycardia in zebrafish. A similar result was observed with 21 out of 26 compounds which block hERG current. Among the 30 compounds which induced human QT prolongation, 25 caused bradycardia in this model. Thus, the risk of compounds causing bradycardia in this transgenic zebrafish correlated with that causing QT prolongation and hERG K⁺ current blockage in established models. The tendency that high logP values lead to high risk of QT prolongation in this model was indicated, and non-sensitivity of this model to antibacterial agents was revealed. These data suggest application of this transgenic zebrafish as a high-throughput model to screen QT prolongation-related cardio toxicity of the drug candidates. Copyright © 2012 John Wiley & Sons, Ltd.

Exchangeability, extreme returns and Value-at-Risk forecasts

NASA Astrophysics Data System (ADS)

Huang, Chun-Kai; North, Delia; Zewotir, Temesgen

2017-07-01

In this paper, we propose a new approach to extreme value modelling for the forecasting of Value-at-Risk (VaR). In particular, the block maxima and the peaks-over-threshold methods are generalised to exchangeable random sequences. This caters for the dependencies, such as serial autocorrelation, of financial returns observed empirically. In addition, this approach allows for parameter variations within each VaR estimation window. Empirical prior distributions of the extreme value parameters are attained by using resampling procedures. We compare the results of our VaR forecasts to that of the unconditional extreme value theory (EVT) approach and the conditional GARCH-EVT model for robust conclusions.

Consumption of meat and fish and risk of lung cancer: results from the European Prospective Investigation into Cancer and Nutrition.

PubMed

Linseisen, Jakob; Rohrmann, Sabine; Bueno-de-Mesquita, Bas; Büchner, Frederike L; Boshuizen, Hendriek C; Agudo, Antonio; Gram, Inger Torhild; Dahm, Christina C; Overvad, Kim; Egeberg, Rikke; Tjønneland, Anne; Boeing, Heiner; Steffen, Annika; Kaaks, Rudolf; Lukanova, Annekatrin; Berrino, Franco; Palli, Domenico; Panico, Salvatore; Tumino, Rosario; Ardanaz, Eva; Dorronsoro, Miren; Huerta, José-Maria; Rodríguez, Laudina; Sánchez, María-José; Rasmuson, Torgny; Hallmans, Göran; Manjer, Jonas; Wirfält, Elisabet; Engeset, Dagrun; Skeie, Guri; Katsoulis, Michael; Oikonomou, Eleni; Trichopoulou, Antonia; Peeters, Petra H M; Khaw, Kay-Tee; Wareham, Nicholas; Allen, Naomi; Key, Tim; Brennan, Paul; Romieu, Isabelle; Slimani, Nadia; Vergnaud, Anne-Claire; Xun, Wei W; Vineis, Paolo; Riboli, Elio

2011-06-01

Evidence from case-control studies, but less so from cohort studies, suggests a positive association between meat intake and risk of lung cancer. Therefore, this association was evaluated in the frame of the European Prospective Investigation into Cancer and Nutrition, EPIC. Data from 478,021 participants, recruited from 10 European countries, who completed a dietary questionnaire in 1992-2000 were evaluated; 1,822 incident primary lung cancer cases were included in the present evaluation. Relative risk estimates were calculated for categories of meat intake using multi-variably adjusted Cox proportional hazard models. In addition, the continuous intake variables were calibrated by means of 24-h diet recall data to account for part of the measurement error. There were no consistent associations between meat consumption and the risk of lung cancer. Neither red meat (RR = 1.06, 95% CI 0.89-1.27 per 50 g intake/day; calibrated model) nor processed meat (RR = 1.13, 95% CI 0.95-1.34 per 50 g/day; calibrated model) was significantly related to an increased risk of lung cancer. Also, consumption of white meat and fish was not associated with the risk of lung cancer. These findings do not support the hypothesis that a high intake of red and processed meat is a risk factor for lung cancer.

Spatial modeling of malaria incidence rates in Sistan and Baluchistan province, Islamic Republic of Iran.

PubMed

Salehi, Masoud; Mohammad, Kazem; Farahani, Mahmud M; Zeraati, Hojjat; Nourijelyani, Keramat; Zayeri, Farid

2008-12-01

To identify the effect of environmental factors on malaria risk, and to visualize spatial map of malaria standard incidence rates in Sistan and Baluchistan province, Islamic Republic of Iran. In this cross-sectional study, the data from 42,162 registered new malaria cases from 21 March 2001 (Iranian new year) to 21 of March 2006 were studied. To describe the statistical association between environmental factors and malaria risk, a generalized linear mixed model approach was utilized. In addition, we used the second ordered stationary Kriging, and a variogram to determine the appropriate spatial correlation structure among the malaria standard incidence rates, and provide a proper malaria risk map in the area under study. The obtained results from the spatial modeling revealed that humidity (p=0.0004), temperature (p<0.0001), and elevation (p<0.0001) were positively, and precipitation (p=0.0029) was inversely correlated with the malaria risk. Moreover, the malaria risk map based on the predicted values showed that the south part of this province (Baluchistan), has a higher risk of malaria, compared to the northern area (Sistan). Since the effective environmental factors on malaria risk are out of human's control, the health policy makers in this province should pay more attention to the areas with high temperature, elevation, and humidity, as well as, low rainfall districts.

Association of human height-related genetic variants with familial short stature in Han Chinese in Taiwan.

PubMed

Lin, Ying-Ju; Liao, Wen-Ling; Wang, Chung-Hsing; Tsai, Li-Ping; Tang, Chih-Hsin; Chen, Chien-Hsiun; Wu, Jer-Yuarn; Liang, Wen-Miin; Hsieh, Ai-Ru; Cheng, Chi-Fung; Chen, Jin-Hua; Chien, Wen-Kuei; Lin, Ting-Hsu; Wu, Chia-Ming; Liao, Chiu-Chu; Huang, Shao-Mei; Tsai, Fuu-Jen

2017-07-25

Human height can be described as a classical and inherited trait model. Genome-wide association studies (GWAS) have revealed susceptible loci and provided insights into the polygenic nature of human height. Familial short stature (FSS) represents a suitable trait for investigating short stature genetics because disease associations with short stature have been ruled out in this case. In addition, FSS is caused only by genetically inherited factors. In this study, we explored the correlations of FSS risk with the genetic loci associated with human height in previous GWAS, alone and cumulatively. We systematically evaluated 34 known human height single nucleotide polymorphisms (SNPs) in relation to FSS in the additive model (p < 0.00005). A cumulative effect was observed: the odds ratios gradually increased with increasing genetic risk score quartiles (p < 0.001; Cochran-Armitage trend test). Six affected genes-ZBTB38, ZNF638, LCORL, CABLES1, CDK10, and TSEN15-are located in the nucleus and have been implicated in embryonic, organismal, and tissue development. In conclusion, our study suggests that 13 human height GWAS-identified SNPs are associated with FSS risk both alone and cumulatively.

Educational Attainment and Mortality in the United States: Effects of Degrees, Years of Schooling, and Certification

PubMed Central

Lawrence, Elizabeth M.; Rogers, Richard G.; Zajacova, Anna

2016-01-01

Researchers have extensively documented a strong and consistent education gradient for mortality, with more highly educated individuals living longer than those with less education. This study contributes to our understanding of the education-mortality relationship by determining the effects of years of education and degree attainment on mortality, and by including nondegree certification, an important but understudied dimension of educational attainment. We use data from the mortality-linked restricted-use files of the Panel Study of Income Dynamics (PSID) sample (N=9,821) and Cox proportional hazards models to estimate mortality risk among U.S. adults. Results indicate that more advanced degrees and additional years of education are associated with reduced mortality risk in separate models, but when included simultaneously, only degrees remain influential. Among individuals who have earned a high school diploma only, additional years of schooling (beyond 12) and vocational school certification (or similar accreditation) are both independently associated with reduced risks of death. Degrees appear to be most important for increasing longevity; the findings also suggest that any educational experience can be beneficial. Future research in health and mortality should consider including educational measures beyond a single variable for educational attainment. PMID:27482124

Risk transfer modeling among hierarchically associated stakeholders in development of space systems

NASA Astrophysics Data System (ADS)

Henkle, Thomas Grove, III

Research develops an empirically derived cardinal model that prescribes handling and transfer of risks between organizations with hierarchical relationships. Descriptions of mission risk events, risk attitudes, and conditions for risk transfer are determined for client and underwriting entities associated with acquisition, production, and deployment of space systems. The hypothesis anticipates that large client organizations should be able to assume larger dollar-value risks of a program in comparison to smaller organizations even though many current risk transfer arrangements via space insurance violate this hypothesis. A literature survey covers conventional and current risk assessment methods, current techniques used in the satellite industry for complex system development, cardinal risk modeling, and relevant aspects of utility theory. Data gathered from open literature on demonstrated launch vehicle and satellite in-orbit reliability, annual space insurance premiums and losses, and ground fatalities and range damage associated with satellite launch activities are presented. Empirically derived models are developed for risk attitudes of space system clients and third-party underwriters associated with satellite system development and deployment. Two application topics for risk transfer are examined: the client-underwriter relationship on assumption or transfer of risks associated with first-year mission success, and statutory risk transfer agreements between space insurance underwriters and the US government to promote growth in both commercial client and underwriting industries. Results indicate that client entities with wealth of at least an order of magnitude above satellite project costs should retain risks to first-year mission success despite present trends. Furthermore, large client entities such as the US government should never pursue risk transfer via insurance under previously demonstrated probabilities of mission success; potential savings may reasonably exceed multiple tens of $millions per space project. Additional results indicate that current US government statutory arrangements on risk sharing with underwriting entities appears reasonable with respect to stated objectives. This research combines aspects of multiple disciplines to include risk management, decision theory, utility theory, and systems architecting. It also demonstrates development of a more general theory on prescribing risk transfer criteria between distinct, but hierarchically associated entities involved in complex system development with applicability to a variety of technical domains.

[Chemical risk in farming].

PubMed

Moretto, Angelo

2013-01-01

The most important chemical risks in agriculture are plant protection products. Exposure evaluation in agriculture is not an easy task and cannot be carried out with the tools and methodologies of industrial exposures. However, toxicological studies on plant protection products, that are compulsory, provide a lot of useful information for actual risk assessment. Exposure evaluation can be carried out on the basis of exposure models and on semiquantitative measures based on the observation of the activity as it is carried our by the farmer. It is therefore possible to develop risk profiles that can guide exposure evaluation and health surveillance. Concentrated animal feeding operations are associated with several chemical risks including disinfectants, antibiotics, and gases such as ammonia and hydrogen sulfide, in addition to organic dusts and endotoxins.

Genetic variants in IL-6/JAK/STAT3 pathway and the risk of CRC.

PubMed

Wang, Shuwei; Zhang, Weidong

2016-05-01

Interleukin (IL)-6 and the downstream Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway have previously been reported to be important in the development of colorectal cancer (CRC), and several studies have shown the relationship between the polymorphisms of related genes in this pathway with the risk of CRC. However, the findings of these related studies are inconsistent. Moreover, there has no systematic review and meta-analysis to evaluate the relationship between genetic variants in IL-6/JAK/STAT3 pathway and CRC susceptibility. Hence, we conducted a meta-analysis to explore the relationship between polymorphisms in IL-6/JAK/STAT3 pathway genes and CRC risk. Eighteen eligible studies with a total of 13,795 CRC cases and 18,043 controls were identified by searching PubMed, Web of Science, Embase, and the Cochrane Library databases for the period up to September 15, 2015. Odds ratios (ORs) and their 95 % confidence intervals (CIs) were used to calculate the strength of the association. Our results indicated that IL-6 genetic variants in allele additive model (OR = 1.05, 95 % CI = 1.00, 1.09) and JAK2 genetic variants (OR = 1.40, 95 % CI = 1.15, 1.65) in genotype recessive model were significantly associated with CRC risk. Moreover, the pooled data revealed that IL-6 rs1800795 polymorphism significantly increased the risk of CRC in allele additive model in Europe (OR = 1.07, 95 % CI = 1.01, 1.14). In conclusion, the present findings indicate that IL-6 and JAK2 genetic variants are associated with the increased risk of CRC while STAT3 genetic variants not. We need more well-designed clinical studies covering more countries and population to definitively establish the association between genetic variants in IL-6/JAK/STAT3 pathway and CRC susceptibility.

AdipoQ polymorphisms are associated with type 2 diabetes mellitus: a meta-analysis study.

PubMed

Chu, Haiyan; Wang, Meilin; Zhong, Dongyan; Shi, Danni; Ma, Lan; Tong, Na; Zhang, Zhengdong

2013-10-01

Adiponectin (AdipoQ) plays an important role in the pathogenesis of diabetes mellitus and is considered as an important candidate gene for type 2 diabetes mellitus (T2DM). So far, there have been many studies to investigate the association between the adiponectin polymorphisms and T2DM risk. However, the results are conflicting. To derive a more precise estimation, we performed a meta-analysis to assess the association between five AdipoQ polymorphisms [-11426A > G (rs16861194), -11391G > A (rs17300539), -11377C > G (rs266729), +45T > G (rs2241766) and +276G > T (rs1501299)], and T2DM risk. The fixed and random-effects model should be used to assess the summary odds ratios (ORs) of each study. ORs with 95% confidence intervals (CIs) were used to evaluate the strength of association. On the basis of the included criteria, we selected 39 papers, among which eight for -11426A > G, 14 for -11391G > A, 21 for -11377C > G, 28 for +45 T > G and 24 for +276G > T. Sensitivity analyses were conducted to assess the stability of the results. Both Begg's funnel plots and Egger's test are commonly used to evaluate publication bias. Overall, we found that individuals with the -11426G allele had a 0.15-fold significantly increased T2DM risk (additive model: 1.15, 1.04-1.27, 0.222). In the stratified analyses, we found that the -11426A > G, -11391G > A and -11377C > G polymorphisms could increase T2DM risk in European populations in the additive model. For Asian populations, we found that the -11377C > G polymorphism also could elevate T2DM risk. Our results suggested that the adiponectin -11426A > G polymorphism could contribute to the T2DM risk. Copyright © 2013 John Wiley & Sons, Ltd.

Choosing a model to predict hospital admission: an observational study of new variants of predictive models for case finding

PubMed Central

Billings, John; Georghiou, Theo; Blunt, Ian; Bardsley, Martin

2013-01-01

Objectives To test the performance of new variants of models to identify people at risk of an emergency hospital admission. We compared (1) the impact of using alternative data sources (hospital inpatient, A&E, outpatient and general practitioner (GP) electronic medical records) (2) the effects of local calibration on the performance of the models and (3) the choice of population denominators. Design Multivariate logistic regressions using person-level data adding each data set sequentially to test value of additional variables and denominators. Setting 5 Primary Care Trusts within England. Participants 1 836 099 people aged 18–95 registered with GPs on 31 July 2009. Main outcome measures Models to predict hospital admission and readmission were compared in terms of the positive predictive value and sensitivity for various risk strata and with the receiver operating curve C statistic. Results The addition of each data set showed moderate improvement in the number of patients identified with little or no loss of positive predictive value. However, even with inclusion of GP electronic medical record information, the algorithms identified only a small number of patients with no emergency hospital admissions in the previous 2 years. The model pooled across all sites performed almost as well as the models calibrated to local data from just one site. Using population denominators from GP registers led to better case finding. Conclusions These models provide a basis for wider application in the National Health Service. Each of the models examined produces reasonably robust performance and offers some predictive value. The addition of more complex data adds some value, but we were unable to conclude that pooled models performed less well than those in individual sites. Choices about model should be linked to the intervention design. Characteristics of patients identified by the algorithms provide useful information in the design/costing of intervention strategies to improve care coordination/outcomes for these patients. PMID:23980068

An unexpected finding: younger fathers have a higher risk for offspring with chromosomal aneuploidies

PubMed Central

Steiner, Bernhard; Masood, Rahim; Rufibach, Kaspar; Niedrist, Dunja; Kundert, Oliver; Riegel, Mariluce; Schinzel, Albert

2015-01-01

The past decades have seen a remarkable shift in the demographics of childbearing in Western countries. The risk for offspring with chromosomal aneuploidies with advancing maternal age is well known, but most studies failed to demonstrate a paternal age effect. Retrospectively, we analyzed two case data sets containing parental ages from pre- and postnatal cases with trisomies 21, 13 and 18. The reference data set contains the parental ages of the general Swiss population. We dichotomized all couples into two distinct groups. In the first group, the mothers' integral age was as least as the father's age or older. We compared the frequency of cases in nine 5-year intervals of maternal age. In addition, we computed logistic regression models for the binary endpoint aneuploidy yes/no where paternal ages were incorporated as linear or quadratic, as well as smooth functions within a generalized additive model framework. We demonstrated that the proportion of younger fathers is uniformly different between cases and controls of live-born trisomy 21 as well, although not reaching significance, for fetuses over all mother's ages. Logistic regression models with different strategies to incorporate paternal ages confirmed our findings. The negative paternal age effect was also found in pre- and postnatal cases taken together with trisomies 13 and 18. The couples with younger fathers face almost twofold odds for a child with Down syndrome (DS). We estimated odds curves for parental ages. If confirmation of these findings can be achieved, the management of couples at risk needs a major correction of the risk stratification. PMID:25005732

Characterizing mammographic images by using generic texture features

PubMed Central

2012-01-01

Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy. PMID:22490545

Earthquake Hazard and Risk in New Zealand

NASA Astrophysics Data System (ADS)

Apel, E. V.; Nyst, M.; Fitzenz, D. D.; Molas, G.

2014-12-01

To quantify risk in New Zealand we examine the impact of updating the seismic hazard model. The previous RMS New Zealand hazard model is based on the 2002 probabilistic seismic hazard maps for New Zealand (Stirling et al., 2002). The 2015 RMS model, based on Stirling et al., (2012) will update several key source parameters. These updates include: implementation a new set of crustal faults including multi-segment ruptures, updating the subduction zone geometry and reccurrence rate and implementing new background rates and a robust methodology for modeling background earthquake sources. The number of crustal faults has increased by over 200 from the 2002 model, to the 2012 model which now includes over 500 individual fault sources. This includes the additions of many offshore faults in northern, east-central, and southwest regions. We also use the recent data to update the source geometry of the Hikurangi subduction zone (Wallace, 2009; Williams et al., 2013). We compare hazard changes in our updated model with those from the previous version. Changes between the two maps are discussed as well as the drivers for these changes. We examine the impact the hazard model changes have on New Zealand earthquake risk. Considered risk metrics include average annual loss, an annualized expected loss level used by insurers to determine the costs of earthquake insurance (and premium levels), and the loss exceedance probability curve used by insurers to address their solvency and manage their portfolio risk. We analyze risk profile changes in areas with large population density and for structures of economic and financial importance. New Zealand is interesting in that the city with the majority of the risk exposure in the country (Auckland) lies in the region of lowest hazard, where we don't have a lot of information about the location of faults and distributed seismicity is modeled by averaged Mw-frequency relationships on area sources. Thus small changes to the background rates can have a large impact on the risk profile for the area. Wellington, another area of high exposure is particularly sensitive to how the Hikurangi subduction zone and the Wellington fault are modeled. Minor changes on these sources have substantial impacts for the risk profile of the city and the country at large.

Doubly Robust Additive Hazards Models to Estimate Effects of a Continuous Exposure on Survival.

PubMed

Wang, Yan; Lee, Mihye; Liu, Pengfei; Shi, Liuhua; Yu, Zhi; Abu Awad, Yara; Zanobetti, Antonella; Schwartz, Joel D

2017-11-01

The effect of an exposure on survival can be biased when the regression model is misspecified. Hazard difference is easier to use in risk assessment than hazard ratio and has a clearer interpretation in the assessment of effect modifications. We proposed two doubly robust additive hazards models to estimate the causal hazard difference of a continuous exposure on survival. The first model is an inverse probability-weighted additive hazards regression. The second model is an extension of the doubly robust estimator for binary exposures by categorizing the continuous exposure. We compared these with the marginal structural model and outcome regression with correct and incorrect model specifications using simulations. We applied doubly robust additive hazard models to the estimation of hazard difference of long-term exposure to PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 microns) on survival using a large cohort of 13 million older adults residing in seven states of the Southeastern United States. We showed that the proposed approaches are doubly robust. We found that each 1 μg m increase in annual PM2.5 exposure was associated with a causal hazard difference in mortality of 8.0 × 10 (95% confidence interval 7.4 × 10, 8.7 × 10), which was modified by age, medical history, socioeconomic status, and urbanicity. The overall hazard difference translates to approximately 5.5 (5.1, 6.0) thousand deaths per year in the study population. The proposed approaches improve the robustness of the additive hazards model and produce a novel additive causal estimate of PM2.5 on survival and several additive effect modifications, including social inequality.

Polymorphisms in the TNFA and IL6 Genes Represent Risk Factors for Autoimmune Thyroid Disease

PubMed Central

Alvelos, Inês; Mendes, Adélia; Santos, Liliana R.; Machado, José Carlos; Melo, Miguel; Esteves, César; Neves, Celestino; Sobrinho-Simões, Manuel; Soares, Paula

2014-01-01

Background Autoimmune thyroid disease (AITD) comprises diseases including Hashimoto's thyroiditis and Graves' disease, both characterized by reactivity to autoantigens causing, respectively, inflammatory destruction and autoimmune stimulation of the thyroid-stimulating hormone receptor. AITD is the most common thyroid disease and the leading form of autoimmune disease in women. Cytokines are key regulators of the immune and inflammatory responses; therefore, genetic variants at cytokine-encoding genes are potential risk factors for AITD. Methods Polymorphisms in the IL6-174 G/C (rs1800795), TNFA-308 G/A (rs1800629), IL1B-511 C/T (rs16944), and IFNGR1-56 T/C (rs2234711) genes were assessed in a case-control study comprising 420 Hashimoto's thyroiditis patients, 111 Graves' disease patients and 735 unrelated controls from Portugal. Genetic variants were discriminated by real-time PCR using TaqMan SNP genotyping assays. Results A significant association was found between the allele A in TNFA-308 G/A and Hashimoto's thyroiditis, both in the dominant (OR = 1.82, CI = 1.37–2.43, p-value = 4.4×10−5) and log-additive (OR = 1.64, CI = 1.28–2.10, p-value = 8.2×10−5) models. The allele C in IL6-174 G/C is also associated with Hashimoto's thyroiditis, however, only retained significance after multiple testing correction in the log-additive model (OR = 1.28, CI = 1.06–1.54, p-value = 8.9×10−3). The group with Graves' disease also registered a higher frequency of the allele A in TNFA-308 G/A compared with controls both in the dominant (OR = 1.85, CI = 1.19–2.87, p-value = 7.0×10−3) and log-additive (OR = 1.69, CI = 1.17–2.44, p-value = 6.6×10−3) models. The risk for Hashimoto's thyroiditis and Graves' disease increases with the number of risk alleles (OR for two risk alleles is, respectively, 2.27 and 2.59). Conclusions This study reports significant associations of genetic variants in TNFA and IL6 with the risk for AITD, highlighting the relevance of polymorphisms in inflammation-related genes in the etiopathogenesis of AITD. PMID:25127106

Gender differences in risk factors for coronary heart disease.

PubMed

Tan, Yen Y; Gast, Gerrie-Cor M; van der Schouw, Yvonne T

2010-02-01

Coronary heart disease (CHD), traditionally considered a male disease, is also a major threat to women. This review article addresses independent risk factors for CHD that are specific for women as well as non-gender-specific risk factors and how their effects differ between men and women. Although polycystic ovary syndrome (PCOS) in women is associated with an adverse metabolic risk profile, current evidence regarding future risk of CHD is conflicting. Preeclampsia is consistently associated with higher risk of CHD later in life. Menopause is associated with an increased risk of CHD, and the earlier the onset of menopause, the larger the risk. Existing data on postmenopausal hormone therapy (HT) was inconclusive with regard to possible protection when HT is initiated close to menopause in young peri- or postmenopausal women. Evidence on use of low-dose oral contraceptives strongly suggests no increased risk of CHD. Although levels of physical inactivity are similar for men and women, the higher prevalences of hypertension, diabetes, and obesity in older women portends a greater risk in women than in men. Additionally, risk factors like smoking, hypertriglyceridemia and low high-density lipoprotein cholesterol levels have greater impact in women than in men. This review indicates that acknowledgement of non-gender-specific risk factors in addition to those that are unique to women would help optimize diagnosis, treatment and earlier prevention of CHD in women. Further research is needed to ascertain if incorporating these gender-specific risks into a clinically used risk stratification model would change outcome in women. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Egg consumption and risk of bladder cancer: a meta-analysis.

PubMed

Li, Fei; Zhou, You; Hu, Rui-ting; Hou, Li-na; Du, Yue-Jun; Zhang, Xin-ji; Olkkonen, Vesa M; Tan, Wan-long

2013-01-01

The findings of epidemiologic studies on the association between egg consumption and bladder cancer risk remain conflicting. We conducted a meta-analysis to clarify the potential association between egg consumption and bladder cancer risk. Four cohort studies and 9 case-control studies in the PubMed database through February 2012 were identified on egg consumption and risk of bladder cancer involving 2715 cases and 184,727 participants. Random-effects models were used to calculate the summary relative risk estimates (SRRE) based on the highest compared with the lowest category of egg consumption. In addition, we performed stratified analyses and sensitivity and dose-response analyses to examine the association. Overall, no significant association was observed between egg consumption and bladder cancer (SRRE = 1.11 95% CI: 0.90-1.35). However, increased risk of bladder cancer was detected in North/South America (SRRE = 1.40 95% CI: 1.05-1.86) and, moreover, fried egg intake positively associated with bladder cancer as well (SRRE = 2.04, 95% CI: 1.41-2.95). In conclusion, our findings suggest no significant association between egg consumption and bladder cancer risk, except for a possible positive relationship with the intake of fried eggs based on the limited number of studies. Additional studies, especially large prospective cohort studies, are warranted to confirm these findings.

Spatial analysis of gastroschisis in Massachusetts and Texas

PubMed Central

Yazdy, Mahsa M.; Werler, Martha M.; Anderka, Marlene; Langlois, Peter H.; Vieira, Veronica M.

2014-01-01

Purpose Previous research has suggested gastroschisis, a congenital malformation, may be linked to environmental or infectious factors and cases can occur in clusters. The objective of this study was to identify geographic areas of elevated gastroschisis risk. Methods Cases of gastroschisis were identified from birth defect registries in Massachusetts and Texas. Random samples of live births were selected as controls. Generalized additive models were used to create a continuous map surface of odds ratios (OR) by smoothing over latitude and longitude. Maternal age, race/ethnicity, education, cigarette smoking, and insurance status (MA only) were assessed for confounding. We used permutation tests to identify statistically significant areas of increased risk. Results An area of increased risk was identified in north-central Massachusetts, but was not significant after adjustment (p-value=0.07; OR=2.0). In Texas, two statistically significant areas of increased risk were identified after adjustment (p-value=0.02; OR=1.3 and 1.2). Texas had sufficient data to assess the combination of space and time, which identified an increased risk in 2003 and 2004. Conclusion This study suggests there were areas of elevated gastroschisis risk in Massachusetts and Texas that cannot be explained by the risk factors we assessed. Additional exploration of underlying artifactual, environmental, infectious, or behavioral factors may further our understanding of gastroschisis. PMID:25454289

Space Radiation Cancer Risks and Uncertainties for Mars Missions

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Schimmerling, W.; Wilson, J. W.; Peterson, L. E.; Badhwar, G. D.; Saganti, P. B.; Dicello, J. F.

2001-01-01

Projecting cancer risks from exposure to space radiation is highly uncertain because of the absence of data for humans and because of the limited radiobiology data available for estimating late effects from the high-energy and charge (HZE) ions present in the galactic cosmic rays (GCR). Cancer risk projections involve many biological and physical factors, each of which has a differential range of uncertainty due to the lack of data and knowledge. We discuss an uncertainty assessment within the linear-additivity model using the approach of Monte Carlo sampling from subjective error distributions that represent the lack of knowledge in each factor to quantify the overall uncertainty in risk projections. Calculations are performed using the space radiation environment and transport codes for several Mars mission scenarios. This approach leads to estimates of the uncertainties in cancer risk projections of 400-600% for a Mars mission. The uncertainties in the quality factors are dominant. Using safety standards developed for low-Earth orbit, long-term space missions (>90 days) outside the Earth's magnetic field are currently unacceptable if the confidence levels in risk projections are considered. Because GCR exposures involve multiple particle or delta-ray tracks per cellular array, our results suggest that the shape of the dose response at low dose rates may be an additional uncertainty for estimating space radiation risks.

Lipid-related markers and cardiovascular disease prediction.

PubMed

Di Angelantonio, Emanuele; Gao, Pei; Pennells, Lisa; Kaptoge, Stephen; Caslake, Muriel; Thompson, Alexander; Butterworth, Adam S; Sarwar, Nadeem; Wormser, David; Saleheen, Danish; Ballantyne, Christie M; Psaty, Bruce M; Sundström, Johan; Ridker, Paul M; Nagel, Dorothea; Gillum, Richard F; Ford, Ian; Ducimetiere, Pierre; Kiechl, Stefan; Koenig, Wolfgang; Dullaart, Robin P F; Assmann, Gerd; D'Agostino, Ralph B; Dagenais, Gilles R; Cooper, Jackie A; Kromhout, Daan; Onat, Altan; Tipping, Robert W; Gómez-de-la-Cámara, Agustín; Rosengren, Annika; Sutherland, Susan E; Gallacher, John; Fowkes, F Gerry R; Casiglia, Edoardo; Hofman, Albert; Salomaa, Veikko; Barrett-Connor, Elizabeth; Clarke, Robert; Brunner, Eric; Jukema, J Wouter; Simons, Leon A; Sandhu, Manjinder; Wareham, Nicholas J; Khaw, Kay-Tee; Kauhanen, Jussi; Salonen, Jukka T; Howard, William J; Nordestgaard, Børge G; Wood, Angela M; Thompson, Simon G; Boekholdt, S Matthijs; Sattar, Naveed; Packard, Chris; Gudnason, Vilmundur; Danesh, John

2012-06-20

The value of assessing various emerging lipid-related markers for prediction of first cardiovascular events is debated. To determine whether adding information on apolipoprotein B and apolipoprotein A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 to total cholesterol and high-density lipoprotein cholesterol (HDL-C) improves cardiovascular disease (CVD) risk prediction. Individual records were available for 165,544 participants without baseline CVD in 37 prospective cohorts (calendar years of recruitment: 1968-2007) with up to 15,126 incident fatal or nonfatal CVD outcomes (10,132 CHD and 4994 stroke outcomes) during a median follow-up of 10.4 years (interquartile range, 7.6-14 years). Discrimination of CVD outcomes and reclassification of participants across predicted 10-year risk categories of low (<10%), intermediate (10%-<20%), and high (≥20%) risk. The addition of information on various lipid-related markers to total cholesterol, HDL-C, and other conventional risk factors yielded improvement in the model's discrimination: C-index change, 0.0006 (95% CI, 0.0002-0.0009) for the combination of apolipoprotein B and A-I; 0.0016 (95% CI, 0.0009-0.0023) for lipoprotein(a); and 0.0018 (95% CI, 0.0010-0.0026) for lipoprotein-associated phospholipase A2 mass. Net reclassification improvements were less than 1% with the addition of each of these markers to risk scores containing conventional risk factors. We estimated that for 100,000 adults aged 40 years or older, 15,436 would be initially classified at intermediate risk using conventional risk factors alone. Additional testing with a combination of apolipoprotein B and A-I would reclassify 1.1%; lipoprotein(a), 4.1%; and lipoprotein-associated phospholipase A2 mass, 2.7% of people to a 20% or higher predicted CVD risk category and, therefore, in need of statin treatment under Adult Treatment Panel III guidelines. In a study of individuals without known CVD, the addition of information on the combination of apolipoprotein B and A-I, lipoprotein(a), or lipoprotein-associated phospholipase A2 mass to risk scores containing total cholesterol and HDL-C led to slight improvement in CVD prediction.

Functional Risk Modeling for Lunar Surface Systems

NASA Technical Reports Server (NTRS)

Thomson, Fraser; Mathias, Donovan; Go, Susie; Nejad, Hamed

2010-01-01

We introduce an approach to risk modeling that we call functional modeling , which we have developed to estimate the capabilities of a lunar base. The functional model tracks the availability of functions provided by systems, in addition to the operational state of those systems constituent strings. By tracking functions, we are able to identify cases where identical functions are provided by elements (rovers, habitats, etc.) that are connected together on the lunar surface. We credit functional diversity in those cases, and in doing so compute more realistic estimates of operational mode availabilities. The functional modeling approach yields more realistic estimates of the availability of the various operational modes provided to astronauts by the ensemble of surface elements included in a lunar base architecture. By tracking functional availability the effects of diverse backup, which often exists when two or more independent elements are connected together, is properly accounted for.

Vaccinating in disease-free regions: a vaccine model with application to yellow fever.

PubMed

Codeço, Claudia T; Luz, Paula M; Coelho, Flavio; Galvani, Alison P; Struchiner, Claudio

2007-12-22

Concerns regarding natural or induced emergence of infectious diseases have raised a debate on the pros and cons of pre-emptive vaccination of populations under uncertain risk. In the absence of immediate risk, ethical issues arise because even smaller risks associated with the vaccine are greater than the immediate disease risk (which is zero). The model proposed here seeks to formalize the vaccination decision process looking from the perspective of the susceptible individual, and results are shown in the context of the emergence of urban yellow fever in Brazil. The model decomposes the individual's choice about vaccinating or not into uncertain components. The choice is modelled as a function of (i) the risk of a vaccine adverse event, (ii) the risk of an outbreak and (iii) the probability of receiving the vaccine or escaping serious disease given an outbreak. Additionally, we explore how this decision varies as a function of mass vaccination strategies of varying efficiency. If disease is considered possible but unlikely (risk of outbreak less than 0.1), delay vaccination is a good strategy if a reasonably efficient campaign is expected. The advantage of waiting increases as the rate of transmission is reduced (low R0) suggesting that vector control programmes and emergency vaccination preparedness work together to favour this strategy. The opposing strategy, vaccinating pre-emptively, is favoured if the probability of yellow fever urbanization is high or if expected R0 is high and emergency action is expected to be slow. In summary, our model highlights the nonlinear dependence of an individual's best strategy on the preparedness of a response to a yellow fever outbreak or other emergent infectious disease.

Statistical correlations and risk analyses techniques for a diving dual phase bubble model and data bank using massively parallel supercomputers.

PubMed

Wienke, B R; O'Leary, T R

2008-05-01

Linking model and data, we detail the LANL diving reduced gradient bubble model (RGBM), dynamical principles, and correlation with data in the LANL Data Bank. Table, profile, and meter risks are obtained from likelihood analysis and quoted for air, nitrox, helitrox no-decompression time limits, repetitive dive tables, and selected mixed gas and repetitive profiles. Application analyses include the EXPLORER decompression meter algorithm, NAUI tables, University of Wisconsin Seafood Diver tables, comparative NAUI, PADI, Oceanic NDLs and repetitive dives, comparative nitrogen and helium mixed gas risks, USS Perry deep rebreather (RB) exploration dive,world record open circuit (OC) dive, and Woodville Karst Plain Project (WKPP) extreme cave exploration profiles. The algorithm has seen extensive and utilitarian application in mixed gas diving, both in recreational and technical sectors, and forms the bases forreleased tables and decompression meters used by scientific, commercial, and research divers. The LANL Data Bank is described, and the methods used to deduce risk are detailed. Risk functions for dissolved gas and bubbles are summarized. Parameters that can be used to estimate profile risk are tallied. To fit data, a modified Levenberg-Marquardt routine is employed with L2 error norm. Appendices sketch the numerical methods, and list reports from field testing for (real) mixed gas diving. A Monte Carlo-like sampling scheme for fast numerical analysis of the data is also detailed, as a coupled variance reduction technique and additional check on the canonical approach to estimating diving risk. The method suggests alternatives to the canonical approach. This work represents a first time correlation effort linking a dynamical bubble model with deep stop data. Supercomputing resources are requisite to connect model and data in application.

Mouse Model of Halogenated Platinum Salt Hypersensitivity

EPA Science Inventory

Occupational exposure to halogenated platinum salts can trigger the development of asthma. Concern for increased asthma risk exists for the general population due to the use of platinum (Pt) in catalytic converters and its emerging use as a diesel fuel additive. To investigate a...

Predictors of non-vertebral fracture in older Chinese males and females: Mr. OS and Ms. OS (Hong Kong).

PubMed

Kwok, Timothy Chi Yui; Su, Yi; Khoo, Chyi Chyi; Leung, Jason; Kwok, Anthony; Orwoll, Eric; Woo, Jean; Leung, Ping Chung

2017-05-01

Clinical risk factors to predict fracture are useful in guiding management of patients with osteoporosis or falls. Clinical predictors may however be population specific because of differences in lifestyle, environment and ethnicity. Four thousand community-dwelling Chinese males and females with average ages of 72.4 and 72.6 years were followed up for incident fractures, with an average of 6.5 and 8.8 years, respectively. Clinical information was collected, and bone mineral density (BMD) measurements were carried out at baseline. Stepwise Cox regression models were used to identify risk factors of nonvertebral fractures, with BMD as covariate. Areas under the receiver-operating characteristic (ROC) curve (AUC) were compared among different risk models. The incidence rates of nonvertebral fractures were 10.3 and 20.5 per 1000 person years in males and females, respectively. In males, age ≥80, history of a fall in the past year, fracture history, chronic obstructive pulmonary disease, impaired visual depth perception and low physical health-related quality of life were significant fracture risk factors, independent of BMD. In females, the significant factors were fracture history, low visual acuity and slow narrow walking speed. The clinical risk factors had a significant influence on fracture risk irrespective of osteoporosis status, even having a better risk discrimination than BMD alone, especially in males. The best risk prediction model consisted both BMD and clinical risk factors. Clinical risk factors have additive value to hip BMD in predicting nonvertebral fractures in older Chinese people and may predict them better than BMD alone in older Chinese males.

Default risk modeling beyond the first-passage approximation: Extended Black-Cox model

NASA Astrophysics Data System (ADS)

Katz, Yuri A.; Shokhirev, Nikolai V.

2010-07-01

We develop a generalization of the Black-Cox structural model of default risk. The extended model captures uncertainty related to firm’s ability to avoid default even if company’s liabilities momentarily exceeding its assets. Diffusion in a linear potential with the radiation boundary condition is used to mimic a company’s default process. The exact solution of the corresponding Fokker-Planck equation allows for derivation of analytical expressions for the cumulative probability of default and the relevant hazard rate. Obtained closed formulas fit well the historical data on global corporate defaults and demonstrate the split behavior of credit spreads for bonds of companies in different categories of speculative-grade ratings with varying time to maturity. Introduction of the finite rate of default at the boundary improves valuation of credit risk for short time horizons, which is the key advantage of the proposed model. We also consider the influence of uncertainty in the initial distance to the default barrier on the outcome of the model and demonstrate that this additional source of incomplete information may be responsible for nonzero credit spreads for bonds with very short time to maturity.

[Evaluation of a training system for middle ear surgery with optoelectric detection].

PubMed

Strauss, G; Bahrami, N; Pössneck, A; Strauss, M; Dietz, A; Korb, W; Lüth, T; Haase, R; Moeckel, H; Grunert, R

2009-10-01

This work presents a new training concept for surgery of the temporal bone. It is based on a model of gypsum plastic with optoelectric detection of risk structures. A prototypical evaluation is given. The training models are based on high-resolution computed tomographic data of a human skull. The resulting data set was printed by a three-dimensional (3D) printer. A 3D phantom is created from gypsum powder and a bonding agent. Risks structures are the facial nerve, semicircular canal, cochlea, ossicular chain, sigmoid sinus, dura, and internal carotid artery. An electrically conductive metal (Wood's metal) and a fiber-optic cable were used as detection materials for the risk structures. For evaluating the training system, a study was done with eight inexperienced and eight experienced ear surgeons. They were asked to perform temporal bone surgery using two identical training models (group A). In group B, the same surgeons underwent surgical training with human cadavers. In the case of injuries, the number, point in time, degree (facial nerve), and injured structure were documented during the training on the model. In addition, the total time needed was noted. The training systems could be used in all cases. Evaluation of the anatomic accuracy of the models showed results that were between 49.5% and 90% agreement with the anatomic origin. Error detection was evaluated with values between 79% and 100% agreement with the perception of an experienced surgeon. The operating setting was estimated to be better than the previous"gold standard." The possibility of completely replacing the previous training method, which uses cadavers, with the examined training model was affirmed. This study shows that the examined system fulfills the conditions for a new training concept for temporal bone surgery. The system connects the preliminary work with printed and sintered models with the possibilities of microsystem engineering. In addition, the model's digital database permits a complete virtual representation of the model with appropriate further applications ("look behind the wall," virtual endoscopy).

Methods for assessing fracture risk prediction models: experience with FRAX in a large integrated health care delivery system.

PubMed

Pressman, Alice R; Lo, Joan C; Chandra, Malini; Ettinger, Bruce

2011-01-01

Area under the receiver operating characteristics (AUROC) curve is often used to evaluate risk models. However, reclassification tests provide an alternative assessment of model performance. We performed both evaluations on results from FRAX (World Health Organization Collaborating Centre for Metabolic Bone Diseases, University of Sheffield, UK), a fracture risk tool, using Kaiser Permanente Northern California women older than 50yr with bone mineral density (BMD) measured during 1997-2003. We compared FRAX performance with and without BMD in the model. Among 94,489 women with mean follow-up of 6.6yr, 1579 (1.7%) sustained a hip fracture. Overall, AUROCs were 0.83 and 0.84 for FRAX without and with BMD, suggesting that BMD did not contribute to model performance. AUROC decreased with increasing age, and BMD contributed significantly to higher AUROC among those aged 70yr and older. Using an 81% sensitivity threshold (optimum level from receiver operating characteristic curve, corresponding to 1.2% cutoff), 35% of those categorized above were reassigned below when BMD was added. In contrast, only 10% of those categorized below were reassigned to the higher risk category when BMD was added. The net reclassification improvement was 5.5% (p<0.01). Two versions of this risk tool have similar AUROCs, but alternative assessments indicate that addition of BMD improves performance. Multiple methods should be used to evaluate risk tool performance with less reliance on AUROC alone. Copyright © 2011 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Mortality in US Army Gulf War Veterans Exposed to 1991 Khamisiyah Chemical Munitions Destruction

PubMed Central

Bullman, Tim A.; Mahan, Clare M.; Kang, Han K.; Page, William F.

2005-01-01

Objectives. We investigated whether US Army Gulf War veterans who were potentially exposed to nerve agents during the March 1991 weapons demolitions at Khamisiyah, Iraq, are at increased risk of cause-specific mortality. Methods. The cause-specific mortality of 100487 exposed US Army Gulf War veterans was compared with that of 224980 unexposed US Army Gulf War veterans. Exposure was determined with the Department of Defense 2000 plume model. Relative risk estimates were derived from Cox proportional hazards models. Results. The risks of most disease-related mortality were similar for exposed and unexposed veterans. However, exposed veterans had an increased risk of brain cancer deaths (relative risk [RR]=1.94; 95% confidence interval [CI]=1.12, 3.34). The risk of brain cancer death was larger among those exposed 2 or more days than those exposed 1 day when both were compared separately to all unexposed veterans (RR=3.26; 95% CI=1.33, 7.96; RR=1.72; 95% CI=0.95,3.10, respectively). Conclusions. Exposure to chemical munitions at Khamisiyah may be associated with an increased risk of brain cancer death. Additional research is required to confirm this finding. PMID:16043669

Mortality in US Army Gulf War veterans exposed to 1991 Khamisiyah chemical munitions destruction.

PubMed

Bullman, Tim A; Mahan, Clare M; Kang, Han K; Page, William F

2005-08-01

We investigated whether US Army Gulf War veterans who were potentially exposed to nerve agents during the March 1991 weapons demolitions at Khamisiyah, Iraq, are at increased risk of cause-specific mortality. The cause-specific mortality of 100487 exposed US Army Gulf War veterans was compared with that of 224980 unexposed US Army Gulf War veterans. Exposure was determined with the Department of Defense 2000 plume model. Relative risk estimates were derived from Cox proportional hazards models. The risks of most disease-related mortality were similar for exposed and unexposed veterans. However, exposed veterans had an increased risk of brain cancer deaths (relative risk [RR]=1.94; 95% confidence interval [CI]=1.12, 3.34). The risk of brain cancer death was larger among those exposed 2 or more days than those exposed 1 day when both were compared separately to all unexposed veterans (RR=3.26; 95% CI=1.33, 7.96; RR=1.72; 95% CI=0.95,3.10, respectively). Exposure to chemical munitions at Khamisiyah may be associated with an increased risk of brain cancer death. Additional research is required to confirm this finding.

Segregation analysis of prostate cancer in France: evidence for autosomal dominant inheritance and residual brother-brother dependence.

PubMed

Valeri, A; Briollais, L; Azzouzi, R; Fournier, G; Mangin, P; Berthon, P; Cussenot, O; Demenais, F

2003-03-01

Four segregation analyses concerning prostate cancer (CaP), three conducted in the United States and one in Northern Europe, have shown evidence for a dominant major gene but with different parameter estimates. A recent segregation analysis of Australian pedigrees has found a better fit of a two-locus model than single-locus models. This model included a dominantly inherited increased risk that was greater at younger ages and a recessively inherited or X-linked increased risk that was greater at older ages. Recent linkage analyses have led to the detection of at least 8 CaP predisposing genes, suggesting a complex inheritance and genetic heterogeneity. To assess the nature of familial aggregation of prostate cancer in France, segregation analysis was conducted in 691 families ascertained through 691 CaP patients, recruited from three French hospitals and unselected with respect to age at diagnosis, clinical stage or family history. This mode of family inclusion, without any particular selection of the probands, is unique, as probands from all previous analyses were selected according to various criteria. Segregation analysis was carried out using the logistic hazard regressive model, as incorporated in the REGRESS program, which can accommodate a major gene effect, residual familial dependences of any origin (genetic and/or environmental), and covariates, while including survival analysis concepts. Segregation analysis showed evidence for the segregation of an autosomal dominant gene (allele frequency of 0.03%) with an additional brother-brother dependence. The estimated cumulative risks of prostate cancer by age 85 years, among subjects with the at-risk genotype, were 86% in the fathers' generation and 99% in the probands' generation. This study supports the model of Mendelian transmission of a rare autosomal dominant gene with high penetrance, and demonstrates that additional genetic and/or common sibling environmental factors are involved to account for the familial clustering of CaP.

Medication use and associated risk of falling in a geriatric outpatient population.

PubMed

Freeland, Kathryn N; Thompson, Amy N; Zhao, Yumin; Leal, Julie E; Mauldin, Patrick D; Moran, William P

2012-09-01

Studies have shown that approximately one third of community-dwelling people aged 65 years and older will experience a fall each year. Many studies indicate that use of multiple medications may put patients at an increased risk of falling, but few studies have been conducted to correlate the number of medications with the risk of falls. To determine the medications most frequently used in patients aged 65 years or older who have experienced a fall within the past year, with particular attention to type or number of medications most commonly associated with multiple falls or a fall with injury. We conducted a chart review in an outpatient internal medicine clinic over a 13-month period. A total of 118 patients 65 years of age or older who were taking 4 or more medications and had experienced at least 1 fall in the previous 12 months were included. Data relating to sex, age, race, diagnoses, medications, and number and type of falls were obtained during the chart review. The primary end point of the study was number and type of medications most commonly used in patients experiencing a fall. A total of 116 patients were examined for trends in fall risk. A logistic regression model and receiver operating characteristic curve demonstrated significant fall risk with the addition of medications, with patients experiencing a 14% increase in fall risk with the addition of each medication beyond a 4-medication regimen (OR 1.14; 95% CI 1.02 to 1.27; p = 0.027). The addition of medications is associated with a significant increase in risk of falls in elderly patients, regardless of drug class. Further studies are needed to assess the possible increased risk of falls with increasing number of medications.

Risk factors for breast cancer in postmenopausal Caucasian and Chinese-Canadian women.

PubMed

Tam, Carolyn Y; Martin, Lisa J; Hislop, Gregory; Hanley, Anthony J; Minkin, Salomon; Boyd, Norman F

2010-01-01

Striking differences exist between countries in the incidence of breast cancer. The causes of these differences are unknown, but because incidence rates change in migrants, they are thought to be due to lifestyle rather than genetic differences. The goal of this cross-sectional study was to examine breast cancer risk factors in populations with different risks for breast cancer. We compared breast cancer risk factors among three groups of postmenopausal Canadian women at substantially different risk of developing breast cancer - Caucasians (N = 413), Chinese women born in the West or who migrated to the West before age 21 (N = 216), and recent Chinese migrants (N = 421). Information on risk factors and dietary acculturation were collected by telephone interviews using questionnaires, and anthropometric measurements were taken at a home visit. Compared to Caucasians, recent Chinese migrants weighed on average 14 kg less, were 6 cm shorter, had menarche a year later, were more often parous, less often had a family history of breast cancer or a benign breast biopsy, a higher Chinese dietary score, and a lower Western dietary score. For most of these variables, Western born Chinese and early Chinese migrants had values intermediate between those of Caucasians and recent Chinese migrants. We estimated five-year absolute risks for breast cancer using the Gail Model and found that risk estimates in Caucasians would be reduced by only 11% if they had the risk factor profile of recent Chinese migrants for the risk factors in the Gail Model. Our results suggest that in addition to the risk factors in the Gail Model, there likely are other factors that also contribute to the large difference in breast cancer risk between Canada and China.

Urinary Sodium Concentration Is an Independent Predictor of All-Cause and Cardiovascular Mortality in a Type 2 Diabetes Cohort Population

PubMed Central

Gand, Elise; Ragot, Stéphanie; Bankir, Lise; Piguel, Xavier; Fumeron, Frédéric; Halimi, Jean-Michel; Marechaud, Richard; Roussel, Ronan; Hadjadj, Samy; Study group, SURDIAGENE

2017-01-01

Objective. Sodium intake is associated with cardiovascular outcomes. However, no study has specifically reported an association between cardiovascular mortality and urinary sodium concentration (UNa). We examined the association of UNa with mortality in a cohort of type 2 diabetes (T2D) patients. Methods. Patients were followed for all-cause death and cardiovascular death. Baseline UNa was measured from second morning spot urinary sample. We used Cox proportional hazard models to identify independent predictors of mortality. Improvement in prediction of mortality by the addition of UNa to a model including known risk factors was assessed by the relative integrated discrimination improvement (rIDI) index. Results. Participants (n = 1,439) were followed for a median of 5.7 years, during which 254 cardiovascular deaths and 429 all-cause deaths were recorded. UNa independently predicted all-cause and cardiovascular mortality. An increase of one standard deviation of UNa was associated with a decrease of 21% of all-cause mortality and 22% of cardiovascular mortality. UNa improved all-cause and cardiovascular mortality prediction beyond identified risk factors (rIDI = 2.8%, P = 0.04 and rIDI = 4.6%, P = 0.02, resp.). Conclusions. In T2D, UNa was an independent predictor of mortality (low concentration is associated with increased risk) and improved modestly its prediction in addition to traditional risk factors. PMID:28255559

Parental Warmth and Risks of Substance Use in Children with Attention-Deficit/Hyperactivity Disorder: Findings from a 10–12 Year Longitudinal Investigation

PubMed Central

Tandon, Mini; Tillman, Rebecca; Spitznagel, Edward; Luby, Joan

2013-01-01

Objective The study examined factors in the risk trajectory for Substance Use Disorder (SUD) over a 10–12 year period in children with ADHD. Method N=145 children between the ages of 7 and 16 with ADHD and healthy controls were assessed every 2 years for 10–12 years as part of a larger, longitudinal investigation. Onset of substance use disorder was examined using Cox proportional hazards modeling, and included child and parent psychopathology, and parental warmth as well as other key factors. Results Low paternal warmth and maternal SUD were predictors of SUD in n=59 ADHD participants after adjusting for gender, child ODD, paternal SUD, maternal/paternal ADHD, maternal/paternal major depressive disorder (MDD), maternal/paternal anxiety, and low maternal warmth in the Cox model. Conclusions Longitudinal study findings suggest that in addition to the established risk of ADHD and maternal SUD in development of child SUD, low paternal warmth is also associated with onset of SUD. This was evident after controlling for pertinent parent and child psychopathology. These findings suggest that paternal warmth warrants further investigation as a key target for novel interventions to prevent SUD in children with ADHD. More focused investigations examining paternal parenting factors in addition to parent and child psychopathology in the risk trajectory from ADHD to SUD are now warranted. PMID:24955084

Parental Warmth and Risks of Substance Use in Children with Attention-Deficit/Hyperactivity Disorder: Findings from a 10-12 Year Longitudinal Investigation.

PubMed

Tandon, Mini; Tillman, Rebecca; Spitznagel, Edward; Luby, Joan

2014-06-01

The study examined factors in the risk trajectory for Substance Use Disorder (SUD) over a 10-12 year period in children with ADHD. N=145 children between the ages of 7 and 16 with ADHD and healthy controls were assessed every 2 years for 10-12 years as part of a larger, longitudinal investigation. Onset of substance use disorder was examined using Cox proportional hazards modeling, and included child and parent psychopathology, and parental warmth as well as other key factors. Low paternal warmth and maternal SUD were predictors of SUD in n=59 ADHD participants after adjusting for gender, child ODD, paternal SUD, maternal/paternal ADHD, maternal/paternal major depressive disorder (MDD), maternal/paternal anxiety, and low maternal warmth in the Cox model. Longitudinal study findings suggest that in addition to the established risk of ADHD and maternal SUD in development of child SUD, low paternal warmth is also associated with onset of SUD. This was evident after controlling for pertinent parent and child psychopathology. These findings suggest that paternal warmth warrants further investigation as a key target for novel interventions to prevent SUD in children with ADHD. More focused investigations examining paternal parenting factors in addition to parent and child psychopathology in the risk trajectory from ADHD to SUD are now warranted.

On cancer risk estimation of urban air pollution.

PubMed Central

Törnqvist, M; Ehrenberg, L

1994-01-01

The usefulness of data from various sources for a cancer risk estimation of urban air pollution is discussed. Considering the irreversibility of initiations, a multiplicative model is preferred for solid tumors. As has been concluded for exposure to ionizing radiation, the multiplicative model, in comparison with the additive model, predicts a relatively larger number of cases at high ages, with enhanced underestimation of risks by short follow-up times in disease-epidemiological studies. For related reasons, the extrapolation of risk from animal tests on the basis of daily absorbed dose per kilogram body weight or per square meter surface area without considering differences in life span may lead to an underestimation, and agreements with epidemiologically determined values may be fortuitous. Considering these possibilities, the most likely lifetime risks of cancer death at the average exposure levels in Sweden were estimated for certain pollution fractions or indicator compounds in urban air. The risks amount to approximately 50 deaths per 100,000 for inhaled particulate organic material (POM), with a contribution from ingested POM about three times larger, and alkenes, and butadiene cause 20 deaths, respectively, per 100,000 individuals. Also, benzene and formaldehyde are expected to be associated with considerable risk increments. Comparative potency methods were applied for POM and alkenes. Due to incompleteness of the list of compounds considered and the uncertainties of the above estimates, the total risk calculation from urban air has not been attempted here. PMID:7821292

12 CFR Appendix H to Part 1022 - Appendix H-Model Forms for Risk-Based Pricing and Credit Score Disclosure Exception Notices

Code of Federal Regulations, 2013 CFR

2013-01-01

... addresses that may change over time. ii. The addition of graphics or icons, such as the person's corporate... change the forms by rearranging the format or by making technical modifications to the language of the... required to conduct consumer testing when rearranging the format of the model forms. a. Acceptable changes...

Risk analysis of emergent water pollution accidents based on a Bayesian Network.

PubMed

Tang, Caihong; Yi, Yujun; Yang, Zhifeng; Sun, Jie

2016-01-01

To guarantee the security of water quality in water transfer channels, especially in open channels, analysis of potential emergent pollution sources in the water transfer process is critical. It is also indispensable for forewarnings and protection from emergent pollution accidents. Bridges above open channels with large amounts of truck traffic are the main locations where emergent accidents could occur. A Bayesian Network model, which consists of six root nodes and three middle layer nodes, was developed in this paper, and was employed to identify the possibility of potential pollution risk. Dianbei Bridge is reviewed as a typical bridge on an open channel of the Middle Route of the South to North Water Transfer Project where emergent traffic accidents could occur. Risk of water pollutions caused by leakage of pollutants into water is focused in this study. The risk for potential traffic accidents at the Dianbei Bridge implies a risk for water pollution in the canal. Based on survey data, statistical analysis, and domain specialist knowledge, a Bayesian Network model was established. The human factor of emergent accidents has been considered in this model. Additionally, this model has been employed to describe the probability of accidents and the risk level. The sensitive reasons for pollution accidents have been deduced. The case has also been simulated that sensitive factors are in a state of most likely to lead to accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of risk assessment based on clinical judgement and Cariogram in addition to patient perceived treatment need.

PubMed

Hänsel Petersson, Gunnel; Åkerman, Sigvard; Isberg, Per-Erik; Ericson, Dan

2016-07-07

Predicting future risk for oral diseases, treatment need and prognosis are tasks performed daily in clinical practice. A large variety of methods have been reported, ranging from clinical judgement or "gut feeling" or even patient interviewing, to complex assessments of combinations of known risk factors. In clinical practice, there is an ongoing continuous search for less complicated and more valid tools for risk assessment. There is also a lack of knowledge how different common methods relates to one another. The aim of this study was to investigate if caries risk assessment (CRA) based on clinical judgement and the Cariogram model give similar results. In addition, to assess which factors from clinical status and history agree best with the CRA based on clinical judgement and how the patient's own perception of future oral treatment need correspond with the sum of examiners risk score. Clinical examinations were performed on randomly selected individuals 20-89 years old living in Skåne, Sweden. In total, 451 individuals were examined, 51 % women. The clinical examination included caries detection, saliva samples and radiographic examination together with history and a questionnaire. The examiners made a risk classification and the authors made a second risk calculation according to the Cariogram. For those assessed as low risk using the Cariogram 69 % also were assessed as low risk based on clinical judgement. For the other risk groups the agreement was lower. Clinical variables that significantly related to CRA based on clinical judgement were DS (decayed surfaces) and combining DS and incipient lesions, DMFT (decayed, missed, filled teeth), plaque amount, history and soft drink intake. Patients' perception of future oral treatment need correlated to some extent with the sum of examiners risk score. The main finding was that CRA based on clinical judgement and the Cariogram model gave similar results for the groups that were predicted at low level of future disease, but not so well for the other groups. CRA based on clinical judgement agreed best with the number of DS plus incipient lesions.

Classification of co-occurring depression and substance abuse symptoms predicts suicide attempts in adolescents.

PubMed

Effinger, Jenell M; Stewart, David G

2012-08-01

Although both depression and substance use have been found to contribute to suicide attempts, the synergistic impact of these disorders has not been fully explored. Additionally, the impact of subthreshold presentations of these disorders has not been researched. We utilized the Quadrant Model of Classification (a matrix of severity of two disorders) to assess for suicide attempt risk among adolescents. Logistic regression was used to examine the impact of co-occurring disorder classification on suicide risk attempts. Results indicate that quadrant classification had a dramatic impact on suicide attempt risk, with individuals with high severity co-occurring disorders at greatest risk. © 2012 The American Association of Suicidology.

Creation of mortality risk charts using 123I meta-iodobenzylguanidine heart-to-mediastinum ratio in patients with heart failure: 2- and 5-year risk models.

PubMed

Nakajima, Kenichi; Nakata, Tomoaki; Matsuo, Shinro; Jacobson, Arnold F

2016-10-01

(123)I meta-iodobenzylguanidine (MIBG) imaging has been extensively used for prognostication in patients with chronic heart failure (CHF). The purpose of this study was to create mortality risk charts for short-term (2 years) and long-term (5 years) prediction of cardiac mortality. Using a pooled database of 1322 CHF patients, multivariate analysis, including (123)I-MIBG late heart-to-mediastinum ratio (HMR), left ventricular ejection fraction (LVEF), and clinical factors, was performed to determine optimal variables for the prediction of 2- and 5-year mortality risk using subsets of the patients (n = 1280 and 933, respectively). Multivariate logistic regression analysis was performed to create risk charts. Cardiac mortality was 10 and 22% for the sub-population of 2- and 5-year analyses. A four-parameter multivariate logistic regression model including age, New York Heart Association (NYHA) functional class, LVEF, and HMR was used. Annualized mortality rate was <1% in patients with NYHA Class I-II and HMR ≥ 2.0, irrespective of age and LVEF. In patients with NYHA Class III-IV, mortality rate was 4-6 times higher for HMR < 1.40 compared with HMR ≥ 2.0 in all LVEF classes. Among the subset of patients with b-type natriuretic peptide (BNP) results (n = 491 and 359 for 2- and 5-year models, respectively), the 5-year model showed incremental value of HMR in addition to BNP. Both 2- and 5-year risk prediction models with (123)I-MIBG HMR can be used to identify low-risk as well as high-risk patients, which can be effective for further risk stratification of CHF patients even when BNP is available. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Cardiology.

Job strain (demands and control model) as a predictor of cardiovascular risk factors among petrochemical personnel

PubMed Central

Habibi, Ehsanollah; Poorabdian, Siamak; Shakerian, Mahnaz

2015-01-01

Background: One of the practical models for the assessment of stressful working conditions due to job strain is job demand and control model, which explains how physical and psychological adverse consequences, including cardiovascular risk factors can be established due to high work demands (the amount of workload, in addition to time limitations to complete that work) and low control of the worker on his/her work (lack of decision making) in the workplace. The aim of this study was to investigate how certain cardiovascular risk factors (including body mass index [BMI], heart rate, blood pressure, cholesterol and smoking) and the job demand and job control are related to each other. Materials and Methods: This prospective cohort study was conducted on 500 workers of the petrochemical industry in south of Iran, 2009. The study population was selected using simple random statistical method. They completed job demand and control questionnaire. The cardiovascular risk factors data was extracted from the workers hygiene profiles. Chi-square (χ2) test and hypothesis test (η) were used to assess the possible relationship between different quantified variables, individual demographic and cardiovascular risk factors. Results: The results of this study revealed that a significant relationship can be found between job demand control model and cardiovascular risk factors. Chi-square test result for the heart rate showed the highest (χ2 = 145.078) relationship, the corresponding results for smoking and BMI were χ2 = 85.652 and χ2 = 30.941, respectively. Subsequently, hypothesis testing results for cholesterol and hypertension was 0.469 and 0.684, respectively. Discussion: Job strain is likely to be associated with an increased risk of cardiovascular risk factors among male staff in a petrochemical company in Iran. The parameters illustrated in the Job demands and control model can act as acceptable predictors for the probability of job stress occurrence followed by showing a high trend of CVD risk factors. PMID:25861661

Radiation-Induced Leukemia at Doses Relevant to Radiation Therapy: Modeling Mechanisms and Estimating Risks

NASA Technical Reports Server (NTRS)

Shuryak, Igor; Sachs, Rainer K.; Hlatky, Lynn; Mark P. Little; Hahnfeldt, Philip; Brenner, David J.

2006-01-01

Because many cancer patients are diagnosed earlier and live longer than in the past, second cancers induced by radiation therapy have become a clinically significant issue. An earlier biologically based model that was designed to estimate risks of high-dose radiation induced solid cancers included initiation of stem cells to a premalignant state, inactivation of stem cells at high radiation doses, and proliferation of stem cells during cellular repopulation after inactivation. This earlier model predicted the risks of solid tumors induced by radiation therapy but overestimated the corresponding leukemia risks. Methods: To extend the model to radiation-induced leukemias, we analyzed in addition to cellular initiation, inactivation, and proliferation a repopulation mechanism specific to the hematopoietic system: long-range migration through the blood stream of hematopoietic stem cells (HSCs) from distant locations. Parameters for the model were derived from HSC biologic data in the literature and from leukemia risks among atomic bomb survivors v^ ho were subjected to much lower radiation doses. Results: Proliferating HSCs that migrate from sites distant from the high-dose region include few preleukemic HSCs, thus decreasing the high-dose leukemia risk. The extended model for leukemia provides risk estimates that are consistent with epidemiologic data for leukemia risk associated with radiation therapy over a wide dose range. For example, when applied to an earlier case-control study of 110000 women undergoing radiotherapy for uterine cancer, the model predicted an excess relative risk (ERR) of 1.9 for leukemia among women who received a large inhomogeneous fractionated external beam dose to the bone marrow (mean = 14.9 Gy), consistent with the measured ERR (2.0, 95% confidence interval [CI] = 0.2 to 6.4; from 3.6 cases expected and 11 cases observed). As a corresponding example for brachytherapy, the predicted ERR of 0.80 among women who received an inhomogeneous low-dose-rate dose to the bone marrow (mean = 2.5 Gy) was consistent with the measured ERR (0.62, 95% Cl =-0.2 to 1.9). Conclusions: An extended, biologically based model for leukemia that includes HSC initiation, inactivation, proliferation, and, uniquely for leukemia, long-range HSC migration predicts, %Kith reasonable accuracy, risks for radiationinduced leukemia associated with exposure to therapeutic doses of radiation.

Predicting preterm birth among participants of North Carolina’s Pregnancy Medical Home Program

PubMed Central

Tucker, Christine M.; Berrien, Kate; Menard, M. Kathryn; Herring, Amy H.; Daniels, Julie; Rowley, Diane L.; Halpern, Carolyn Tucker

2016-01-01

Objective To determine which combination of risk factors from Community Care of North Carolina’s (CCNC) Pregnancy Medical Home (PMH) risk screening form was most predictive of preterm birth (PTB) by parity and race/ethnicity. Methods This retrospective cohort included pregnant Medicaid patients screened by the PMH program before 24 weeks gestation who delivered a live birth in North Carolina between September 2011-September 2012 (N=15,428). Data came from CCNC’s Case Management Information System, Medicaid claims, and birth certificates. Logistic regression with backward stepwise elimination was used to arrive at the final models. To internally validate the predictive model, we used bootstrapping techniques. Results The prevalence of PTB was 11%. Multifetal gestation, a previous PTB, cervical insufficiency, diabetes, renal disease, and hypertension were the strongest risk factors with odds ratios ranging from 2.34 to 10.78. Non-Hispanic black race, underweight, smoking during pregnancy, asthma, other chronic conditions, nulliparity, and a history of a low birth weight infant or fetal death/second trimester loss were additional predictors in the final predictive model. About half of the risk factors prioritized by the PMH program remained in our final model (ROC=0.66). The odds of PTB associated with food insecurity and obesity differed by parity. The influence of unsafe or unstable housing and short interpregnancy interval on PTB differed by race/ethnicity. Conclusions Evaluation of the PMH risk screen provides insight to ensure women at highest risk are prioritized for care management. Using multiple data sources, salient risk factors for PTB were identified, allowing for better-targeted approaches for PTB prevention. PMID:26112751