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At least 505 records · Page 28Linked to original sources
PubMed1997

Curvilinearity in the dose-response curve for cancer in Japanese atomic bomb survivors.

Recently released data on cancer incidence in Japanese atomic bomb survivors are analyzed using a variety of relative risk models that take account of errors in estimates of dose to assess the dose response at low doses. If a relative risk model with a threshold (the dose response is assumed linear above the threshold) is fitted to solid cancer data, a threshold of more than about 0.2 Sv is inconsistent with the data, whereas these data are consistent with there being no threshold. Among solid cancer subtypes there is strong evidence for a possible dose threshold only for nonmelanoma skin cancer. If a relative risk model with a threshold (the dose response is assumed linear above the threshold) is fitted to the leukemia data, a threshold of more than about 0.3 Sv is inconsistent with the data. In contrast to the estimates for the threshold level for solid cancer data, the best estimate for the threshold level in the leukemia data is significantly different from zero even when allowance is made for a possible quadratic term in the dose response, albeit at borderline levels of statistical significance (p = 0.04). There is little evidence for curvature in the leukemia dose response from 0.2 Sv upwards. However, possible underestimation of the errors in the estimates of the dose threshold as a result of confounding and uncertainties not taken into account in the analysis, together with the lack of biological plausibility of a threshold, makes interpretation of this finding questionable.

Dose-Response Relationship, Radiation↗
PubMed2002

Risk-based modeling of early warning systems for pollution accidents.

An early warning system is a mechanism for detecting, characterizing and providing notification of a source water contamination event (spill event) in order to mitigate the impact of contamination. Spill events are highly probabilistic occurrences with major spills, which can have very significant impacts on raw water sources of drinking water, being relatively rare. A systematic method for designing and operating early warning systems that considers the highly variable, probabilistic nature of many aspects of the system is described. The methodology accounts for the probability of spills, behavior of monitoring equipment, variable hydrology, and the probability of obtaining information about spills independent of a monitoring system. Spill Risk, a risk-based model using Monte Carlo simulation techniques has been developed and its utility has been demonstrated as part of an AWWA Research Foundation sponsored project. The model has been applied to several hypothetical river situations and to an actual section of the Ohio River. Additionally, the model has been systematically applied to a wide range of conditions in order to develop general guidance on design of early warning systems.

Accidents↗
PubMed2001

Small scale water recycling systems--risk assessment and modelling.

This paper aims to use quantitative risk analysis, risk modelling and simulation modelling tools to assess the performance of a proprietary single house grey water recycling system. A preliminary Hazard and Operability study (HAZOP) identified the main hazards, both health related and economic, associated with installing the recycling system in a domestic environment. The health related consequences of system failure were associated with the presence of increased concentrations of micro-organisms at the point of use, due to failure of the disinfection system and/or the pump. The risk model was used to assess the increase in the probability of infection for a particular genus of micro-organism, Salmonella spp, during disinfection failure. The increase in the number of cases of infection above a base rate rose from 0.001% during normal operation, to 4% for a recycling system with no disinfection. The simulation model was used to examine the possible effects of pump failure. The model indicated that the anaerobic COD release rate in the system storage tank increases over time and dissolved oxygen decreases during this failure mode. These conditions are likely to result in odour problems.

Conservation of Natural Resources↗
PubMed1991

Analysis of a risk-based model for the growth of AIDS infection.

Several models for the spread of AIDS within a homosexual community have been proposed that incorporate biased mixing of different risk groups. A simple model is presented that captures many of the features of these more complex models. Analytical expressions are derived for the time to the state of maximum infection (SMI) in a particular risk group, the proportion infected at SMI, and the number of infected individuals as the group approaches SMI. These results agree qualitatively with numerical simulations of the model.

Acquired Immunodeficiency Syndrome↗
PubMed2006

Modelling competing risks in cancer studies.

Competing risks arise commonly in the analysis of cancer studies. Most common are the competing risks of relapse and death in remission. These two risks are the primary reason that patients fail treatment. In most medical papers the effects of covariates on the three outcomes (relapse, death in remission and treatment failure) are model by distinct proportional hazards regression models. Since the hazards of relapse and death in remission must add to that of treatment failure, we argue that this model leads to internal inconsistencies. We argue that additive models for either the hazard rates or the cumulative incidence functions are more natural and that these models properly partition the effect of a covariate on treatment failure into its component parts. We illustrate the use and interpretation of additive models for the hazard rate or for the cumulative incidence function using data from a study of the efficacy of two preparative regimes for hematopoietic stem cell transplantation.

Adult↗
PubMed2001

A risk-stratification model of non-small cell lung cancers using cyclin E, Ki-67, and ras p21: different roles of G1 cyclins in cell proliferation and prognosis.

A large number of biological factors that seem to have important prognostic significance have been identified in non-small cell lung cancers (NSCLCs). In the present study, we have characterized expression of cyclin D1 and cyclin E in a cohort of 217 resected NSCLCs from a single institution by immunohistochemistry to analyze their expression in relation to the growth fraction determined by Ki-67 and to prognosis, and then we have constructed a risk-stratification model of cancer death by multiple biological factors in p-stage I NSCLCs. The cyclin E labeling index (LI) was significantly associated with the Ki-67 LI (r = 0.45; P < 0.001). Tumors having high-level cyclin E expression (cyclin E LI > or =30%) showed a significantly higher Ki-67 LI than tumors having low-level cyclin E expression (cyclin E LI <30%; P < 0.001), whereas positive or negative cyclin D1 expression was not associated with the Ki-67 LI (P = 0.1). Cyclin E expression was a significant and independent unfavorable prognostic factor (hazards ratio = 2.09; P = 0.03), as reported previously (Clin. Cancer Res., 6: 11-16, 2000), whereas cyclin D1 expression was not. These findings indicate different roles of cyclin D1 and cyclin E in cell proliferation and in the prognosis of NSCLCs. Furthermore, we stratified this cohort of p-stage I NSCLCs into different survival groups by using biological factors, including cyclin E, Ki-67, and ras p21, which previously we have found to be independent prognostic factors among 10 factors studied in p-stage I NSCLCs. Four groups of patients with markedly different survivals were identified with 5-year survival rates that ranged from 96% for patients with no factors altered to 41% for patients with all three factors altered (P < 0.001). This combination of biological factors was a significant and independent prognostic factor (hazards ratio = 7.94; P = 0.001).

Aged↗
PubMed1994

Compartmental models and competing risk.

General compartmental models are derived using competing risk arguments. When the risk variables are exponential, the results specialize to the standard stationary Markov compartmental model. Iterative methods of solving the fundamental integral equation are given, and the uniqueness of the solution is incidentally established. The analysis is extended to include fixed inputs, orderly and nonorderly stream infusions, and time dependency. The study is motivated by a biological system that evolves through various stages over time.

Biological Evolution↗
PubMed2006

Comparison of 19 pre-operative risk stratification models in open-heart surgery.

AIMS: To compare 19 risk score algorithms with regard to their validity to predict 30-day and 1-year mortality after cardiac surgery. METHODS AND RESULTS: Risk factors for patients undergoing heart surgery between 1996 and 2001 at a single centre were prospectively collected. Receiver operating characteristics (ROC) curves were used to describe the performance and accuracy. Survival at 1 year and cause of death were obtained in all cases. The study included 6222 cardiac surgical procedures. Actual mortality was 2.9% at 30 days and 6.1% at 1 year. Discriminatory power for 30-day and 1-year mortality in cardiac surgery was highest for logistic (0.84 and 0.77) and additive (0.84 and 0.77) European System for Cardiac Operative Risk Evaluation (EuroSCORE) algorithms, followed by Cleveland Clinic (0.82 and 0.76) and Magovern (0.82 and 0.76) scoring systems. None of the other 15 risk algorithms had a significantly better discriminatory power than these four. In coronary artery bypass grafting (CABG)-only surgery, EuroSCORE followed by New York State (NYS) and Cleveland Clinic risk score showed the highest discriminatory power for 30-day and 1-year mortality. CONCLUSION: EuroSCORE, Cleveland Clinic, and Magovern risk algorithms showed superior performance and accuracy in open-heart surgery, and EuroSCORE, NYS, and Cleveland Clinic in CABG-only surgery. Although the models were originally designed to predict early mortality, the 1-year mortality prediction was also reasonably accurate.

Adolescent↗
PubMed2006

Use of a risk communication model to evaluate dietetics professionals' viewpoints on genetically engineered foods and crops.

The complex issues surrounding the application of genetic engineering to food and agriculture have generated a contentious debate among diverse interest groups. One pervasive dimension in the resultant discourse is the varying perceptions of the risks and benefits of genetically engineered foods and crops. In the risk communication model, technical information is evaluated within the context of an individual's values and perceptions. The purpose of this study was to explore how dietetics professionals respond to a complex set of interrelated issues associated with genetically engineered foods and crops and to identify what varying viewpoints may exist. Participants were asked to sort a total of 48 statements distributed across eight issue areas according to level of agreement and disagreement. Using Q methodology, a total of 256 sortings were analyzed using the centroid method and varimax rotation in factor analysis. Three distinct viewpoints emerged: Precautionary (R(2)=43%), Discerning Supporter (R(2)=11%), and Promoting (R(2)=5%). Across all viewpoints, respondents agreed that dietetics professionals should employ critical thinking skills to communicate the social, economic, environmental, ethical, and technical aspects of genetically engineered foods and crops. The findings have implications for how dietetics professionals can foster an open interchange of information among diverse groups.

Attitude of Health Personnel↗
PubMed1993

Measures of effect based on the sufficient causes model. 1. Risks and rates of disease associated with a single causative agent.

The sufficient causes model of disease occurrence leads to a specific conception of how the risk of disease resulting from exposure to an agent combines with background risks. From this conception, one can derive a method for quantifying in populations the respective effects of the agent and background, using either rates or risks. This method differs from the usual difference or ratio measures of effect by taking into account the probability that the sufficient cause of disease involving the agent of interest and that not involving it will both occur during the observation period. The method leads to: (1) measures of the risks or rates of completion of sufficient causes involving or not involving the agent of interest; (2) a measure of the proportion of cases preventable by removing or blocking the agent, based on observed risks of disease. This proportion varies as a function of the duration of exposure; (3) a measure of the proportion of cases caused by the agent, based on observed rates of disease. This proportion is constant over time, if the rates are; (4) a causal interpretation of a constant rate ratio, when the rates vary over time.

Acquired Immunodeficiency Syndrome↗
PubMed1995

Models of risk assessments for biologicals or related products in the European Union.

In the context of veterinary biologicals, environmental risk assessment means the evaluation of the risk to human health and the environment (which includes plants and animals) connected with the release of such products. The following categories or types of veterinary biologicals can be distinguished: non-genetically modified organisms (non-GMOs) (inactivated/live) GMOs (inactivated/live) carrier products related products (e.g. non-specific "inducers'). Suitable models used in risk assessment for these products should aim to identify all possible adverse effects. A good working model should lead, at least, to a qualitative judgement on the environmental risk of the biological product (e.g. negligible, low, medium, severe, unacceptable). Quantifiable outcomes are rare; therefore, the producer of a biological product and the European control authorities should accept only models which are based on testable points and which are relevant to the type of product and its instructions for use. In view of animal welfare aspects, models working without animals should be preferred. In recent years, some of these methods have been integrated into safety tests described in European Union Directives and in monographs of the European Pharmacopoeia. By reviewing vaccine/registration problems (e.g. Aujeszky's disease live vaccine for pigs, and vaccinia-vectored rabies vaccine), several models used in risk assessment are demonstrated and discussed.

Animals↗
PubMed2005

Comment on "Derivation of numerical values for the World Health Organization guidelines for recreational waters".

The subject paper describes a procedure for adjusting a risk model based upon a measure of personal exposure (the "UK personal exposure model") in order to attribute an expected rate of gastroenteritis among a group of swimmers to a mean recreational water quality value (enterococci per 100mL). We term the resulting model for group risk the "UK ecologic exposure model." The distinction is essential to establishing recreational water quality guidelines because exposures of individual bathers are not known from a water monitoring program, the only assessment available being some form of ecologic exposure such as a mean log indicator density. While the authors of the subject paper solved the UK ecologic exposure model for only a single point (that value of mean log10 enterococcus density which is expected to result in five extra cases of gastroenteritis per 100 swimmers), we extend their model to show the entire curve over a relevant range of densities. The resulting exposure-response curve is seen to not differ substantially from the existing USEPA model for "highly credible gastrointestinal illness" in marine waters. However, particularly since such correspondence is not guaranteed for future studies or for other existing epidemiological studies, we recommend the direct approach to evaluating ecologic exposure, such as used in the USEPA studies, rather than the indirect approach of the UK ecologic exposure model, given the number of untested assumptions that are necessary for accomplishing the latter.

Ecology↗
PubMed2002

The use of biologically based modeling in risk assessment.

Technological advances are rapidly leading toxicology and risk assessment to an age where there are advantages of routine use of biologically based modeling as an adjunct to laboratory experiments will be compelling. The biologically based model, a formal representation of the system being studied, serves both the experimentalist and the risk assessor. Benefits of its development include identification of data gaps, optimization of experimental design and, with sufficient validation, quantitative extrapolations between routes of exposure, species and doses. This article focuses on the role of biologically based modeling in support of the dose-response assessment component of risk assessment. The problem of uncertainty in dose-response assessment and the role of mechanistic studies combined with modeling to efficiently reduce uncertainty are discussed. The need for close cooperation between experimentalists, modelers, and risk assessors to achieve this efficiency is emphasized. A model for formaldehyde is briefly described to illustrate key issues.

Animals↗
PubMed1995

1988: use of a Bayesian statistical model for risk assessment in coronary artery surgery. Updated in 1995.

A computerized statistical model based on the theorem of Bayes was developed to predict mortality after coronary artery bypass grafting. From January, 1984, to April, 1987, at our hospital, 700 patients underwent isolated coronary artery bypass grafting. The presence or absence of 20 risk factors was determined for each patient. The first 300 patients formed the initial database of the Bayesian predictive model, and the remaining 400 patients were prospectively evaluated in four groups of 100 each. Each group was prospectively evaluated and then incorporated into the database to update the model. There was good agreement between predicted and observed results. Bayesian theory is particularly suited to this task because it (1) accommodates multiple risk factors, (2) is tailored to one's specific practice, (3) determines individual, rather than group, prognosis, and (4) can be updated with time to compensate for a changing patient population. These flexible attributes are especially valuable in light of recent changes in the coronary artery bypass graft patient profile.

Bayes Theorem↗
PubMed1997

Using actuarial models to assess managed care risk.

Actuarial models can be used to illustrate the financial risks inherent in healthcare provider operations. They are especially useful in analyzing the implications of managed care agreements, which revolve around risk and the financing of risk. Simple actuarial models may focus on inpatient utilization and reimbursement under capitation. More sophisticated models detail risks associated with individual diagnosis-related groups, as well as with many types of outpatient and physician services. Actuarial models can provide an objective basis for planning for the future and can be used to build consensus on strategies that will ensure success under managed care agreements.

Actuarial Analysis↗
PubMed2000

On the role of animal models in risk assessment of neurotoxic pesticides.

A complication is given on the elements of risk assessment of hazardous neurotoxic pesticides, using data from human epidemiological studies, as well as animal experiments. Well-controlled laboratory studies of neurotoxicity have the potential to provide adequate exposure and effect data for accurate hazard identification. Using animal models of neurotoxicity as highly sensitive behavioral and neurophysiological methods as a function of doses, provide data for human low dose extrapolation by mathematical models. To reduce risk ("risk management") some examples are given how to handle properly neurotoxic pesticides with high risk.

Animals↗
PubMed2005

BRCA1 and BRCA2 mutation predictions using the BOADICEA and BRCAPRO models and penetrance estimation in high-risk French-Canadian families.

INTRODUCTION: Several genetic risk models for breast and ovarian cancer have been developed, but their applicability to specific populations has not been evaluated. We used data from French-Canadian families to evaluate the mutation predictions given by the BRCAPRO and BOADICEA models. We also used this data set to estimate the age-specific risks for breast and ovarian cancer in BRCA1 and BRCA2 mutation carriers. METHODS: A total of 195 families with multiple affected individuals with breast or ovarian cancer were recruited through the INHERIT (INterdisciplinary HEalth Research International Team on BReast CAncer susceptibility) BRCAs research program. Observed BRCA1 and BRCA2 mutation status was compared with predicted carrier probabilities under the BOADICEA and BRCAPRO models. The models were assessed using Brier scores, attributes diagrams and receiver operating characteristic curves. Log relative risks for breast and ovarian cancer in mutation carriers versus population risks were estimated by maximum likelihood, using a modified segregation analysis implemented in the computer program MENDEL. Twenty-five families were eligible for inclusion in the BRCA1 penetrance analysis and 27 families were eligible for the BRCA2 penetrance analysis. RESULTS: The BOADICEA model predicted accurately the number of BRCA1 and BRCA2 mutations for the various groups of families, and was found to discriminate well at the individual level between carriers and noncarriers. BRCAPRO over-predicted the number of mutations in almost all groups of families, in particular the number of BRCA1 mutations. It significantly overestimated the carrier frequency for high predicted probabilities. However, it discriminated well between carriers and noncarriers. Receiver operating characteristic (ROC) curves indicate similar sensitivity and specificity for BRCAPRO and BOADICEA. The estimated risks for breast and ovarian cancer in BRCA1 and BRCA2 mutation carriers were consistent with previously published estimates. CONCLUSION: The BOADICEA model predicts accurately the carrier probabilities in French-Canadian families and may be used for counselling in this population. None of the penetrance estimates was significantly different from previous estimates, suggesting that previous estimates may be appropriate for counselling in this population.

Adolescent↗