Heart failure (HF) care constitutes an increasing economic burden on the health care system, and has become a key focus in the health care debate. However, there are limited data on the lifetime health care costs for individuals with HF after initial diagnosis. Read More on PubMed

Blood lipids are important cardiovascular disease (CVD) risk factors with both genetic and environmental determinants. The Whitehall II study (n=5592) was genotyped with the gene-centric HumanCVD BeadChip (Illumina). We identified 195 SNPs in 16 genes/regions associated with 3 major lipid fractions and 2 apolipoprotein components at p<10(-5), with the associations being broadly concordant with prior genome-wide analysis. SNPs associated with LDL cholesterol and apolipoprotein B were located in LDLR, PCSK9, APOB, CELSR2, HMGCR, CETP, the TOMM40-APOE-C1-C2-C4 cluster, and the APOA5-A4-C3-A1 cluster; SNPs associated with HDL cholesterol and apolipoprotein AI were in CETP, LPL, LIPC, APOA5-A4-C3-A1, and ABCA1; and SNPs associated with triglycerides in GCKR, BAZ1B, MLXIPL, LPL, and APOA5-A4-C3-A1. For 48 SNPs in previously unreported loci that were significant at p<10(-4) in Whitehall II, in silico analysis including the British Women's Heart and Health Study, BRIGHT, ASCOT, and NORDIL studies (total n>12,500) revealed previously unreported associations of SH2B3 (p<2.2x10(-6)), BMPR2 (p<2.3x10(-7)), BCL3/PVRL2 (flanking APOE; p<4.4x10(-8)), and SMARCA4 (flanking LDLR; p<2.5x10(-7)) with LDL cholesterol. Common alleles in these genes explained 6.1%-14.7% of the variance in the five lipid-related traits, and individuals at opposite tails of the additive allele score exhibited substantial differences in trait levels (e.g., >1 mmol/L in LDL cholesterol [approximately 1 SD of the trait distribution]). These data suggest that multiple common alleles of small effect can make important contributions to individual differences in blood lipids potentially relevant to the assessment of CVD risk. These genes provide further insights into lipid metabolism and the likely effects of modifying the encoded targets therapeutically. Read More on PubMed

The communication of risk is a central activity in clinical genetics, with genetic health professionals encouraging the dissemination of relevant information by individuals to their at-risk family members. To understand the process by which communication occurs as well as its outcomes, a systematic review of actual communication in families about genetic risk was conducted. Findings from 29 papers meeting the inclusion criteria were summarised and are presented narratively. Family communication about genetic risk is described as a deliberative process, in which: sense is made of personal risk; the vulnerability and receptivity of the family member is assessed; decisions are made about what will be conveyed; and the right time to disclose is selected. The communication strategy adopted will depend on these factors and varies within families as well as between families. Inherent in these processes are conflicting senses of responsibility: to provide potentially valuable information and to prevent harm that may arise from this knowledge. However, the research 'outcomes' of communication have been professionally determined (number of relatives reported as informed, uptake of testing, knowledge of the recipient) and are typically unrelated to the concerns of the family member. The impact of communication on the individual, family members, and family relationships is of concern to the individual conveying the information, but this is largely self-reported. Currently, there is insufficient information to inform the development of theoretically and empirically based practice to foster 'good' communication. The implications for future research are discussed. Read More on PubMed

New genetic tests for adult-onset diseases raise concerns about possible adverse selection in insurance markets. To test for this behavior, we followed 148 cognitively normal people participating in a randomized clinical trial of genetic testing for Alzheimer's disease for one year after risk assessment and Apolipoprotein E (APOE) genotype disclosure. Although no significant differences were found in health, life, or disability insurance purchases, those who tested positive were 5.76 times more likely to have altered their long-term care insurance than those who did not receive APOE genotype disclosure. If genetic testing for Alzheimer's risk assessment becomes common, it could trigger adverse selection in long-term care insurance. Read More on PubMed

As patients become more involved in health care decisions, there may be greater opportunity for decision regret. The authors could not find a validated, reliable tool for measuring regret after health care decisions. Read More on PubMed

Despite the potential importance of family communication, little is known about the process and content of communicating BRCA1/2 test results to relatives. The objectives of this observational study were to describe the process and content of communicating BRCA1/2 test results to sisters, and to evaluate whether the proband's carrier status influenced communication outcomes. Participants were 43 women who were the first family member to have genetic testing (probands). Probands reported on communication outcomes for 81 sisters. Process and content variables were evaluated 1-month after receipt of BRCA1/2 test results using the Family Communication Questionnaire (FCQ). Overall, BRCA1/2 test results were communicated to 85% of sisters, and carriers communicated their results to significantly more sisters compared to uninformative (96% vs. 76%, FET = 0.02). The most important reason for communicating results was to provide genetic risk information; however, compared to uninformatives, carriers communicated their results to significantly more sisters to obtain emotional support (74%) and to get advice about medical decisions (42%) (FET = 0.001). Carriers also discussed the possibility of discrimination and recommendations for cancer management with significantly more sisters. Among sisters to whom BRCA1/2 test results were not communicated, the most important reason for not sharing test results was because of emotionally distant relationships. The results of this study suggest that probands are likely to quickly communicate their BRCA1/2 test results to relatives and that although needs for social support may motivate family communication, emotionally distant relationships may be a barrier to communication with relatives. Read More on PubMed

Predictions of cost over well-defined time horizons are frequently required in the analysis of clinical trials and social experiments, for decision models investigating the cost-effectiveness of interventions, and for macro-level estimates of the resource impact of disease. With rare exceptions, cost predictions used in such applications continue to take the form of deterministic point estimates. However, the growing availability of large administrative and clinical data sets offers new opportunities for a more general approach to disease cost forecasting: the estimation of multivariable cost functions that yield predictions at the individual level, conditional on intervention(s), patient characteristics, and other factors. This raises the fundamental question of how to choose the "best" cost model for a given application. The central purpose of this paper is to demonstrate how to evaluate competing models on the basis of predictive validity. This concept is operationalized according to three alternative criteria: 1) root mean square error (RMSE), for evaluating predicted mean cost; 2) mean absolute error (MAE), for evaluating predicted median cost; and 3) a logarithmic scoring rule (log score), an information-theoretic index for evaluating the entire predictive distribution of cost. To illustrate these concepts, the authors conducted a split-sample analysis of data from a national sample of Medicare-covered patients hospitalized for ischemic stroke in 1991 and followed to the end of 1993. Using test and training samples of about 500,000 observations each, they investigated five models: single-equation linear models, with and without log transform of cost; two-part (mixture) models, with and without log transform, to directly address the problem of zero-cost observations; and a Cox proportional-hazards model stratified by time interval. For deriving the predictive distribution of cost, the log transformed two-part and proportional-hazards models are superior. For deriving the predicted mean or median cost, these two models and the commonly used log-transformed linear model all perform about the same. The untransformed models are dominated in every instance. The approaches to model selection illustrated here can be applied across a wide range of settings. Read More on PubMed