Incorporating Family History Research Articles

Hesse‐Biber, S.Waiting for Cancer to Come: Women's Experiences with Genetic Testing and Medical Decision Making for Breast and Ovarian Cancer, Michigan: University of Michigan Press. 2014. 216pp $50 (hbk) $24.95 (pbk) $24.95 (ebk) ISBN 978–0‐47205219–6

Hesse‐Biber, S.Waiting for Cancer to Come: Women's Experiences with Genetic Testing and Medical Decision Making for Breast and Ovarian Cancer, Michigan: University of Michigan Press. 2014. 216pp $50 (hbk) $24.95 (pbk) $24.95 (ebk) ISBN 978–0‐47205219–6

Leveraging Family History in Population‐Based Case‐Control Association Studies

Population-based epidemiologic studies often gather information from study participants on disease history among their family members. Although investigators widely recognize that family history will be associated with genotypes of the participants at disease susceptibility loci, they commonly ignore such information in primary genetic association analyses. In this report, we propose a simple approach to association testing by incorporating family history information as a "phenotype." We account for the expected attenuation in strength of association of the genotype of study participants with family history under Mendelian transmission. The proposed analysis can be performed using standard statistical software adopting either a meta- or pooled-analysis framework. Re-analysis of a total of 115 known susceptibility single-nucleotide polymorphisms, discovered through genome-wide association studies for several disease traits, indicates that incorporation of family history information can increase efficiency by as much as 40%. Efficiency gain depends on the type of design used for conducting the primary study, extent of family history, and accuracy and completeness of reporting.

Improving Assessment of Cardiovascular Disease Risk by Using Family History

Cardiovascular disease (CVD) is the number one killer in the United States. Although the causes of CVD are multifactorial, including genetic and environmental influences, it is largely a preventable disease. The cornerstone of CVD prevention is accuracy in risk prediction to identify patients who will benefit from interventions aimed at reducing risk. Nurse practitioners commonly perform CVD risk assessments and are well positioned to impact preventive therapy. Cardiovascular disease risk scoring systems currently in use substantially underestimate risk in large part because these do not include family history of premature CVD as a high-risk factor. We sought to examine the state of evidence for the use of family history as a predictor in CVD risk stratification. A comprehensive literature search using the Medical Subject Headings terms of family history of CVD, family history of premature CVD, risk assessment, and risk estimation displayed 416 articles; a review of the titles and subsequent evaluation of the articles eliminated 392 references, leaving 24 for review. By incorporating family history in risk assessment, categorization of CVD risk improves substantially. The evidence demonstrates that family history is an independent contributor to risk appraisal and unequivocally supports its incorporation to improve accuracy in global CVD risk estimation. Underestimation of CVD risk leaves patients and providers misinformed, promoting the ongoing epidemic of chronic disease. Translating this evidence into practice by establishing a clinical algorithm that incorporates family history into risk prediction will standardize CVD risk assessment, improve the identification of high-risk patients, and provide the indicated aggressive care to prevent CVD.

Abstract 314: Systematic Inquiry of Family History Improves Cardiovascular Disease Risk Assessment

Background: Numerous research publications substantiate the value of family history of premature cardiovascular disease (CVD) as an independently predictive risk factor for CVD. However, many traditional CVD risk assessment tools do not incorporate family history and therefore underestimate true risk. Risk assessment is the cornerstone of determining therapeutic goals and preventive intervention. Objective: We sought to implement and validate a clinical decision support tool that incorporates family history as a high-risk factor to guide risk stratification in a population identified as low and intermediate risk by Framingham Risk Score (FRS). Methods: In a retrospective analysis of patients entering our CVD prevention program, the clinical decision support tool was applied. The clinical decision support tool defines family history of premature CVD as having a parent and/or sibling with a CVD event before the age of 65. Patients entering our CVD prevention program have a comprehensive risk assessment including measurement of blood pressure, lipids, glucose metabolism and Carotid Intima Media Thickness (CIMT). Results: Of 394 patients entering our program, 239 (61%) were scored as low or intermediate risk by FRS. These patients had a mean age of 49 years (range 20-76), 60% women, 52% Caucasian, 37% Black, 5% Hispanic and 6% other. The decision support tool identified 114 (48%) of these patients as high-risk for CVD as a result of the inclusion of family history of premature CVD. In these patients, 72% had dyslipidemia, 35% hypertension, 20% prediabetes and 61% had early atherosclerotic disease by CIMT. Conclusions: In our population, almost half of the patients previously determined as low or intermediate risk were reclassified as high-risk for CVD. This reclassification is underscored and validated in view of both the high frequency of metabolic abnormalities revealed and the atherosclerotic plaque burden seen by CIMT. These findings are highly relevant particularly in middle-aged women who are frequently more vulnerable to overt heart disease and require improved risk assessment for aggressive treatment goals to enhance prevention.

Carotid Ultrasound Identifies High Risk Subclinical Atherosclerosis in Adults with Low Framingham Risk Scores

Conclusion: A high percentage of young to middle-aged individuals with a Framingham Risk Score (FRS) indicating <5% risk of cardiovascular events have abnormal carotid ultrasound findings associated with an increased risk for cardiovascular events. Summary: Atherosclerosis-related clinical events are presumably preceded by a period of asymptomatic atherosclerosis. The FRS is a population-based algorithm recommended to identify at-risk individuals and determine the aggressiveness of preventive therapy (JAMA 2001;285:2486-97). However, population-based risk algorithms do not quantify atherosclerosis. They provide only a probability of cardiovascular events over a relatively short fixed period, usually <10 years. The FRS risk assessment also does not incorporate family history, premature coronary artery disease, remote smoking history, impaired fasting glucose, triglyceride levels, or waist circumference. Tests for subclinical atherosclerosis are therefore sometimes recommended to add incremental information and provide more accurate risk stratification. The authors tested the hypothesis that patients with a low (<5%) FRS 10-year risk for a first cardiovascular event and intermediate (6% to 20%) FRS 10-year risk will have increased cardiovascular risk as determined by an abnormal carotid intima-media thickness (IMT). This study included individuals aged <65 years who were not taking statins and who did not have diabetes or a history of coronary artery disease, but who did undergo a determination of carotid IMT and plaque for primary intervention. Clinical variables analyzed included lipid values, family history of coronary artery disease, FRS, and subsequent pharmacotherapy recommendations. The study comprised 441 individuals who were a mean age of 49.7 ± 7.9 years. Of these patients, 184 (42%, 95% CI, 37.3%-46.5%) had high-risk carotid IMT findings (carotid IMT ≥75th percentile adjusted for age, sex, race, or presence of plaque). In 336 individuals with the lowest FRS score of <5%, 127 (38%, 95% CI, 32.6%-43.0%) had high-risk carotid ultrasound findings. The treating physicians recommended lipid-lowering therapy for 77 individuals (61%) with a FRS ≤5% and high-risk carotid ultrasound findings. Comment: This study indicates a disconnect between the risk assessment by the FRS and carotid IMT. Studies have also found high-risk carotid ultrasound findings influence physicians to prescribe aspirin or lipid-lowering therapies (Wyman RA, et al; Am Heart J 2007;154:1072-7 and Korcarz CE, et al; J Am Soc Echocardiogr 2008;21:1156-62). However, although physicians may make treatment decisions based on a finding of increased carotid IMT, it appears that observing changes in IMT to monitor effects of drug therapy will not reduce subsequent clinical events. A practical point may be that carotid IMT can be used to identify patients at increased risk for cardiovascular events, but once treatment is initiated, subsequent studies to monitor effectiveness of treatment may not be needed.

Risk Prediction of Complex Diseases from Family History and Known Susceptibility Loci, with Applications for Cancer Screening

Risk prediction based on genomic profiles has raised a lot of attention recently. However, family history is usually ignored in genetic risk prediction. In this study we proposed a statistical framework for risk prediction given an individual's genotype profile and family history. Genotype information about the relatives can also be incorporated. We allow risk prediction given the current age and follow-up period and consider competing risks of mortality. The framework allows easy extension to any family size and structure. In addition, the predicted risk at any percentile and the risk distribution graphs can be computed analytically. We applied the method to risk prediction for breast and prostate cancers by using known susceptibility loci from genome-wide association studies. For breast cancer, in the population the 10-year risk at age 50 ranged from 1.1% at the 5th percentile to 4.7% at the 95th percentile. If we consider the average 10-year risk at age 50 (2.39%) as the threshold for screening, the screening age ranged from 62 at the 20th percentile to 38 at the 95th percentile (and some never reach the threshold). For women with one affected first-degree relative, the 10-year risks ranged from 2.6% (at the 5th percentile) to 8.1% (at the 95th percentile). For prostate cancer, the corresponding 10-year risks at age 60 varied from 1.8% to 14.9% in the population and from 4.2% to 23.2% in those with an affected first-degree relative. We suggest that for some diseases genetic testing that incorporates family history can stratify people into diverse risk categories and might be useful in targeted prevention and screening.

Proposed criteria for familial amyotrophic lateral sclerosis

There is currently no consensus on the definition of familial ALS (FALS). We propose criteria for FALS that incorporate family history and genetic analysis. The aim is to increase the yield of gene...

Integrating Tools for Breast Cancer Risk Assessment, Risk Reduction, and Early Detection

Commentary on Graubard et al., [p. 2430][1] In 2010, it is projected that there will be 207,090 diagnoses and 39,840 deaths from breast cancer among women in the United States. Approximately 10,300 will be diagnosed before the age of 40 ([1][2]), the age when the American Cancer Society ([2][3])

Exploring the role of family history and lay understanding of genetics on the self‐management of disease

lindsay s (2010) Journal of Nursing and Healthcare of Chronic Illness 2, 135–143 Exploring the role of family history and lay understanding of genetics on the self‐management of diseaseAims and objectives. This project drew a sample from coronary heart disease registries (n = 108) to explore how people incorporate knowledge of lay genetics and family history of a disease to manage their health. Questionnaires and focus groups were analysed to explore whether having a family history of coronary heart disease (CHD) influenced how patients’ self‐managed their health.Background. Although evidence suggests that genes have an important influence on susceptibility to many diseases, little is known about how people use this knowledge to manage their health. Most research on lay perceptions of genetic causes of disease focuses on people at risk of particular genetic condition, rather than on those who already have a disease.Results. Four key themes emerged from the data that people used to understand their heart disease while incorporating family history in different ways including: (1) being ‘doomed’ because of bad genes; (2) not wanting to change health behaviours; (3) wanting to be careful and lead a healthy lifestyle because of a known family history of heart disease and (4) uncertainty of the role of family history in heart disease.Conclusions. Knowledge of family history of the disease influenced how people experienced health and was inherently embedded within social context to shape new meanings of health.Implications for practice. The recommendations based on this research are to encourage health care providers to develop an understanding of patients’ conception of how their disease was caused so they can give them advice that will fit within their framework. It is important to understand the different ways in which patients conceptualise and respond to their illness.

Limitations of the Gail Model in the Specialized Breast Cancer Risk Assessment Clinic

The Gail model is a risk assessment tool that is accurate for general breast cancer risk screening. Because of the limited way that this model incorporates family history information, however, there are concerns that it may underestimate risk for many women attending specialized breast cancer risk assessment clinics. We collected comprehensive breast cancer risk factor information for 213 women attending a specialized breast cancer risk assessment clinic using a modified version of the CancerGene software. Breast cancer risk was calculated using the models of Gail and Claus as well as BRCAPRO and the tables of Bodian (for women with lobular neoplasia). Eighty-six percent of the women had a family history of breast cancer. Although 74% of women had risk factor histories that are thought to confound the Gail model (family history of breast cancer in second-degree relatives, family history of breast cancer before the age of 50, family history of bilateral breast cancer, family history of ovarian cancer, or personal history of lobular neoplasia), the inclusion of other models increased the risk level assignment in only 13% of the cases. We conclude that the Gail model is an appropriate risk assessment tool for most women attending specialized clinics, although the inclusion of models better able to account for family history information and personal history of lobular neoplasia is required to accommodate all women.

A Comparison of NCEP and Absolute Risk Stratification Methods for Lipid-Lowering Therapy in Middle-Aged Adults: The ARIC Study. The ARIC Investigators.

Lipid-lowering therapy has been shown to reduce cardiovascular disease risk in individuals with low-density lipoprotein cholesterol (LDL-C) levels of at or above 130 mg/dL. Several methods have been developed for identifying those at highest risk for treatment. The objective was to compare the 1993 National Cholesterol Education Program guidelines to absolute risk assessment methods similar to those used by recently developed European and British cholesterol treatment guidelines. The design and setting was a population-based, prospective cohort study in four US communities. Among Atherosclerosis Risk in the Communities study participants aged 45-64 years followed for a mean of 7 years, 7314 women and 5762 men were included who had no evidence of clinical cardiovascular disease and were not receiving lipid-lowering drug therapy at entry. Main outcome measures were number meeting criteria for treatment, number of cardiovascular events expected to be prevented with treatment, number needed to treat to prevent one cardiovascular event, and sensitivity of criteria for detecting cases for the entire cohort and for those at or above the LDL-C treatment threshold (within-group). The 1993 National Cholesterol Education Program guidelines identified 16% of participants for treatment: n=2112; events expected to be prevented=77; number needed to treat=27; sensitivity=0.31 (0.28-0.35); sensitivity when LDL-C was greater-than-or-equal160 mg/dL=0.86. Use of a LDL-C treatment threshold of greater-than-or-equal130 mg/dL, a greater-than-or-equal20% 10-year absolute risk cut-point (similar to European guidelines) identified 13% for treatment: n=1701; events expected to be prevented=66; number needed to treat=26; sensitivity=0.29 (0.25-0.32); sensitivity when LDL-C was >130 mg/dL=0.43. A greater-than-or-equal15% risk cut-point (similar to British guidelines) identified 17% for treatment: n=2233; events expected to be prevented=82; number needed to treat=27; sensitivity=0.37 (0.33-0.40); sensitivity when LDL-C was greater-than-or-equal130 mg/dL=0.55. Modified National Cholesterol Education Program guidelines (LDL-C treatment threshold lowered from 160 to 130 mg/dL for those with greater-than-or-equal2 risk factors) identified 30% for treatment: n=3867; events expected to be prevented=120; number needed to treat=32; sensitivity=0.55 (0.52-0.59); sensitivity when LDL-C was 130 mg/dL=0.83. A hybrid strategy using greater-than-or-equal15% risk, or 10% to 14% risk with a parental history of premature coronary heart disease or treated, controlled hypertension, identified 20% for treatment: n=2646; events expected to be prevented=97; number needed to treat=27; sensitivity=0.44 (0.40-0.47); sensitivity when LDL-C was greater-than-or-equal130 mg/dL=0.66. Depending on the priorities of a health care system, higher absolute cut-points can be used for allocating health care resources to those at the highest risk. However, fewer cardiovascular events will be prevented and fewer patients who later experience cardiovascular events will be offered treatment despite acceptable numbers needed to treat to prevent one cardiovascular disease event. A hybrid absolute risk strategy incorporating family history and treated hypertension information appears to be superior to absolute risk strategies that do not include this information. Copyright 2001 CHF, Inc.

Incorporation of family history in logistic regression models.

For diseases with a genetic component, logistic regression models are presented that incorporate family history in a quantitative way. In the largest model, every type of relative has their own regression coefficient. The other two models are submodels, which incorporate family history either by the number of cases in the family minus its expectation or by a weighted number of cases in the family minus its expectation. For various genetic effects, namely polygenic and autosomal dominant effects, the performance of these simple logistic models is studied. First, the predictive values of the logistic and true genetic models are computed and compared. Secondly, a simulation study is carried out to investigate the effects of estimation of the parameters in a small data set. Thirdly, the logistic models are fitted to a data set of Von Willebrand Factor responses of target individuals and their families; in these models, family history has a significant effect. The conclusion is that for the genetic effects considered the logistic models perform well.

Genetic--epidemiologic study of early-onset ischemic heart disease.

A genetic-epidemiologic study was undertaken of a white Colorado population of 207 patients who had a myocardial infarction before age 55 years. Nineteen independent variables were compared between the 207 cases and 621 controls, matched 3:1. The highest risk ratios were associated with a positive family history for ischemic heart disease (IHD). The heritability of IHD was 63% when families with the monogenic forms of hyperlipoproteinemia were included, and 56% when they were excluded. A risk index was developed that incorporates family history into a data base of risk factors, which can be readily assessed by the clinician obtaining a screening history, physical and standard laboratory tests. A scale of 0-10 was devised and the predictive value of the index was tested against another data set. The efficiency of the index was maximal at a screening level of 5. This study suggests that it is logistically feasible to seek patients at high risk for intensive management in a clinical setting (high-risk strategy) using risk indices similar to the one developed for this study, which emphasize the very important familial component to IHD.