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At least 523 records · Page 29Linked to original sources
PubMed2005

Risk assessment for asbestos-related cancer from the 9/11 attack on the World Trade Center.

OBJECTIVE: We sought to estimate the lifetime risk of asbestos-related cancer for residents of Lower Manhattan attributable to asbestos released into the air by the 9/11 attack on New York City's World Trade Center (WTC). METHODS: Exposure was estimated from available data and reasoned projections based on these data. Cancer risk was assessed using an asbestos risk model that differentiates asbestos fiber-types and the US Environmental Protection Agency's model that does not differentiate fiber-types and combines mesothelioma and lung cancer risks. RESULTS: The upper limit for the expected number of asbestos-related cancers is less than one case over the lifetime of the population for the risk model that is specific for fiber-types and 12 asbestos-related cancers with the US Environmental Protection Agency's model. CONCLUSIONS: The cancer risk associated with asbestos exposures for residents of Lower Manhattan resulting from the collapse of the WTC is negligible.

Adolescent↗
PubMed2000

Principal inpatient diagnostic cost group model for Medicare risk adjustment.

The Balanced Budget Act (BBA) of 1997 required HCFA to implement health-status-based risk adjustment for Medicare capitation payments for managed care plans by January 1, 2000. In support of this mandate, HCFA has been collecting inpatient encounter data from health plans since 1997. These data include diagnoses and other information that can be used to identify chronic medical problems that contribute to higher costs, so that health plans can be paid more when they care for sicker patients. In this article, the authors describe the risk-adjustment model HCFA is implementing in the year 2000, known as the Principal Inpatient Diagnostic Cost Group (PIPDCG) model.

Adolescent↗
PubMed2004

Risk assessment of patients with hematologic malignancies who develop fever accompanied by pulmonary infiltrates: a historical cohort study.

BACKGROUND: The mortality rate associated with fever accompanied by pulmonary infiltrates after chemotherapy for hematologic malignancies remains higher than the corresponding rate associated with febrile neutropenia without pulmonary infiltrates. Nonetheless, few studies have focused on the factors that predict outcome for patients with lung infiltrates. The purpose of the current study was to construct a risk model for clinical use by assessing the factors that affect outcome for patients with fever and pulmonary infiltrates. METHODS: A historical cohort of 110 patients with hematologic malignancies who developed fever and pulmonary infiltrates was examined. Using parameters for which data were available at the onset of lung infiltrates, univariate and multivariate analyses were performed to assess factors affecting outcome. After a value of one point was assigned to each significant variable, a prediction score was calculated for each patient; scores were used to generate a system for identifying patients with a low risk of death due to fever accompanied by pulmonary infiltrates. RESULTS: The crude mortality rate associated with pulmonary infiltrates was 23%; factors associated with cure included a favorable change in white blood cell counts (odds ratio [OR], 5.6; 95% confidence interval [CI], 1.7-18.9; P = 0.001), C-reactive protein levels < 10 mg/dL (OR, 4.6; 95% CI, 1.6-13.8; P = 0.001), and serum albumin levels > or = 3 g/dL (OR, 3.2; 95% CI, 1.4-7.3; P = 0.004). Low-risk patients (risk score, 2-3) and high-risk patients (risk score, 0-1) had survival rates of 95% and 46%, respectively (P < 0.0001). The risk model had a specificity of 88% and a positive predictive value of 95%. CONCLUSIONS: The risk model tested in the current study accurately predicted the survival of patients with hematologic malignancies who developed fever with pulmonary infiltrates. Once prospectively validated, the model could be used to select patients for trials involving novel diagnostic and therapeutic strategies.

Age Distribution↗
PubMed1995

Estimates of radiogenic cancer risks.

A methodology recently developed by the U.S. EPA for estimating the carcinogenic risks from ionizing radiation is described. For most cancer sites, the risk model is one in which age-specific, relative risk coefficients are obtained by taking a geometric mean of the coefficients derived from the atomic bomb survivor data using two different methods for transporting risks from the Japanese to the U.S. population. The risk models are applied to estimate organ-specific risks per unit dose for a stationary population with mortality rates governed by 1980 U.S. vital statistics. With the exception of breast cancer, low-LET radiogenic cancer risk estimates are reduced by a factor of 2 at low doses and dose rates compared to acute high dose exposure conditions. For low dose (or dose rate) conditions, the risk of inducing a premature cancer death from uniform, whole body, low-LET irradiation is calculated to be 5.1 x 10(-2) Gy-1. Neglecting nonfatal skin cancers, the corresponding incidence risk is 7.6 x 10(-2) Gy-1. High-LET (alpha particle) risks are presumed to increase linearly with dose and to be independent of dose rate. High-LET risks are estimated to be 20 times the low-LET risks estimated under low dose rate conditions, except for leukemia and breast cancer where RBEs of 1 and 10 are adopted, respectively.

Adolescent↗
PubMed1995

Identifying adults at increased risk of coronary disease. How well do the current cholesterol guidelines work?

OBJECTIVE: To assess the accuracy of lipid screening strategies to identify individuals at increased risk of coronary heart disease mortality. PATIENTS: The 15% random sample of adults recruited into the Lipid Research Clinic Prevalence and Follow-up Studies, which included 3678 men and women aged 35 to 74 years. Total plasma cholesterol levels, lipoprotein fractions, and other coronary risk factors at study entry were compared with subsequent coronary heart disease mortality (mean follow-up, 12.2 years). MAIN OUTCOME MEASURES: The areas under receiver operating characteristic curves for blood lipids, lipid ratios, the screening guidelines proposed by the National National Cholesterol Education Program, those of the Canadian Consensus Conference on Cholesterol, and a coronary risk model that used Framingham data. MAIN RESULTS: The current National Cholesterol Education Program guidelines (area under the curve, 0.74) were significantly (P = .03) more accurate than the old National Cholesterol Education Program guidelines (area, 0.72). The ratio of total plasma cholesterol level to high-density lipoprotein cholesterol level (area, 0.72) was as accurate as current National Cholesterol Education Program guidelines. The coronary risk model (area, 0.85) was superior (P < .003) to all other screening maneuvers. Compared with the current National Cholesterol Education Program guidelines, the risk model demonstrated superior test sensitivity (70% vs 45%) with only slightly reduced specificity (82% vs 86%). CONCLUSION: The ratio of total plasma cholesterol level to high-density lipoprotein cholesterol level is as accurate as current American screening guidelines. Future guidelines should better incorporate high-density lipoprotein cholesterol levels and nonlipid risk factors to target high-risk individuals accurately.

Adult↗
PubMed2003

Assessment of the disposal of radioactive petroleum industry waste in nonhazardous landfills using risk-based modeling.

Certain petroleum production activities cause naturally occurring radioactive materials (NORM) to accumulate in concentrations above natural background levels, making safe and cost-effective management of such technologically enhanced NORM (TENORM) a key issue for the petroleum industry. As a result, both industry and regulators are interested in identifying cost-effective disposal alternatives that provide adequate protection of human health and the environment One such alternative, currently allowed in Michigan with restrictions, is the disposal of TENORM wastes in nonhazardous waste landfills. The disposal of petroleum industry wastes containing radium-226 (Ra-226) in nonhazardous landfills was modeled to evaluate the potential radiological doses and health risks to workers and the public. Multiple scenarios were considered in evaluating the potential risks associated with landfill operations and the future use of the property. The scenarios were defined, in part, to evaluate the Michigan policy; sensitivity analyses were conducted to evaluate the impact of key parameters on potential risks. The results indicate that the disposal of petroleum industry TENORM wastes in nonhazardous landfills in accordance with the Michigan policy and existing landfill regulations presents a negligible risk to most of the potential receptors considered in this study.

Background Radiation↗
PubMed2000

Regression models and risk estimation for mixed discrete and continuous outcomes in developmental toxicology.

Multivariate dose-response models have recently been proposed for developmental toxicity data to simultaneously model malformation incidence (a binary outcome), and reductions in fetal weight (a continuous outcome). In this and other applications, the binary outcome often represents a dichotomization of another outcome or a composite of outcomes, which facilitates analysis. For example, in Segment II developmental toxicology studies, multiple malformation types (i.e., external, visceral, skeletal) are evaluated on each fetus; malformation status may also be ordinally measured (e.g., normal, signs of variation, full malformation). A model is proposed is for fetal weight and multiple malformation variables measured on an ordinal scale, where the correlations between the outcomes and between the offspring within a litter are taken into account. Fully specifying the joint distribution of outcomes within a litter is avoided by specifying only the distribution of the multivariate outcome for each fetus and using generalized estimating equation methodology to account for correlations due to litter clustering. The correlations between the outcomes are required to characterize joint risk to the fetus, and are therefore a focus of inference. Dose-response models and their application to quantitative risk assessment are illustrated using data from a recent developmental toxicology experiment of ethylene oxide in mice.

Abnormalities, Drug-Induced↗
PubMed1999

Pre-existing medical conditions as predictors of adverse events in day-case surgery.

We have developed mathematical models to estimate the risk of perioperative adverse events in patients with pre-existing conditions undergoing day-case surgery. We studied 17,638 consecutive day-case surgical patients in a prospective study. Preoperative, intraoperative and postoperative data were collected. Risk modelling was performed with backward stepwise multiple logistic regression and validated on a separate subset of our patients. Eighteen pre-existing conditions were entered into the model. We adjusted for age, sex, and duration and type of surgery. Seven associations between pre-existing medical conditions and perioperative adverse events were statistically significant. Hypertension predicted the occurrence of any intraoperative event and intraoperative cardiovascular events. Obesity predicted intraoperative and postoperative respiratory events, and smoking and asthma predicted postoperative respiratory events. Gastro-oesophageal reflux predicted intubation-related events. The presented models of risk estimation were validated internally and provided a useful tool for accurate risk estimation.

Adolescent↗
PubMedDate not supplied

[Spatial risk distribution: modeling infant mortality in Porto Alegre, Rio Grande do Sul State, Brazil].

Estimation and mapping of risk profiles are the main concerns of epidemiology. This paper analyzes spatial distribution of infant mortality cases as compared to live-born controls from Porto Alegre, Rio Grande do Sul. The modeling framework adopted in this research work is a spatial point process. Under this structure, a risk measure which continuously varies over the study region is defined and estimated using generalized additive model methods. This approach has the advantage of allowing for risk factors that are simple and easy to interpret. The procedure also allows the construction of tolerance contours which help identify areas of significantly high/low risk and an overall test for the null hypothesis of constant risk over the region. Application of this method to infant mortality data showed a highly significant spatial variation in risk for neonatal mortality data and non-significant results for post-neonatal mortality data.

Brazil↗
PubMed1996

Biokinetics and biokinetic models in risk assessment.

Risk assessment of xenobiotics using animal data involves extrapolation from high doses to low ones, and from animal species to humans. In some cases it also involves extrapolation from one route of exposure to another. To assess the risk of exposure to xenobiotics, information on both biokinetics and biodynamics are needed. The contribution of biokinetics to risk assessment is the subject of this review. The review includes the general aspects of biokinetics of chemicals, the models available to describe the biokinetic behaviour of a chemical and a discussion of the class of biokinetic models that is considered most suited for application to risk assessment: the physiologically-based biokinetic (PBBK) models. The power of PBBK models is illustrated with a few examples.

Administration, Cutaneous↗
PubMed1990

Towards an understanding of risk behavior: an AIDS risk reduction model (ARRM).

This report presents a three-stage model (ARRM) that characterize people's efforts to change sexual behaviors related to HIV transmission. ARRM focuses on social and psychological factors hypothesized to influence (1) labeling of high risk behaviors as problematic, (2) making a commitment to changing high risk behaviors, and (3) seeking and enacting solutions directed at reducing high risk activities. The proposed model integrates important concepts from prior behavioral medicine and human sexuality studies, specifies their differential import to achieving the goals associated with each stage of the model, and denotes factors hypothesized to influence people's motivation to continue the change process over time. Current findings are discussed within this three-stage model and directions for further research are suggested. Recent findings from our ongoing studies of gays and heterosexuals in San Francisco are presented.

Acquired Immunodeficiency Syndrome↗
PubMed2006

Mammographic density correlation with Gail model breast cancer risk estimates and component risk factors.

BACKGROUND: The Gail model is a validated breast cancer risk assessment tool that is primarily based on nonmodifiable breast cancer risk factors. Conversely, mammographic breast density is strongly correlated with breast cancer risk and responds to risk-modifying interventions. The purpose of our study was to correlate mammographic density with breast cancer risk as calculated by the Gail model and to examine the relative association of each of the model covariates to mammographic density. METHODS: The study included 99 participants of the National Surgical Breast and Bowel Project P-1 trial, ages 36 to 74 years, all of whom had a mammogram and Gail model risk estimates done upon trial entry. Baseline mammograms were retrieved and digitized, and mammographic density was assessed by both subjective and computer-assisted objective measures. RESULTS: Mammographic density was 2-fold higher in women with a >15% lifetime risk of breast cancer compared with those with <15% risk, by all density assessment methods. This was equivalent to a 3% to 6% increase in density per 10% increase in risk. Gail model covariates that measured benign or premalignant breast tissue changes accounted for the majority (41%) of the relationship with increased mammographic density. Seven percent of density was not explained by risk factors included in the Gail model. CONCLUSIONS: The Gail model does not fully account for the association between breast density and calculated breast cancer risk. Because mammographic density is a modifiable marker, development of a breast cancer risk assessment tool that includes mammographic density could be beneficial for assessing individual risk.

Adult↗
PubMed2004

Microbiological risk assessment models for partitioning and mixing during food handling.

To describe the transmission dynamics of a pathogen over a food pathway in quantitative microbiological risk assessment (QMRA), several types of processes need to be modelled. Next to microbial processes like bacterial growth and inactivation, four food handling processes can be identified. Among these are partitioning and mixing of the food product. With these processes, the (sizes of) units of food product are modified and the pathogenic cells are reallocated over the units, so that the prevalence of contaminated units and the number of cells per unit may change. Usually, simple models of these processes are applied in QMRA food chain models. These models assume independence of units, random homogeneous distribution of cells (for partitioning) and equal contribution of units (for mixing), which is often not realistic in food and food handling processes. In this paper, these assumptions are abandoned. The use of multivariate distributions is proposed to include the effect of dependence between units: the Multinomial distribution for partitioning and the Dirichlet distribution for mixing. Effects of cell clustering and/or unequal sizes of units formed by partitioning or contributing to mixing are incorporated. Some algorithms are derived that are easily implemented in spreadsheet models that simulate food production and preparation. Some examples show the effect of more realistic modelling by implementation of these algorithms on the prevalence and the probability distribution of the number of pathogens per unit of food product. In general, cell clustering will result in lower prevalences, but higher levels of contamination in contaminated food units. With the methods presented, these effects can be quantified. Difficulties in estimating the model parameters and the impact of implementation of the proposed methods on risk estimates in QMRA are discussed.

Bacteria↗
PubMed1995

Neurotoxicity modeling for risk assessment.

The setting of acceptable exposure levels for neurotoxicants has followed the traditional approach of dividing experimental no-observed-adverse-effect-levels (NOAELs) by safety/uncertainty factors. NOAELs are believed by many toxicologists to represent levels having zero or negligible risk, while uncertainty factors are used to account for a number of sources of variation. Although the use of NOAELs in this manner has been criticized because of their imprecise quantitative definition, NOAELs for nonquantal neurotoxic effects have not been replaced by more precisely defined quantities (e.g., benchmark doses), partly due to the absence of a generally accepted methodology for attaching specific risk levels to low exposures. The present paper describes a quantitative approach to modeling nonquantal neurotoxic effects for risk assessment, which can be used to obtain results similar to the familiar results obtained in risk assessment for carcinogenicity and developmental toxicity. The steps involved in implementing the process are discussed, with particular attention being given to the critical step of defining an adverse neurologic effect. An experimental data set is used to illustrate the methodology.

Animals↗
PubMedDate not supplied

Women's perceptions of breast cancer risk: are they accurate?

BACKGROUND: The objective was to compare women's personal estimates of their risk with objective breast cancer risk estimates and to describe the risk factors for breast cancer identified by women. METHODS: Telephone survey of a random sample of 761 rural and urban women with no history of breast cancer. Survey instrument included measures of perceptions of lifetime risk for breast cancer for themselves and for the average woman, perceptions of risk factors that influenced their risk and the average woman's risk for breast cancer. Objective estimates of breast cancer risk were calculated using the Gail et al. algorithm. Descriptive statistics and multiple linear regression were used to analyze the data. RESULTS: Women's estimates of their own lifetime risk for breast cancer were significantly higher than their Gail model risk estimates (mean difference = 19%, p < 0.001). The women's personal breast cancer risk estimates were lower than estimates of risk for a hypothetical average woman (mean difference = -8%, p < 0.001). Fifty percent of the sample reported a perceived risk estimate at least 15% above their Gail risk estimate. The risk factors for breast cancer most frequently identified included family history, nutrition/diet, smoking, lifestyle, environment, stress and age. Although the risk factors used to calculate the Gail model risk estimates were reported by some study participants, these women consistently identified only family history as their personal risk factor. CONCLUSION: Women have difficulty accurately estimating their breast cancer risk and identifying known risk factors for breast cancer. Individual risk information may be more useful in enhancing accurate risk perceptions than the "1 in 9" message.

Adult↗
PubMed2005

The effect of censoring on cancer risk estimates based on the Canadian National Dose Registry of occupational radiation exposure.

Cohort studies represent an important epidemiological tool for exploring the potential adverse health effects of low-dose exposure to ionizing radiation in the workplace. Analyses of data from the National Dose Registry of Canada have suggested that occupational radiation exposure leads to increased risk of several specific types of cancer, as well as increased overall risk of cancer. An important aspect of such studies is the censoring in recorded exposures induced by dosimetry detection limits. Such a censoring effect can lead to significant underestimation of cumulative doses which, in turn, can result in overestimation of the excess cancer risk associated with occupational radiation exposure. In this article, we present analytic results, supported by a simulation study, on the magnitude of overestimation of risk based on the additive relative risk model used in the analysis of the NDR data that can occur due to censoring. Our results indicate that overestimation of risk is modest, being less than 20% in all situations considered here. Because censoring also results in ovestimation of the precision of the risk estimates, the significance levels of Wald-type statistical tests for increased risk based on the ratio of the estimate to its standard error are virtually unaffected by censoring. These results suggest that although the application of the additive excess relative risk model in the presence of censoring may lead to some overestimation of risk, the model does not lead to invalid conclusions regarding the association between occupational radiation exposure and cancer risk based on data from the NDR.

Canada↗