MULTIPLE DISEASES IN CARRIER PROBABILITY ESTIMATION: ACCOUNTING FOR SURVIVING ALL CANCERS OTHER THAN BREAST AND OVARY IN BRCAPRO

Mendelian models can predict who carries an inherited deleterious mutation of known disease genes based on family history. For example, the BRCAPRO model is commonly used to identify families who carry mutations of BRCA1 and BRCA2, based on familial breast and ovarian cancers. These models incorporate the age of diagnosis of diseases in relatives and current age or age of death. We develop a rigorous foundation for handling multiple diseases with censoring. We prove that any disease unrelated to mutations can be excluded from the model, unless it is sufficiently common and dependent on a mutation-related disease time. Furthermore, if a family member has a disease with higher probability density among mutation carriers, but the model does not account for it, then the carrier probability is deflated. However, even if a family only has diseases the model accounts for, if the model excludes a mutation-related disease, then the carrier probability will be inflated. In light of these results, we extend BRCAPRO to account for surviving all non-breast/ovary cancers as a single outcome. The extension also enables BRCAPRO to extract more useful information from male relatives. Using 1500 familes from the Cancer Genetics Network, accounting for surviving other cancers improves BRCAPRO’s concordance index from 0.758 to 0.762 (p = 0.046), improves its positive predictive value from 35% to 39% (p < 10−6) without impacting its negative predictive value, and improves its overall calibration, although calibration slightly worsens for those with carrier probability < 10%. Copyright c 2000 John Wiley & Sons, Ltd.

Perspectives on periodontal risk factors

The development of a clinical decision tree based on knowledge about risks and reported outcomes of therapy is a necessity for successful planning and outcome of periodontal therapy. This requires a well-founded knowledge of the disease entity and a broad knowledge of how different risk conditions attribute to periodontitis. The infectious etiology, a complex immune response, and influence from a large number of co-factors are challenging conditions in clinical periodontal risk assessment. The difficult relationship between independent and dependent risk conditions paired with limited information on periodontitis prevalence adds to difficulties in periodontal risk assessment. The current information on periodontitis risk attributed to smoking habits, socio-economic conditions, general health and subjects' self-perception of health, is not comprehensive, and this contributes to limited success in periodontal risk assessment. New models for risk analysis have been advocated. Their utility for the estimation of periodontal risk assessment and prognosis should be tested. The present review addresses several of these issues associated with periodontal risk assessment.

Review of assessment, design, and mitigation of multiple hazards

Large parts of the world are subjected to one or more natural hazards, such as earthquakes, tsunamis, landslides, tropical storms (hurricanes, cyclones and typhoons), costal inundation and flooding. Virtually the entire world is at risk of man-made hazards. In recent decades, rapid population growth and economic development in hazard-prone areas have greatly increased the potential of multiple hazards to cause damage and destruction of buildings, bridges, power plants, and other infrastructure; thus posing a grave danger to the community and disruption of economic and societal activities. Although an individual hazard is significant in many parts of the United States (U.S.), in certain areas more than one hazard may pose a threat to the constructed environment. In such areas, structural design and construction practices should address multiple hazards in an integrated manner to achieve structural performance that is consistent with owner expectations and general societal objectives. The growing interest and importance of multiple-hazard engineering has been recognized recently. This has spurred the evolution of multiple-hazard risk-assessment frameworks and development of design approaches which have paved way for future research towards sustainable construction of new and improved structures and retrofitting of the existing structures. This report provides a review of literature and the current state of practice for assessment, design and mitigation of the impact of multiple hazards on structural infrastructure. It also presents an overview of future research needs related to multiple-hazard performance of constructed facilities.

Risk analysis of light-frame wood construction due to multiple hazards

Light-frame wood buildings are widely built in the United States (U.S.). Natural hazards cause huge losses to light-frame wood construction. This study proposes methodologies and a framework to evaluate the performance and risk of light-frame wood construction. Performance-based engineering (PBE) aims to ensure that a building achieves the desired performance objectives when subjected to hazard loads. In this study, the collapse risk of a typical one-story light-frame wood building is determined using the Incremental Dynamic Analysis method. The collapse risks of buildings at four sites in the Eastern, Western, and Central regions of U.S. are evaluated. Various sources of uncertainties are considered in the collapse risk assessment so that the influence of uncertainties on the collapse risk of lightframe wood construction is evaluated. The collapse risks of the same building subjected to maximum considered earthquakes at different seismic zones are found to be non-uniform. In certain areas in the U.S., the snow accumulation is significant and causes huge economic losses and threatens life safety. Limited study has been performed to investigate the snow hazard when combined with a seismic hazard. A Filtered Poisson Process (FPP) model is developed in this study, overcoming the shortcomings of the typically used Bernoulli model. The FPP model is validated by comparing the simulation results to weather records obtained from the National Climatic Data Center. The FPP model is applied in the proposed framework to assess the risk of a light-frame wood building subjected to combined snow and earthquake loads. The snow accumulation has a significant influence on the seismic losses of the building. The Bernoulli snow model underestimates the seismic loss of buildings in areas with snow accumulation. An object-oriented framework is proposed in this study to performrisk assessment for lightframe wood construction. For home owners and stake holders, risks in terms of economic losses is much easier to understand than engineering parameters (e.g., inter story drift). The proposed framework is used in two applications. One is to assess the loss of the building subjected to mainshock-aftershock sequences. Aftershock and downtime costs are found to be important factors in the assessment of seismic losses. The framework is also applied to a wood building in the state of Washington to assess the loss of the building subjected to combined earthquake and snow loads. The proposed framework is proven to be an appropriate tool for risk assessment of buildings subjected to multiple hazards. Limitations and future works are also identified.

Risk scoring for setting priorities in a monitoring of antimicrobial resistance in meat and meat products

Meat and meat products can be contaminated with different species of bacteria resistant to various antimicrobials. The human health risk of a type of meat or meat product carry by emerging antimicrobial resistance depends on (i) the prevalence of contamination with resistant bacteria, (ii) the human health consequences of an infection with a specific bacterium resistant to a specific antimicrobial and (iii) the consumption volume of a specific product. The objective of this study was to compare the risk for consumers arising from their exposure to antibiotic resistant bacteria from meat of four different types (chicken, pork, beef and veal), distributed in four different product categories (fresh meat, frozen meat, dried raw meat products and heat-treated meat products). A semi-quantitative risk assessment model, evaluating each food chain step, was built in order to get an estimated score for the prevalence of Campylobacter spp., Enterococcus spp. and Escherichia coli in each product category. To assess human health impact, nine combinations of bacterial species and antimicrobial agents were considered based on a published risk profile. The combination of the prevalence at retail, the human health impact and the amount of meat or product consumed, provided the relative proportion of total risk attributed to each category of product, resulting in a high, medium or low human health risk. According to the results of the model, chicken (mostly fresh and frozen meat) contributed 6.7% of the overall risk in the highest category and pork (mostly fresh meat and dried raw meat products) contributed 4.0%. The contribution of beef and veal was of 0.4% and 0.1% respectively. The results were tested and discussed for single parameter changes of the model. This risk assessment was a useful tool for targeting antimicrobial resistance monitoring to those meat product categories where the expected risk for public health was greater.

Spatiotemporal dynamics: the need for an innovative approach in mountain hazard risk management

Starting with an overview on losses due to mountain hazards in the Russian Federation and the European Alps, the question is raised why a substantial number of events still are recorded—despite considerable efforts in hazard mitigation and risk reduction. The main reason for this paradox lies in a missing dynamic risk-based approach, and it is shown that these dynamics have different roots: firstly, neglecting climate change and systems dynamics, the development of hazard scenarios is based on the static approach of design events. Secondly, due to economic development and population dynamics, the elements at risk exposed are subject to spatial and temporal changes. These issues are discussed with respect to temporal and spatial demands. As a result, it is shown how risk is dynamic on a long-term and short-term scale, which has to be acknowledged in the risk concept if this concept is targeted at a sustainable development of mountain regions. A conceptual model is presented that can be used for dynamical risk assessment, and it is shown by different management strategies how this model may be converted into practice. Furthermore, the interconnectedness and interaction between hazard and risk are addressed in order to enhance prevention, the level of protection and the degree of preparedness.

Assessment of metabolic stability using the rainbow trout (Oncorhynchus mykiss) liver S9 fraction

Standard protocols are given for assessing metabolic stability in rainbow trout using the liver S9 fraction. These protocols describe the isolation of S9 fractions from trout livers, evaluation of metabolic stability using a substrate depletion approach, and expression of the result as in vivo intrinsic clearance. Additional guidance is provided on the care and handling of test animals, design and interpretation of preliminary studies, and development of analytical methods. Although initially developed to predict metabolism impacts on chemical accumulation by fish, these procedures can be used to support a broad range of scientific and risk assessment activities including evaluation of emerging chemical contaminants and improved interpretation of toxicity testing results. These protocols have been designed for rainbow trout and can be adapted to other species as long as species-specific considerations are modified accordingly (e.g., fish maintenance and incubation mixture temperature). Rainbow trout is a cold-water species. Protocols for other species (e.g., carp, a warm-water species) can be developed based on these procedures as long as the specific considerations are taken into account.

Efficiency of risk-based vs . random sampling for the monitoring of tetracycline residues in slaughtered calves in Switzerland

In all European Union countries, chemical residues are required to be routinely monitored in meat. Good farming and veterinary practice can prevent the contamination of meat with pharmaceutical substances, resulting in a low detection of drug residues through random sampling. An alternative approach is to target-monitor farms suspected of treating their animals with antimicrobials. The objective of this project was to assess, using a stochastic model, the efficiency of these two sampling strategies. The model integrated data on Swiss livestock as well as expert opinion and results from studies conducted in Switzerland. Risk-based sampling showed an increase in detection efficiency of up to 100% depending on the prevalence of contaminated herds. Sensitivity analysis of this model showed the importance of the accuracy of prior assumptions for conducting risk-based sampling. The resources gained by changing from random to risk-based sampling should be transferred to improving the quality of prior information.

Attitudes of Parents at risk of inheriting Li-Fraumeni Syndrome towards predictive genetic testing in their minor-aged children.

Li-Fraumeni Syndrome (LFS) is a hereditary cancer syndrome which predisposes individuals to cancer beginning in childhood. These risks are spread across a lifetime, from early childhood to adulthood. Mutations in the p53 tumor suppressor gene are known to cause the majority of cases of LFS. The risk for early onset cancer in individuals with Li-Fraumeni Syndrome is high. Studies have shown that individuals with LFS have a 90% lifetime cancer risk. Children under 18 have up to a 15% chance of cancer development. Effectiveness of cancer screening and management in individuals with Li-Fraumeni Syndrome is unclear. Screening for LFS-associated cancers has not been shown to reduce mortality. Due to the lack of effective screening techniques for childhood cancers, institutions vary with regard to their policies on testing children for LFS. There are currently no national guidelines regarding predictive testing of children who are at risk of inheriting LFS. No studies have looked at parental attitudes towards predictive p53 genetic testing in their children. This was a cross-sectional pilot study aimed at describing these attitudes. We identified individuals whose children were at risk for inheriting p53 genetic mutations. These individuals were provided with surveys which included validated measures addressing attitudes and beliefs towards genetic testing. The questionnaire included qualitative and quantitative measures. Six individuals completed and returned the questionnaire with a response rate of 28.57%. In general, respondents agreed that parents should have the opportunity to obtain p53 genetic testing for their child. Parents vary in regard to their attitudes towards who should be involved in the decision making process and at what time and under what considerations testing should occur. Testing motivations cited most important by respondents included family history, planning for the future and health management. Concern for insurance genetic discrimination was cited as the most important “con” to genetic testing. Although limited by a poor response rate, this study can give health care practitioners insight into testing attitudes and beliefs of families considering pediatric genetic testing.